Data Fusion based on RBF Neural Network for Error Compensation in Resistance Strain Gauge Force Transducers

2007 ◽  
Author(s):  
Yan Chen ◽  
Benoit Boulet ◽  
Ping Chen ◽  
Mingbo Zhao
Keyword(s):  
Neural Network ◽  
Data Fusion ◽  
Strain Gauge ◽  
Error Compensation ◽  
Rbf Neural Network ◽  
Resistance Strain ◽  
Resistance Strain Gauge ◽  
Force Transducers

Research on Temperature Compensation of the Fiber Bragg Grating Sensor and the Resistance Strain Gauge

2021 ◽  
Vol 16 (6) ◽  
pp. 1020-1027
Author(s):  
Feng Zhu ◽  
Min Liu ◽  
Chengjun Xu ◽  
Sheng Zou ◽  
Chentong Chen ◽  
...  
Keyword(s):  
Fiber Bragg Grating ◽  
Strain Gauge ◽  
Temperature Compensation ◽  
Metal Structure ◽  
Resistance Strain ◽  
Fiber Bragg Grating Sensor ◽  
Bragg Grating ◽  
Resistance Strain Gauge ◽  
Strain Monitoring ◽  
Bragg Grating Sensor

The fiber Bragg grating sensor is widely used in strain monitoring of large metal structure and trend to replace the resistance strain gauge due to its advantages of strong stability, high measurement accuracy, multiple points measuring, strong environmental suitability and long transmission distance. The temperature-induced strain, which can have the same order of magnitudes as the mechanically-induced strain, will cause great errors in the strain monitoring. Therefore, the temperature compensation for the sensors is essential to guarantee the measurement accuracy. The existing theoretical models and experiment platforms for analyzing the temperature compensation are established by assuming that the testing temperature is constant. However, the surrounding temperature of some large metal structure is not stable, and the effect of temperature change cannot be neglected. This paper aims to establish an analytic model and an experiment platform to compare the temperature compensation of the fiber bragg grating sensor and the resistance strain gauge. The superiority of the temperature compensation for the fiber bragg grating sensor is verified. The result provides theoretical support for choosing the fiber bragg grating sensor in the long-time strain monitoring.

Study on Eliminating the Effect of Bending Moment in Torque Measurement

2012 ◽  
Vol 217-219 ◽  
pp. 2293-2298
Author(s):  
Qing Hai Jiang ◽  
Yu Sun ◽  
Xiao Yong Xu
Keyword(s):  
Adverse Effect ◽  
Strain Gauge ◽  
Bending Moment ◽  
Resistance Strain ◽  
Torque Measurement ◽  
Motor Shaft ◽  
Principle Of Superposition ◽  
Resistance Strain Gauge ◽  
Transmission Shaft

The function characteristics of bending moment and torque were analyzed based on the principle of torque measurement and the adverse effect of bending moment to torque measurement was proved theoretically. By distributing the positions of resistance strain gauge on the transmission shaft and the relative positions in the bridge, an effective method of eliminating the adverse effect of bending moment was proposed base on the principle of superposition and counterbalance in the bridge, and the potential errors were analyzed and corrected. Then the proposed method was applied in measuring the torque of a motor shaft. The result shows that the effect of bending moment has been eliminated, and this method is feasible and effective.

An RBF neural network approach to geometric error compensation with displacement measurements only

2016 ◽  
Vol 28 (6) ◽  
pp. 1235-1248 ◽  
Author(s):  
Rui Yang ◽  
Kok Kiong Tan ◽  
Arthur Tay ◽  
Sunan Huang ◽  
Jie Sun ◽  
...  
Keyword(s):  
Neural Network ◽  
Error Compensation ◽  
Rbf Neural Network ◽  
Geometric Error ◽  
Network Approach ◽  
Neural Network Approach ◽  
Displacement Measurements
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