CN109255447B - Automatic analysis method of vibration data - Google Patents
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Abstract
The invention provides an automatic analysis method of vibration data, which comprises the following steps: step S1, deploying a Webservice interface on the vibration server to open vibration data in the vibration server; step S2, configuring a CSV file on a vibration data calculation server, wherein the CSV file comprises names of vibration monitoring points, rotating speed thresholds, starting and stopping frequencies of band-pass filtering, a plurality of fault characteristic data and a plurality of trend analysis parameter thresholds; step S3, reading the CSV file and calling the vibration data in the vibration server in the vibration data calculation server, processing the vibration data, and writing the judged fault into a log file; step S4, the log file is provided to the staff member, and the staff member performs the corresponding processing. The automatic analysis method of the vibration data can realize automatic analysis of the vibration data, judge whether the fault exists according to the analysis result of the vibration data, and facilitate maintenance personnel to timely maintain the fault in the wind generating set.
Description
Technical Field
The invention relates to the field of data analysis, in particular to an automatic analysis method of vibration data.
Background
In the wind power generation industry, the analysis of vibration data is usually carried out manually, so that an experienced vibration analyst is required to comprehensively judge equipment fault points and fault levels through an auxiliary analysis tool in relevant vibration data acquisition and analysis software, but a large amount of manpower, material resources and financial resources are required to be invested in cultivating one vibration analyst, and therefore software development work for automatic analysis of vibration data is urgently needed.
Disclosure of Invention
In order to solve the problems in the prior art, the invention provides an automatic analysis method of vibration data, so that the automatic analysis of the vibration data can be realized, and maintenance personnel can conveniently and timely maintain the faults in the wind generating set.
In order to achieve the above object, the present invention provides a method for automatically analyzing vibration data, the method comprising the steps of:
step S1, deploying a Webservice interface on the vibration server to open vibration data in the vibration server;
step S2, configuring a CSV file on a vibration data calculation server, wherein the CSV file comprises names of vibration monitoring points, rotating speed thresholds, starting and stopping frequencies of band-pass filtering, a plurality of fault characteristic data and a plurality of trend analysis parameter thresholds;
step S3, reading the CSV file and calling the vibration data in the vibration server in the vibration data calculation server, processing the vibration data, and writing the judged fault into a log file;
step S4, providing the log file to a worker for corresponding processing;
wherein, the processing of the vibration data in the step S3 includes the following steps:
step S301, calling n vibration data corresponding to a certain vibration monitoring point name in a vibration server through a Webservice interface, wherein n is a positive integer;
step S302, decomposing one vibration data in the n vibration data, wherein the decomposed data comprises a rotating speed, vibration waveform data and a total value;
step S303, judging whether the rotating speed after the vibration data is decomposed is larger than the rotating speed threshold value in the step S2, and if so, jumping to the step S304; if not, jumping to step S312;
step S304, carrying out fast Fourier transform on the vibration waveform data after the vibration data are decomposed;
step S305, judging whether fault characteristic data matched with the fast Fourier transform result exists in the step S2, and if so, jumping to the step S306; if not, jumping to step S308;
step S306, performing trend analysis on the total value after the vibration data decomposition, judging whether the total value has an ascending trend, and whether the ascending trend is greater than the corresponding trend analysis parameter threshold value in the step S2, if so, jumping to the step S307; if not, jumping to step S312;
step S307, outputting a level 2 of the log file, wherein the log file indicates a late-stage fault;
step S308, carrying out envelope demodulation on the vibration waveform data;
step S309, judging whether fault characteristic data matched with the envelope demodulated result exists in the step S2, if so, jumping to the step S310; if not, jumping to step S312;
step S310, performing trend analysis on the total value after the vibration data decomposition, judging whether the total value has an ascending trend, and whether the ascending trend is greater than the corresponding trend analysis parameter threshold value in the step S2, if so, jumping to the step S311; if not, jumping to step S312;
step S311, outputting a level 1 of the log file, which indicates an early failure;
step S312, outputting the grade 0 of the log file, which indicates no fault;
step S313, repeating the steps S302 to S312, processing the rest vibration data corresponding to the vibration monitoring point name, and writing the judged fault into a log file;
and S314, repeating the steps S301 to S313, processing each vibration data corresponding to each vibration monitoring point name, and writing the judged fault into a log file.
Preferably, in step S1, the vibration data in the vibration server is collected vibration data of vibration monitoring points in each fan, each fan includes a transmission chain, each transmission chain includes a plurality of vibration monitoring points, and each vibration monitoring point includes a plurality of vibration data.
Preferably, in step S308, the envelope demodulation is implemented by using band-pass filtering and hilbert algorithm.
The method for automatically analyzing the vibration data has the advantages that the method for automatically analyzing the vibration data can automatically analyze the vibration data, judge whether the fault exists or not according to the analysis result of the vibration data, and facilitate maintenance personnel to timely maintain the fault in the wind generating set.
Drawings
Fig. 1 shows a flow chart of a method for automatic analysis of vibration data according to the present invention.
Fig. 2 shows a flowchart of a specific process for the vibration data in step S3 in fig. 1.
Detailed Description
The following further describes embodiments of the present invention with reference to the drawings.
As shown in fig. 1, the method for automatically analyzing vibration data according to the present invention includes the steps of:
and step S1, deploying a Webservice interface on the vibration server to open the vibration data in the vibration server. The vibration data in the vibration server is vibration data of vibration monitoring points in each fan, each fan comprises a transmission chain, each transmission chain comprises a plurality of vibration monitoring points, a certain vibration monitoring point is a vibration sensor arranged at a bearing at a certain position on the transmission chain, such as a generator front bearing vibration sensor and a generator rear bearing vibration sensor, each vibration monitoring point comprises a plurality of vibration data, in the embodiment, each vibration monitoring point comprises three vibration data, namely 16k of vibration data, 128k of vibration data and 256k of vibration data, wherein the 16k of vibration data is used for analyzing the fault of a bearing retainer, the 128k of vibration data is used for analyzing the fault of the inner ring or the outer ring of the bearing, and the 256k of vibration data is used for analyzing the fault of a bearing rolling body.
Step S2, configuring a CSV file on the vibration data calculation server, wherein the CSV file comprises names of vibration monitoring points, rotating speed thresholds, starting and stopping frequencies of band-pass filtering, a plurality of fault characteristic data and a plurality of trend analysis parameter thresholds.
Step S3, in the vibration data calculation server, the CSV file is read, the vibration data in the vibration server is retrieved, the vibration data is processed, and the determined failure is written in the log file. Specifically, the EXE executive program may be embedded in the vibration data calculation server so as to read the CSV file and retrieve the vibration data in the vibration server.
Step S4, the log file is provided to the staff member, and the staff member performs the corresponding processing.
As shown in fig. 2, the processing of the vibration data in step S3 specifically includes the following steps:
step S301, through a Webservice interface, n vibration data corresponding to a certain vibration monitoring point name in a vibration server are called, wherein n is a positive integer.
And step S302, decomposing one vibration data in the n vibration data, wherein the decomposed data comprises the rotating speed, the alarm level, the vibration waveform data, the total value and the like.
Step S303, judging whether the rotating speed after the vibration data is decomposed is larger than the rotating speed threshold value in the step S2, and if so, jumping to the step S304; if not, it jumps to step S312.
And step S304, performing fast Fourier transform on the vibration waveform data after the vibration data decomposition.
Step S305, judging whether fault characteristic data matched with the fast Fourier transform result exists in the step S2, and if so, jumping to the step S306; if not, it jumps to step S308.
Step S306, performing trend analysis on the total value after the vibration data decomposition, judging whether the total value has an ascending trend, and whether the ascending trend is greater than the corresponding trend analysis parameter threshold value in the step S2, if so, jumping to the step S307; if not, it jumps to step S312. In this embodiment, during the trend analysis, the total value may be compared with the related historical data to determine whether the total value is in an ascending trend, and if the total value is in an ascending trend, the total value is compared with a certain historical data to determine whether the difference value is greater than the corresponding trend analysis parameter threshold in step S2.
Step S307, log file output level 2. Level 2 indicates that the failure is late, severe and in urgent need of treatment.
And step S308, performing envelope demodulation on the vibration waveform data. The specific envelope demodulation is implemented by using a band-pass filter and a hilbert algorithm, and the start-stop frequency of the band-pass filter is preset in step S2.
Step S309, judging whether fault characteristic data matched with the envelope demodulated result exists in the step S2, if so, jumping to the step S310; if not, it jumps to step S312.
Step S310, performing trend analysis on the total value after the vibration data decomposition, judging whether the total value has an ascending trend, and whether the ascending trend is greater than the corresponding trend analysis parameter threshold value in the step S2, if so, jumping to the step S311; if not, it jumps to step S312.
Step S311, log file output level 1. Level 1 represents the earlier stage of the failure.
And step S312, outputting the log file with the level 0. Level 0 represents no failure.
And step S313, repeating the steps S302 to S312, processing the rest vibration data corresponding to the vibration monitoring point name, and writing the judged fault into a log file.
And S314, repeating the steps S301 to S313, processing each vibration data corresponding to each vibration monitoring point name, and writing the judged fault into a log file.
The automatic analysis method of the vibration data can realize automatic analysis of the vibration data, judge whether the fault exists according to the analysis result of the vibration data, and facilitate maintenance personnel to timely maintain the fault in the wind generating set.
Claims (1)
1. A method for automatically analyzing vibration data is characterized in that: the method comprises the following steps:
step S1, deploying a Webservice interface on the vibration server to open vibration data in the vibration server; the vibration data in the vibration server is acquired vibration data of vibration monitoring points in each fan, each fan comprises a transmission chain, each transmission chain comprises a plurality of vibration monitoring points, and each vibration monitoring point comprises a plurality of vibration data;
step S2, configuring a CSV file on a vibration data calculation server, wherein the CSV file comprises names of vibration monitoring points, rotating speed thresholds, starting and stopping frequencies of band-pass filtering, a plurality of fault characteristic data and a plurality of trend analysis parameter thresholds;
step S3, reading the CSV file and calling the vibration data in the vibration server in the vibration data calculation server, processing the vibration data, and writing the judged fault into a log file;
step S4, providing the log file to a worker for corresponding processing;
wherein, the processing of the vibration data in the step S3 includes the following steps:
step S301, calling n vibration data corresponding to a certain vibration monitoring point name in a vibration server through a Webservice interface, wherein n is a positive integer;
step S302, decomposing one vibration data in the n vibration data, wherein the decomposed data comprises a rotating speed, vibration waveform data and a total value;
step S303, judging whether the rotating speed after the vibration data is decomposed is larger than the rotating speed threshold value in the step S2, and if so, jumping to the step S304; if not, jumping to step S312;
step S304, carrying out fast Fourier transform on the vibration waveform data after the vibration data are decomposed;
step S305, judging whether fault characteristic data matched with the fast Fourier transform result exists in the step S2, and if so, jumping to the step S306; if not, jumping to step S308;
step S306, performing trend analysis on the total value after the vibration data decomposition, judging whether the total value has an ascending trend, and whether the ascending trend is greater than the corresponding trend analysis parameter threshold value in the step S2, if so, jumping to the step S307; if not, jumping to step S312;
step S307, outputting a level 2 of the log file, wherein the log file indicates a late-stage fault;
step S308, carrying out envelope demodulation on the vibration waveform data; the envelope demodulation is realized by adopting band-pass filtering and a Hilbert algorithm;
step S309, judging whether fault characteristic data matched with the envelope demodulated result exists in the step S2, if so, jumping to the step S310; if not, jumping to step S312;
step S310, performing trend analysis on the total value after the vibration data decomposition, judging whether the total value has an ascending trend, and whether the ascending trend is greater than the corresponding trend analysis parameter threshold value in the step S2, if so, jumping to the step S311; if not, jumping to step S312;
step S311, outputting a level 1 of the log file, which indicates an early failure;
step S312, outputting the grade 0 of the log file, which indicates no fault;
step S313, repeating the steps S302 to S312, processing the rest vibration data corresponding to the vibration monitoring point name, and writing the judged fault into a log file;
and S314, repeating the steps S301 to S313, processing each vibration data corresponding to each vibration monitoring point name, and writing the judged fault into a log file.
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN102156043A (en) * | 2010-12-31 | 2011-08-17 | 北京四方继保自动化股份有限公司 | Online state monitoring and fault diagnosis system of wind generator set |
| CN102620807A (en) * | 2012-03-22 | 2012-08-01 | 内蒙古科技大学 | System and method for monitoring state of wind generator |
| KR20180035549A (en) * | 2016-09-29 | 2018-04-06 | 한국전력공사 | apparatus and method for evaluating fault risk index of a rotator |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN102156043A (en) * | 2010-12-31 | 2011-08-17 | 北京四方继保自动化股份有限公司 | Online state monitoring and fault diagnosis system of wind generator set |
| CN102620807A (en) * | 2012-03-22 | 2012-08-01 | 内蒙古科技大学 | System and method for monitoring state of wind generator |
| KR20180035549A (en) * | 2016-09-29 | 2018-04-06 | 한국전력공사 | apparatus and method for evaluating fault risk index of a rotator |
Non-Patent Citations (1)
| Title |
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| 风电机组发电机故障分析诊断;徐颖剑;《中国优秀硕士学位论文全文数据库 工程科技II辑》;20131215;正文第35页-第64页 * |
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