Search

In order to effectively reduce the failure rate of vibrating screens, a vibration monitoring system design was proposed based on the structure and working principle. The system should be able to monitor the operating state of the vibrating screen in real time, including vibration amplitude, frequency, axial displacement, etc., and be able to detect abnormal conditions in time and give warning prompts. The key hardware of the monitoring system was designed, including acceleration sensor, power module, signal filtering circuit, etc. The sensitivity of the acceleration sensor was measured using comparative method and accurately completed parameter calibration. The eccentric block was used to simulate different deviation of excitation force for system vibration signal test and calibration. The results show that under normal operating conditions, the amplitude of each frequency of the vibrating screen is less than 0.04 g. Under the condition of excitation force deviation, the amplitude of 16 Hz is obviously lower than that of other frequencies, which means that the vibrating screen is currently experiencing lateral oscillation. [ABSTRACT FROM AUTHOR]

To study the effect of track precision measurement and adjustment technology on subway vibration source intensity, a quantitative analysis method was adopted to conduct vibration tests on the steel rails, track beds, and tunnel walls before and after track precision adjustment. A typical section of a subway line during a certain operating period was selected as the test section, and an arbitrary station control network was established in this test section. Based on this section's arbitrary station control network, the absolute deviation value of the line relative to the design position was measured by absolute measurement of the track geometry state. Combined with the relative measurement data of the track geometry state, a track precision adjustment plan was developed to guide the track precision adjustment operation of this test section. At the same time, a typical section in the experimental section was selected as the detection section to detect the maximum Z vibration level (VLzmax) of the steel rail, track bed, and tunnel wall before and after precision measurement and adjustment of the track at that section. By comparing the VLzmax of the steel rail, track bed, and tunnel wall before and after precision measurement and adjustment of the track, the effect of precision measurement and adjustment technology on subway vibration source intensity was quantitatively analyzed. The results obtained from the study includes: the dynamic average of the experimental section decreases from 7.09 to 4.98 before and after precision adjustment of the track. Vibration tests conducted before and after precision adjustment of the track shows that the VLzmax of the rail, track bed, and tunnel wall decrease by 3.62 dB, 4.94 dB, and 1.52 dB, respectively. The conclusion of this study is that the precise measurement and adjustment technology of the track has brought significant effects on track vibration reduction, which can effectively reduce the intensity value of subway vibration source. [ABSTRACT FROM AUTHOR]

To analyze the mechanical performance of the arc end tooth connection structure, the optimization of electronic sensors based on the connection structure of double rotors with circular arc end teeth was studied. By designing and optimizing the structural dimensions of the arc end tooth, the relative position of the grinding wheel and the workpiece was determined, and the optimal electromagnetic actuator size, as well as the number and installation position of the optimized sensors, were obtained. The experimental results showed that the relative error of the rigid vibration mode of the arc end tooth double rotor connection structure was controlled within 10 %. At high speeds, the electromagnetic actuator had a significant control effect on the vibration of the centrifugal machine shaft. It diminished the vibration amplitudes in the X and Y directions by 37.6 % and 30.2 %, respectively. By optimizing the double rotor connection structure with circular end teeth and electronic sensors, effective control of the relative error of rigid vibration modes has been achieved, leading to significant reduction of the centrifugal shaft's vibration at high speeds. In addition, the sensor layout was optimized to enable real-time equipment vibration monitoring, ensuring equipment safety and stability. These achievements not only enhance the mechanical performance of the rotor system, but also provide important guarantees for the stability of the mechanical system. [ABSTRACT FROM AUTHOR]

Vibration is an essential indicator that reflects the robust status of industrial robots. To improve the detection effect and resilience for articulated industrial robot in-situ, a novel non-invasive self-diagnostic method is proposed. Feasible embedded motor current is used to calculate the extended Teager indicator at a low sampling rate. Compared with common Teager and other indicators, both theoretical analysis and experimental data indicate the effectiveness and robustness of the proposed method. [ABSTRACT FROM AUTHOR]

This study proposes the utilization of an optical fiber vibration sensor for detecting the superposition of extremely close frequencies in vibration signals. Integration of deep neural networks (DNN) proves to be meaningful and efficient, eliminating the need for signal analysis methods involving complex mathematical calculations and longer computation times. Simulation results of the proposed model demonstrate the remarkable capability to accurately distinguish frequencies below 1 Hz. This underscores the effectiveness of the proposed image-based vibration signal recognition system embedded in DNN as a streamlined yet highly accurate method for vibration signal detection, applicable across various vibration sensors. Both simulation and experimental evaluations substantiate the practical applicability of this integrated approach, thereby enhancing electric motor vibration monitoring techniques. [ABSTRACT FROM AUTHOR]

Modal and damage identification based on ambient excitation can greatly improve the efficiency of high-speed railway bridge vibration detection. This paper first describes the basic principles of stochastic subspace identification, peak-picking, and frequency domain decomposition method in modal analysis based on ambient excitation, and the effectiveness of these three methods is verified through finite element calculation and numerical simulation. Then the damage element is added to the finite element model to simulate the crack, and the curvature mode difference and the curvature mode area difference square ratio are calculated by using the stochastic subspace identification results to verify their ability of damage identification and location. Finally, the above modal and damage identification techniques are integrated to develop a bridge modal and damage identification software platform. The final results show that all three modal identification methods can accurately identify the vibration frequency and mode shape, both damage identification methods can accurately identify and locate the damage, and the developed software platform is simple and efficient.

In this work, a 1550-nm full-fiber Doppler lidar via software-defined platform is built to realize flexible and low-cost contactless vibration measurement of high-voltage power equipment. A 1550-nm fiber layout is designed to generate optical interference between vibration signal and carrier wave. The reflected vibration signal is collected by an optical transceiver and the carrier wave is generated by an acousto-optic modulator (AOM). The optical beat signal is collected by a balanced detector (BD) then sent into a general software defined radio (SDR) receiver. By GNU developing platform, the target mechanical vibration signal is demodulated and several flexible functions such as speed-acceleration trans, harmonic component analysis and fault diagnosis is realized. Performance of Doppler lidar is first verified on mechanical vibration source by PZT vibration actuator, results show that the designed lidar could retrieve 50 Hz–20 kHz mechanical vibration signals within the working distance is up to 20 m. Further case application scenarios on the power transformer and gas-insulated switchgear (GIS) are also conducted to verify the feasibility of proposed lidar.

In order to detect and diagnose the operating status without disassembling automobile parts, engine speed and suspension status were tested and analyzed based on vibration detection technology. Based on a DSP processor and an acceleration sensor, the speed of a single cylinder engine was tested under steady-state and transient conditions, respectively. Using the cepstrum method, the vibration signals were collected at different speeds are processed, the fundamental frequency was extracted, and the engine speed information was obtained. According to the speed verification using the Otsu EWT method, the maximum relative error of engine speed was less than 1.5 %, and the error decreases as the speed increases. In order to ensure the reliability of suspension vibration signals, the overall structure and safety of the vibration characteristic detection scheme were designed. Due to the limited sampling frequency of suspension load status sensor data, the EMD method was adopted to process dynamic load signals, which had a good separation effect on suspension vibration signals. [ABSTRACT FROM AUTHOR]

Judging the working status of a gearbox through the characteristics of vibration signals was an effective fault diagnosis method. In order to improve the efficiency and reliability of vibration detection, a multi node testing system based on a microcontroller was designed and validated. The system mainly consists of signal processing equipment, signal collector, upper computer, sensors, and experimental workbench. Under different types of gear faults, the vibration signals of ten sets of gearboxes were synchronously collected and processed. In order to ensure the resolution of frequency conversion and accurately locate frequency conversion, the low-pass filtered spectrum with a filtering frequency of 1000 was verified and used to calculate the amplitude of frequency conversion. The normalization of amplitude was more conducive to feature recognition, and the frequency amplitude was proportional to its corresponding energy. According to standard spectral data and spectral analysis, wear, pitting, fracture, and bonding faults in the gearbox were identified and classified. Through the verification of three order feature spectrum, it can be seen that the accuracy of fault prediction for gearbox through vibration signals is high, which can effectively reduce maintenance and repair costs. [ABSTRACT FROM AUTHOR]

Rail transport comfort is ensured by predictive maintenance and continuous supervision of rail quality. Besides the specialized equipment, the authors are proposing a simple system that can be implemented on operational wagons while in service, aiming to detect irregularities in the rail and report them using the train's online communication lines. The sensor itself is an acceleration sensor connected to an electronic microcontroller able to filter the inrush acceleration and send it to the diagnosis system of the wagon. This paper presents a study of real data recorded of the transversal and vertical vibrations of a standard tank wagon, measured on 2 axles and the car body, followed by the interpretation of the recorded data. [ABSTRACT FROM AUTHOR]

Video magnification has received increased attention in structural deformation measurement. Current video magnification methods typically chose the Eulerian perspective rather than the Lagrangian, which requires tedious work for tedious parameter adjustment. However, the low computational efficiency is a prominent problem of the Euler-based method due to the complex time domain filtering processing. To address this issue, a novelty motion magnification algorithm, called Euler fast motion detection (EFMD), is proposed in this paper, which can realize real-time measurement with low computation cost. Laboratory verification and field experiments were carried out to verify the accuracy of the algorithm in deck and cable dynamic response measurement. In laboratory experiments, the error of natural frequency measured by the proposed method is within 2%. In the field experiments, the small displacements (about 1.5 mm) can be achieved by the proposed method at a distance greater than 20 m, and the error of the cable vibration is less than 4%. [ABSTRACT FROM AUTHOR]

Copyright of DYNA - Ingeniería e Industria is the property of Publicaciones Dyna SL 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.)

In this work, a 1550-nm full-fiber Doppler lidar via software-defined platform is built to realize flexible and low-cost contactless vibration measurement of highvoltage power equipment. A 1550-nm fiber layout is designed to generate optical interference between vibration signal and carrier wave. The reflected vibration signal is collected by an optical transceiver and the carrier wave is generated by an acousto-optic modulator (AOM). The optical beat signal is collected by a balanced detector (BD) then sent into a general software defined radio (SDR) receiver. By GNU developing platform, the target mechanical vibration signal is demodulated and several flexible functions such as speed-acceleration trans, harmonic component analysis and fault diagnosis is realized. Performance of Doppler lidar is first verified on mechanical vibration source by PZT vibration actuator, results show that the designed lidar could retrieve 50 Hz-20 kHz mechanical vibration signals within the working distance is up to 20 m. Further case application scenarios on the power transformer and gas-insulated switchgear (GIS) are also conducted to verify the feasibility of proposed lidar. [ABSTRACT FROM AUTHOR]

Copyright of Laser Technology is the property of Gai Kan Bian Wei Hui 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.)

This study proposes the utilization of an optical fiber vibration sensor for detecting the superposition of extremely close frequencies in vibration signals. Integration of deep neural networks (DNN) proves to be meaningful and efficient, eliminating the need for signal analysis methods involving complex mathematical calculations and longer computation times. Simulation results of the proposed model demonstrate the remarkable capability to accurately distinguish frequencies below 1 Hz. This underscores the effectiveness of the proposed image-based vibration signal recognition system embedded in DNN as a streamlined yet highly accurate method for vibration signal detection, applicable across various vibration sensors. Both simulation and experimental evaluations substantiate the practical applicability of this integrated approach, thereby enhancing electric motor vibration monitoring techniques.

The rapid and accurate identification of the opening and closing state of the knife switch in a gas insulated switchgear (GIS) is very important for the timely detection of equipment faults and for the reduction of related accidents. However, existing technologies, such as image recognition, are vulnerable to weather or light intensity, while microswitch, attitude sensing and other methods are unable to induce equipment power failure with sufficient speed, which brings many new challenges to the operation and maintenance of a GIS. Therefore, this research designs a GIS shell vibration detection system for knife switch state discrimination, introduces a deep learning algorithm for knife switch vibration signal analysis, and proposes a fast convolutional neural network (FCNN) to identify the knife switch state. For the designed FCNN, a normalization layer and a nonlinear activation layer are used after each convolution layer to obviously reduce feature quantity and increase algorithm efficiency. In order to test the recognition performance based on the vibration detection system, this study carried out two kinds of knife switch opening and closing experiments. One group with artificial noise was added, the other group did not include artifical noise, and a corresponding data set was constructed. The experimental results show that the recognition accuracy for both datasets reaches 100%, and the FCNN algorithm is better than the five classical algorithms in terms of prediction efficiency. This study shows that the vibration detection technology based on deep learning can be used to effectively identify the opening and closing state of a GIS knife switch, and is expected to be promoted and applied. [ABSTRACT FROM AUTHOR]

Vibration measurements are essential for studying the dynamic properties of structures, as they can better capture the global characteristics of the structure. This paper proposes a three-dimensional measurement method based on projected structured light to address the challenge of measuring the vibration information of engine pipes during operation. By using the data obtained from this method and applying the time domain analysis method for modal analysis, the modal parameters of the engine under operating conditions can be obtained. The feasibility of this method is demonstrated by comparing it with different measurement methods, and it provides an effective solution for modal identification of engines under operating conditions. [ABSTRACT FROM AUTHOR]

Due to the harsh working environment and various types of faults in mine hoists, the implementation of conventional detection is relatively difficult. In order to improve the maintenance and fault detection efficiency of mine hoist, a portable vibration detection system is designed and applied in this paper, which can judge the type and characteristics of mechanical faults according to the different responses of vibration signals. According to the test conditions of the vibration system, the overall structure and functional composition of the hardware system are established. The key functional modules are designed, including signal conditioning module, main control module, vibration sensor and power management module. The main reasons that affect and produce the hoist fault and mechanical vibration are analyzed. The wavelet packet analysis method is proposed to realize the decomposition of low frequency and high frequency signals to improve the signal resolution of the whole frequency band in the frequency domain. The vibration test system has the function of real-time data transmission and control. The realization methods include WiFi and reserved RS485 communication interface, which can match the communication rate with the data sampling rate. The amplifying circuit of the electric signal is designed to effectively ensure that the output voltage of the charge amplifier is within the input range of the amplified ADC value. In order to verify the working effect of the system, the most common gearbox and bearing failures are taken as examples. The response signals of vibration test and diagnosis can be effectively obtained, and the fault types and characteristics can be accurately judged. Through confusion matrix analysis, the reliability of the system detection index is effectively verified. The research results show that the data of the vibration detection system is stable and reliable, and can achieve good troubleshooting effect. It also can be known that different fault types can excite different vibration responses, especially at resonance frequencies. According to the verification, the data of the vibration detection system is stable and reliable, and can achieve good troubleshooting effect. [ABSTRACT FROM AUTHOR]

Copyright of Computer Measurement & Control is the property of Magazine Agency of Computer Measurement & Control 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.)

This paper shows that ultra-fine vibration can be detected by designing and manufacturing a 24 GHz six-port topology using ADS. The six-port topology consists of one Wilkinson divider, three 90° hybrid couplers, RF detectors using Schottky diodes, couplers, circulators, Ka-band antennas, an Arduino UNO, and MATLAB, and phase changes were measured by the output voltages of the four RF detectors. As a result of RF detector simulation, S11 was designed to be −38.2 dB owing to 24 GHz. However, as a result of fabrication, the output voltages of the four RF detectors were small and the amplitudes were not the same. To solve this problem, an operational amplifier with a gain of 45 was added to the rear end of the RF detector to increase the output voltage, and the amplitude was made equal by compensating the value using MATLAB. As a result of the experiment, ultra-fine vibration of approximately 20 μm could be detected. [ABSTRACT FROM AUTHOR]

This paper studies the vibration detection technique based on the piezoelectric cantilever structure, and analyzes the relationship between the resonance frequency and the structure parameters. Although the output of the electrical signal is too small, it can be used to detect vibration during resonance with the maximum output voltage. A vibration testing device is designed based on piezoelectric cantilever structure, because in the vibration environment of the same frequency the vibration detection technology can obtain larger electrical signals. It can realize the automatic detection of real-time vibration state, and the vibration energy can charge the power supply through the energy storage circuit. Through the experimental method to verify relationship between the output voltage of piezoelectric cantilever beam, mass block, piezoelectric cantilever structure parameters and frequency, the experimental value of resonance frequency is very close with theoretical calculation value. The experimental resonant frequency of the designed piezoelectric cantilever beam is 16.5 Hz, which is slightly lower than the theoretical value of resonant frequency of 17.6 Hz, and the peak value of the piezoelectric output open-circuit voltage is 7.1 V. [ABSTRACT FROM AUTHOR]

Rail transport comfort is ensured by predictive maintenance and continuous supervision of rail quality. Besides the specialized equipment, the authors are proposing a simple system that can be implemented on operational wagons while in service, aiming to detect irregularities in the rail and report them using the train’s online communication lines. The sensor itself is an acceleration sensor connected to an electronic microcontroller able to filter the inrush acceleration and send it to the diagnosis system of the wagon. This paper presents a study of real data recorded of the transversal and vertical vibrations of a standard tank wagon, measured on 2 axles and the car body, followed by the interpretation of the recorded data.

In unmanned monitoring such as perimeter security, pipeline detection, railway security, and so on, it is still a challenging task to accurately locate the irregular vibration events. Compared with traditional vibration detection technologies, distributed optical fiber vibration sensors (DOFVSs) have superior advantages such as high spatial resolution, large monitoring range, good concealment, excellent flexibility, and simple sensing structure. The DOFVS can be mainly classified into two types, i.e., the interferometer-based DOFVS (IDOFVS) and the backscattering-based DOFVS (BDOFVS). In particular, IDOFVS has unique sensing advantages, such as high stability, simple structure, high sensitivity, and wide frequency response. In this article, the development of long-distance IDOFVS in recent years has been summarized. The sensing principle of IDOFVS has been theoretically explained. The specific classification of the IDOFVS and the corresponding sensing structures are described in detail. In addition, the long-distance distributed vibration sensing structure and processing algorithms, such as denoising and locating algorithms, are analyzed. Finally, the performance of recent long-distance IDOFVS has been compared and the development direction has been discussed. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Donghua University (Natural Science Edition) is the property of Journal of Donghua University (Natural Science) 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.)

Vibration measurements are essential for studying the dynamic properties of structures, as they can better capture the global characteristics of the structure. This paper proposes a three-dimensional measurement method based on projected structured light to address the challenge of measuring the vibration information of engine pipes during operation. By using the data obtained from this method and applying the time domain analysis method for modal analysis, the modal parameters of the engine under operating conditions can be obtained. The feasibility of this method is demonstrated by comparing it with different measurement methods, and it provides an effective solution for modal identification of engines under operating conditions.

Among all renewable energy sources, wind energy is a cost-effective alternative energy source. The majority of wind turbines are built in harsh environments due to their power generation characteristics, which is one of the prime reasons resulting in frequent failures of wind turbine. Among various failures, the vibration of wind turbine tower cannot be ignored because it is a precursor of the failure of the wind turbine. The electrical vibration sensors have the problems of power supply and electromagnetic interference for the condition assessment of wind turbine tower. A vibration sensor based on optical Fabry-Perot (F-P) interference principle with high sensitivity is designed, fabricated and characterized to further meet the requirements of vibration detection of wind turbine tower. The mechanical simulation model of the diaphragm and optical vibration platform is constructed to verify the sensing characteristic of the F-P optical fiber vibration sensor (OFVS). The experiment results indicate a resonant frequency of the F-P OFVS of 223 Hz, an output sensitivity of 122.22 mV/m·s−2 at 10 Hz, and a horizontal output of less than 6 %. In addition, the designed F-P OFVS possesses the superiorities of compact structure, passive and excellent anti-electromagnetic interference, and has a wide application prospect in the vibration detection of the wind turbine tower. [Display omitted] • Design the sensitive end structure of the vibration sensor to meet the requirements of low-frequency vibration detection. • Establish a vibration experimental platform to complete the measurement of the sensing characteristic of the vibration sensor. • The beam structure with uniform strength is beneficial to improve the sensitivity and increase the horizontal interference. • Prospects for the data fusion of energy networks and multi-dimensional sensor networks. [ABSTRACT FROM AUTHOR]

• Possibility of abnormal behavior in the turbine shaft of a power plant that has the potential of sudden failure was identified, measured, and predicted. • To collect experimental data in Kirkuk power plant of Iraq, CA 202 piezoelectric accelerometer was used. • New method was presented to reduce the volume of input data by extracting the output of the hidden layer of an Autoencoder, which was then applied to feature recognition. • The output of the hidden layer from the encoder was used to train a three-hidden DLSTM to predict the occurrence of errors by considering the anomaly detection approach. Developing a maintenance schedule for different parts of a power plant can help to prevent serious system damage while also having a direct effect on reducing maintenance time and costs. Moreover, the proposed procedure can provide a better understanding of the health state of the system. The occurrence of problems (anomalous behavior) in power plants usually takes time and happens gradually. Predicting the possibility of anomalous behavior arising can therefore result in the prediction of a failure. In this paper, the authors tried to propose a new method for reducing the volume of input data by extracting the latent layer output of an Autoencoder, which was then applied to identify features. We achieved this by keeping relevant features and learning the anomalous behavior's encoded representation. Furthermore, the latent layer output from the encoder was used to train a Deep Long-Short-Term Memory (DLSTM) model with three hidden layers for fault occurrence prediction by considering an anomaly detection approach. To this end, a threshold approach was used to determine the possibility of a fault occurring in the turbine, with data collected from the Kirkuk gas turbine power plant. Piezoelectric accelerometer CA 202 was utilized as a sensor to collect data in industry. Since most of the recorded data were normal and the amount of abnormal data was small, various techniques, i.e., flipping and jittering, were employed to create synthetic abnormal data and augment the applicable dataset. In summary, according to the proposed methodology, the system is modelled as a time series classification problem to mimic the anomaly detection problem. The results showed that the accuracy of the trained model for detecting turbine vibration as a system abnormality is over 86%. Also, the implementation of the proposed prediction model on the experimental dataset yielded satisfactory results for detecting and predicting the occurrence of faults in Kirkuk gas turbine power plant. [ABSTRACT FROM AUTHOR]

High-frequency global navigation satellite system (GNSS) observations are of great significance for structural health monitoring. At present, most studies on high-frequency GNSS observations focus on displacement extraction, while there are few studies on vibration detection. The purpose of this research is to explore a vertical vibration detection method based on high-frequency GNSS observations. The principle of GNSS kinematic positioning is presented, and a vibration detection method based on high-frequency GNSS observations is proposed. A stationary state model and a vibration state model are designed to represent the vibration state and static state of the structure. We introduce the interactive multiple-model Kalman filter to detect vibrations through model probabilities automatically. To reduce the influence of the trend term caused by unmodeled errors, we preprocess original positioning results by a moving average. To reduce the false alarm rate caused by local disturbance, a hold-on mechanism is proposed. Only when the number of the hold-on epoch is greater than the preset hold-on parameter, it is considered that vibration has occurred. Then, the detected epoch and corresponding displacement are further analyzed and processed. Simulation and field experiments were carried out to verify the proposed method. The results show the feasibility and effectiveness of the method for vertical vibration detection. Therefore, this study should be of value to practitioners wishing to implement an early warning system based on high-frequency GNSS observations. [ABSTRACT FROM AUTHOR]

In order to overcome the limitation of weak intensity of Rayleigh backward scattering signal for long-distance ${\Phi } $ -OTDR system, a global phase demodulation method is proposed to extend the sensing distance without additional optical amplification. The localization limitation of conventional difference cumulative average algorithm is firstly analyzed. The global phase demodulation is carried out for all the signals on the whole sensing fiber. The autocorrelation processing is then realized to obtain the autocorrelation curves, on which the difference values between two instants can be used to locate the position of vibration signal. Experimental results show that according to the characteristics of autocorrelation curves, the vibration signal and noise signal can be distinguished. The sinusoidal signal with a frequency of 5 Hz and the third harmonic signal with the frequency of 5 Hz, 10 Hz, 15 Hz can be successfully located on the sensing fiber with the length of 90 km, without additional optical amplification. This method can achieve the long-distance detection for periodic vibration signal in ${\Phi } $ -OTDR system. [ABSTRACT FROM AUTHOR]

This paper describes a perforating gun detonation monitoring system developed to meet the need for real-time monitoring of perforation effect in the petroleum industry. A high-sensitivity acceleration sensor, serving as the response module of the physical characteristics of the tubing vibration, acquires a set of vibration signals of the whole physical process during the impact after the detonation of the shaped charge. The jump point in the monitoring process is extracted by comparing the signal's short-time energy. The amplitude, energy, and envelope characteristics of the signal are then evaluated. From the time-frequency characteristics of the tubing vibration upon the detonation of the perforating gun, a judgment is made as to whether the perforating gun has detonated. Tubing vibration experiments were conducted involving different perforating guns. The results suggested that the proposed monitoring method is able to monitor perforating guns of different shaped charges with a perforating depth between 500m-3500m and in oil wells with an inclination of 0° - 90°. As a means of vibration detection, this method also works well in other types of vibration monitoring.

In recent years, large-scale renewable energy access to substations has brought overload, harmonic, short circuit and other problems, which has led to an increase in the failure rate and shortening the service life of important power equipment such as transformers. Transformer is one of the key equipment in power system, and its operation status has an important impact on the safe and stable operation of power grid. In order to realize the real-time state evaluation of transformer, a real-time vibration signal detection method based on video is proposed in this paper. Firstly, YOLOv4 is used to detect the transformer object, and then the pyramid Lucas-Kanade optical flow method and Otsu method are used to calculate the transformer vibration vector. Experimental results show that the transformer vibration vector can be calculated in real time and accurately by using the proposed algorithm, so as to realize the real-time reliable analysis of the transformer state.

This study aims to develop a vision-based measurement method for machine tool vibrations and dynamic motion errors. In this study, the potential of the vision-based method in high resolution measurement is evaluated. A model fitting method is considered for the image processing that is appropriate for mechanical vibration measurement. The influence of lighting on the measurement resolution is also evaluated. In the method, the displacement of the marker attached to the object is obtained through a video captured by using a high-speed camera. To obtain the marker displacement, the center position of the marker is tracked by fitting a quadratic function to the intensity distribution of the marker. Experiments are conducted to evaluate the measurement resolution of the model fitting method. The vibration displacement of a cantilever with various amplitudes was measured using the vision based method under different lighting conditions. The measured displacement is analyzed in the frequency domain to determine the measurement resolution and noise level. In addition to the model fitting method, an edge detection method and a threshold detection method are used for the marker position detection and compared with the model fitting method. The experiment results indicate that the model fitting method has the ability to detect the minimum amplitude of 1/53 pixels that corresponds to a 3.8 μm resolution in 120 × 160 mm range.

Phase-sensitive optical time-domain reflectometry $\Phi $ -OTDR) is a powerful sensing device that enables fully distributed optical fiber vibration detection with fast response and high sensitivity. Based on the introduction of its principles, Rayleigh backscatter, sensing mechanism, the characteristics of the $\Phi $ -OTDR system are analyzed in detail. Some gaps in the $\Phi $ -OTDR technology are outlined, and its development trends are highlighted. The application of its current technology is illustrated in different fields such as the perimeter security monitoring system, submarine cable surveillance, and so on. In the experiments analysis, it was pointed out that the device is very sensitive, which is subject to a high rate of false alarms; it also has unresolved types of disturbances. For these purposes, this paper first summarizes the development status of the $\Phi $ -OTDR-based fully distributed optical fiber sensing device. Then, it analyzes and proposes the use of a Printed Circuit Board (PCB) winding flyback converter with shielding, to solve the problem of sensitivity. The shielding method has been proven to significantly reduce high frequency noise up to 30 MHz. This will enable relevant industries and future researchers to know the current state of the $\Phi $ -OTDR device. [ABSTRACT FROM AUTHOR]

The abnormal vibration of the loom spindle will seriously affect the quality of the textile. Based on the inherent embedded control system of the rapier loom, this paper develops an embedded system that monitors and analyzes the vibration signal of the spindle to determine the cause of the spindle failure. The system improves the traditional vibration sensor signal acquisition method, design the sensor peripheral auxiliary circuit and vibration signal conditioning circuit, and design the data storage and communication module so that the system has the characteristics of low cost, strong flexibility and scalability. The embedded algorithm program of Fast Fourier transform is developed, optimized, and is applied to embedded platform, therefore the system can analyze the characteristics of vibration signal in frequency domain. Finally, back propagation neural network (BPNN) is introduced to investigate and match the relationship between the vibration spectrum characteristics and fault types of the loom spindle. The extracted back propagation (BP) learning result is a mathematical mapping formula, which enables the embedded system to analyze and determine the cause of vibration fault by using this formula. System design is conducive to improving the level of production intelligence and reducing personnel costs in the production process. [ABSTRACT FROM AUTHOR]

Biotremology is a field of study focused on an ancient way of communication by animals endowed with specialized organs for emission and reception of substrate-borne vibrations. Established as a scientific discipline of its own, formally separated from bioacoustics only recently, biotremology is now rapidly spreading throughout the scientific community, offering valuable cooperation also to numerous other scientific disciplines. Insects, make significant use of substrate-borne vibrational signals and cues for inter- and intraspecific communication, to accomplish many different behaviours. In this chapter, after highlighting the main relations, and differences, between insect acoustic and vibrational communication, we provide a detailed, comprehensive overview of the knowledge and ongoing research in the field of insect biotremology. We particularly emphasise the mechanisms of sensory detection of vibrational signals and cues, and the central neural processing of the received information; the latter especially being discussed in relation to insect auditory processing. In addition, we dedicate considerable attention to the behavioural and ecological aspects of insect vibrational communication, to the methods and instruments of research in neurophysiology and behavioural ecology, as well as the use of acquired basic knowledge in practical applications. Whilst some topics in biotremology, such as the neuronal basis of behaviour, need highly increased research attention, the interest in applied biotremology is rising especially quickly for the high potential offered by substrate-borne vibrations as semiophysicals for pest control. Hence, insects are both the elected study model for basic biotremology research and strongly relevant for agricultural and resource management issues. [ABSTRACT FROM AUTHOR]

This paper proposes a method for detecting the vibration of subsea spanning pipelines by using a spherical detector (SD) equipped with a triaxial accelerometer. The mathematical analyses and experiments demonstrate that the acceleration modulus square (AMS) and the AMS of the ac components (AMS_AC) of the acceleration signals recorded by the SD have one characteristic component whose frequency is equal to and can be used to determine the pipeline vibration frequency. As the amplitude of this component is immune to the rotation noises of the SD, its signal-to-noise ratio is higher than that of other components whose frequencies are the mixture of the vibration and rotation frequencies. Removing the dc bias along the three sensitive axes can eliminate other characteristic frequencies to make the AMS_AC having the unique frequency to indicate the pipeline vibration. The vibration frequency can be accurately and sensitively identified by using the AMS_AC. The detection thresholds of 5-, 10-, and 15-Hz vibrations are 0.6, 0.4, and 0.2 mm with regard to the amplitude, respectively.

Based upon a phase-sensitive optical time-domain reflectometer (ϕ-OTDR) using a probe light with a pulse width of 200 ns, we propose and experimentally validate a cross-correlation spectrum analysis method for distributed optical fiber low frequency vibration detecting, for the first time to our knowledge. Experimental results show that it can detect and locate vibrations with a low-frequency of 0.0001 Hz. Besides, two vibrations at different positions with a 3 m interval can be successfully located, which suggests the proposed method is capable of locating low-frequency vibrations in high spatial resolution (SR) although the theoretical SR of the ϕ-OTDR is 20 m using conventional methods. There is no fundamental limit in achieving higher spatial resolution as long as the frequencies of vibrations to be located are different. [ABSTRACT FROM AUTHOR]

Ziyuan3-01 and Ziyuan3-02, Chinese civilian high-resolution stereo mapping satellites, were designed to satisfy the requirements of 1:50,000 digital topographical mapping. Platform vibration detection plays an important role in the Ziyuan3 satellite project. Various methods have been used to detect the vibration of Ziyuan3-01, but none focuses on that the vibration frequency is not a fixed value. To detect and model the vibration, this study proposes a method based on a set of raw gyroscope data to detect long-term vibration and model it with considering frequency changing. Two experiments were conducted, and the results showed that (a) the proposed method can detect the long-term vibration frequency and model it; (b) there is a same vibration frequency of approximately 0.65 Hz in the Ziyuan3-01 and Ziyuan3-02; (c) the 0.65 Hz vibration suffered by the Ziyuan3 satellite series is not a fixed value, varying from 0.59 Hz to 0.7 Hz, and the period of the vibration change is a constant value of approximately 1 year, which we modeled with a sine function; and (d) the working state of loads on the platform, such as solar panels, has an influence on the vibration frequency certainly. [ABSTRACT FROM AUTHOR]

With the development of lean manufacturing, it is imperative to make use of high technology and science to innovate manufacturing. To avoid poor working environment, reduce high cost of artificial maintenance and realize real-time watching, a wireless vibration acquisition system is need to be built. The information acquisition platform is built by a plurality of three axis acceleration sensor, a plurality of large tonnage dynamic pressure sensor, and the infrared temperature sensor to collect data. Then the real-time data is transmitted to the server, and it would be disposed by signal analysis methods on the server. By signal denoising, feature extraction, vibrating trajectory fitting, dynamic gravity center computing and error compensation calculation, the vibration amplitude, vibration velocity, vibration acceleration, vibration frequency, bearing temperature, vibration trajectory, vibration angle and dynamic load would be gotten and stored. Through the comparison and analysis of the fault database with the gotten information, the equipment running status can be judged. If there is any abnormal condition, the reason can find. Finally the fault information and operation tips are to be sent to terminal mobile phone via wireless network. The wireless acquisition platform of this system solves the disadvantages of installation problems as the traditional collection system, improves the accuracy by the error compensation algorithm, and increases the real-time performance by industrial internet. [ABSTRACT FROM AUTHOR]

This study realizes the activity sensing of honeybees flying in a natural outdoor environment by inspecting pixel-level temporal frequency responses in the brightness in a high-frame-rate (HFR) video, computed by executing short-time Fourier transforms (STFTs) of the brightness signals at all pixels. To localize multiple flying honeybees in an HFR video, the periodic brightness changes at pixels around the wings of honeybees that were flapping at hundreds of Hertz were detected in the frequency range below the Nyquist frequency, which is defined as half the frame rate of the HFR video by executing STFTs at all pixels. Vibration pixels around each honeybee were identified as a labeled region with connected components labeling. For each labeled region, STFTs were recomputed for brightness signals in a tracked region-of-interest image, in which its labeled region was located in the center; the trajectory of a honeybee is monitored with the peak frequency of these tracked STFTs as its flight activity. The performance of the HFR-video-based honeybee activity sensing was verified by analyzing several scenes of 12–14-mm-size honeybees flying around a beehive in $1024\times1024$ images captured at 500 fps. [ABSTRACT FROM AUTHOR]

Measuring the vibrating states of an artificial structure is an important approach to monitor the stability of the structure. However, the existing radar vibration measurement methods do not have enough azimuth resolution for measuring the vibrations in a relatively large scene, which contains multiple buildings or a large building. For such application scene, this paper proposes a vibration measurement method based on multiple-input multiple-output imaging radar system, which can achieve high azimuth resolution. Features of the proposed method are threefold: first of all, by utilizing the ability of quickly acquiring imaging data, the proposed method can achieve vibration measurement for the entire area simultaneously; second, in order to detect the positions of vibrating objects and decrease the time of vibration parameter estimation part, this paper proposes vibration similarity index to quantify the similarity between the detected signal and ideal vibration signal; at last, due to the limitations of the hardware performance, this paper adopts multiple signal classification least-squares estimation method to estimate the vibrating frequency and amplitude. To evaluate the performance of the proposed method, ideal point target simulation and vibrating calibrator experiment have been conducted, and the results show that the positions and the vibrating parameters of the vibrating objects fit well with the reference values. In addition, car experiment and bridge experiment have been carried out to verify the ability of the proposed method to measure the vibration of real artificial structures, which cannot be seen as point targets. [ABSTRACT FROM AUTHOR]