加速度信号积分求解位移方法研究

目的研究动力学环境试验分析中时域积分算法和频域积分算法两种加速度信号积分求解位移方法。方法动力学环境试验中,利用不同算法对被试品测点处所采集到的加速度信号进行二次积分处理,计算求解位移。采集过程中,再利用激光传感器测量位移,以激光所测位移为基准,对比分析不同算法求解结果的准确性,并分析其结果的误差来源、其优缺点及适用范围。结果在动力学环境试验的不同工况下,两种不同积分法得到的位移数据与激光测定数据基本重合,积分得到的位移最大误差均小于5%,符合实际应用需求。时域积分算法在两次积分中受到噪声以及直流分量误差的影响较大;频域积分算法的计算结果相对更加准确,但是受到低频误差影响较大,具有低频敏感性。结论在动力学环境试验中,时域积分算法适用于噪声和直流分量可忽略的情况,频域积分算法适应于低频误差较小的情况。对加速度信号数据进行必要且有效的预处理后,时域积分算法和频域积分算法的位移积分结果都具有较高的准确性,能够满足一般工程实际中的测试需求。

Research on the Method of Solving Displacement by Integrating Acceleration Signal

This paper studies two acceleration signal integration methods to solve displacement in time domain integration algorithm and frequency domain integration algorithm in dynamic environment test analysis. In the dynamic environment test, different algorithms are used to perform quadratic integration processing on the acceleration signal collected at the measuring point of the test product to calculate and solve the displacement. In the acquisition process, the laser sensor is used to measure the displacement. Based on the measurement results of laser displacement sensor, the accuracy, error sources, advantages and disadvantages and application scope of two different integral methods is compared and analyzed. Under different working conditions of dynamic environment test, the displacement data obtained by two different integration methods are basically coincident with the laser measurement data and the maximum error of displacement obtained by two kinds of integral methods is less than 5%. These all meet the needs of practical application. The time domain integration algorithm is greatly affected by noise and DC component error. The result of frequency domain integration algorithm is more accurate relatively, but it is greatly affected by low frequency error and it has low frequency sensitivity. In the dynamic environment test, the time domain integration algorithm is suitable for the case that the noise and DC component can be ignored. And the frequency domain integral algorithm is suitable for the case of small low frequency error. After necessary and effective preprocessing of acceleration signal data, the displacement results obtained by time domain integration algorithm and frequency domain integration algorithm have high accuracy. Therefore, both methods can meet the actual test requirements of general engineering.