Error characteristic analysis and experimental research on a fiber optic current transformer

2018 ◽  
Vol 57 (28) ◽  
pp. 8359 ◽  
Author(s):  
Yansong Li ◽  
Xinying Liu ◽  
Weiwei Zhang ◽  
Jun Liu
Keyword(s):  
Experimental Research ◽  
Fiber Optic ◽  
Current Transformer ◽  
Error Characteristic ◽  
Characteristic Analysis

scholarly journals Error Characteristic Analysis of Fluid Momentum Law Test Apparatus

2020 ◽  
Vol 11 (1) ◽  
pp. 90
Author(s):  
Song Yang ◽  
Xianyong Zhu ◽  
Hui Wang
Keyword(s):  
Measurement Error ◽  
Control Method ◽  
Theoretical Research ◽  
Structural Deformation ◽  
Error Characteristic ◽  
Characteristic Analysis ◽  
Jet Impact ◽  
Effect Theory ◽  
Characteristic Points ◽  
Periodic Error

The flat-plate momentum test bench is a widely used experimental device in the verification of the momentum law of fluid mechanics, and its error characteristics are of positive significance for theoretical research and engineering innovation and expansion. The SPH-FEM coupling algorithm and spectrum analysis method are used to calculate and analyze the displacement response and spectrum characteristics of the characteristic points of the sensor under different jet loads. Based on them, the cause, classification, law, scope, influence and control method of the measurement error of the system are discussed and analyzed with the application of the error theory and the lateral effect theory of strain gauges; combined with physical experiments, the relevant analysis methods and conclusions are verified. The results show that the measurement error of the system includes linear error and periodic error. Structural deformation in the direction of jet impact is the main source of linear error; linear error increases with the increase of jet loads. Meanwhile, periodic vibration in non-jet direction is the main cause of periodic error, and the periodic error decreases with the increase of jet loads.

Experimental Research on Interferometric Fiber-Optic Sensing System with Polarization Diversity Receiver

2010 ◽  
Vol 30 (6) ◽  
pp. 1566-1570
Author(s):  
王潇 Wang Xiao ◽  
张学亮 Zhang Xueliang ◽  
胡正良 Hu Zhengliang ◽  
曹春燕 Cao Chunyan ◽  
胡永明 Hu Yongming
Keyword(s):  
Experimental Research ◽  
Fiber Optic ◽  
Polarization Diversity ◽  
Sensing System ◽  
Fiber Optic Sensing ◽  
Diversity Receiver

Influence of Sensing Coil Errors on Portable Fiber-Optic Current Transformer

2017 ◽  
Vol 54 (1) ◽  
pp. 010601
Author(s):  
王夏霄 Wang Xiaxiao ◽  
张宇宁 Zhang Yuning ◽  
于 佳 Yu Jia ◽  
李传生 Li Chuansheng ◽  
张 猛 Zhang Meng
Keyword(s):  
Fiber Optic ◽  
Current Transformer

Intelligent fault diagnosis algorithm for fiber optic current transformer

2020 ◽  
Vol 64 (1-4) ◽  
pp. 3-10
Author(s):  
Lihui Wang ◽  
Kai Zhao ◽  
Wenpeng Zhang ◽  
Jian Liu ◽  
Fubin Pang
Keyword(s):  
Fault Diagnosis ◽  
Fiber Optic ◽  
Short Term Memory ◽  
Current Transformer ◽  
Support Vector ◽  
Intelligent Fault Diagnosis ◽  
Signal Prediction ◽  
Residual Signal ◽  
Signal Characteristics ◽  
Diagnosis Algorithm

Affected by environmental factors, the performance of fiber optic current transformer (FOCT) will deteriorate over a long period of time. Intelligent fault diagnosis algorithm of Long-Short Term Memory (LSTM) combing with Support Vector Machine (SVM) is an effective way to deal with FOCT failures. According to the characteristics of LSTM, a signal prediction model in FOCT based on LSTM is proposed by analyzing the historical data. The residual signal can be obtained by the prediction signal and the observed signal. Set the residual threshold to determine whether the FOCT has fault. With the residual signal characteristics, a fault diagnosis model based on SVM is established. By analyzing the residual signal and extracting features, the diagnostic network can realize the pattern recognition and system fault diagnosis. Experiments demonstrate that the drift deviation fault, the ratio deviation fault and the fixed deviation fault can be diagnosed with an accuracy of 94.5%.

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