本文選題：扭擺式硅微加速度計 + 神經(jīng)網(wǎng)絡(luò)�。� 參考：《儀表技術(shù)與傳感器》2015年11期

【摘要】：隨著MEMS加速度計應(yīng)用領(lǐng)域的不斷廣泛,其溫度性能越來越受到重視。在研究扭擺式硅微加速度計結(jié)構(gòu)與溫度特性的基礎(chǔ)上,采用改進LM_BP神經(jīng)網(wǎng)絡(luò)來構(gòu)建MEMS加速度計的補償模型,通過實時溫度變化優(yōu)化出溫度補償模型參數(shù),進而實現(xiàn)實時溫度補償。實驗結(jié)果表明,通過該方法補償后的標(biāo)度因數(shù)溫度系數(shù)和全溫零偏穩(wěn)定性分別由252 ppm/℃和16.62 mg/h減小為100 ppm/℃和2.30 mg/h,證明了該溫度補償方法的有效性和可行性。
[Abstract]:With the wide application of MEMS accelerometer, more and more attention has been paid to its temperature performance. Based on the study of the structure and temperature characteristics of the torsion pendulum silicon microaccelerometer, an improved LM_BP neural network is used to construct the compensation model of the MEMS accelerometer, and the parameters of the temperature compensation model are optimized by real-time temperature variation. Furthermore, real-time temperature compensation is realized. The experimental results show that the scaling factor temperature coefficient and the total temperature zero bias stability are reduced from 252 ppm/ 鈩，

本文編號：1774850