Application of WNN in Ring Ball Gratings Torque Sensors Signal Demodulation
The components structure and principle of ring ball gratings sensor is put forward for the present state that there still has not a better method to detect torque under the extreme environment in domestic. According to the localization property in time and frequency domains and the translation invariant property, the preprocessed signal of sensor is decomposed with multi resolution, and the signal is reconstructed with wavelet under the intervention of neural network. The wavelet neural networks (WNN) model is constructed and the algorithm routine is realized in laboratory virtual instrument engineering workbench (LabVIEW). With the testing device, the demodulation experiments are carried out for the corresponding sensor signals when the shaft is continuous rotated along the same direction, rotated along the alternate direction and knocked. The results indicate that the demodulation effect and confidence level are very well.
Ring Ball Gratings Torque Sensor Wavelet Neural Networks Undecimated Wavelet Transform
Wu yongfeng Yu honglin Li xiaodong Kang zhiping
Engineering and Technology College, Southwest University, Chongqing ,China, 400716 Key Laboratory of Key Laboratory of Opto-Electronic Technology and System, Ministry of Education, Chongqing Univers Engineering and Technology College, Southwest University, Chongqing ,China, 400716
国际会议
合肥
英文
4152-4157
2011-09-23（万方平台首次上网日期，不代表论文的发表时间）