Laser pulse mass spectrometry (LPMS) mass estimating method based on data matching

Abstract

The invention discloses a laser pulse mass spectrometry (LPMS) mass estimating method based on data matching. The method comprises the steps of arranging a piezoelectric type acceleration sensor; collecting shocking signals of different masses and different falling heights; performing Fourier transform on the time-domain signals so as to transform the signals into a frequency spectrum; setting a cut-off frequency to obtain an effective frequency spectrum; setting a polynomial fitting order to perform curve fitting on the effective frequency spectrum; regarding all fitting curves as samples to form a mass estimating database; collecting site data and obtaining a fitting curve; performing correlation matching analysis on the obtained curve and all samples in the database; calculating a signal channel mass estimated value according to a relevant coefficient and the sample information; removing the abnormal values and calculating the final mass estimated value. The method disclosed by the invention is not influenced by the falling heights and environment noises, has the advantages of high precision and strong capacity of resisting disturbance, and also has robustness.

Description

technical field [0001] The invention relates to the technical field of nuclear engineering, in particular to an LPMS quality estimation method based on data matching. Background technique [0002] Loose part monitoring system (LPMS) is one of the basic safety tools for primary circuits of nuclear power plants, and is of great significance to the safe operation of nuclear power plants. Among them, the quality estimation of loose parts is one of the basic functions of LPMS system. Accurately estimate the mass of the loose parts when they are detached or collided, and then judge the type and degree of damage of the loose parts, providing a basis for subsequent fault diagnosis and elimination. The currently commonly used LPMS quality estimation methods are: [0003] (1) A mass estimation method based on the energy ratio of the high and low frequency bands of the collision signal; this method is extremely dependent on the selection of the high and low frequency band boundary po...

AI Technical Summary

Problems solved by technology

[0003] (1) A mass estimation method based on the energy ratio of the high and low frequency bands of the collision signal; this method is extremely dependent on the selection of the high and low frequency band boundary points, and at the same time depends on the selection of the high and low frequency bands. Improper selection of the above parameters will produce quality estimation results with large errors

[0004] (2) A quality estimation method based on spectral features and pattern recognition; a method for realizing LPMS quality estimation using pattern recognition and artificial neural network theory, mainly has the following problems: a large number of training samples are required, the learning speed is slow, and local convergence may occur

In this case, it is difficult to accurately reflect the quality characteristics and ensure the accuracy of quality estimation only by relying on frequency information

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