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Multiple oscillation detection method of nonlinear chirp mode decomposition algorithm based on intelligent optimization

A modal decomposition and detection method technology, applied in electrical testing/monitoring, testing/monitoring control systems, comprehensive factory control, etc., can solve problems such as unresearched, achieve good detection accuracy and reliability, and improve performance.

Active Publication Date: 2021-11-02
HUZHOU TEACHERS COLLEGE
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How to choose these two parameters is an important question but has not been studied

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  • Multiple oscillation detection method of nonlinear chirp mode decomposition algorithm based on intelligent optimization
  • Multiple oscillation detection method of nonlinear chirp mode decomposition algorithm based on intelligent optimization
  • Multiple oscillation detection method of nonlinear chirp mode decomposition algorithm based on intelligent optimization

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[0076] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be noted that the following embodiments are intended to facilitate the understanding of the present invention, but do not limit it in any way.

[0077] The invention combines an intelligent optimization algorithm with nonlinear chirp mode decomposition (NCMD), and proposes a new oscillation detector. Since the performance of NCMD depends on the selection of the mode number Q and the bandwidth parameter α, an intelligent optimization algorithm is used to search for the optimal parameter pair. Then, the optimized NCMD algorithm is used to extract multiple modes contained in the process variables. The normalized correlation coefficient and the sparse index were used to eliminate stray modes and quantify the degree of oscillation, respectively. After detection, the time-frequency information provided by the oscillation mode can be used to a...

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Abstract

The invention discloses a multiple oscillation detection method of a nonlinear chirp mode decomposition algorithm based on intelligent optimization. The multiple oscillation detection method comprises the following steps: (1) collecting a loop output signal of a to-be-detected industrial process; (2) decomposing the signal by using an NCMD method to obtain a plurality of initial decomposition modes; (3) calculating the fitness of each decomposition mode, and obtaining an optimal parameter pair of the NCMD method through intelligent optimization, including a mode number and a bandwidth parameter; (4) re-decomposing the loop output signal by using the optimized NCMD method to obtain a plurality of optimized decomposition modes; (5) calculating a normalized correlation coefficient and a sparse index of each optimized decomposition mode, and reserving the decomposition mode meeting an oscillation detection index as a final mode so as to detect oscillation; (6) estimating the oscillation frequency of each final mode by using power weighted average; and (7) researching the frequency relationship between different final modes to represent the oscillation type. The method has the advantages of high mold mixing resistance, high detection precision and high reliability.

Description

technical field [0001] The invention belongs to the field of performance evaluation and fault diagnosis in industrial control systems, and in particular relates to a multiple oscillation detection method based on a nonlinear chirp mode decomposition algorithm based on intelligent optimization. Background technique [0002] The detection and characterization of multiple oscillations is currently still a challenging problem due to factors such as nonlinearity, non-stationarity, and noise. Naghoosi and Huang combined a clustering algorithm and an autocovariance function to detect multiple oscillations and estimate the corresponding oscillation frequencies. Since multiple oscillations can be seen as frequency components contained in the data, researchers and engineers tend to use Fourier power spectroscopy to detect oscillations over the full range of the process. But the Fourier transform is only suitable for dealing with linear stationary signals, which is difficult to satisf...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05B23/02
CPCG05B23/0243G05B2219/24065Y02P90/02
Inventor 吴夏来张宁林灵
Owner HUZHOU TEACHERS COLLEGE
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