CN205175690U - Online fault diagnostic of wind generating set based on DSP - Google Patents
Online fault diagnostic of wind generating set based on DSP Download PDFInfo
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- CN205175690U CN205175690U CN201520800224.0U CN201520800224U CN205175690U CN 205175690 U CN205175690 U CN 205175690U CN 201520800224 U CN201520800224 U CN 201520800224U CN 205175690 U CN205175690 U CN 205175690U
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Abstract
The utility model discloses an online fault diagnostic of wind generating set based on DSP contains piezoelectric acceleration sensor, preprocessing circuit, DSP, light friendship machine, host computer, configuration king's software, the data transfer that piezoelectric acceleration sensor will gather gives preprocessing circuit, preprocessing circuit enlargies the vibrational acceleration signal of gathering, filtering, the information after the preliminary treatment makes in being in DSP's working range, then the AD sampling is carried out to the information of DSP after to the preliminary treatment, the analysis is carried out to procedure through DSP, handle, obtain antifriction bearing's peak factor numerical value and kurtosis numerical value, then cross light friendship machine through the ethernet antilinear on the DSP and transfer the host computer, show peak factor numerical value and kurtosis numerical value on configuration king's software of host computer, can also look over the history and the alarm information of section any time. The utility model discloses can realize automated inspection, can monitor a plurality of antifriction bearing simultaneously moreover, can in time discover the antifriction bearing that goes wrong, shorten the time of maintenance, improve the security, convenient to use, easy operation.
Description
Technical field
The utility model relates to the wind power generating set online system failure diagnosis based on DSP, belongs to wind power generating set fault diagnosis technology field.
Background technology
Under the background emphasizing protection of the environment, sustainable development now, the wind-power electricity generation of consumption of fossil fuels, non-environmental-pollution is not considered to the most clean energy utilization type.In in the past 10 years, because annual average rate of increase is close to 28%, wind-power electricity generation has become the fastest-rising class renewable sources of energy in the world.Recent years, because the development of China's wind-power electricity generation installation amount is rapid, the fault diagnosis technology of corresponding wind power generating set there has also been certain progress, but compared with speed of development faster wind power equipment, the fault diagnosis technology of wind power equipment need further raising.In addition, due to the singularity of wind-powered electricity generation industry, equipment operation and maintenance somewhat expensive.According to statistics, wind power equipment operation and maintenance cost exceedes 10% ~ 15% of total revenue, and carries out more changing jobs of a gear case and will spend unit up to a million.Therefore, at present in the urgent need to studying a kind of on-line fault monitoring and diagnostic method, Timeliness coverage fault initial stage sign, prevents the generation of catastrophic failure or serious accident.
Rolling bearing is the most basic part as rotating machinery in wind power system, and can the quality of its performance normally work directly having influence on whole system.Because rolling bearing breaks down feature not obvious in early days, artificially judge that rolling bearing is fine or not and there is very high False Rate.Too early replacing rolling bearing can increase production cost, and spending evening and change rolling bearing may damage equipment, and even affect the normal operation of miscellaneous equipment, What is more can cause security incident.Therefore, research and develop a set of online system failure diagnosis to have great importance.
Therefore, the condition monitoring and fault diagnosis of Wind turbines seems particularly important, is the key ensureing the operation of unit long-term stability and safe power generation.Fault diagnosis of wind turbines is beneficial to the economic benefit reducing failure rate, reduce servicing time, increase annual electricity generating capacity and raising wind energy turbine set; Be beneficial to discovery initial failure, the necessary time can not only be provided for unit maintenance personnel placement standby device and goods and materials, and guidance and suggestion can be provided for designer.
Summary of the invention
For the problems referred to above, the technical problems to be solved in the utility model is to provide a kind of wind power generating set online system failure diagnosis based on DSP.
A kind of wind power generating set online system failure diagnosis based on DSP of the present utility model, it comprises piezoelectric acceleration sensor, pre-process circuit, DSP, light friendship machine, host computer, KingView software.Piezoelectric acceleration sensor sends the data collected to pre-process circuit, pre-process circuit amplifies the vibration acceleration signal gathered, filtering, the information after pre-service is made to be in the working range of DSP, then DSP carries out A/D sampling to pretreated information, program through DSP is analyzed, process, obtain peak factor numerical value and the kurtosis numerical value of rolling bearing, then machine is handed over to pass to host computer by the Ethernet interface on DSP through light, peak value display factor value and kurtosis numerical value on the KingView software of host computer, historical record and the warning message of section any time can also be checked.
As preferably, the information of described online system failure diagnosis after DSP process hands over machine to send host computer to by Ethernet interface through light, realizes Long Distant Transmit.
As preferably, described line fault diagnosis system host computer can monitor multiple wind power generating set simultaneously.
The beneficial effects of the utility model are: can realize automatically detecting, be convenient to the fault finding genset early, shorten the time of maintenance, improve security, easy to use, simple to operate.
accompanying drawing illustrates:
For ease of illustrating, the utility model is described in detail by following concrete enforcement and accompanying drawing.
Fig. 1 is structural representation of the present utility model;
Piezoelectric acceleration sensor (1), pre-process circuit (2), DSP(3), light hand over machine (4), host computer (5), KingView software (6)
In figure: 1-piezoelectric acceleration sensor; 2-pre-process circuit; 3-DSP; 4-light hands over machine; 5-host computer, 6-KingView.
embodiment:
For making the purpose of this utility model, technical scheme and advantage clearly understand, below by the specific embodiment shown in accompanying drawing, the utility model is described.But should be appreciated that, these describe just exemplary, and do not really want to limit scope of the present utility model.In addition, in the following description, the description to known features and technology is eliminated, to avoid unnecessarily obscuring concept of the present utility model.
As shown in Figure 1, this embodiment by the following technical solutions: it comprises piezoelectric acceleration sensor 1, pre-process circuit 2, DSP3, light friendship machine 4, host computer 5, KingView software 6.Piezoelectric acceleration sensor 1 sends the data collected to pre-process circuit 2, pre-process circuit amplifies the vibration acceleration signal gathered, filtering, the information after pre-service is made to be in the working range of DSP, then DSP3 carries out A/D sampling to pretreated information, program through DSP3 is analyzed, process, obtain peak factor numerical value and the kurtosis numerical value of rolling bearing, then machine 4 is handed over through fiber optic cables to light by the Ethernet interface on DSP3, light hands over machine 4 and host computer 5 to be linked by fiber optic cables, peak value display factor value and kurtosis numerical value on the KingView software 6 of host computer 5, historical record and the warning message of section any time can also be checked.Further, the information of described online system failure diagnosis after DSP process hands over machine to send host computer to by Ethernet interface through light, realizes Long Distant Transmit.
Further, described line fault diagnosis system host computer can monitor multiple wind power generating set simultaneously.
The principle of work of this embodiment is: by the position Information Monitoring of piezoelectric acceleration sensor to on-site supervision, pre-process circuit amplifies the vibration acceleration signal gathered, filtering, the signal collected is made to be in the working range of DSP, then the A/D sampling module on DSP carries out A/D sampling to pretreated signal, and treatment and analysis is carried out to signal, obtain peak factor and kurtosis, machine is handed over to send to host computer through light, KingView software on host computer can remote monitoring online, when the numerical value of peak factor and kurtosis has during larger change and can send warning, be convenient to on-call maintenance, easy to use, easy and simple to handle.
More than show and describe ultimate principle of the present utility model and principal character and advantage of the present utility model.The technician of the industry should understand; the utility model is not restricted to the described embodiments; what describe in above-described embodiment and instructions just illustrates principle of the present utility model; under the prerequisite not departing from the utility model spirit and scope; the utility model also has various changes and modifications, and these changes and improvements all fall within the scope of claimed the utility model.The claimed scope of the utility model is defined by appending claims and equivalent thereof.
Claims (3)
1. based on the wind power generating set online system failure diagnosis of DSP, it is characterized in that: it comprises piezoelectric acceleration sensor (1), pre-process circuit (2), DSP(3), light hand over machine (4), host computer (5), KingView software (6), piezoelectric acceleration sensor (1) sends the data collected to pre-process circuit (2), pre-process circuit amplifies the vibration acceleration signal gathered, filtering, the information after pre-service is made to be in the working range of DSP, then DSP(3) A/D sampling is carried out to pretreated information, through DSP(3) program analyze, process, obtain peak factor numerical value and the kurtosis numerical value of rolling bearing, then by DSP(3) on Ethernet interface hand over machine (4) to pass to host computer (5) through light, at the upper peak value display factor value of the KingView software (6) of host computer (5) and kurtosis numerical value, historical record and the warning message of section any time can also be checked.
2. the wind power generating set online system failure diagnosis based on DSP according to claim 1, is characterized in that: the information after DSP process hands over machine to send host computer to by Ethernet interface through light, realizes Long Distant Transmit.
3. the wind power generating set online system failure diagnosis based on DSP according to claim 1, is characterized in that: host computer can monitor multiple wind power generating set simultaneously.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201520800224.0U CN205175690U (en) | 2015-10-13 | 2015-10-13 | Online fault diagnostic of wind generating set based on DSP |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201520800224.0U CN205175690U (en) | 2015-10-13 | 2015-10-13 | Online fault diagnostic of wind generating set based on DSP |
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| Publication Number | Publication Date |
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| CN205175690U true CN205175690U (en) | 2016-04-20 |
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| Application Number | Title | Priority Date | Filing Date |
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| CN201520800224.0U Expired - Fee Related CN205175690U (en) | 2015-10-13 | 2015-10-13 | Online fault diagnostic of wind generating set based on DSP |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109556858A (en) * | 2017-09-26 | 2019-04-02 | 南京淳泰控制设备有限公司 | A kind of flywheel bearing unit running-in test equipment |
| CN112362236A (en) * | 2020-11-16 | 2021-02-12 | 苏州铁马自动化科技有限公司 | Dynamic balance measuring system supporting Ethernet big data transmission and control method thereof |
| CN114705430A (en) * | 2022-04-15 | 2022-07-05 | 广东石油化工学院 | Rolling bearing fault monitoring method, device, equipment and storage medium |
-
2015
- 2015-10-13 CN CN201520800224.0U patent/CN205175690U/en not_active Expired - Fee Related
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109556858A (en) * | 2017-09-26 | 2019-04-02 | 南京淳泰控制设备有限公司 | A kind of flywheel bearing unit running-in test equipment |
| CN112362236A (en) * | 2020-11-16 | 2021-02-12 | 苏州铁马自动化科技有限公司 | Dynamic balance measuring system supporting Ethernet big data transmission and control method thereof |
| CN114705430A (en) * | 2022-04-15 | 2022-07-05 | 广东石油化工学院 | Rolling bearing fault monitoring method, device, equipment and storage medium |
| CN114705430B (en) * | 2022-04-15 | 2022-09-20 | 广东石油化工学院 | Rolling bearing fault monitoring method, device, equipment and storage medium |
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| Date | Code | Title | Description |
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| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20160420 Termination date: 20171013 |