Adaptive Wavelet Denoising Method for Ezhaust Temperature Measurement of Microturbine
Exhaust temperature measurement is very important in the microturbine control and it accompanies with the whole process of microturbine operating. Generally, exhaust temperature can not be measured correctly due to harmonics interference of high frequency converter. An adaptive wavelet denoising method is proposed to eliminate this interference induced by the drive system of microturbine, which is based on orthogonal wavelet transform and adaptive learning algorithm . In the algorithm, original signal is changed into a number of small bands by mean of orthogonal wavelet transform. Finally, optimal threshold is gotten utilizing adaptive learning algorithm based on gradient. By applying this method, the shortcoming of threshold of hard and soft threshold method is overcome. The results of simulation are used to demonstrate the validity of the algorithm.
Microturbine Ezhaust temperature Harmonics interference Adaptive wavelet denoising Threshold
Yan Shijie Wang Xu Jing Yanqiang
School of Information Science and Engineering, Northeastern University, China
国际会议
沈阳
英文
91-94
2009-08-27（万方平台首次上网日期，不代表论文的发表时间）