CN109234871B - Textile machinery equipment fault prevention processing method - Google Patents
Textile machinery equipment fault prevention processing method Download PDFInfo
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- CN109234871B CN109234871B CN201811307026.5A CN201811307026A CN109234871B CN 109234871 B CN109234871 B CN 109234871B CN 201811307026 A CN201811307026 A CN 201811307026A CN 109234871 B CN109234871 B CN 109234871B
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- D—TEXTILES; PAPER
- D01—NATURAL OR MAN-MADE THREADS OR FIBRES; SPINNING
- D01H—SPINNING OR TWISTING
- D01H13/00—Other common constructional features, details or accessories
- D01H13/32—Counting, measuring, recording or registering devices
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Abstract
The invention relates to a textile machinery equipment fault prevention processing method, which comprises the steps of collecting numerous textile machinery equipment and sensor data through an industrial Internet of things, connecting the data to a big data cloud platform through the Internet, knowing the running state data of the equipment in time, predicting hidden equipment hazards in advance, preventing in advance, automatically matching a solution according to fault identification if a fault occurs, automatically matching a solution by a simple fault system, remotely solving difficult faults by a remote expert, remotely consulting, and monitoring videos and programs; after the fault is solved, the fault is solidified to a knowledge base and used as experience knowledge to provide a corresponding scheme for the subsequent fault treatment. The invention has the advantages of reducing the frequency of equipment failure, reducing the time for repairing the equipment failure, improving the operation efficiency of enterprise equipment and reducing the cost of after-sale service manpower and material resources of equipment manufacturers.
Description
Technical Field
The invention belongs to the technical field of textile machinery, relates to fault prevention and treatment of textile machinery equipment, and particularly relates to a fault prevention and treatment method of the textile machinery equipment.
Background
At present, after a product is delivered, workshop equipment and factory equipment operate independently, the operation state of the equipment cannot be known in time in the operation process of the equipment, and only after the equipment is stopped due to failure, field security personnel can process the equipment. The mobility of textile mill personnel is large, the technical level difference is large, field faults often occur and cannot be solved, the field faults need to be solved by equipment manufacturers for sending after-sales service personnel, the production of textile enterprises is delayed, and manpower and material resources of the equipment manufacturers are wasted.
Disclosure of Invention
In order to solve the technical problems, the invention provides a method for preventing and treating the equipment faults of textile machinery, and aims to reduce the equipment fault frequency, shorten the equipment fault repairing time, improve the equipment operation efficiency of enterprises and reduce the after-sales service manpower and material resource cost of equipment manufacturers.
The technical scheme of the invention is as follows:
a method for preventing and treating the failure of textile machinery comprises the following steps,
firstly, establishing a data acquisition platform at a client to acquire operating data of the textile machinery;
secondly, uploading the acquired data to a client server, and uploading the data to an operation and maintenance platform of the server cluster through the Internet;
thirdly, monitoring the operation and maintenance of the textile equipment through an operation and maintenance platform;
the operation maintenance method in the third step comprises 1) acquiring data in real time when the equipment normally operates, comparing and analyzing the transverse data and the longitudinal data, and actively early warning; 2) when a fault occurs, sending a fault reminding message at the first time, automatically matching a fault solution, and looking up product data at any time; 3) when a fault is difficult, remote debugging and program upgrading are carried out, an expert video is connected, and a nearby service person dispatches the fault; 4) and after the fault is solved, a fault library and an experience library are formed, and fault statistics and analysis are carried out.
Compared with the prior art, the technical scheme has the advantages that a large number of textile machinery equipment and sensor data are collected through the industrial Internet of things and then are connected to the big data cloud platform through the Internet, the running state data of the equipment can be known in time, the hidden danger of the equipment can be predicted in advance, the equipment can be prevented in advance, if the fault occurs, firstly, the solution is automatically matched according to the fault identification, the solution is automatically matched through a simple fault system, the remote expert of the difficult and complicated fault is solved, the remote consultation is carried out, and the video and program monitoring are carried; after the fault is solved, the fault is solidified to a knowledge base and used as experience knowledge to provide a corresponding scheme for the subsequent fault treatment.
Based on the scheme, the invention also makes the following improvements:
further, the active early warning comprises frequency conversion detection early warning, power consumption detection early warning, sensor detection early warning, technical index early warning, quality early warning and mechanical abnormity early warning.
Further, the statistical analysis of the faults comprises comparative analysis of fault rate, fault time, downtime, repair time, fault occurrence rate, repair time and average repair time, and a fault total report is formed after analysis.
Furthermore, the operation data of the textile machinery is collected through a built-in upper computer, an industrial personal computer, a controller, a frequency converter, a speed tester, a sensor and an electric meter of the textile machinery.
The beneficial effects of this technical scheme are that master weaving equipment operating data anytime and anywhere through big data cloud platform, foresee equipment hidden danger in advance, prevent in advance, the rapid solution that breaks down provides the improvement scheme, promotes textile enterprise operating efficiency, reduces the silver yarn broken end joint rate that the trouble caused, promotes product quality. And the cost of after-sale service manpower and material resources of equipment manufacturers is reduced.
Drawings
Fig. 1 is a flow chart of the inventive fault handling.
Detailed Description
As shown in fig. 1, a method for preventing and treating faults of textile machinery equipment is characterized in that: comprises the following steps of (a) carrying out,
firstly, establishing a data acquisition platform at a client to acquire operating data of the textile machinery;
secondly, uploading the acquired data to a client server, and uploading the data to an operation and maintenance platform of the server cluster through the Internet;
thirdly, monitoring the operation and maintenance of the textile equipment through an operation and maintenance platform;
the operation maintenance method in the third step comprises 1) acquiring data in real time when the equipment normally operates, comparing and analyzing the transverse data and the longitudinal data, and actively early warning; 2) when a fault occurs, sending a fault reminding message at the first time, automatically matching a fault solution, and looking up product data at any time; 3) when a fault is difficult, remote debugging and program upgrading are carried out, an expert video is connected, and a nearby service person dispatches the fault; 4) and after the fault is solved, a fault library and an experience library are formed, and fault statistics and analysis are carried out.
The active early warning comprises frequency conversion detection early warning, power consumption detection early warning, sensor detection early warning, technical index early warning, quality early warning and mechanical abnormity early warning. And the fault statistical analysis comprises the comparative analysis of fault rate, fault time, downtime, repair time, fault occurrence rate, repair time and average repair time, and a fault total report is formed after the analysis. The operation data of the textile machinery is collected through a built-in upper computer, an industrial personal computer, a controller, a frequency converter, a speed tester, a sensor and an ammeter of the textile machinery.
Active early warning, based on a big data model, carrying out comparison analysis on data in a transverse direction (same batch of machines) and a longitudinal direction (long time segment), and early finding abnormality and problems; taking the carding machine cylinder current monitoring as an example: the current of the cylinder is compared with the numerical value of big data monitored by the machine for a long time under the condition of the same variety and the same process; or comparing a plurality of data on the same production line; thus predicting the running condition of the cylinder: the wall plate plugging condition of the cylinder, the abrasion degree of a bearing, the tightness change of a belt and the like. The early warning is sent to related personnel computers, mobile phones, WeChat and the like in time, deviation rectification measures are taken in time, and equipment faults can be prevented in time.
Claims (4)
1. A method for preventing and treating faults of textile machinery equipment is characterized by comprising the following steps: comprises the following steps of (a) carrying out,
firstly, establishing a data acquisition platform at a client to acquire operating data of the textile machinery;
secondly, uploading the acquired data to a client server, and uploading the data to an operation and maintenance platform of the server cluster through the Internet;
thirdly, monitoring the operation and maintenance of the textile equipment through an operation and maintenance platform;
the operation maintenance method in the third step comprises 1) acquiring data in real time when the equipment normally operates, comparing and analyzing the transverse data and the longitudinal data, and actively early warning; 2) when a fault occurs, sending a fault reminding message at the first time, automatically matching a fault solution, and looking up product data at any time; 3) when a fault is difficult, remote debugging and program upgrading are carried out, an expert video is connected, and a nearby service person dispatches the fault; 4) after the fault is solved, a fault library and an experience library are formed, and fault statistics and analysis are carried out; the transverse data comparison analysis is big data comparison of machines in the same batch or machines in the same production line or a plurality of textile client machines in the same variety and the same process, and the longitudinal data comparison analysis is big data comparison analysis of different long-time segments of the same machine.
2. The textile machinery apparatus failure prevention processing method according to claim 1, characterized in that: the active early warning comprises frequency conversion detection early warning, power consumption detection early warning, sensor detection early warning, technical index early warning, quality early warning and mechanical abnormity early warning.
3. The textile machinery apparatus failure prevention processing method according to claim 1, characterized in that: and the fault statistical analysis comprises the comparative analysis of fault rate, fault time, downtime, repair time, fault occurrence rate, repair time and average repair time, and a fault total report is formed after the analysis.
4. The textile machinery apparatus failure prevention processing method according to claim 1, characterized in that: the operation data of the textile machinery is collected through a built-in upper computer, an industrial personal computer, a controller, a frequency converter, a speed tester, a sensor and an ammeter of the textile machinery.
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| Application Number | Priority Date | Filing Date | Title |
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| CN201811307026.5A CN109234871B (en) | 2018-11-05 | 2018-11-05 | Textile machinery equipment fault prevention processing method |
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| CN201811307026.5A CN109234871B (en) | 2018-11-05 | 2018-11-05 | Textile machinery equipment fault prevention processing method |
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| CN109234871A CN109234871A (en) | 2019-01-18 |
| CN109234871B true CN109234871B (en) | 2020-05-19 |
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| DE10349094A1 (en) * | 2003-10-22 | 2005-05-25 | Rieter Ingolstadt Spinnereimaschinenbau Ag | Textile machine and method for improving the production process |
| CN104267672A (en) * | 2014-09-02 | 2015-01-07 | 吴江华宏软件有限公司 | Automatic fault detection and data acquisition early warning system of textile two-for-one twister |
| CN105045189A (en) * | 2015-06-16 | 2015-11-11 | 吴江澳明纺织品有限公司 | Safety alarm device for textile machine |
| CN106774124A (en) * | 2016-12-27 | 2017-05-31 | 上海展湾信息科技有限公司 | Operation of industrial installation monitoring system |
| CN107635008A (en) * | 2017-10-09 | 2018-01-26 | 浙江理工大学 | A kind of knitting machine interconnection plane system and operational process |
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