基于粒子群参数优化的 O-VMD 数据处理方法研究

针对电磁超声测厚换能器保护提离距过大导致回波信号微弱且信噪比低,难以在时域内直接准确提取渡越时间得到精 确厚度值的问题,提出频域内粒子群(PSO)优化变分模态分解(VMD)参数的 O-VMD 渡越时间提取方法。 分别对分解层数和 惩罚因子选取固定参数,及基于峭度与功率谱熵联合适应度函数的 PSO 算法获取 VMD 遍历优化参数,进行双次 VMD 处理,滤 除高频及低频噪声;选取能量最大模态进行信号重构,并应用希尔伯特变换获取回波信号时差。 在不同提离条件下,对不同厚 度铝板检测数据采用 O-VMD、经验模态分解(EMD)等方法进行信号对比处理,结果表明,提离距在 0 ~ 2. 1 mm,O-VMD 方法最 大误差为 0. 67% ,且误差与提离距成正比,为精确获取高提离距测厚数据提供依据。

Research on the O-VMD thickness measurement data processing method based on particle swarm optimization

To solve the problem of weak echo signal and low signal-to-noise ratio caused by large lift-off distance of electromagnetic ultrasonic thickness measurement transducer protection, which makes it difficult to directly and accurately extract transit time to obtain accurate thickness value in time domain, this article proposes an O-VMD transit time extraction method based on particle swarm optimization of variational modal decomposition parameters in frequency domain. The fixed parameters are selected for decomposition layers and penalty factors respectively, and the particle swarm optimization algorithm based on the joint fitness function of kurtosis and power spectrum entropy is used to obtain the ergodic optimization parameters of the variational mode decomposition. The VMD processing is performed twice to filter high-frequency and low-frequency noise. The maximum energy mode is selected for signal reconstruction, and the transit time of echo signal is obtained by applying Hilbert transform. Under different lift off distances, O-VMD, EMD and other methods are used for signal contrast processing of aluminum plate detection data with different thicknesses. The results show that the maximum error of O-VMD method is 0. 67% when the lift off distance is within 0 ~ 2. 1 mm, and the error is proportional to the lift off distance, providing a basis for accurately obtaining thickness measurement data with high lift off distance.