Method for processing online oil path grain signal
A treatment method and technology of abrasive particles, applied in particle size analysis, particle and sedimentation analysis, measuring devices, etc., to achieve the effect of improving accuracy
Inactive Publication Date: 2015-06-24
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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[0012] However, the online oil circuit wear particle signal contains some interference signals. How to obtain an effective wear particle signal and make the online oil circuit wear particle monitoring more accurate is an important problem that needs to be solved
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[0059] Specific embodiments of the present invention will be described below in conjunction with the accompanying drawings, so that those skilled in the art can better understand the present invention. It should be noted that in the following description, when detailed descriptions of known functions and designs may dilute the main content of the present invention, these descriptions will be omitted here.
[0060] figure 2 It is a flow chart of a specific embodiment of the processing method of the online oil circuit wear particle signal of the present invention.
[0061] In this example, if figure 2 As shown, the processing method of the online oil circuit wear particle signal of the present invention includes several steps such as double-buffering online oil circuit wear particle signal acquisition 1, FFT frequency domain filtering 2, dynamic average extraction 3 and effective wear particle signal extraction 4, etc. Each step will be described in detail below in combinati...
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The invention provides a method for processing an online oil path grain signal. The method comprises the steps of: firstly, carrying out alternative cache and reading on the acquired online oil path grain signal through two cache regions with storage depth of N so that continuous acquisition is realized and a condition is provided for continuous processing; secondly, circularly splicing the online oil path grain signal data acquired by the two front and rear cache regions to obtain the online oil path grain signal data with length of 2N, and then carrying out overlapping redundancy FFT (Fast Fourier Transform)-denoising-IFFT (Inverse Fast Fourier Transform) frequency domain filtering to ensure that the signal data with frequency higher than a set frequency fset is filtered; and thirdly, extracting a dynamic average, and extracting an effective grain signal according to the constraint condition. According to the method, the signal data such as a carrier signal with the frequency higher than the set frequency fset can be effectively filtered so as to avoid the interference, low-frequency components generated by power voltage low-frequency fluctuation, sensor temperature drift and the like can be filtered, and the effective grain signal is accurately obtained according to the constraint condition, and thus the size of grains is accurately known, and the accuracy of monitoring the grains of an online oil path is improved.
Description
technical field [0001] The invention belongs to the technical field of abrasive particle monitoring, and more specifically relates to a processing method of an online oil path abrasive particle signal. Background technique [0002] Wear is one of the main reasons for the failure of mechanical parts. The abrasive particles in the oil circuit oil are important information carriers about the wear state of the engine. The number and size classification of the abrasive particles can be used to judge the degree of wear and tear of the machine. Operating status, predicting potential hazards. [0003] At present, there are mainly methods for monitoring wear particles in oil circuit oil at home and abroad, including spectroscopy, ferrography, particle counting and magnetic plug method. These methods belong to off-line measurement and have limited real-time performance. [0004] The applicant proposed an online wear particle monitoring method, which uses the principle of electromagne...
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IPC IPC(8): G01N15/00G01N15/02
Inventor 赵辉古军杨坚杨红宇张放詹惠琴
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA