CN109255447A - A kind of automatic analysis method of vibration data - Google Patents
A kind of automatic analysis method of vibration data Download PDFInfo
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- CN109255447A CN109255447A CN201811092443.2A CN201811092443A CN109255447A CN 109255447 A CN109255447 A CN 109255447A CN 201811092443 A CN201811092443 A CN 201811092443A CN 109255447 A CN109255447 A CN 109255447A
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Abstract
The present invention proposes a kind of automatic analysis method of vibration data comprising following steps: step S1, Webservice interface is disposed on vibration server, with the vibration data in open vibration server；Step S2, csv file is configured on vibration data calculation server, the csv file includes each vibration monitoring point title, rotary speed threshold value, the start-stop frequency of bandpass filtering, several fault signature data and several trend analysis parameter thresholds；Step S3, it in vibration data calculation server, reads csv file and transfers the vibration data in vibration server, vibration data is handled, journal file is written into the failure judged；Step S4, journal file is supplied to staff, it is made to carry out alignment processing.The automatic analysis method of vibration data according to the present invention can be realized automatically analyzing for vibration data, determines whether failure according to the analysis result to vibration data, maintenance personal is facilitated timely to repair to the failure occurred in wind power generating set.
Description
Technical field
The present invention relates to data analysis field more particularly to a kind of automatic analysis methods of vibration data.
Background technique
In wind power industry, at present about the analysis of vibration data often using artificially being analyzed, this is required
Vibration analysis teacher of experience is acquired by coupled vibration data, the assistant analysis tool in analysis software is come the event of comprehensive descision equipment
Hinder point, fault level, but cultivates vibration analysis teacher and need to put into a large amount of manpower, material resources and financial resources, therefore be badly in need of shaking
The software development work of dynamic data analysis.
Summary of the invention
In order to solve the problems in the existing technology, the invention proposes a kind of automatic analysis method of vibration data,
So as to realize automatically analyzing for vibration data, facilitate maintenance personal timely to the failure occurred in wind power generating set into
Row maintenance.
To achieve the goals above, the invention proposes a kind of automatic analysis method of vibration data, the method includes
Following steps:
Step S1, Webservice interface is disposed on vibration server, with the vibration data in open vibration server；
Step S2, csv file is configured on vibration data calculation server, the csv file includes each vibration monitoring point
Title, rotary speed threshold value, the start-stop frequency of bandpass filtering, several fault signature data and several trend analysis parameter thresholds；
Step S3, it in vibration data calculation server, reads csv file and transfers the vibration number in vibration server
According to, vibration data is handled, by the failure judged be written journal file；
Step S4, journal file is supplied to staff, it is made to carry out alignment processing；
Wherein, vibration data is handled in the step S3, comprising the following steps:
Step S301, by Webservice interface, transfer in vibration server with a certain vibration monitoring point title phase
Corresponding n vibration data, wherein n is positive integer；
Step S302, some vibration data in above-mentioned n vibration data is decomposed, the data after decomposition include
Revolving speed, vibrational waveform data and total value；
Step S303, judge whether the revolving speed after above-mentioned vibration data decomposes is greater than the rotary speed threshold value in step S2, if
It is the S304 that then gos to step；If it is not, then the S312 that gos to step；
Step S304, the vibrational waveform data after decomposing to above-mentioned vibration data carry out Fast Fourier Transform (FFT)；
Step S305, with the presence or absence of the fault signature number to match with Fast Fourier Transform (FFT) result in judgment step S2
According to if it is, the S306 that gos to step；If it is not, then the S308 that gos to step；
Step S306, the total value after decomposing to above-mentioned vibration data carries out trend analysis, judges the total value with the presence or absence of upper
The trend of liter, and whether the trend risen is greater than in step S2 corresponding trend analysis parameter threshold, if it is, going to step
S307；If it is not, then the S312 that gos to step；
Step S307, journal file output level 2, is shown to be late-in-life failure；
Step S308, envelope demodulation is carried out to above-mentioned vibrational waveform data；
Step S309, with the presence or absence of the fault signature number to match with the result after above-mentioned envelope demodulation in judgment step S2
According to if it is, the S310 that gos to step；If it is not, then the S312 that gos to step；
Step S310, the total value after decomposing to above-mentioned vibration data carries out trend analysis, judges the total value with the presence or absence of upper
The trend of liter, and whether the trend risen is greater than in step S2 corresponding trend analysis parameter threshold, if it is, going to step
S311；If it is not, then the S312 that gos to step；
Step S311, journal file output level 1, is shown to be initial failure；
Step S312, journal file output level 0, shows fault-free；
Step S313, step S302 to step S312 is repeated, by remaining each vibration corresponding to the vibration monitoring point title
Data are handled, and journal file is written in the failure judged；
Step S314, step S301 to step S313 is repeated, by each vibration data corresponding to each vibration monitoring point title
It is handled, journal file is written into the failure judged.
Preferably, in the step S1, the vibration data in the vibration server is in each blower of acquisition
The vibration data of each vibration monitoring point contains a transmission chain in every Fans, includes several vibration monitorings on each transmission chain
Point, each vibration monitoring point includes several vibration datas.
Preferably, in the step S308, envelope demodulation comes using bandpass filtering and Hilbert algorithm
It realizes.
The beneficial effect of the program of the present invention is that the automatic analysis method of above-mentioned vibration data can be realized vibration number
According to automatically analyze, failure is determined whether according to the analysis result to vibration data, facilitates maintenance personal timely to wind-force
The failure occurred in generating set repairs.
Detailed description of the invention
Fig. 1 shows the flow chart of the automatic analysis method of vibration data according to the present invention.
Fig. 2 shows in step S3 in Fig. 1 to the specific process flow diagram of vibration data.
Specific embodiment
A specific embodiment of the invention is further described with reference to the accompanying drawing.
As shown in Figure 1, the automatic analysis method of vibration data according to the present invention the following steps are included:
Step S1, Webservice interface is disposed on vibration server, with the vibration data in open vibration server.
Wherein the vibration data in the vibration server is the vibration data of each vibration monitoring point in each blower of acquisition, every typhoon
Contain a transmission chain in machine, include several vibration monitoring points on each transmission chain, some vibration monitoring point is certain on transmission chain
The vibrating sensor being arranged at one position bearing, such as generator fore bearing vibrating sensor, generator rear bearing vibrating sensing
Device, each vibration monitoring point includes several vibration datas, and in the present embodiment, each vibration monitoring point includes three vibration numbers
According to being the vibration data of the vibration data of 16k, the vibration data of 128k and 256k respectively, wherein the vibration data of 16k is used for
Bearing retainer failure is analyzed, the vibration data of 128k is for analyzing bearing inside/outside circle failure, and the vibration data of 256k is for dividing
Analyse bearing roller failure.
Step S2, csv file is configured on vibration data calculation server, the csv file includes each vibration monitoring point
Title, rotary speed threshold value, the start-stop frequency of bandpass filtering, several fault signature data and several trend analysis parameter thresholds.
Step S3, it in vibration data calculation server, reads csv file and transfers the vibration number in vibration server
According to, vibration data is handled, by the failure judged be written journal file.It can specifically calculate and service in vibration data
It is embedded in EXE in device and executes program, to read csv file and to transfer the vibration data in vibration server.
Step S4, journal file is supplied to staff, it is made to carry out alignment processing.
As shown in Fig. 2, vibration data is handled in the step S3, specifically includes the following steps:
Step S301, by Webservice interface, transfer in vibration server with a certain vibration monitoring point title phase
Corresponding n vibration data, wherein n is positive integer.
Step S302, some vibration data in above-mentioned n vibration data is decomposed, the data after decomposition include
Revolving speed, alarm level, vibrational waveform data and total value etc..
Step S303, judge whether the revolving speed after above-mentioned vibration data decomposes is greater than the rotary speed threshold value in step S2, if
It is the S304 that then gos to step；If it is not, then the S312 that gos to step.
Step S304, the vibrational waveform data after decomposing to above-mentioned vibration data carry out Fast Fourier Transform (FFT).
Step S305, with the presence or absence of the fault signature number to match with Fast Fourier Transform (FFT) result in judgment step S2
According to if it is, the S306 that gos to step；If it is not, then the S308 that gos to step.
Step S306, the total value after decomposing to above-mentioned vibration data carries out trend analysis, judges the total value with the presence or absence of upper
The trend of liter, and whether the trend risen is greater than in step S2 corresponding trend analysis parameter threshold, if it is, going to step
S307；If it is not, then the S312 that gos to step.It in the present embodiment, can be by the total value during carrying out trend analysis
Be compared with relevant historical data, see it is whether in rising trend, if in rising trend, then by the total value and a certain historical data
It is compared, sees whether difference is greater than in step S2 corresponding trend analysis parameter threshold.
Step S307, journal file output level 2.It is 2 representing fault of grade more advanced stage, in need of immediate treatment than more serious.
Step S308, envelope demodulation is carried out to above-mentioned vibrational waveform data.Specific envelope demodulation is filtered using band logical
Wave and Hilbert algorithm realize that the start-stop frequency of bandpass filtering has been preset in the step S2.
Step S309, with the presence or absence of the fault signature number to match with the result after above-mentioned envelope demodulation in judgment step S2
According to if it is, the S310 that gos to step；If it is not, then the S312 that gos to step.
Step S310, the total value after decomposing to above-mentioned vibration data carries out trend analysis, judges the total value with the presence or absence of upper
The trend of liter, and whether the trend risen is greater than in step S2 corresponding trend analysis parameter threshold, if it is, going to step
S311；If it is not, then the S312 that gos to step.
Step S311, journal file output level 1.1 representing fault of grade more early stage.
Step S312, journal file output level 0.Grade 0 represents fault-free.
Step S313, step S302 to step S312 is repeated, by remaining each vibration corresponding to the vibration monitoring point title
Data are handled, and journal file is written in the failure judged.
Step S314, step S301 to step S313 is repeated, by each vibration data corresponding to each vibration monitoring point title
It is handled, journal file is written into the failure judged.
The automatic analysis method of vibration data according to the present invention can be realized automatically analyzing for vibration data, according to right
The analysis result of vibration data determines whether failure, facilitates the maintenance personal timely to the failure occurred in wind power generating set
It repairs.
Claims (3)
1. a kind of automatic analysis method of vibration data, it is characterised in that: the described method comprises the following steps:
Step S1, Webservice interface is disposed on vibration server, with the vibration data in open vibration server；
Step S2, configure csv file on vibration data calculation server, the csv file include each vibration monitoring point title,
Rotary speed threshold value, the start-stop frequency of bandpass filtering, several fault signature data and several trend analysis parameter thresholds；
Step S3, it in vibration data calculation server, reads csv file and transfers the vibration data in vibration server,
Vibration data is handled, journal file is written into the failure judged；
Step S4, journal file is supplied to staff, it is made to carry out alignment processing；
Wherein, vibration data is handled in the step S3, comprising the following steps:
Step S301, it by Webservice interface, transfers corresponding with a certain vibration monitoring point title in vibration server
N vibration data, wherein n be positive integer；
Step S302, some vibration data in above-mentioned n vibration data is decomposed, the data after decomposition include turning
Speed, vibrational waveform data and total value；
Step S303, judge whether the revolving speed after above-mentioned vibration data decomposes is greater than the rotary speed threshold value in step S2, if it is,
Go to step S304；If it is not, then the S312 that gos to step；
Step S304, the vibrational waveform data after decomposing to above-mentioned vibration data carry out Fast Fourier Transform (FFT)；
Step S305, with the presence or absence of the fault signature data to match with Fast Fourier Transform (FFT) result in judgment step S2, such as
Fruit is the S306 that then gos to step；If it is not, then the S308 that gos to step；
Step S306, the total value after decomposing to above-mentioned vibration data carries out trend analysis, judges that the total value becomes with the presence or absence of rising
Gesture, and whether the trend risen is greater than in step S2 corresponding trend analysis parameter threshold, if it is, going to step
S307；If it is not, then the S312 that gos to step；
Step S307, journal file output level 2, is shown to be late-in-life failure；
Step S308, envelope demodulation is carried out to above-mentioned vibrational waveform data；
Step S309, it whether there is the fault signature data to match with the result after above-mentioned envelope demodulation in judgment step S2,
If it is, the S310 that gos to step；If it is not, then the S312 that gos to step；
Step S310, the total value after decomposing to above-mentioned vibration data carries out trend analysis, judges that the total value becomes with the presence or absence of rising
Gesture, and whether the trend risen is greater than in step S2 corresponding trend analysis parameter threshold, if it is, going to step
S311；If it is not, then the S312 that gos to step；
Step S311, journal file output level 1, is shown to be initial failure；
Step S312, journal file output level 0, shows fault-free；
Step S313, step S302 to step S312 is repeated, by remaining each vibration data corresponding to the vibration monitoring point title
It is handled, journal file is written into the failure judged；
Step S314, step S301 to step S313 is repeated, each vibration data corresponding to each vibration monitoring point title is carried out
Journal file is written in the failure judged by processing.
2. the automatic analysis method of vibration data according to claim 1, it is characterised in that: in the step S1, institute
The vibration data that the vibration data in vibration server is each vibration monitoring point in each blower of acquisition is stated, is contained in every Fans
There is a transmission chain, includes several vibration monitoring points on each transmission chain, each vibration monitoring point includes several vibration datas.
3. the automatic analysis method of vibration data according to claim 1 or 2, it is characterised in that: in the step S308
In, envelope demodulation is realized using bandpass filtering and Hilbert algorithm.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110553723A (en) * | 2019-08-26 | 2019-12-10 | 苏州德姆斯信息技术有限公司 | vibration signal processing system and method |
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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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- 2018-09-19 CN CN201811092443.2A patent/CN109255447B/en active Active
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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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| 徐颖剑: "风电机组发电机故障分析诊断", 《中国优秀硕士学位论文全文数据库 工程科技II辑》 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110553723A (en) * | 2019-08-26 | 2019-12-10 | 苏州德姆斯信息技术有限公司 | vibration signal processing system and method |
| CN110553723B (en) * | 2019-08-26 | 2020-10-02 | 苏州德姆斯信息技术有限公司 | Vibration signal processing system and method |
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