Pulse Train Fx-LMS Algorithm for Drive File Identification

Machines Pub Date : 2024-04-25 DOI:10.3390/machines12050286
Bharath Balasubramanya, Steve C. Southward
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Abstract

A novel time-domain algorithm is proposed in this paper for the iterative estimation of drive files. A drive file is a synchronized batch of dynamic time series commands that are simultaneously sent to one or more actuators in a test rig that is designed for service environment replication (SER). When drive file commands are input to an SER test rig, the response of the article under test is similar to what was measured in a service environment. The proposed Pulse Train Filtered-X Least Mean Square (PT-Fx-LMS) algorithm is based on methods developed for active noise and vibration control (ANVC). A time-domain PT-Fx-LMS algorithm is shown through several simulation studies to rapidly converge to a dynamic solution in a small number of iterations for a one degree-of-freedom nonlinear suspension. The PT-Fx-LMS algorithm is also shown to enable targeted iteration over isolated time slices within the data set, which challenges conventional frequency-domain techniques.
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用于驱动器文件识别的脉冲序列 Fx-LMS 算法
本文提出了一种新颖的时域算法,用于迭代估算驱动文件。驱动文件是一批同步的动态时间序列命令,这些命令被同时发送到为服务环境复制(SER)而设计的测试装置中的一个或多个执行器上。当驱动文件命令被输入到 SER 测试台时,被测物品的响应与在服务环境中测量到的类似。所提出的脉冲序列滤波-X 最小均方(PT-Fx-LMS)算法基于为主动噪声和振动控制(ANVC)开发的方法。通过几项仿真研究表明,时域 PT-Fx-LMS 算法能在少量迭代中快速收敛到一自由度非线性悬架的动态解。研究还表明,PT-Fx-LMS 算法能够对数据集中的孤立时间片进行有针对性的迭代,这对传统的频域技术提出了挑战。
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