Damped SVD for operational transfer path analysis

Wei Cheng, Yapeng Chu, Yingying Lu, Y. Zi
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Abstract

Transfer path analysis (TPA) is a method to identify energy transfer paths based on experiment and principle of linear superposition, which is widely used to identify the source of main faults based on vibration and noise signals, thus benefiting the works of PHM. However, load identification and transfer function measurement make it complex and slow to carry out. Operational transfer path analysis (OTPA) gets rid of the load identification and transfer function measurement, has attracted more attention due to simple and fast modeling. From a theoretical perspective, OTPA belongs to an inverse problem. Conventional OTPA use truncated singular value decomposition (TSVD) to identify transmissibility function matrix, which has two main shortages. Firstly, TSVD uses 0 and 1 as filter factors, without considering smoothness of filter factors, the sudden change of filter factors will result in large rounding errors, thus aggravating the ill-conditioned degree and approximate solution distortion. Secondly, the truncating parameter is usually chosen from experience, which is one of the most important parameters in TSVD, it's obviously not precise enough to meet the requirements. DSVD uses smooth filter factors to overcome the shortage of sudden change of filter factors in TSVD. Moreover, the regularization parameter is used to calculate the filter factors, which is easy to figure out by L-curve, overcoming the shortage of choosing from experience. A simulation experiment is adopted to test the proposed OTPA which proves that the proposed OTPA is correct and effective to solve vibration and noise problems. The proposed OTPA is also compared with the conventional OTPA which proves that precision of the proposed OTPA is much higher than that of the conventional OTPA.
用于操作传递路径分析的阻尼奇异值分解
传递路径分析(TPA)是一种基于实验和线性叠加原理的能量传递路径识别方法,广泛应用于基于振动和噪声信号的主故障源识别,有利于电力机械的工作。然而,载荷识别和传递函数测量使其复杂且执行缓慢。运行传递路径分析(OTPA)摆脱了负荷识别和传递函数测量,由于建模简单、快速而受到越来越多的关注。从理论角度看,OTPA属于一个逆问题。传统的OTPA方法采用截断奇异值分解(TSVD)来识别传递函数矩阵,存在两个主要不足。首先,TSVD使用0和1作为滤波因子,如果不考虑滤波因子的平滑性,滤波因子的突然变化会导致较大的舍入误差,从而加重了病态程度和近似解失真。其次,截断参数通常是根据经验选择的,这是TSVD中最重要的参数之一,其精度显然不能满足要求。DSVD采用平滑滤波因子,克服了TSVD中滤波因子突变的不足。利用正则化参数计算滤波因子,克服了以往经验选择的不足,易于用l曲线计算。通过仿真实验对所提出的OTPA进行了验证,验证了所提出的OTPA解决振动和噪声问题的正确性和有效性。并与传统的OTPA进行了比较,证明了该方法的精度比传统的OTPA要高得多。
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