scholarly journals Research on Mechanical Defect Detection and Diagnosis Method for GIS Equipment Based on Vibration Signal

Energies ◽  
2021 ◽  
Vol 14 (17) ◽  
pp. 5507
Author(s):  
Liang He ◽  
Jie Yang ◽  
Ziwei Zhang ◽  
Zongwu Li ◽  
Dengwei Ding ◽  
...  
Keyword(s):  
Experimental Research ◽  
Detection System ◽  
Engineering Application ◽  
Vibration Signal ◽  
Signal Amplitude ◽  
Field Application ◽  
Large Current ◽  
Three Phase ◽  
Diagnosis Method ◽  
Detection And Diagnosis

Gas insulated switchgear equipment (GIS) is widely used in power system, and more attention has been paid to discharge defects than mechanical defects. However, since mechanical defects are a major cause of the failure in GIS, it is of great significance to carry out relevant research on mechanical defects. Detection and diagnosis methods of mechanical defects based on vibration signal are studied in this paper. Firstly, vibration mechanisms of GIS are analyzed. Due to structural differences between single phase insulated type GIS and three phase insulated type GIS, there are big differences in vibration mechanisms between the two types of GISs. Secondly, experimental research on mechanical defects is carried out based on a 110 kV GIS equipment and a self-developed vibration detection system; results show that mechanical defects can be diagnosed by analyzing signal amplitude, frequency spectrum and waveform distortion rate, and a large current is more beneficial for diagnosing mechanical defects. Lastly, field application has been carried out on 220 kV GIS equipment, and a poor contact defect is found, demonstrating that abnormal diagnosis can be realized by method proposed in this paper. Experimental research and field application demonstrate the feasibility and effectiveness of detection and diagnosis method for mechanical defects based on vibration signal and provide experience for subsequent engineering application.

scholarly journals Mechanical defect detection of porcelain column high-voltage disconnector based on operating torque

2020 ◽  
Vol 17 (1) ◽  
pp. 172988141990084
Author(s):  
Taotao Zhou ◽  
Jiangjun Ruan ◽  
Zhifei Yang ◽  
Yufei Liu
Keyword(s):  
High Voltage ◽  
Defect Detection ◽  
Mechanical State ◽  
Detection Technology ◽  
Three Phase ◽  
Torque Curve ◽  
Diagnosis Method ◽  
Defect Simulation ◽  
Detection And Diagnosis ◽  
Mechanical Defect

Currently, there is no effective detection and diagnosis technology for the frequently happened mechanical defects of disconnectors. A porcelain column high-voltage disconnector is taken as the object to study the influence of mechanical defects, including bearing jamming, axle pin jamming, and three-phase position asynchrony on the operating torque through geometric mechanics deduction. An operating torque detection technology is proposed, which could accurately measure the operating torque of the disconnector without destroying its original shafting. Using this technology, the operating torque curves of the disconnector in normal state and typical mechanical defect simulation states are measured and compared. The results indicate that the operating torque changes with the mechanical state of disconnector, and these changes could be quantified through the proposed detection technology. And the types of mechanical defects can be distinguished according to their different effects on the operating torque curve. Based on this, a practical mechanical defects diagnosis method is summarized to provide reference for maintainers to diagnose the mechanical defects of disconnectors.

The Study of Vibration Diagnosis Method for GIS

2013 ◽  
Vol 295-298 ◽  
pp. 2429-2432
Author(s):  
Pei Ding ◽  
Zhen Hua Yan ◽  
Fei Yue Ma ◽  
Liang Zhang ◽  
Jun Hao Li ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Field Test ◽  
Detection Method ◽  
Detection System ◽  
Vibration Signal ◽  
Normal Operation ◽  
Vibration Test ◽  
Test Results ◽  
Vibration Detection ◽  
Diagnosis Method

Gas insulated switchgear (GIS) will generate vibration during normal operation for the electromagnetic force. There will be generate abnormal vibration when the contacts are undesirable, the guide rod stressed unevenness. Therefore, it can be effective in fault diagnosis of this machineries through the vibration test of GIS in field. The vibration detection method of GIS equipment in field is studied in this paper, the composition of the vibration detection system is described. The field test has been done using vibration detection system and the test results show that through the vibration signal detected from the GIS equipment, the vibration characteristics of GIS can be clarified and make the fault diagnosis effectively.

Research on Roller Bearing with Fault Diagnosis Method Based on EMD and BP Neural Network

2014 ◽  
Vol 1014 ◽  
pp. 501-504 ◽  
Author(s):  
Shu Guo ◽  
You Cai Xu ◽  
Xin Shi Li ◽  
Ran Tao ◽  
Kun Li ◽  
...  
Keyword(s):  
Neural Network ◽  
Fault Diagnosis ◽  
Bp Neural Network ◽  
Roller Bearing ◽  
Vibration Signal ◽  
Classification Performance ◽  
Outer Race ◽  
Mode Decomposition ◽  
Diagnosis Method ◽  
Main Fault

In order to discover the fault with roller bearing in time, a new fault diagnosis method based on Empirical mode decomposition (EMD) and BP neural network is put forward in the paper. First, we get the fault signal through experiments. Then we use EMD to decompose the vibration signal into a series of single signals. We can extract main fault information from the single signals. The kurtosis coefficient of the single signals forms a feature vector which is used as the input data of the BP neural network. The trained BP neural network can be used for fault identification. Through analyzing, BP neural network can distinguish the fault into normal state, inner race fault, outer race fault. The results show that this method can gain very stable classification performance and good computational efficiency.

Gear Fault Diagnosis Methods Based on EMD and HMM

2013 ◽  
Vol 333-335 ◽  
pp. 1684-1687
Author(s):  
Bin Wu ◽  
Song He Zhang ◽  
Yue Gang Luo ◽  
Shan Ping Yu
Keyword(s):  
Fault Diagnosis ◽  
Vibration Signal ◽  
Modulation Amplitude ◽  
Double Frequency ◽  
Gear Mesh ◽  
Gear Fault ◽  
Diagnosis Method ◽  
Modulation Signal ◽  
Gear Fault Diagnosis ◽  
Modulation Sideband

Due to the feature and the forms of motion of the gears, the vibration signal of the gear is mainly the frequency modulation, amplitude modulation, or hybrid modulation signal corresponding to the gear-mesh frequency and its double frequency signal. When faults arise on the gears, the number and shape of the modulation sideband will be changed. The structures and forms of the FM composition differ according to the type of faults. According to the above mentioned characteristic, this essay raises a method to disassemble the gear vibrate signal, points out the formulas to build up characteristic vector, on that basis, the essay raised a gear fault diagnosis method based on EMD and Hidden Markov Model (HMM), this method can identify the working condition of the normal gears, snaggletooth gears, and pitting gears.

scholarly journals Faults diagnosis in stator windings of high speed solid rotor induction motors using fuzzy neural network

2021 ◽  
Vol 12 (1) ◽  
pp. 597
Author(s):  
Ahmed Thamer Radhi ◽  
Wael Hussein Zayer
Keyword(s):  
Neural Network ◽  
Equivalent Circuit ◽  
High Speed ◽  
Fuzzy Neural Network ◽  
Induction Motors ◽  
Stator Winding ◽  
Three Phase ◽  
Fuzzy Neural ◽  
Diagnosis Method ◽  
Faults Diagnosis

The paper deals with faults diagnosis method proposed to detect the inter-turn and turn to earth short circuit in stator winding of three-phase high-speed solid rotor induction motors. This method based on negative sequence current of motor and fuzzy neural network algorithm. On the basis of analysis of 2-D electromagnet field in the solid rotor the rotor impedance has been derived to develop the solid rotor induction motor equivalent circuit. The motor equivalent circuit is simulated by MATLAB software to study and record the data for training and testing the proposed diagnosis method. The numerical results of proposed approach are evaluated using simulation of a three-phase high-speed solid-rotor induction motor of two-pole, 140 Hz. The results of simulation shows that the proposed diagnosis method is fast and efficient for detecting inter-turn and turn to earth faults in stator winding of high-speed solid-rotor induction motors with different faults conditions

scholarly journals Rib fracture detection system based on deep learning

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Liding Yao ◽  
Xiaojun Guan ◽  
Xiaowei Song ◽  
Yanbin Tan ◽  
Chun Wang ◽  
...  
Keyword(s):  
Deep Learning ◽  
Learning Algorithm ◽  
Detection System ◽  
Rib Fracture ◽  
Diagnostic Efficiency ◽  
Fracture Detection ◽  
Deep Learning Algorithm ◽  
Experienced Radiologist ◽  
Comparable Performance ◽  
Detection And Diagnosis

AbstractRib fracture detection is time-consuming and demanding work for radiologists. This study aimed to introduce a novel rib fracture detection system based on deep learning which can help radiologists to diagnose rib fractures in chest computer tomography (CT) images conveniently and accurately. A total of 1707 patients were included in this study from a single center. We developed a novel rib fracture detection system on chest CT using a three-step algorithm. According to the examination time, 1507, 100 and 100 patients were allocated to the training set, the validation set and the testing set, respectively. Free Response ROC analysis was performed to evaluate the sensitivity and false positivity of the deep learning algorithm. Precision, recall, F1-score, negative predictive value (NPV) and detection and diagnosis were selected as evaluation metrics to compare the diagnostic efficiency of this system with radiologists. The radiologist-only study was used as a benchmark and the radiologist-model collaboration study was evaluated to assess the model’s clinical applicability. A total of 50,170,399 blocks (fracture blocks, 91,574; normal blocks, 50,078,825) were labelled for training. The F1-score of the Rib Fracture Detection System was 0.890 and the precision, recall and NPV values were 0.869, 0.913 and 0.969, respectively. By interacting with this detection system, the F1-score of the junior and the experienced radiologists had improved from 0.796 to 0.925 and 0.889 to 0.970, respectively; the recall scores had increased from 0.693 to 0.920 and 0.853 to 0.972, respectively. On average, the diagnosis time of radiologist assisted with this detection system was reduced by 65.3 s. The constructed Rib Fracture Detection System has a comparable performance with the experienced radiologist and is readily available to automatically detect rib fracture in the clinical setting with high efficacy, which could reduce diagnosis time and radiologists’ workload in the clinical practice.

scholarly journals Experimental Research into the Influence of Photodetector Types on Characteristics of Optical Mini-Sticks of Unified Human- Machine Interfaces

2018 ◽  
pp. 137-142
Author(s):  
Sergey A. Golubin ◽  
Alexei N. Lomanov ◽  
Vladimir S. Nikitin ◽  
Valery M. Komarov
Keyword(s):  
Experimental Research ◽  
Test Bench ◽  
Signal Amplitude ◽  
Central Position ◽  
Signal Quality ◽  
Path Diagram ◽  
Photo Detectors ◽  
The Right ◽  
The Cost ◽  
Ray Path

The article provides the results of the experimental research into the influence of different types of photo detectors of digital optical mini­sticks on their transformation function – the useful mini­stick signal as a function of the mini­stick control lever deviation value. The set problem was solved using experimental research methods. Circuits with a photo diode (PIN photodiode PD15– 21B/TR8 manufactured by Everlight company) and circuits with a phototransistor (phototransistor KP2012P3C manufactured by Kingbright company) were studied. An automated test bench was used for the research. The test bench allows setting the mini­stick rotation angle and the value of mini­stick lever deviation from the central position to the left or to the right. The influence on mini­sticks was set by the test bench software. Based on the test results the test bench software plotted a ray path diagram. The mini­stick signal quality was assessed in terms of resolution, accuracy, non­linearity and hysteresis. The following results were obtained in the research. The mini­stick using a photo transistor as a photo detector ensures the output signal amplitude and resolution which exceed those of mini­stick with a photodiode by factor of 3.5 to 4. It allows using mini­sticks with a phototransistor for high­precision control of complex robotic systems, manipulators and aircraft, and for designing joysticks and unified human­machine interfaces on their basis. The indices of precision, non­linearity and hystere sis of both mini­stick types are comparable and meet the basic requirements applied to control devices. Thus, mini­sticks based on phototransistors can be regarded as the best in terms of the signal quality. Taking into consideration the circuitry, overall dimensions and the cost of hardware components which are identical for both photo detectors, mini­sticks based on phototransistors shall be considered to be more advanced switching devices.

Modeling, Analysis, of Induction Motor's Stator Turns Fault Using Neuro-Fuzzy

2021 ◽  
pp. 498-520
Author(s):  
Hussein. A. Taha ◽  
M. E. Ammar ◽  
M. A. Moustafa Hassan
Keyword(s):  
Induction Motor ◽  
Diagnostic Tool ◽  
Short Circuit ◽  
Simulated Data ◽  
Fault Detection And Diagnosis ◽  
Modeling And Analysis ◽  
Motor Current ◽  
Neuro Fuzzy ◽  
Three Phase ◽  
Detection And Diagnosis

This chapter discusses modeling and analysis methods for fault detection and diagnosis of stator inter-turn short circuit in three-phase induction machines. dq frame was used to model the induction motor for both health and fault cases to facilitate recognition of motor current and simulate motor environment. Fault diagnosis system was designed with adaptive neuro-fuzzy inference system (ANFIS) to provide an efficient online diagnostic tool. ANFIS diagnostic tool was trained with simulated data that generated by induction motor healthy and faulty models. Approached tool is verified online with a motor under different loading conditions. It determines the fault severity values using the motor current signature analysis (MCSA). Developed tool performance is investigated with a case study of two HP three-phase induction motor using Matlab/Simulink® software.

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