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The main problems in the practice of traditional shrimp aquaculture are related with maintaining good water quality and reducing high operational cost. In this paper it will be described the application of wireless sensors and Android based application as mobile monitoring tool in achieving highly efficient shrimp aquaculture monitoring system. A set of four water quality parameter sensors (pH, temperature, conductivity and DO) were submerged into the pond using a buoy, in which an electronics and Xbee wireless transmitter have been installed to transmit the measured data into a fixed monitoring station. The main component of the fixed monitoring station was a smart data logger capable of performing automatic aeration system. Data transmission from the monitoring station to the master station was done through GSM/GPRS module of a Raspberry microcontroller. Using internet connection, a web based server has been developed from which the Android based application retrieved the measured parameter data. Graphical analysis of water quality data can be performed from a mobile phone, allowing users to monitor the aquaculture regardless of their geographical location. This system has been implemented in a shrimp aquaculture in Bangka island, Indonesia. In addition to giving real-time water quality data, the system was able to reduce the operational electricity cost because of the automatic aeration feature. Consistenly, the system has been sending the measurement data to the web server, which is accessible using Android mobile phones worldwide.

In the aviation industry, increasing research and applications of carbon fibres have led to a higher demand of carbon fibre reinforced polymer (CFRP) material. The moulding process of CFRP material is not precise enough to be directly moulded into its end form and an additional machining process is required. The machining of CFRP materials can result into generation of defects such as fibre overhang, cracking and delamination. Normally, the visual quality checks are carried out after machining is completed and hence, the damage at the end of the process is significantly more which can result into rework or rejection of the product. To solve this problem, an online quality monitoring system was developed in which the defects were measured, processed and identified online during the milling process. In order to achieve this, a line sensor was mounted behind the tool, which followed the tool and captured the data of the edge while milling. In the end, defects such as fibre overhang and delamination were detected simultaneously during the milling process.

For the long-term operation of municipal solid waste incineration (MSWI), online monitoring and feedback control of polychlorinated dibenzo-p-dioxin and dibenzofuran (PCDD/F) can be used to control the emissions to national or regional standards. In this study, 500 PCDD/F samples were determined by thermal desorption gas chromatography coupled to tunable-laser ionization time-of-flight mass spectrometry (TD-GC-TLI-TOFMS) for 168 h. PCDD/F emissions range from 0.01 ng I-TEQ/Nm3 to 2.37 ng I-TEQ/Nm3, with 44% of values below 0.1 ng I-TEQ/Nm3 (the national standard). In addition, the temperature of the furnace outlet, bed pressure, and oxygen content are considered as key operating parameters among the 13 operating parameters comprising four temperature parameters, four pressure parameters, four flow parameters, and oxygen content. More specifically, maintaining the furnace outlet temperature to be higher than 800 °C, or bed pressure higher than 13 kPa, or the oxygen content stably and above 10% are effective methods for reducing PCDD/F emissions. According to the analysis of the Pearson coefficients and maximal information coefficients, there is no significant correlation between operating parameters and PCDD/F I-TEQ. Only when there is a significant change in one of these factors will the PCDD/F emissions also change accordingly. The feedback control of PCDD/F emissions is realized by adjusting the furnace outlet temperature, bed temperature, and bed pressure to control the PCDD/F to be less than 0.1 ng I-TEQ/Nm3.

Both poor cooling methods and complex heat dissipation lead to prominent asymmetry in transformer temperature distribution. Both the operating life and load capacity of a power transformer are closely related to the winding hotspot temperature. Realizing accurate prediction of the hotspot temperature of transformer windings is the key to effectively preventing thermal faults in transformers, thus ensuring the reliable operation of transformers and accurately predicting transformer operating lifetimes. In this paper, a hot spot temperature prediction method is proposed based on the transformer operating parameters through the particle filter optimization support vector regression model. Based on the monitored transformer temperature, load rate, transformer cooling type, and ambient temperature, the hotspot temperature of a dry-type transformer can be predicted by a support vector regression method. The hyperparameters of the support vector regression are dynamically optimized here according to the particle filter to improve the optimization accuracy. The validity and accuracy of the proposed method are verified by comparing the proposed method with a traditional support vector regression method based on the real operating data of a 35 kV dry-type transformer.

Microbiological risks associated with drinking water can be minimized by providing enhanced integrity monitoring of bacterial removal by water treatment processes. This study aimed to evaluate the efficacy of real-time bacteriological counters for continuously assessing the performance of a full-scale sand filter to remove bacteria. Over the course of an 8-day evaluation, online counting of bacteria was successfully performed, providing continuous bacterial counts in the sand filter influent and effluent over approximate ranges from 17 × 10 4 to 94 × 10 4 and from 0.2 × 10 4 to 1.3 × 10 4 counts/mL, respectively. Periodic variations were observed with online bacterial counts in the sand filter influent because of the changes in the performance of flocculation and sedimentation processes. Overall, online removal rates of bacteria determined during the full-scale test were 95.2?99.3% (i.e., 1.3?2.2-log), indicating that online bacterial counting can continuously demonstrate over 1.3-log removal in the sand filter. Real-time bacteriological counting technology can be a useful tool for assessing variability and detecting bacterial breakthrough. It can be integrated with other online water quality measurements to evaluate underlying trends and the performance of sand filters for bacterial removal, which can enhance the safety of drinking water., Chemosphere, 229, pp.509-514; 2019

Ammonia is a necessary monitoring parameter that should be controlled within an optimum range in the whole process of wastewater treatment and recycling, but few reliable real-time monitoring technologies are available currently under such harsh water conditions. This study proposes a continuous conductometric flow-through analyzer for ammonia monitoring (CFAA) in the wastewater treatment process. It is developed based on the gas diffusion mechanisms, and the proposed analytical principle has been validated in which the real-time conductivity increment rate is linearly proportional to the real-time ammonia concentration in the sample. This method could be generally applicable in monitoring a wide ammonia concentration range (10.2 μg L-1 to 500 mg L-1), and it is capable of achieving long-term ammonia monitoring by periodic renewal of the receiving solution. The potential impact factors and corresponding calibration principles are also developed to avoid tedious ongoing calibration. The field application results demonstrate that CFAA can effectively and directly achieve real-time and average ammoniacal nitrogen monitoring at different treatment stages regardless of the complexity of wastewater, not requiring any sample pretreatment. Compared with other ammonia online monitoring technologies, the proposed CFAA shows remarkable advantages in high reliability, durability, and accuracy, especially under severe monitoring condition. It can be a useful monitoring tool for continuous ammonia control in the wastewater treatment process. Refereed/Peer-reviewed

[EN] This paper presents a modeling methodology, detection and isolation of faults on the operative part of Flexible Manufacturing Systems (FMS) through a Complex Networks (CN) approach. As a result, an online fault detection and location scheme is proposed, based on the structural symmetry of interrelation and the non-distinguishable dynamic of the complex network model. Moreover, a second scheme is implemented, which is based on the detection of a fault through the observation of an abrupt change (produced by the fault) in the ith order derivatives of the state variables on Linear Time-Invariant (LTI) system’s networks. In this context, an online monitoring and signal acquisition system was developed to validate the schemas described above on a Canning Process Line (CPL). The theoretical and experimental results validate the schemas and confirm the existence of phenomena like self-regulation, symmetry and organization, in manufacturing systems., [ES] En este trabajo se presenta una metodología de modelado, detección y aislamiento de fallas en la parte operativa de los Sistemas de Manufactura Flexible (SMF), desde el enfoque de la teoría de Redes Complejas (RC). Como resultado, se propone un esquema en línea de detección y localización de fallas, basado en la simetría estructural de interrelación y la dinámica no distinguible del modelo de red compleja. Además, se implementa un segundo esquema que se basa en la detección de una falla, a través de la observación de un cambio abrupto (producido por la falla) en la derivada de i-ésimo orden de las variables de estado, de una red de sistemas Lineales e Invariantes en el tiempo (LIT). En este contexto, un sistema de monitoreo en línea y adquisición de señales es desarrollado para validar los esquemas antes descritos en una Línea de Proceso de Enlatado (LPE). Los resultados teóricos y experimentales validan los esquemas y confirman la existencia de fenómenos como auto regulación, simetría y organización, en los sistemas de manufactura., Este trabajo fue apoyado por el Consejo Nacional de Ciencia y Tecnología CONACyT, con el número de becario 743557; y el TecNM/Instituto Tecnológico de Aguascalientes.

Urea is an added value chemical with wide applications in the industry and agriculture. The release of urea waste to the environment affects ecosystem health despite its low toxicity. Online monitoring of urea for industrial applications and environmental health is an unaddressed challenge. Electroanalytical techniques can be a smart integrated solution for online monitoring if sensors can overcome the major barrier associated with long-term stability. Mixed metal oxides have shown excellent stability in environmental conditions with long lasting operational lives. However, these materials have been barely explored for sensing applications. This work presents a proof of concept that demonstrates the applicability of an indirect electroanalytical quantification method of urea. The use of Ti/RuO2-TiO2-SnO2 dimensional stable anode (DSA®) can provide accurate and sensitive quantification of urea in aqueous samples exploiting the excellent catalytic properties of DSA® on the electrogeneration of active chlorine species. The cathodic reduction of accumulated HClO/ClO− from anodic electrogeneration presented a direct relationship with urea concentration. This novel method can allow urea quantification with a competitive LOD of 1.83 × 10−6 mol L−1 within a linear range of 6.66 × 10−6 to 3.33 × 10−4 mol L−1 of urea concentration.

The detection of nitrate pollutants is a widely used strategy for protecting water sources. Although ion-selective electrodes (ISEs) have been considered for the determination of ion concentrations in water, the accuracy of ISE technology decreases owing to the signal drift and decreasing sensitivity over time. The objectives of the present study were: (1) to develop an online water monitoring system mainly consisting of an Arduino board-based Internet-of-Things (IoT) device and nitrate ISEs, and (2) to propose a self-diagnostic function for monitoring and reporting the condition of the ISEs. The developed system communicates with the cloud server by using the message queuing telemetry transport (MQTT) protocol and provides monitoring information through the developed cloud-based webpage. In addition, the online monitoring system provides information on the electrode status, which is determined based on a self-diagnostic index (SDI, with a range of 0–100) of the electrode drift and sensitivity. The diagnostic method for monitoring and reporting the electrode status was validated in a one-month-long laboratory test followed by a field test in a stream near an agricultural facility. Moreover, a self-diagnostic index (SDI) was applied in the final field experiments with an accuracy of 0.77.

Spatial and short-term temporal changes in water quality as a result of water age and fluctuating hydraulic conditions were investigated in a drinking water distribution system. Online measurements of total and intracellular adenosine tri-phosphate (ATP), total and intact cell concentrations measured with flow cytometry (FCM), turbidity, and particle counts were performed over five weeks at five subsequent locations of the distribution system. The high number of parallel FCM and ATP measurements revealed the combined effect of water age and final disinfection on spatial changes in microbiology in the system. The results underlined that regular daily dynamics in flow velocities are normal and inevitable in drinking water distribution systems, and significantly impact particle counts and turbidity. However, hydraulic conditions had no detectable impact on the concentration of suspended microbial cells. A weak correlation between flow velocity and ATP concentrations suggests incidental resuspension of particle-bound bacteria, presumably caused by either biofilm detachment or resuspension from sediment when flow velocities increase. The highly dynamic hydraulic conditions highlight the value of online monitoring tools for the meaningful description of short-term dynamics (day-scale) in drinking water distribution systems.

A novel concept for online monitoring of nitrosamines, solvent amines and their degradation products in amine absorber emissions to air was demonstrated at the Tiller CO2-lab pilot facility. The monitoring concept is based on SINTEF patent No. PCT/EP2011/073557. The measurement method applies gas sampling by capture of analytes in a condensate stream from a single stage condensate collector unit. An improved design for the SINTEF prototype for online gas and liquid measurements has been established as part of the CCUS-ALIGN project. The new design has low complexity and improved robustness, making it applicable as integrated part of industrial monitoring systems. The established prototype was successfully tested for monitoring of trace gas emission from a CO2 capture pilot plant, demonstrating measurements of nitrosamines at levels far below the lower detection limits of commercial industrial online analyzers. Results from testing of a condensate collector prototype indicate high capture efficiency for analytes of interest, including analytes present in aerosols during operation conditions where the absorber emit mist to the atmosphere. The measurement concept has potential for significantly reducing the costs related to manual gas measurements for critical trace gas components in plant operation. Application of the concept can enable continuous measurements of nitrosamines and other critical trace gas analytes in the emissions to air not currently available in absorption-based CO2 capture processes.

Near-real-time event detection is crucial for water utilities to be able to detect failure events in their water treatment works (WTW) quickly and efficiently. This paper presents a new method for an automated, near-real-time recognition of failure events at WTWs by the application of combined statistical process control and machine-learning techniques. The resulting novel hybrid CUSUM event recognition system (HC-ERS) uses two distinct detection methodologies: one for fault detection at the level of individual water quality signals and the second for the recognition of faulty processes at the WTW level. HC-ERS was tested and validated on historical failure events at a real-life UK WTW. The new methodology proved to be effective in the detection of failure events, achieving a high true-detection rate of 82% combined with a low false-alarm rate (average 0.3 false alarms per week), reaching a peak F1 score of 84% as a measure of accuracy. The new method also demonstrated higher accuracy compared with the CANARY detection methodology. When applied to real-world data, the HC-ERS method showed the capability to detect faulty processes at WTW automatically and reliably, and hence potential for practical application in the water industry. HIGHLIGHTS The novel HC-ERS combines the conventional SPC-type method with RF advanced machine-learning technique to ultimately detect WTW-level failure events.; When applied on unseen data HC-ERS proved to be capable of detecting failure events in WTW processes in near-real-time.; HC-ERS outperformed threshold-based and CANARY event detection methods.; HC-ERS showed potential for practical application in the water industry.

Anaerobic digestion is a chemical process whose purpose is to maximize biogas production whilst concomitantly treating organic waste mostly through co-digestion due to the variety of substrates. To avoid failures, the process requires the monitoring of several parameters and / or inhibitors. The existing strategies and methods used in the process monitoring still lack sensitivity and robustness, when taken individually. The current study investigated the use of sequential and orthogonalized partial least squares (SO-PLS) regression to relate these parameters to several blocks of data coming for near infrared spectroscopy, chemical routine analysis and kinetics of biogas production. The models produced were able to extract relevant information from each block’s data and discard redundancies. Moreover, to meet biogas plant operators’ requirements, variable selection was performed on the infrared blocks using a recent method: SO-CovSel. SO-CovSel is a method resulting from coupling SO-PLS and Covariance Selection (CovSel) method. The method has been demonstrated to be suitable for multi-response calibration purposes with infrared calibration. It has provided good predictions and an interesting interpretation of wavelengths involved in the monitoring of the relevant parameters of stability in anaerobic co-digestion.

In the last two decades, food scientists have attempted to develop new technologies that can improve the detection of insect infestation in fruits and vegetables under postharvest conditions using a multitude of non-destructive technologies. While consumers’ expectations for higher nutritive and sensorial value of fresh produce has increased over time, they have also become more critical on using insecticides or synthetic chemicals to preserve food quality from insects’ attacks or enhance the quality attributes of minimally processed fresh produce. In addition, the increasingly stringent quarantine measures by regulatory agencies for commercial import–export of fresh produce needs more reliable technologies for quickly detecting insect infestation in fruits and vegetables before their commercialization. For these reasons, the food industry investigates alternative and non-destructive means to improve food quality. Several studies have been conducted on the development of rapid, accurate, and reliable insect infestation monitoring systems to replace invasive and subjective methods that are often inefficient. There are still major limitations to the effective in-field, as well as postharvest on-line, monitoring applications. This review presents a general overview of current non-destructive techniques for the detection of insect damage in fruits and vegetables and discusses basic principles and applications. The paper also elaborates on the specific post-harvest fruit infestation detection methods, which include principles, protocols, specific application examples, merits, and limitations. The methods reviewed include those based on spectroscopy, imaging, acoustic sensing, and chemical interactions, with greater emphasis on the noninvasive methods. This review also discusses the current research gaps as well as the future research directions for non-destructive methods’ application in the detection and classification of insect infestation in fruits and vegetables.

Condition based assessment of OLTCs has become more popular in recent years, and the importance of reliable and accurate diagnostic techniques is being realized. The work described in this paper aims to improve existing diagnostic techniques, develop new ones and combine some techniques (hybrid) in order to realize a highly reliable set of diagnostics for tap changers. Topics addressed in this paper include motor power measurement, dynamic resistance measurement and vibro-acoustic measurement, the latter designed and tested as part of this project. Preliminary results show that in particular a combination of aforementioned techniques may lead to improved condition assessment and may lead towards automated and online monitoring of tap changer operation.

Nature-based solutions, such as Constructed Wetlands (CWs), for the treatment of industrial wastewater can be more efficiently operated making use of online monitored parameters as inlet/outlet flows and concentrations for specific substances. The present study compares different datasets acquired in a two-and-a-half-year-long period by normal laboratory methods and also from a specific COD/BOD sensor installed at a winery CWs wastewater treatment plant in Tuscany, Italy. The CW wastewater treatment plant (WWTP) is composed of: equalization tank (70 m3), French Reed Bed (1200 m2), horizontal subsurface flow (HF) CW (960 m2): free water system (850 m2), optional post-treatment sand filter (50 m2), and emergency recirculation. The obtained average performances for this last period are for COD 97.5%, for MBAS 93.1%, for N-NO2- 84.7%, for NO3- 39.9%, and for TP 45.5%. The online sensor has shown excellent performance in following the COD concentration patterns along the observed period. The qualitative and quantitative validity of the online sensor measurements has been assessed by statistical analysis (t-test) and reported in the paper. Online data, acquired every 30 min, availability is of extreme importance for the CW system performance optimization, for understanding the behavior of the WWTP in different operative scenarios, and finally for driving the powering on or off eventual process enhancement tools.

Process optimization and quality control are important issues in cold spraying and coating development. Because the cold spray processing is based on high kinetic energy by high particle velocities, online spray monitoring of particle inflight properties can be used as an assisting process tool. Particle velocities, their positions in the spray jet, and particle size measurements give valuable information about spraying conditions. This, in turn, improves reproducibility and reliability of coating production. This study focuses on cold spraying of Al6061 material and the connections between particle inflight properties and coating characteristics such as structures and mechanical properties. Furthermore, novel 2D velocity scan maps done with theHWCS2 online spray monitoring system are presented as an advantageous powder and spray condition controlling tool. Cold spray processing conditions were similar using different process parameters, confirmed with the online spray monitoring prior to coating production. Higher particle velocities led to higher particle deformation and thus, higher coating quality, denser structures, and improved adhesions. Also, deposition efficiency increased significantly by using higher particle velocities. publishedVersion

A case study of applying chemometrics approach, k-means, a clustering algorithm to develop a real-time industrial process early warning system using online measurements was conducted. An online spectrophotometer was installed for an eighteen-month monitoring study between 2013 and 2015 at the inlet of a wastewater treatment plant. During this time a web-based prototype portal with data integration, visualization, prediction and anomaly detection functions for complex online data sets was developed in-house to assess the spectral data acquired by the spectrophotometer together with other databases (such as rainfall and temperature). Several chemometrics options, such as association analysis and feature selection, were used to extract useful operational information from the acquired data. In this paper, the anomaly detection function which includes pattern learning and comparison algorithms and a powerful user interface was described in detail. By using the functions, process upsets were successfully detected from the spectral data at the inlet of the treatment plant. The detected events/upsets were then compared with the treatment plant logs and they were found aligned well, which proved that the anomaly detection technique was effective and has the potential to inform decision to assist plant operators. In addition, the proposed anomaly detection technique is also a flexible algorithm which works with any similar time series data to detect other process related issues to provide real-time warning to support treatment plant operations Refereed/Peer-reviewed

Desalinated seawater enters the urban water supply network on a large scale, which brings new challenges to water quality assurance. In order to strengthen the safety supervision of the pipeline network, ensure the stability of water quality, prevent pipeline corrosion, and avoid the “red water” problem, this study constructed a safety supervision system for desalinated seawater entering the urban water supply pipeline network. In this system, the on-line monitoring system can monitor water quality, water quantity, water pressure and the corrosion of pipeline network in real-time. Early warning system can quickly identify problems and initiate based on the threshold exceeding, statistical analysis, and model prediction. The safety regulation system (including water source regulation system, water quality adjustment system and operation management system) is used to regulate and control water quality problems in the urban water supply network. The application of this safety supervision system is conducive to improving regulation efficiency and ensuring water supply safety.

Due to the constant changes of the environment and load, the insulated-gate bipolar transistor (IGBT) module is subjected to a large amount of junction temperature (Tj) fluctuations, which often leads to damage to the bond wires. The monitoring parameters of IGBTs are often coupled with Tj, which increases the difficulty of monitoring IGBTs’ health status online. In this paper, based on the collector current (Ic) and collector-emitter on-state voltage (Vce_on) online monitoring circuit, an online monitoring method of IGBT bond wire aging against interference is proposed. First, the bond wire aging model is established, and the Vce_on is selected as the monitoring parameter. Secondly, taking a three-phase inverter circuit as an example, the Vce_on and Ic waveforms of the IGBT module are monitored in real time, and the process of online monitoring is introduced accordingly. Finally, the experimental results output by RT-LAB indicate that the method proposed in this paper can accurately identify the aging state of IGBT bond wires under different conditions.

The production of active pharmaceutical ingredients (APIs) is currently undergoing its biggest transformation in a century. The changes are based on the rapid and dramatic introduction of protein- and macromolecule-based drugs (collectively known as biopharmaceuticals) and can be traced back to the huge investment in biomedical science (in particular in genomics and proteomics) that has been ongoing since the 1970s. Biopharmaceuticals (or biologics) are manufactured using biological-expression systems (such as mammalian, bacterial, insect cells, etc.) and have spawned a large (>E35 billion sales annually in Europe) and growing biopharmaceutical industry (BioPharma). The structural and chemical complexity of biologics, combined with the intricacy of cell-based manufacturing, imposes a huge analytical burden to correctly characterize and quantify both processes (upstream) and products (downstream). In small molecule manufacturing, advances in analytical and computational methods have been extensively exploited to generate process analytical technologies (PAT) that are now used for routine process control, leading to more efficient processes and safer medicines. In the analytical domain, biologic manufacturing is considerably behind and there is both a huge scope and need to produce relevant PAT tools with which to better control processes, and better characterize product macromolecules. Raman spectroscopy, a vibrational spectroscopy with a number of useful properties (nondestructive, non-contact, robustness) has significant potential advantages in BioPharma. Key among them are intrinsically high molecular specificity, the ability to measure in water, the requirement for minimal (or no) sample pre-treatment, the flexibility of sampling configurations, and suitability for automation. Here, we review and discuss a representative selection of the more important Raman applications in BioPharma (with particular emphasis on mammalian cell culture). The review shows that the properties of Raman have been successfully exploited to deliver unique and useful analytical solutions, particularly for online process monitoring. However, it also shows that its inherent susceptibility to fluorescence interference and the weakness of the Raman effect mean that it can never be a panacea. In particular, Raman-based methods are intrinsically limited by the chemical complexity and wide analyte-concentration-profiles of cell culture media/bioprocessing broths which limit their use for quantitative analysis. Nevertheless, with appropriate foreknowledge of these limitations and good experimental design, robust analytical methods can be produced. In addition, new technological developments such as time-resolved detectors, advanced lasers, and plasmonics offer potential of new Raman-based methods to resolve existing limitations and/or provide new analytical insights. KB is a Government of Ireland Postdoctoral Fellow and would like to thank the Irish Research Council for their support (Grant no.: GOIPD/2015/88). Some support for KB from the Synthesis and Solid State Pharmaceutical Centre, funded by Science Foundation Ireland and industry partners (Grant no.: 12/RC/2275) is also acknowledged. peer-reviewed

In the process of electron beam freeform fabrication (EBF3), due to the continuous change of thermal conditions and variability in wire feeding in the deposition process, geometric deviations are generated in the deposition of each layer. In order to prevent the layer-by-layer accumulation of the deviation, it is necessary to perform online geometry measurement for each deposition layer, based on which the error compensation can be done for the previous deposition layer in the next deposition layer. However, the traditional three-dimensional reconstruction method that employs structured laser cannot meet the requirements of long-term stable operation in the manufacturing process of EBF3. Therefore, this paper proposes a method to measure the deposit surfaces based on the position information of electron beam speckle, in which an electron beam is used to bombard the surface of the deposit to generate the speckle. Based on the structured information of the electron beam in the vacuum chamber, the three-dimensional reconstruction of the surface of the deposited parts is realized without need of additional structured laser sensor. In order to improve the detection accuracy, the detection error is theoretically analyzed and compensated. The absolute error after compensation is smaller than 0.1 mm, and the precision can reach 0.1%, which satisfies the requirements of 3D reconstruction of the deposited parts. An online measurement system is built for the surface of deposited parts in the process of electron beam freeform fabrication, which realizes the online 3D reconstruction of the surface of the deposited layer. In addition, in order to improve the detection stability of the whole system, the image processing algorithm suitable for this scene is designed. The reliability and speed of the algorithm are improved by ROI extraction, threshold segmentation, and expansion corrosion. In addition, the speckle size information can also reflect the thermal conditions of the surface of the deposited parts. Hence, it can be used for online detection of defects such as infusion and voids.

Aluminium coatings that are formed by physical vapour deposition (PVD) on rolled steel products are more resistant to atmospheric and seawater corrosion than zinc coatings. We developed a coating thickness analyzer (CTA) with an X-ray fluorescence (XRF) measuring head, that is integrated into the PVD pilot line. In this study, to conduct measurements of elements with atomic numbers less than 20 while avoiding the problem of registration of light elements, the measuring head was integrated into a process vacuum chamber to maintain a vacuum during the measurements. To validate the proposed tool, cold-rolled steel strips of different grades are used as substrates, and aluminium was deposited on the surface via PVD in thicknesses ranging from 1 to 20 g/m2. The thin-film thickness measurements during a pre-acceptance test were found to have a relative accuracy of less than 5% and a relative precision of less than 1% &ndash, 2%. The proposed CTA can be readily integrated in the factory&rsquo, s automatic process control system and the real-time measurements in operating and calibration modes, and the status of all spectrometric equipment (X-ray tube, detector etc.) can be transmitted to the upper-level computer. Thus, the process engineer can properly control the deposition process.

Microbial cell factories 18(78), 16 (2019). doi:10.1186/s12934-019-1126-9, Published by Biomed Central, London

This paper describes an automatic sampling system for anaerobic reactors that allows taking representative samples following the guidelines of Gy&rsquo, s (1998) theory of sampling. Due to the high heterogeneity degree in a digester the sampling errors are larger than the analysis error, making representative sampling a prerequisite for successful process control. In our system, samples are automatically processed, generating a higher density of data and avoiding human error by sample manipulation. The combination of a representative sampling system with a commercial automate titration unit generates a robust online monitoring system for biogas plants. The system was successfully implemented in an operating biogas plant to control a feeding-on-demand biogas system.

An integrated DC/DC converter with online monitoring of the degradation induced by hot-carrier stress (HCD) in new generation power LDMOS transistors is proposed. In particular, when a relatively high drain voltage is applied during on-state regime (switching phase), degradation mechanisms lead to an increase of the transistor on-resistance (R ON ). To this purpose, the converter is able to dynamically estimate the R ON of the power LDMOS and to provide its value to the user during normal operation. The presented solution, developed in STMicroelectronics 90nm BCD technology, features a non-invasive current sensing and voltage sampling architecture, which is applied to a common DC/DC boost converter to evaluate the resistance of the power LDMOS. Without lack of generality, this specific sensing structure can be applied to any kind of converter, e.g. buck or buck-boost, as it does not require any change in the main conversion circuit.

The paper deals with the potential of employing accompanying physical phenomena, acoustic emissions, during monitoring of abrasive water jet disintegration of rotating workpiece. It focuses on the acquisition of theoretical knowledge about this technology with the aid of SEM surface analysis. Variation in traverse speed of the cutting head is used during the experiments. All values were obtained during experimental materials turning by AWJ method. The surfaces were scanned using optical profilometer MicroProf FRT to obtain surface roughness parameters such as Ra (10.75 µm–22.5 µm), Rq (13.75 µm–28.25 µm) and Rz (88 µm–166 µm). The result includes the possibility of on-line control in the form of an adaptive connection, which applies information gathered by an array of sensors and its transformation into a digital form. The acquired signals represent that with increase in traverse speed, the signal intensities decrease due to shorter interaction time. SEM images provide characteristics of surfaces created by HADRO process such as craters, peaks and valleys, micro-cracks and striations marks.

Biotechnology progress (2019). doi:10.1002/btpr.2911, Published by Wiley, Malden, MA

Herein, we reported a homemade waveguide-based evanescent wave aptasensor for the facile online monitoring of mercury pollution. The aptasensor exploited the high selectivity of hairpin structure-based thymidine–Hg2+–thymidine coordination chemistry (T–T mismatch) for Hg2+ recognition and the stably regenerable capability of DNA-functionalized waveguide surfaces. The presence of Hg2+ caused the T–T mismatch of Cy5.5-labeled T-rich single-stranded DNA sequences. The formed hairpin structures blocked the further hybridization of T-rich single-stranded DNA sequences with the complementary DNA strands that are modified on the waveguide surface; this phenomenon was accompanied by the decrease in the fluorescent signals excited by the evanescent wave. The limit of detection in real water samples was determined to be 0.2 μg/L, which was comparable with that of 0.4 μg/L in an ultrapure water under controlled conditions. And the linear range was observed from 1.4 µg/L to 240.7 µg/L. The negligible environmental matrix effect on the performance ensured the reliability of the proposed aptasensor. Moreover, the cross reactivity of this method toward other investigated metal ions was negligible. Through the delicate surface modification with DNA molecules covalently, the chip was reused at least 31 times with a relative standard deviation (RSD) of less than 19%. A Hg2+ pollution accident was successfully detected within 30 min, shedding new light in pollution monitoring, environment restoration, and emergency treatment.

The event mean concentrations (EMCs) that would have been obtained by four different stormwater sampling strategies are simulated by using total suspended solids (TSS) and flowrate time series (about one minute time-step and one year of data). These EMCs are compared to the reference EMCs calculated by considering the complete time series. The sampling strategies are assessed with datasets from four catchments: (i) Berlin, Germany, combined sewer overflow (CSO); (ii) Graz, Austria, CSO; (iii) Chassieu, France, separate sewer system; and (iv) Ecully, France, CSO. A sampling strategy in which samples are collected at constant time intervals over the rainfall event and sampling volumes are pre-set as proportional to the runoff volume discharged between two consecutive sample leads to the most representative results. Recommended sampling time intervals are of 5 min for Berlin and Chassieu (resp. 100 and 185 ha area) and 10 min for Graz and Ecully (resp. 335 and 245 ha area), with relative sampling errors between 7% and 20% and uncertainties in sampling errors of about 5%. Uncertainties related to sampling volumes, TSS laboratory analyses and beginning/ending of rainstorm events are reported as the most influent sources in the uncertainties of sampling errors and EMCs.

Microbiological water quality is traditionally assessed using culture-based enumeration of faecal indicator bacteria such as Escherichia coli. Despite their relative ease of use, these methods require a minimal 18-24 h-incubation step before the results are obtained. This study aimed to assess the suitability of an autonomous online fluorescence-based technology measuring β-glucuronidase (GLUC) activity for rapid near-real time monitoring of E. coli in water. The analytical precision was determined and compared to an automated microbial detection system, two culture-based assays and quantitative real-time PCR (qPCR). Using replicate measurements of grab samples containing E. coli concentrations between 50 and 2330 CFU.100 mL−1, the autonomous GLUC activity measurement technology displayed an average coefficient of variation (CV) of less than 5% that was 4–8-fold lower than other methods tested. Comparable precision was observed during online in situ monitoring of GLUC activity at a drinking water intake using three independent instruments. GLUC activity measurements were not affected by sewage or sediments at concentrations likely to be encountered during long-term monitoring. Furthermore, significant (p < 0.05) correlations were obtained between GLUC activity and the other assays including defined substrate technology (r = 0.77), membrane filtration (r = 0.73), qPCR (r = 0.55) and the automated microbial detection system (r = 0.50). This study is the first to thoroughly compare the analytical performance of rapid automated detection technologies to established culture and molecular-based methods. Results show that further research is required to correlate GLUC activity to the presence of viable E. coli as measured in terms of CFU.100 mL−1. This would allow the use of autonomous online GLUC activity measurements for rapid E. coli monitoring in water supplies used for drinking water production and recreation., SCOPUS: ar.j, info:eu-repo/semantics/published

Fine particulate matter (PM2.5) has a small particle size, which allows it to directly enter the respiratory mucosa and reach the alveoli and even the blood. Many countries are already aware of the adverse effects of PM2.5, and determination of the sources of PM2.5 is a critical step in reducing its concentration to protect public health. This study monitored PM2.5 in the summer (during the southwest monsoon season) of 2017. Three online monitoring systems were used to continuously collect hourly concentrations of key chemical components of PM2.5, including anions, cations, carbon, heavy metals, and precursor gases, for 24 h per day. The sum of the concentrations of each compound obtained from the online monitoring systems is similar to the actual PM2.5 concentration (98.75%). This result suggests that the on-line monitoring system of this study covers relatively complete chemical compounds. Positive matrix factorization (PMF) was adopted to explore and examine the proportion of each source that contributed to the total PM2.5 concentration. According to the source contribution analysis, 55% of PM2.5 can be attributed to local pollutant sources, and the remaining 45% can be attributed to pollutants emitted outside Taipei City. During the high-PM2.5-concentration (episode) period, the pollutant conversion rates were higher than usual due to the occurrence of vigorous photochemical reactions. Moreover, once pollutants are emitted by external stationary pollutant sources, they move with pollution air masses and undergo photochemical reactions, resulting in increases in the secondary pollutant concentrations of PM2.5. The vertical monitoring data indicate that there is a significant increase in PM2.5 concentration at high altitudes. High-altitude PM2.5 will descend to the ground and thereby affect the ground-level PM2.5 concentration.

2-cyano-2-propyl dithiobenzoates (CPDB)-mediated reversible addition-fragmentation chain transfer (RAFT) polymerization was monitored by online flow microreactor/mass spectrometry. This enabled the reactions to be followed in a time-resolved manner, closely resolving product patterns in the reaction mixtures at any point in time. RAFT polymerization was investigated for low RAFT to monomer ratios, enabling the monitoring of the early stages of a typical RAFT polymerization. The expected transition from pre- to the RAFT main equilibrium is observed. However, very high abundancies for cross-termination products were also identified, both in the pre- and main equilibrium stage. This is a somewhat surprising result as such products have always been expected, but to date have not been observed in the majority of studies. Product isolation and NMR analysis revealed that cross-termination occurs in the para position of the benzoate ring and becomes fully irreversible via re-aromatization of the ring in a H-shift reaction. The present data suggest a pronounced chain-length dependence of the cross-termination reaction, which would explain why the products are seen here, but not in other studies. This research received no external funding. The authors are grateful for provision of the mass spectrometer via the Hercules fund, Belgium.

The implementation of damage-detection methods for continuously assessing structural integrity entails systems with attractive features such as storage capabilities, memory capacity, computational complexity and time-consuming processing. In this sense, embedded hardware platforms are a promising technology for developing integrated solutions in Structural Health Monitoring. In this paper, design, test, and specifications for a standalone inspection prototype are presented, which take advantage of piezo-diagnostics principle, statistical processing via Principal Component Analysis (PCA) and embedded systems. The equipment corresponds to a piezoelectric active system with the capability to detect defects in structures, by using a PCA-based algorithm embedded in the Odroid-U3 ARM Linux platform. The operation of the equipment consists of applying, at one side of the structure, wide guided waves by means of piezoelectric devices operated in actuation mode and to record the wave response in another side of the structure by using the same kind of piezoelectric devices operated in sensor mode. Based on the nominal response of the guide wave (no damages), represented by means of a PCA statistical model, the system can detect damages between the actuated/sensed points through squared prediction error (Q-statistical index). The system performance was evaluated in a pipe test bench where two kinds of damages were studied: first, a mass is added to the pipe surface, and then leaks are provoked to the pipe structure by means of a drill tool. The experiments were conducted on two lab structures: (i) a meter carbon-steel pipe section and (ii) a pipe loop structure. The wave response was recorded between the instrumented points for two conditions: (i) The pipe in nominal conditions, where several repetitions will be applied to build the nominal statistical model and (ii) when damage is caused to the pipe (mass adding or leak). Damage conditions were graphically recognized through the Q-statistic chart. Thus, the feasibility to implement an automated real-time diagnostic system is demonstrated with minimum processing resources and hardware flexibility.

BMC plant biology 18(1), 101-114 (2018). doi:10.1186/s12870-018-1305-6, Published by BioMed Central, London

A large class of sequential change point tests are based on estimating functions where estimation is computationally efficient as (possibly numeric) optimization is restricted to an initial estimation. This includes examples as diverse as mean changes, linear or non-linear autoregressive and binary models. While the standard cumulative-sum-detector (CUSUM) has recently been considered in this general setup, we consider several modifications that have faster detection rates in particular if changes do occur late in the monitoring period. More presicely, we use three different types of detector statistics based on partial sums of a monitoring function, namely the modified moving-sum-statistic (mMOSUM), Page’s cumulative-sum-statistic (Page-CUSUM) and the standard moving-sum-statistic (MOSUM). The statistics only differ in the number of observations included in the partial sum. The mMOSUM uses a bandwidth parameter which multiplicatively scales the lower bound of the moving sum. The MOSUM uses a constant bandwidth parameter, while Page-CUSUM chooses the maximum over all possible lower bounds for the partial sums. So far, the first two schemes have only been studied in a linear model, the MOSUM only for a mean change. We develop the asymptotics under the null hypothesis and alternatives under mild regularity conditions for each test statistic, which include the existing theory but also many new examples. In a simulation study we compare all four types of test procedures in terms of their size, power and run length. Additionally we illustrate their behavior by applications to exchange rate data as well as the Boston homicide data.

International audience; The aim of this study is to investigate the potential of ultraviolet/visible (UV/Vis) spectrometry as a complementary method for routine monitoring of reclaimed water production. Robustness of the models and compliance of their sensitivity with current quality limits are investigated. The following indicators are studied: total suspended solids (TSS), turbidity, chemical oxygen demand (COD) and nitrate. Partial least squares regression (PLSR) is used to find linear correlations between absorbances and indicators of interest. Artificial samples are made by simulating a sludge leak on the wastewater treatment plant and added to the original dataset, then divided into calibration and prediction datasets. The models are built on the calibration set, and then tested on the prediction set. The best models are developed with: PLSR for COD (R-pred(2) = 0.80), TSS (R-pred(2) = 0.86) and turbidity (R-pred(2) = 0.96), and with a simple linear regression from absorbance at 208 nm (R-pred(2) = 0.95) for nitrate concentration. The input of artificial data significantly enhances the robustness of the models. The sensitivity of the UV/Vis spectrometry monitoring system developed is compatible with quality requirements of reclaimed water production processes.

The online and accurate monitoring of drinking water supply networks is critically in demand to rapidly detect the accidental or deliberate contamination of drinking water. At present, miniaturized water quality monitoring sensors developed in the laboratories are usually tested under ambient pressure and steady-state flow conditions; however, in Water Distribution Systems (WDS), both the pressure and the flowrate fluctuate. In this paper, an interface is designed and fabricated using additive manufacturing or 3D printing technology—material extrusion (Trade Name: fused deposition modeling, FDM) and material jetting—to provide a conduit for miniaturized sensors for continuous online water quality monitoring. The interface is designed to meet two main criteria: low pressure at the inlet of the sensors and a low flowrate to minimize the water bled (i.e., leakage), despite varying pressure from WDS. To meet the above criteria, a two-dimensional computational fluid dynamics model was used to optimize the geometry of the channel. The 3D printed interface, with the embedded miniaturized pH and conductivity sensors, was then tested at different temperatures and flowrates. The results show that the response of the pH sensor is independent of the flowrate and temperature. As for the conductivity sensor, the flowrate and temperature affect only the readings at a very low conductivity (4 µS/cm) and high flowrates (30 mL/min), and a very high conductivity (460 µS/cm), respectively.

Composite materials are becoming ever more popular and being used in an increasing number of applications. This because, to meet the users' demand, it is possible to create a new material of given characteristics in a quite simple way by changing either the type of matrix, or reinforcement. Of course, any new material requires characterization for its appropriate exploitation. In this context, infrared thermography (IRT) represents a viable means since it is non-contact, non-intrusive and can be used either for non-destructive evaluation to detect manufacturing defects, or fatigue induced degradation, or else for monitoring online the response to applied loads. In this work, IRT is used to investigate different types of composite materials which are based on either a thermoset, or a thermoplastic matrix, which may be neat, or modified by addition of a percentage of a specific compatibilizing agent, and reinforced with carbon, glass, or jute fibers. IRT is used with a twofold function. First, to non-destructively evaluate, with the lock-in technique, materials before and after impact to either assure absence of manufacturing defects, or discover the damage caused by the impact. Second, IRT is used to visualize thermal effects, which develop when the material is subjected to impact. The obtained results show that it is possible to follow the material bending, delamination and eventual failure under impact and get information, which may be valuable to deepen the complex impact damaging mechanisms of composites.

Contact erosion is one of the most crucial factors affecting the electrical service lifetime of high-voltage circuit breakers (HVCBs). On-line monitoring the contacts’ erosion degree is increasingly in demand for the sake of condition based maintenance to guarantee the functional operation of HVCBs. A spectroscopic monitoring system has been designed based upon a commercial 245 kV/40 kA S F 6 live tank circuit breaker with copper–tungsten (28 wt % and 72 wt %) arcing contacts at atmospheric S F 6 pressure. Three optical-fibre based sensors are used to capture the time-resolved spectra of arcs. A novel approach using chromatic methods to process the time-resolved spectral signal has been proposed. The processed chromatic parameters have been interpreted to show that the time variation of spectral emission from the contact material and quenching gas are closely correlated to the mass loss and surface degradation of the plug arcing contact. The feasibility of applying this method to online monitoring of contact erosion is indicated.

Poly(lactic acid) (PLA) is receiving ever more attention from both the academic and the industrial communities because it is green, biobased, and complies well with requirements for work safety and environmental safeguards. However, a question may arise regarding the suitability of PLA in replacing conventional plastics. The response requires a complete material characterization and analysis of its performance in service and its resistance to impact loads. This work is focused on monitoring with infrared thermography the impact damage of a biobased thermoplastic composite, in this case a poly(lactic acid) (PLA) matrix reinforced with jute fibers. The visualization of thermal signatures that develop under impact supplies information useful to understanding the material impact damage mechanisms, such as formation of cracks and their propagation and the overall extension of damage. © 2017 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2017, 134, 45579.

The current state of the art of polymer synthesis in (microstructured) continuous-flow reactors is given, focusing on controlled/ living polymerization methods that allow for precision polymer design. Emerging trends and the most notable developments are discussed. Especially, the field of multistep reactions and online monitoring are highlighted, which in combination may give access to fully automated high-throughput polymer synthesis reactors in the future. T. J. wishes to thank the Fonds Wetenschappelijk Onderzoek (FWO) for a research grant.

Most power transformers operating in a power system possess oil-paper insulation. A serious defect of this type of insulation, which is associated with long operation time, is an increase in the moisture content. Moisture introduces a number of threats to proper operation of the transformer, e.g., ignition of partial discharges (PDs). Due to the varying temperature of the insulation system during the unit’s normal operation, a dynamic change (migration of water) takes place, precipitating the oil-paper system from a state of hydrodynamic equilibrium. This causes the PDs to be variable in time, and they may intensify or extinguish. Studies on model objects have been conducted to determine the conditions (temperature, humidity, time) that will have an impact on the ignition and intensity of the observed phenomenon of PDs. The conclusions of this study will have a practical application in the evaluation of measurements conducted in the field, especially in relation to the registration of an online PD monitoring system.

Past waterborne outbreaks have demonstrated that informed vulnerability assessment of drinking water supplies is paramount for the provision of safe drinking water. Although current monitoring frameworks are not designed to account for short-term peak concentrations of fecal microorganisms in source waters, the recent development of online microbial monitoring technologies is expected to fill this knowledge gap. In this study, online near real-time monitoring of β-D-glucuronidase (GLUC) activity was conducted for 1.5 years at an urban drinking water intake impacted by multiple point sources of fecal pollution. Parallel routine and event-based monitoring of E. coli and online measurement of physico-chemistry were performed at the intake and their dynamics compared over time. GLUC activity fluctuations ranged from seasonal to hourly time scales. All peak contamination episodes occurred between late fall and early spring following intense rainfall and/or snowmelt. In the absence of rainfall, recurrent daily fluctuations in GLUC activity and culturable E. coli were observed at the intake, a pattern otherwise ignored by regulatory monitoring. Cross-correlation analysis of time series retrieved from the drinking water intake and an upstream Water Resource Recovery Facility (WRRF) demonstrated a hydraulic connection between the two sites. Sewage by-passes from the same WRRF were the main drivers of intermittent GLUC activity and E. coli peaks at the drinking water intake following intense precipitation and/or snowmelt. Near real-time monitoring of fecal pollution through GLUC activity enabled a thorough characterization of the frequency, duration and amplitude of peak contamination periods at the urban drinking water intake while providing crucial information for the identification of the dominant upstream fecal pollution sources. To the best of our knowledge, this is the first characterization of a hydraulic connection between a WRRF and a downstream drinking water intake across hourly to seasonal timescales using high frequency microbial monitoring data. Ultimately, this should help improve source water protection through catchment mitigation actions, especially in a context of de facto wastewater reuse., SCOPUS: ar.j, info:eu-repo/semantics/published

Pressure-driven membrane processes are often used for the separation and purification of organic compounds originating from biomass. However, membrane fouling remains a challenge as these bio-based streams have a very complex composition and comprise a high fouling tendency. Conventional, the fouling is monitored based on either a decrease in flux or an increase in pressure over time. Those conventional techniques provide no information on the location, composition or amount of fouling. As fouling is often cumulative, it will be detected as a loss of performance. Once fouling becomes irreversible, it is often not possible to clean the membrane without chemicals and the filtration/separation process has to be stopped eventually. In situ real-time monitoring of membrane fouling could provide dynamic information on the development of fouling allowing optimization of the process. This paper reviews the state of the art in in situ monitoring techniques that could be applied to membrane processes in the biotechnology, biorefinery and food sectors and briefly reflects on the current awareness of in situ monitoring techniques among experienced industrial users of membrane processes. The physical principles as well as the strengths and weaknesses are addressed, as well as potentially and promising techniques are identified. Post-print / Final draft

Introduction: End-stage renal disease (ESRD) patients depend on dialysis for removal of toxic waste products, fluid overload relief and maintenance of electrolyte balance. Dialysis prolongs millions of lives. To some extent, ESRD has become a manageable disease with a steadily growing dialysis population of increasing average age and associated comorbidity. During 7 decades many technical refinements have been developed e.g. sodium profiling, blood volume, ultrafiltration variation based on blood pressure measurement, urea kinetics etc. Despite its large potentials, in-line electrolyte monitoring lags behind in dialysis treatment.Areas covered: In this paper, we review the state of technologies available for in-line monitoring of the electrolytes sodium, potassium and calcium during hemodialysis.Expert commentary: We concluded that individual optimization of dialysate composition should be able to improve hard medical outcomes, but practical clinical implementation stands/falls with reliable and affordable in-line ion-selective sensing technology. Optical ion-selective microsensors and microsystems form a promising pathway for individualizing the dialysis treatment.

Stormwater runoff quality was measured with online turbidity sensors at four common types of small urban subcatchments: (i) a flat roof; (ii) a parking lot; (iii) a residential catchment; and (iv) a high-traffic street. Samples were taken to estimate site-specific correlations between total suspended solids (TSS) and turbidity. Continuous TSS time series were derived from online turbidity measurements and were used to estimate event loads and event mean concentrations. Rainfall runoff event characteristics were subjected to correlation analysis to TSS loads. Significant correlations were found for rainfall intensities at sites with high imperviousness and decrease with increasing catchment size. Antecedent dry weather periods are only correlated at the parking lot site. Intra-event TSS load distributions were studied with M (V)-curves. M (V)-curves are grouped at runoff quantiles and statistically described with boxplots. All sites show, in general, a more pronounced first-flush effect. While wash-off of the flat roof tends to be source-limited, the parking lot and high-traffic street sites show a more transport-limited behavior. Wash-off process of the residential catchment appears to be influenced by a composition of different subcatchments.

Ultra-high-frequency (UHF) partial discharge (PD) online monitoring is an effective way to inspect potential faults and insulation defects in power transformers. The construction of UHF PD online monitoring system is a challenge because of the high-frequency and wide-frequency band of the UHF PD signal. This paper presents a novel, intelligent sensor for UHF PD online monitoring based on a new method, namely a level scanning method. The intelligent sensor can directly acquire the statistical characteristic quantities and is characterized by low cost, few data to output and transmit, Ethernet functionality, and small size for easy installation. The prototype of an intelligent sensor was made. Actual UHF PD experiments with three typical artificial defect models of power transformers were carried out in a laboratory, and the waveform recording method and intelligent sensor proposed were simultaneously used for UHF PD measurement for comparison. The results show that the proposed intelligent sensor is qualified for the UHF PD online monitoring of power transformers. Additionally, three methods to improve the performance of intelligent sensors were proposed according to the principle of the level scanning method.

Accurate real-time process control is necessary to increase process efficiency, and optical sensors offer a competitive solution because they provide diverse system information in a noninvasive manner. We used an innovative scattered light sensor for the online monitoring of biomass during lactic acid production in a membrane bioreactor system because biomass determines productivity in this type of process. The upper limit of the measurement range in fermentation broth containing Bacillus coagulans was ~2.2 g·L(-1). The specific cell growth rate (µ) during the exponential phase was calculated using data representing the linear range (cell density ≤ 0.5 g·L(-1)). The results were consistently and reproducibly more accurate than offline measurements of optical density and cell dry weight, because more data were gathered in real-time over a shorter duration. Furthermore, µ(max) was measured under different filtration conditions (transmembrane pressure 0.3-1.2 bar, crossflow velocity 0.5-1.5 m·s(-1)), showing that energy input had no significant impact on cell growth. Cell density was monitored using the sensor during filtration and was maintained at a constant level by feeding with glucose according to the fermentation kinetics. Our novel sensor is therefore suitable for integration into control strategies for continuous fermentation in membrane bioreactor systems.

An immersion Raman probe was used in emulsion copolymerization reactions to measure monomer concentrations and particle sizes. Quantitative determination of monomer concentrations is feasible in two-monomer copolymerizations, but only the overall conversion could be measured by Raman spectroscopy in a four-monomer copolymerization. The feasibility of measuring monomer conversion and particle size was established using partial least-squares (PLS) calibration models. A simplified theoretical framework for the measurement of particle sizes based on photon scattering is presented, based on the elastic-sphere-vibration and surface-tension models.