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The new power system puts forward higher requirements for the functionality, real-time performance and reliability of relay protection equipment. Therefore, this paper designs a monitoring platform for the operation of relay protection equipment at distribution network side under the background of new power system. The platform obtains the running state of relay protection equipment by establishing simulation models of different types of relay protection equipment on the distribution network side. The fault time, fault type and current action of relay protection equipment at distribution network side are analyzed to realize the monitoring of operation state. At the same time, the visual representation method of monitoring data based on three-dimensional parallel scattergram and human-computer interaction is adopted for human-computer interaction, and the electromechanical protection device is controlled to realize current quick-break protection and overcurrent protection. The experimental results show that the platform can effectively monitor the operation of relay protection equipment on the distribution network side in real time and accurately judge the action of the equipment, and the application effect is good. [ABSTRACT FROM AUTHOR]

Abstract The new power system puts forward higher requirements for the functionality, real-time performance and reliability of relay protection equipment. Therefore, this paper designs a monitoring platform for the operation of relay protection equipment at distribution network side under the background of new power system. The platform obtains the running state of relay protection equipment by establishing simulation models of different types of relay protection equipment on the distribution network side. The fault time, fault type and current action of relay protection equipment at distribution network side are analyzed to realize the monitoring of operation state. At the same time, the visual representation method of monitoring data based on three-dimensional parallel scattergram and human-computer interaction is adopted for human-computer interaction, and the electromechanical protection device is controlled to realize current quick-break protection and overcurrent protection. The experimental results show that the platform can effectively monitor the operation of relay protection equipment on the distribution network side in real time and accurately judge the action of the equipment, and the application effect is good.

In the dynamic industrial sector, the ability to combine and manage data from various sources is essential. This study focuses on the utilization of the PI System to integrate operational data from multiple data sources at power plants, facilitating data driven decision making and enhancing operational efficiency. The application of the PI System in collecting data from Distributed Control Systems (DCS) and asset management systems like Maximo is examined, as well as its potential for integrating data from other power plant units. The study utilizes systems analysis methods to understand the potential of data integration in improving operational visibility and control. Findings from testing reveal that effective data integration can extend monitoring and management capabilities, indicating an overall improvement in operational performance. This study contributes to the literature on industrial data management by demonstrating the effective use of the PI System as a comprehensive tool for integrating data from various systems within power plants. It showcases the system's adaptability in enhancing operational decision-making and providing a cohesive platform for real-time performance monitoring. Additionally, the research offers insights into the practical application of systems analysis methods in the context of power plant operations, contributing to the ongoing discourse on digital transformation in the energy sector.

Humanoid and collaborative robots find their application in numerous sectors, such as automotive, electrical and mechanical engineering, not excluding the field of bioengineering. They replace repetitive and often monotonous human activity. As the trend nowadays is for continuous optimization of production processes, their advantage is easy relocation and operative application to new tasks, which allows the automation of practically all manual work. A common feature of manipulators is the control of the positioning of the actuators, primarily by adjusting the parameters of the drive units. Feedback is often implemented through various sensors that provide real-time information. However, most of the sensors in use do not provide information that would allow obtaining data on the history of the operating load in order to assess the further safe and reliable operation of the mechanical parts. This paper presents a low-cost torque sensor that was proposed by modifying the design of an existing part. The torque sensor was developed on the principle of strain gauge measurement. The results of strain–stress analysis obtained by numerical modelling were experimentally validated under static and dynamic loading. Practical application is mainly the development and long-term testing of prototypes of various types of manipulators and collaborative robots, where high accuracy and repeatability of positioning are essential. [ABSTRACT FROM AUTHOR]

In response to the problems of single signal information and low accuracy of the early warning method for motor bearing health diagnosis, this paper conducts a study on the early warning method for bearing health diagnosis. By performing ensemble empirical modal decomposition (EEMD) on the signal after empirical modal decomposition (EMD) hard threshold noise reduction and then extracting the vibration signal fault characteristic parameters based on the principal components analysis (PCA) algorithm for dimension reduction, an Ensemble Empirical Modal Decomposition-Principal Components Analysis-Adaptive Network-based Fuzzy Inference System-based(EEMD-PCA-ANFIS) bearing fault warning model for vibration signals under defective conditions is established, the vibration signals of different working conditions are selected for diagnosis, and the accuracy of fault identification reaches 93.3%. Subsequently, a bearing failure warning model based on joint analysis of vibration and temperature rise trends was developed for bearing oil deficiency conditions, and the results show that the model can combine the vibration signal and temperature characteristics to complete the accurate judgement of bearing oil deficiency status and achieve the fault diagnosis of bearing defects and oil deficiency status. Compared with the existing methods, the proposed bearing health diagnosis and early warning method based on Ensemble Empirical Modal Decomposition-Principal Components Analysis-Adaptive Network-based Fuzzy Inference System(EEMD-PCA-ANFIS) can diagnose and warn of bearing defects and the state of oil shortages and oil shortages more accurately and lays a foundation for realizing an intelligent fault warning algorithm based on multi-information fusion. [ABSTRACT FROM AUTHOR]

Inventory counting is crucial to manufacturing industries in terms of inventory management, production, and procurement planning. Many companies currently require workers to manually count and track the status of materials, which are repetitive and non-value-added activities but incur significant costs to the companies as well as mental fatigue to the employees. This research aims to develop a computer vision system that can automate the material counting activity without applying any marker on the material. The type of material of interest is metal sheet, whose shape is simple, a large rectangular shape, yet difficult to detect. The use of computer vision technology can reduce the costs incurred from the loss of high-value materials, eliminate repetitive work requirements for skilled labor, and reduce human error. A computer vision system is proposed and tested on a metal sheet picking process for multiple metal sheet stacks in the storage area by using one video camera. Our results show that the proposed computer vision system can count the metal sheet picks under a real situation with a precision of 97.83% and a recall of 100%. [ABSTRACT FROM AUTHOR]

Copyright of Railway Investigation & Surveying is the property of Railway Investigation & Surveying Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Humanoid and collaborative robots find their application in numerous sectors, such as automotive, electrical and mechanical engineering, not excluding the field of bioengineering. They replace repetitive and often monotonous human activity. As the trend nowadays is for continuous optimization of production processes, their advantage is easy relocation and operative application to new tasks, which allows the automation of practically all manual work. A common feature of manipulators is the control of the positioning of the actuators, primarily by adjusting the parameters of the drive units. Feedback is often implemented through various sensors that provide real-time information. However, most of the sensors in use do not provide information that would allow obtaining data on the history of the operating load in order to assess the further safe and reliable operation of the mechanical parts. This paper presents a low-cost torque sensor that was proposed by modifying the design of an existing part. The torque sensor was developed on the principle of strain gauge measurement. The results of strain–stress analysis obtained by numerical modelling were experimentally validated under static and dynamic loading. Practical application is mainly the development and long-term testing of prototypes of various types of manipulators and collaborative robots, where high accuracy and repeatability of positioning are essential.

In recent years, with the frequent occurrence of bridge accidents, bridge health monitoring system has been installed for bridge service safety assessment and life prediction. To make better use of the bridge health monitoring data, the basic characteristics of temperature, strain and deflection were obtained through feature analysis. The correlation between structural temperature and ambient temperature, structural stress and structural deflection was studied. The composition of health monitoring data was divided into load high frequency band and long wave low frequency band. Wavelet transform was used to separate the two, and the bridge stress and deflection data caused by temperature effect and external load was respectively extracted. The results show that bridge structure temperature change mainly depends on the ambient temperature. The temperature of the main girder section is more in line with the change in the ambient temperature than the temperature of the pier section. The main girder has a consistent temperature distribution form at different positions in the longitudinal direction of the bridge. The temperature affects the stress and deflection of the bridge both have a strong correlation. Temperature has strong correlation with bridge stress and deflection. The response results of bridge structure under train load obtained by excluding temperature effect are more accurate, which can provide scientific data and reference for subsequent bridge operation safety analysis and evaluation. [ABSTRACT FROM AUTHOR]

Copyright of Revista IRRIGA - Brazilian Journal of Irrigation & Drainage is the property of Revista IRRIGA (Brazilian Journal of Irrigation & Drainage) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Basic principles are examined of the application of software tools (ST) for predicting the erosion-corrosion (EC) rate to ensure the integrity of equipment and piping of nuclear power station (NPS) power units. Methods for solving the erosion-corrosion problems encountered in NPS power units have been determined. Software tools that are used most widely throughout the world to solve erosion-corrosion problems in the nuclear power industry are reviewed. The specifics in the application abroad and in Russia are highlighted. Attention is given to the successful foreign experience in improving the corrosion-erosion resistance of piping and equipment based on the solution implemented in designing NPS power units. Information is presented on the development of Russian software tools and the results of their application to render the integrity of piping and equipment of NPS power units with a VVER reactor or fast breeder reactor due to numerical prediction and early detection of the maximum allowable erosion-corrosion metal thinning. The feasibility is substantiated of using the software tools in designing new NPS power units with a VVER-1200 reactor, assessing the residual service life, and prolonging the operation of existing NPSs. Examples are given of the ways for reduction in the erosion-corrosion rate of equipment components and piping of nuclear power units, for example, by controlling the intensity of the hydrodynamic component of erosion-corrosion and proper selection of the metal. It is demonstrated that the cost of power units with a VVER-1200 reactor (including export deliveries) can be reduced by a change-over to less erosion-corrosion resistant but relatively inexpensive steels. The prospects are noted on application in practice of STs to assess the carry over of iron-rich corrosion-erosion products into the working fluid of an NPS with a VVER-reactor. It is pointed out that, when changing over to operation of NPS power units at a super-rated power, this factor should be estimated using STs, and its effect on the wear rate and location of the zones wherein is the highest rate of thinning of the pipeline walls and equipment must be considered. [ABSTRACT FROM AUTHOR]

Preparing the medullary space of the femur aims to create an ideal form-fitting of cementless implants to provide sufficient initial stability, which is crucial for osseous integration, ensuring good long-term results. Hammering the implant into the proximal femur creates a press-fit anchoring of the endoprosthesis in the medullary space. Implanting the optimal size of the shaft for best fitting should avoid damage to the bone. Modified acoustic signals in connection with implantation are being detected by surgeons and might be related to the primary stability of the implant. This study aims to explore the relationship between frequency sound patterns and the change in stem stability. For this purpose, n = 32 Metha® short stems were implanted in a clinical setting by the same surgeon. During implantation, the sounds were recorded. To define a change in the acoustic system response during the operation, the individual blows of the implantation sequence were correlated with one another. An algorithm was able to subdivide through sound analysis two groups of hammer blows (area 1 and area 2) since the characteristics of these groups showed significant differences within the frequency range of 100 Hz to 24 kHz. The edge between both groups, detected by the algorithm, was validated with expert surgeons' classifications of the same data. In conclusion, monitoring, the hammer blows sound might allow quantification of the primary stability of the implant. Sound analysis including patient parameters and a classification algorithm could provide a precise characterization of implant stability. • Acoustic analysis in Operation room by 32 endoprosthesis implantation. • New in situ algorithm to detect stem stability via acoustics. • Sound edge detection, where the implantation ton change significantly. • Implantation of endoprosthetics could be improved with acoustic monitoring. [ABSTRACT FROM AUTHOR]

The industrial economy is relevant to all walks of life, from production to distribution, and its service extends to all aspects of daily life such as culture and education. With the rapid development of modern economies, industrial and economic development are facing new opportunities and challenges, such as the reforms of industrial organization and changes in industry linkages, and industry structure updates which are affecting the industry and is driving economic development at this time. The industrial economy monitoring and analysis operation is particularly critical and important. Industry-based monitoring and analysis of economic performance for the national government macro-control features is needed no only to better reflect the country's needs, but also to be more effective in promoting the standardization of industrial and economic development. This paper describes the bases of ADO.NET and ASP.NET, using browser / server architecture to carry out comprehensive economic indicators for industrial data acquisition, sending, collation, analysis and utilization, thereby giving an in-depth study of industrial economic operation monitoring and analysis. [ABSTRACT FROM AUTHOR]

• China's agricultural machinery operation big data system was developed. • The system integrated positioning data and working data of major manufacturers. • A case study for China's wheat harvesters demonstrated its potential. Agricultural machinery operations are mainly performed by cross-regional socialized services in China. It is necessary to take advantage of national data system to implement dynamic monitoring, data sharing, and big data applications for agricultural machinery operations. This application note outlines the system composition, principal technology, primary functions, and application examples of the big data system. This system integrates agricultural machinery operations with big data, which can promote scientific decision-making with data management and facilitate more efficient agricultural production. Promoting the effective, orderly, and scientific growth of agricultural machinery operations and the advancement of agricultural modernization is of theoretical and practical importance. [ABSTRACT FROM AUTHOR]

Aiming at heavy burden and low efficiency of fault repairing for low-voltage distribution equipment of Deqing power grid, a method for fault diagnosis of low-voltage distribution equipment and design of operation monitoring system was proposed, Firstly, some data such as surface temperature of inlet-outlet line in the distribution box and the water level of cable trench were measured by using corresponding sensors integrated in the monitoring device for low--voltage distribution equipment, and data acquisition was realized by using short message terminal. Secondly, data operation, comparison and analysis utilizing the build- in equipment parameter of short message terminal was performed. Finally, fault forecast/alarm messages synchronously were transferred through GSM and GPRS dualchannel wireless network. The results of the processing of the system indicate that the method realizes fault)' forecast and real-time transmission of an alarm message for low- voltage distribution monitoring equipments. Meanwhile, auto- isolation and self- healing technologies for the power supply circuit of low-voltage distribution box about upper limit of temperature and water level have been invented. Consequently .the safeguarding level of public transformer in a rural area has been improved. [ABSTRACT FROM AUTHOR]

• Three layers of subsystems are constructed for the control system of EAST poloidal field power supply. • Architecture based on real-time system and high speed communication network is proposed to make control loops on power supply controllers running at strict cycle-time. • Handy human-machine interface and sensitive alarming mechanism based on EPICS are achieved to monitor the power system. • Unified external clock and external trigger scheme are developed to enhance the data acquisition management system. This paper introduces the architecture and characteristics of the poloidal field power supply, and describes the architecture of its control system, which is composed of data acquisition management system, operation monitoring system and real-time control system. According to the characteristics of the control system, a data acquisition management system based on Qt, an operation monitoring system based on EPICS and the real-time control system is based on Linux real-time kernel are designed. The control system realizes real-time control of EAST poloidal field power supply system in 1 ms cycle time, and the equipment status detection and monitoring, data acquisition, storage and inspection. Several experiments have proved that the control system definitely meets the requirements of the poloidal field power supply control system in the complex situations under magnetic fields. [ABSTRACT FROM AUTHOR]