CN114542443A - Pump intelligent diagnosis system based on internet of things - Google Patents
Pump intelligent diagnosis system based on internet of things Download PDFInfo
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- CN114542443A CN114542443A CN202111659573.1A CN202111659573A CN114542443A CN 114542443 A CN114542443 A CN 114542443A CN 202111659573 A CN202111659573 A CN 202111659573A CN 114542443 A CN114542443 A CN 114542443A
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- 238000003745 diagnosis Methods 0.000 title claims abstract description 33
- 238000007405 data analysis Methods 0.000 claims abstract description 17
- 238000005516 engineering process Methods 0.000 claims abstract description 13
- 230000005540 biological transmission Effects 0.000 claims abstract description 11
- 238000012545 processing Methods 0.000 claims description 16
- 238000012544 monitoring process Methods 0.000 abstract description 8
- 238000004458 analytical method Methods 0.000 abstract description 5
- 238000012423 maintenance Methods 0.000 abstract description 4
- 238000000034 method Methods 0.000 abstract description 4
- 230000008569 process Effects 0.000 abstract description 3
- 230000036541 health Effects 0.000 abstract description 2
- 238000013528 artificial neural network Methods 0.000 description 2
- 238000013145 classification model Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000013473 artificial intelligence Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000008901 benefit Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F04—POSITIVE - DISPLACEMENT MACHINES FOR LIQUIDS; PUMPS FOR LIQUIDS OR ELASTIC FLUIDS
- F04B—POSITIVE-DISPLACEMENT MACHINES FOR LIQUIDS; PUMPS
- F04B51/00—Testing machines, pumps, or pumping installations
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
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Abstract
The invention discloses an intelligent pump diagnosis system based on the technology of Internet of things, which comprises a pump group unit, an information acquisition module in signal connection with the output end of the pump group unit, a data transmission module in signal connection with the output end of the information acquisition module, a big data analysis module in signal connection with the output end of the big data analysis module, and a remote display module in signal connection with the output end of the data analysis module, wherein the remote display module is used for displaying processed data, and the information acquisition module comprises a plurality of sensors which are arranged on the pump group unit and are used for acquiring different states of the pump group unit. The process signals and the control signals of the pump group unit are collected through the comprehensive signal sensor, the operation signals of the pump group unit are monitored, the overall health condition of the pump group unit is comprehensively reflected, reliable and multidimensional basic data are provided for later-stage fault diagnosis and analysis, and unnecessary loss caused by time delay caused by informing related operation and maintenance personnel to operate after the fault is found through monitoring is reduced.
Description
Technical Field
The invention relates to the field of equipment monitoring, in particular to an intelligent pump diagnosis system based on the technology of the Internet of things.
Background
Due to the characteristics of the process industry, field devices are in a complex and harsh environment, and real-time monitoring of the devices is required and the devices are guaranteed to be in a safe and usable state. At present, the on-line monitoring object of the domestic oil exploitation industry is often a key large-scale unit, and the used device is precise and expensive; for some small-sized key rotating equipment (such as a pump, a fan and a motor), corresponding re-visibility is lacked, so most enterprises in the industry still stay in the stage of offline monitoring or manual regular inspection, but due to poor working environment, frequent operation and high fault occurrence rate, the operating quality of the equipment affects the production condition of the enterprises, and the direct economic benefit of the enterprises is also concerned.
At present, most of the existing on-line monitoring means for the state of the pump are that a plurality of vibration and temperature sensors, a plurality of state data gathering devices of the pump and an industrial personal computer serving as a monitoring terminal are used, and the state sensors are correspondingly installed on the pump. However, the type of the sensor is single, the detected running state parameters of the pump are few, and the whole information of the pump cannot be intuitively reflected. The method generally adopts the means that collected data are processed in a centralized mode and transmitted to an industrial personal computer, the real-time state, the historical running state and the fault diagnosis report of the pump are displayed through calculation and processing of the industrial personal computer, and after the fault is detected, field personnel are notified to maintain from beginning to processing to the end, so that the whole early warning and operation and maintenance process is long in time consumption, and certain major faults needing to be processed immediately in the operation of the pump cannot be responded timely and effectively, and the damage speed of the pump is accelerated.
Disclosure of Invention
The invention aims to design an intelligent pump diagnosis system based on the Internet of things technology to solve the problems in the background technology.
In order to achieve the purpose, the invention provides the following technical scheme:
the utility model provides a machine pump intelligent diagnosis system based on internet of things, including pump crowd unit, with the output end signal connection's of pump crowd unit information acquisition module, with the output end signal connection's of information acquisition module data transmission module, with the big data analysis module of data transmission module's output end signal connection, with the output end signal connection's of big data analysis module remote display module, remote display module is used for showing the data after handling, information acquisition module include a plurality of set up in gather on the pump crowd unit the sensor of the different states of pump crowd unit.
Further, the data transmission module comprises an internet of things node connected with the output end signal of the sensor and a network server end connected with the output end signal of the internet of things node.
Further, the big data analysis module comprises a characteristic layer processing module and a decision layer processing module in signal connection with the characteristic layer processing module.
Further, the remote display module comprises a computer web page end, a desktop client end, a smart phone web page end and a smart phone application program end.
Furthermore, the information acquisition module comprises one or a combination of a plurality of temperature sensors, vibration sensors, flow sensors and video sensors.
The invention has the beneficial effects that: compared with the prior art, the intelligent pump diagnosis system based on the internet of things acquires the flow signals and the control signals of the pump group unit through the comprehensive signal sensor, monitors the operation signals of the pump group unit, comprehensively reflects the overall health condition of the pump group unit, provides reliable and multidimensional basic data for later fault diagnosis and analysis, and simultaneously sets the remote display module to remotely monitor the pump group unit, provides a timely response means for major fault events needing to be immediately processed by the pump group unit, solves the problem of poor remote monitoring real-time performance in the conventional communication means at present, and reduces unnecessary loss caused by time delay caused by informing related operation and maintenance personnel to operate after the faults are monitored and found.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic structural diagram of an intelligent pump diagnosis system based on internet of things technology;
fig. 2 is a specific framework schematic diagram of the pump intelligent diagnosis system based on the internet of things technology;
fig. 3 is a flow chart of the pump intelligent diagnosis system based on the internet of things technology.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the accompanying drawings, and obviously, the description is only a part of the embodiments of the present invention, not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, are within the scope of the present invention.
Referring to fig. 1, the intelligent diagnosis system for the pump based on the internet of things technology comprises a pump group unit, an information acquisition module in signal connection with an output end of the pump group unit, a data transmission module in signal connection with an output end of the information acquisition module, a big data analysis module in signal connection with an output end of the big data analysis module, and a remote display module in signal connection with an output end of the data analysis module, wherein the remote display module is used for displaying processed data, and the information acquisition module comprises a plurality of sensors which are arranged on the pump group unit and used for acquiring different states of the pump group unit. The data transmission module comprises an internet of things node and a network server, wherein the internet of things node is in signal connection with the output end of the sensor, and the network server is in signal connection with the output end of the internet of things node. The big data analysis module comprises a characteristic layer processing module and a decision layer processing module in signal connection with the characteristic layer processing module. Referring to fig. 2, in this embodiment, the big data analysis module is composed of a data stream transmission path Node-RED (data stream), a Kafka message queue, an Elasticsearch data storage and Node-RED (data stream), an API service (Gunicorn + flash), and Python data analysis. And the big data analysis module is responsible for sorting and storing the mass data read by the information acquisition module. Based on a big data technology, a high-performance elastic search database is mainly adopted in the database, the database runs in a cluster mode, data are cleaned and processed in real time, then the data are respectively stored in different data warehouses according to data types, and meanwhile, a data interface is provided for an upper layer, so that upper layer application can call and realize various specific services at any time. And the characteristic layer processing module and the decision layer processing module finish the processing of the data based on the data stream transmission path.
The remote display module comprises a computer network page end, a desktop client end, a smart phone page end and a smart phone application program end. By the arrangement, the diagnosis result can be received through different display terminals, so that the relevant operation and maintenance personnel can be informed of the operation in time.
The information acquisition module comprises one or a combination of a plurality of temperature sensors, vibration sensors, flow sensors and video sensors. Different sensors are inserted into a single node to measure different quantities, so that the integration level of the module is higher, and the module has more functions. In the embodiment, the temperature sensor adopts a SG8000 vibration temperature sensor, and the video sensor adopts a DH-EPT230T explosion-proof integrated pan-tilt camera.
The working principle of the embodiment is as follows: referring to fig. 3, the information acquisition module acquires multi-source signal data of the pump group unit by adopting different types of sensors, wherein the multi-source signal data comprises vibration signal data, temperature signal data, video signal data, a flow sensor and the like, and the signal data is transmitted to a diagnosis subsystem for diagnosing based on the signal data; the characteristic layer processing module receives the signal data provided by the information acquisition module, adopts different signal processing methods including a time domain analysis method, a frequency domain analysis method and a time-frequency domain analysis method, and extracts time domain fault characteristics, frequency domain fault characteristics and time-frequency domain fault characteristics hidden under various signals; the decision layer processing module firstly adopts a plurality of artificial intelligence diagnosis algorithms including a shallow neural network, an extreme learning machine, a DBSCAN clustering algorithm, a deep neural network and the like, and constructs a prediction or classification model according to fault feature samples under various signals; secondly, inputting samples acquired by the system in real time into a trained prediction or classification model to obtain initial prediction and diagnosis results of each sub-diagnosis system; and finally, fusing the initial prediction and diagnosis results of each sub-diagnosis system by adopting an intelligent decision algorithm weighted evidence theory, reducing the uncertainty of the initial diagnosis result of a single diagnosis subsystem by comprehensively utilizing the initial diagnosis information of a plurality of sub-diagnosis systems, finally realizing the real-time, quick and accurate diagnosis of the early fault symptom of the pump group unit, forming a diagnosis report, and displaying the diagnosis report by a remote display module.
While the preferred embodiments of the present invention have been illustrated and described, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (5)
1. The utility model provides a machine pump intelligent diagnosis system based on internet of things, its characterized in that: including pump crowd unit, with the output end signal connection's of pump crowd unit information acquisition module, with the output end signal connection's of information acquisition module data transmission module, with the output end signal connection's of data transmission module big data analysis module, with big data analysis module's the output end signal connection's of big data analysis module remote display module, remote display module is used for showing the data after handling, information acquisition module include a plurality of set up in gather on the pump crowd unit the sensor of the different states of pump crowd unit.
2. The intelligent pump diagnosis system based on the internet of things technology of claim 1, wherein: the data transmission module comprises an internet of things node and a network server, wherein the internet of things node is in signal connection with the output end of the sensor, and the network server is in signal connection with the output end of the internet of things node.
3. The intelligent pump diagnosis system based on the internet of things technology of claim 1, wherein: the big data analysis module comprises a characteristic layer processing module and a decision layer processing module in signal connection with the characteristic layer processing module.
4. The intelligent pump diagnosis system based on the internet of things technology of claim 1, wherein: the remote display module comprises a computer network page end, a desktop client end, a smart phone page end and a smart phone application program end.
5. The intelligent pump diagnosis system based on the internet of things technology of claim 1, wherein: the information acquisition module comprises one or a combination of a plurality of temperature sensors, vibration sensors, flow sensors and video sensors.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111659573.1A CN114542443A (en) | 2021-12-30 | 2021-12-30 | Pump intelligent diagnosis system based on internet of things |
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| Application Number | Priority Date | Filing Date | Title |
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| CN202111659573.1A CN114542443A (en) | 2021-12-30 | 2021-12-30 | Pump intelligent diagnosis system based on internet of things |
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| CN114542443A true CN114542443A (en) | 2022-05-27 |
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Citations (6)
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| CN104165138A (en) * | 2014-07-03 | 2014-11-26 | 浙江中自庆安新能源技术有限公司 | Pump group state online monitoring system and method |
| CN106015028A (en) * | 2016-05-04 | 2016-10-12 | 江苏大学 | Intelligent water pump set monitoring and fault early warning method based on internet of things |
| CN108412784A (en) * | 2018-03-02 | 2018-08-17 | 青岛石化检修安装工程有限责任公司 | A kind of group of pump state on_line monitoring system |
| CN108757502A (en) * | 2018-05-15 | 2018-11-06 | 江苏大学 | A kind of water pump assembly typical case's health status monitoring device and method based on Internet of Things |
| CN208751840U (en) * | 2018-08-07 | 2019-04-16 | 重庆川仪自动化股份有限公司 | A kind of pump health monitoring and fault diagnosis system |
| CN113374681A (en) * | 2021-06-30 | 2021-09-10 | 江苏迪肯节能环保科技有限公司 | Intelligent operation and maintenance supervision system based on reciprocating compressor |
-
2021
- 2021-12-30 CN CN202111659573.1A patent/CN114542443A/en active Pending
Patent Citations (6)
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|---|---|---|---|---|
| CN104165138A (en) * | 2014-07-03 | 2014-11-26 | 浙江中自庆安新能源技术有限公司 | Pump group state online monitoring system and method |
| CN106015028A (en) * | 2016-05-04 | 2016-10-12 | 江苏大学 | Intelligent water pump set monitoring and fault early warning method based on internet of things |
| CN108412784A (en) * | 2018-03-02 | 2018-08-17 | 青岛石化检修安装工程有限责任公司 | A kind of group of pump state on_line monitoring system |
| CN108757502A (en) * | 2018-05-15 | 2018-11-06 | 江苏大学 | A kind of water pump assembly typical case's health status monitoring device and method based on Internet of Things |
| CN208751840U (en) * | 2018-08-07 | 2019-04-16 | 重庆川仪自动化股份有限公司 | A kind of pump health monitoring and fault diagnosis system |
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