CN111193806A - Electromechanical device real-time monitoring system based on internet of things technology - Google Patents
Electromechanical device real-time monitoring system based on internet of things technology Download PDFInfo
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- CN111193806A CN111193806A CN202010022145.7A CN202010022145A CN111193806A CN 111193806 A CN111193806 A CN 111193806A CN 202010022145 A CN202010022145 A CN 202010022145A CN 111193806 A CN111193806 A CN 111193806A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/02—Protocols based on web technology, e.g. hypertext transfer protocol [HTTP]
- H04L67/025—Protocols based on web technology, e.g. hypertext transfer protocol [HTTP] for remote control or remote monitoring of applications
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
- G01D21/00—Measuring or testing not otherwise provided for
- G01D21/02—Measuring two or more variables by means not covered by a single other subclass
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/045—Combinations of networks
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
- G06N3/084—Backpropagation, e.g. using gradient descent
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- G—PHYSICS
- G08—SIGNALLING
- G08C—TRANSMISSION SYSTEMS FOR MEASURED VALUES, CONTROL OR SIMILAR SIGNALS
- G08C17/00—Arrangements for transmitting signals characterised by the use of a wireless electrical link
- G08C17/02—Arrangements for transmitting signals characterised by the use of a wireless electrical link using a radio link
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/50—Network services
- H04L67/52—Network services specially adapted for the location of the user terminal
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/12—Messaging; Mailboxes; Announcements
- H04W4/14—Short messaging services, e.g. short message services [SMS] or unstructured supplementary service data [USSD]
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/30—Services specially adapted for particular environments, situations or purposes
- H04W4/38—Services specially adapted for particular environments, situations or purposes for collecting sensor information
Abstract
The invention discloses a real-time monitoring system of electromechanical equipment based on the technology of Internet of things in the field of electromechanical equipment monitoring, which comprises an electromechanical equipment terminal node, a gateway and a background server, wherein the electromechanical equipment terminal node comprises a collecting assembly, a radio frequency module, electromechanical equipment and a control module, the collecting assembly is connected with the electromechanical equipment and is used for collecting the operating parameters of the electromechanical equipment in real time and is connected with the control module through the radio frequency module, the control module is connected with the gateway through a TCP/IP protocol, the background server is a database server and is used for storing, managing and analyzing the operating parameters of the electromechanical equipment collected in real time through a BP neural network module, the gateway is connected with the background server through the Internet, the collecting assembly is used for comprehensively sensing the operating parameters of the electromechanical equipment, and the fault reason, the severity and the fault trend of the electromechanical equipment are intelligently diagnosed, the method provides accurate and reliable basis for emergency control and maintenance management, thereby saving maintenance cost and avoiding major accidents.
Description
Technical Field
The invention relates to the technical field of electromechanical equipment monitoring, in particular to an electromechanical equipment real-time monitoring system based on the technology of the Internet of things.
Background
With the progress of science and technology, large and complex mechatronic equipment is more and more widely applied in the technical fields of agriculture, industry or engineering, generally, because the mechatronic equipment has the characteristics of complex principle, high price and high maintenance difficulty, once a fault occurs in the actual use process, the mechatronic equipment needs to be shut down for a long time to wait for a maintenance engineer to find the reason and maintain, the work efficiency is inevitably reduced, the maintenance time is prolonged, and the wide-range popularization and use of the equipment are limited.
In addition, in the prior art, because the principle of the equipment is not understood clearly by a user, and no technology is found when the equipment fails, a plurality of pieces of equipment are all in 'operation with diseases', the service life of the equipment is seriously reduced, and therefore, if money can be detected and corrected in time when the problem occurs, further damage to the equipment can be avoided to a great extent.
The Internet of things is an important component of a new generation of information technology and is also an important development stage of the 'informatization' era. The internet of things is widely applied to network fusion through communication perception technologies such as intelligent perception, identification technology and pervasive computing, and is also called as the third wave of development of the world information industry after computers and the internet. The internet of things is an application expansion of the internet, and is not a network, but a business and an application. In view of the problems that in the prior art, the electromechanical integration equipment needs to be manually found out when a fault occurs, and then is maintained, so that the maintenance time is long and the use efficiency is low, and in addition, the equipment cannot be prevented in advance before the fault occurs.
Based on the above, the invention designs an electromechanical device real-time monitoring system based on the technology of the internet of things, so as to solve the above mentioned problems.
Disclosure of Invention
The present invention has been made to solve the above-mentioned problems occurring in the prior art.
In order to achieve the purpose, the invention provides the following technical scheme: the utility model provides an electromechanical device real-time monitoring system based on internet of things, includes electromechanical device terminal node, gateway and backend server, electromechanical device terminal node is including gathering subassembly, radio frequency module, electromechanical device and control module, it is connected with electromechanical device to gather the subassembly for gather electromechanical device's operating parameter in real time, and be connected with control module through radio frequency module, control module passes through TCP/IP agreement and is connected with the gateway, backend server is database server for the operating parameter who gathers electromechanical device in real time passes through BP neural network module and stores, manages and the analysis, the gateway passes through the internet and is connected with backend server.
Preferably, the collection assembly comprises a water sensor, a smoke sensor, a temperature sensor, a humidity sensor and Hall sensors with models of HNV025 and HS03-25A-NP, the collection assembly further comprises a signal processing circuit and a power module, the water sensor, the smoke sensor, the temperature sensor, the humidity sensor and the Hall sensors are all connected with the signal processing circuit, and the power module is respectively connected with the signal processing circuit and the radio frequency module.
Preferably, the control module comprises an audible and visual alarm module, a GSM module, a keyboard and a touch display screen, and the control module and the radio frequency module are connected with the signal processing circuit.
Preferably, the microprocessor is a microprocessor with a model number of S3C2440, and the radio frequency module is a radio frequency module with a model number of CC 1110.
Preferably, the gateway is a 4G or 5G gateway.
Preferably, the background server comprises a fault remote diagnosis module, a fault early warning processing module and a maintenance dispatching management module.
Preferably, the fault remote diagnosis module comprises a fault database, fault collection is performed on abnormal data of equipment operation according to data obtained by the collection assembly, diagnosis and analysis are performed by calling the fault database, the fault early warning processing module is used for sending early warning information to electromechanical equipment of the abnormal data of the equipment operation according to the data obtained by the collection assembly and feeding the information back to the fault remote diagnosis module for fault reason diagnosis, and after the fault of the fault remote diagnosis module is predicted, the maintenance dispatching management module dispatches a maintenance engineer with the nearest distance according to the position of the electromechanical equipment with the fault and a mobile phone short message form to perform maintenance work.
Preferably, the remote fault diagnosis module further includes a neural network prediction module, which performs fault prediction on the unit equipment at regular time and outputs a prediction result, including a type of a fault which may occur at present and a corresponding probability.
Compared with the prior art, the invention has the beneficial effects that: the invention can comprehensively sense the operation parameters of the electromechanical equipment through the acquisition assembly, intelligently diagnose the failure reason and severity of the electromechanical equipment and the failure trend, and provide accurate and reliable basis for emergency control and maintenance management, thereby saving the maintenance cost and avoiding major accidents.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic diagram of the principles of the present invention;
FIG. 2 is a schematic block diagram of an acquisition assembly of the present invention;
FIG. 3 is a functional block diagram of a control module of the present invention;
FIG. 4 is a block diagram of a background server according to the present invention.
In the drawings, the components represented by the respective reference numerals are listed below:
1. a terminal node of the electromechanical device; 2. a gateway; 3. a background server; 31. a fault early warning processing module; 32. a fault remote diagnosis module; 33. maintaining the dispatching management module; 4. a collection assembly; 41. a Hall sensor; 42. a smoke sensor; 43. a water immersion sensor; 44. a temperature sensor; 45. a temperature sensor; 46. a signal processing circuit; 5. an electromechanical device; 6. a control module; 61. a microprocessor; 62. a sound and light alarm module; 63. a GSM module; 64. a keyboard; 65. a touch display screen; 7. and a radio frequency module.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1-4, the present invention provides a technical solution: the utility model provides an electromechanical device real-time monitoring system based on internet of things, including electromechanical device 5 terminal node 1, gateway 2 and backend server 3, electromechanical device 5 terminal node 1 includes collection subassembly 4, radio frequency module 7, electromechanical device 5 and control module 6, collection subassembly 4 is connected with electromechanical device 5 for gather electromechanical device 5's operating parameter in real time, and be connected with control module 6 through radio frequency module 7, control module 6 is connected with gateway 2 through the TCP/IP protocol, backend server 3 is the database server, be used for the operating parameter of gathering electromechanical device 5 in real time through BP neural network module storage, management and analysis, gateway 2 is connected with backend server 3 through the internet.
In this embodiment, the collection assembly 4 includes a water sensor 43, a smoke sensor 42, a temperature sensor 4544, a humidity sensor, and hall sensors 41 with models of HNV025 and HS03-25A-NP, the collection assembly 4 further includes a signal processing circuit 46 and a power module, the water sensor 43, the smoke sensor 42, the temperature sensor 4544, the humidity sensor, and the hall sensors 41 are all connected with the signal processing circuit 46, and the power module is respectively connected with the signal processing circuit 46 and the radio frequency module 7.
In this embodiment, the control module 6 includes an audible and visual alarm module 62, a GSM module 63, a keyboard 64 and a touch display screen 65, and the control module 6 and the radio frequency module 7 are connected to the signal processing circuit 46.
In this embodiment, the microprocessor 61 is an S3C2440 microprocessor 61, and the rf module 7 is a CC1110 rf module 7.
In this embodiment, the gateway 2 is a 4G or 5G gateway 2.
In this embodiment, the background server 3 includes a fault remote diagnosis module 32, a fault early warning processing module 31, and a maintenance dispatch management module 33.
In this embodiment, the fault remote diagnosis module 32 includes a fault database, performs fault collection on abnormal data of equipment operation according to data obtained by the acquisition component 4, and performs diagnosis and analysis by calling the fault database, and the fault early warning processing module 31 is configured to send early warning information to the electromechanical device 5 of the abnormal data of the equipment operation according to the data obtained by the acquisition component 4, and feed the information back to the fault remote diagnosis module 32 to perform diagnosis of a fault reason, and after the fault of the fault remote diagnosis module 32 is predicted, the maintenance management module 33 distributes a maintenance engineer with the closest distance to the fault remote diagnosis module according to the position of the electromechanical device 5 with the fault and a form of a mobile phone short message to perform maintenance work.
In this embodiment, the fault remote diagnosis module 32 further includes a neural network prediction module, performs fault prediction on the unit device at regular time, outputs a prediction result including a type of a fault which may occur at present and a corresponding probability, and trains through a BP neural network model, so that it is possible to greatly improve the notification to maintenance personnel before an abnormal condition occurs in the system environment parameters, thereby avoiding an accident and having great practical significance.
The specific working principle is as follows:
the invention monitors the operation parameters of the electromechanical device 5 in real time through the smoke sensor 42, the water sensor 43, the temperature sensor 44, the humidity sensor 45 and the Hall sensor 41, the smoke sensor 42, the water sensor 43, the temperature sensor 44 and the humidity sensor 45 all adopt wireless sensors, the problem of complex wiring is avoided, the Hall sensor 41 measures a voltage and current circuit, the Hall effect and the magnetic compensation principle are utilized, the insulation degree of a measured loop and a test loop is high, direct current, alternating current and pulse signals can be measured, and the electromechanical device 5 can be comprehensively sensed through simultaneous real-time online monitoring of environmental parameters and electrical parameters.
Then the numerical value of monitoring is handled through signal processing circuit 46, and upload to control module 6 department through radio frequency module 7, control module 6 adopts S3C 2440' S microprocessor, receive the signal of handling, handle, send early warning information to electromechanical device 5 of the unusual data of equipment operation according to the data that acquisition component 4 obtained, and assign to microprocessor 61 department, carry out acousto-optic warning through acousto-optic warning module 62, GSM module 63 is then used for the location, the position of electromechanical device 5 that the location broke down, be convenient for maintenance person can accurate understanding electromechanical device 5 that breaks down, can carry out input and output operation through keyboard 64 and touch display 65.
The data collected by the control module 6 is uploaded to the background server 3 through the gateway 2, the fault remote diagnosis module 32 comprises a fault database, fault collection is carried out on abnormal data of equipment operation according to the data obtained by the collection assembly 4, diagnosis and analysis are carried out by calling the fault database, the fault early warning processing module 31 is used for sending early warning information to the electromechanical equipment 5 of the abnormal data of the equipment operation according to the data obtained by the collection assembly 4 and feeding the information back to the fault remote diagnosis module 32 for fault reason diagnosis, and after the fault remote diagnosis module 32 carries out fault prediction, the maintenance management module 33 distributes a maintenance engineer with the nearest distance to carry out maintenance work according to the position of the electromechanical equipment 5 with the fault and the form of mobile phone short messages.
When a prediction result has a potential fault, the background server 3 maintains the order dispatching service for maintenance, changes the manual passive maintenance service into a preventive active service, eliminates potential hidden dangers in time, stops the continuous damage of equipment and effectively prolongs the service life of the equipment; and when the electromechanical integrated equipment breaks down, the background server 3 analyzes the data transmitted by the data background processing center to find the cause of the fault, and selects a corresponding professional maintenance engineer for maintenance according to the maintenance order service of the electromechanical equipment 5, so that the cause troubleshooting time is shortened, the maintenance time is shortened, and the maintenance efficiency is improved. Meanwhile, the invention utilizes the internet technology, has simple structure and lower cost and has wide application prospect.
In the description herein, references to the description of "one embodiment," "an example," "a specific example" or the like are intended to mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The preferred embodiments of the invention disclosed above are intended to be illustrative only. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise embodiments disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best utilize the invention. The invention is limited only by the claims and their full scope and equivalents.
Claims (8)
1. The utility model provides an electromechanical device real-time monitoring system based on internet of things, its characterized in that: the electromechanical equipment terminal node comprises a collection assembly, a radio frequency module, electromechanical equipment and a control module, wherein the collection assembly is connected with the electromechanical equipment and used for collecting the operating parameters of the electromechanical equipment in real time and is connected with the control module through the radio frequency module, the control module is connected with the gateway through a TCP/IP protocol, the background server is a database server and used for storing, managing and analyzing the operating parameters of the electromechanical equipment collected in real time through a BP neural network module, and the gateway is connected with the background server through the Internet.
2. The electromechanical device real-time monitoring system based on the internet of things technology as claimed in claim 1, wherein: the collection assembly comprises a water sensor, a smoke sensor, a temperature sensor, a humidity sensor and Hall sensors of which the models are HNV025 and HS03-25A-NP, and further comprises a signal processing circuit and a power module, wherein the water sensor, the smoke sensor, the temperature sensor, the humidity sensor and the Hall sensors are all connected with the signal processing circuit, and the power module is respectively connected with the signal processing circuit and the radio frequency module.
3. The electromechanical device real-time monitoring system based on the internet of things technology as claimed in claim 2, wherein: the control module comprises an audible and visual alarm module, a GSM module, a keyboard and a touch display screen, and the control module and the radio frequency module are connected with the signal processing circuit.
4. The electromechanical device real-time monitoring system based on the internet of things technology as claimed in claim 3, wherein: the microprocessor is of a type S3C2440, and the radio frequency module is of a type CC 1110.
5. The electromechanical device real-time monitoring system based on the internet of things technology as claimed in claim 1, wherein: the gateway adopts a 4G or 5G gateway.
6. The electromechanical device real-time monitoring system based on the internet of things technology as claimed in claim 1, wherein: the background server comprises a fault remote diagnosis module, a fault early warning processing module and a maintenance dispatching management module.
7. The electromechanical device real-time monitoring system based on the internet of things technology as claimed in claim 6, wherein: the fault remote diagnosis module comprises a fault database, fault acquisition is carried out on abnormal data of equipment operation according to the data obtained by the acquisition assembly, diagnosis and analysis are carried out by calling the fault database, the fault early warning processing module is used for sending early warning information to electromechanical equipment of the abnormal data of the equipment operation according to the data obtained by the acquisition assembly and feeding the information back to the fault remote diagnosis module for fault reason diagnosis, and after the fault of the fault remote diagnosis module is predicted, the maintenance management module distributes a maintenance engineer with the nearest distance to carry out maintenance work according to the position of the electromechanical equipment with the fault and the form of mobile phone short messages.
8. The electromechanical device real-time monitoring system based on the internet of things technology as claimed in claim 7, wherein: the fault remote diagnosis module also comprises a neural network prediction module which carries out fault prediction on the unit equipment at regular time and outputs a prediction result, wherein the prediction result comprises the type of the fault which possibly occurs at present and the corresponding probability.
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Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN112233407A (en) * | 2020-11-10 | 2021-01-15 | 四川富沃得机电设备有限公司 | Well cementation construction monitoring method and system |
| CN112379618A (en) * | 2020-11-06 | 2021-02-19 | 上海好卓机电工程有限公司 | Electromechanical device data acquisition and analysis method |
| CN112837073A (en) * | 2020-12-31 | 2021-05-25 | 广州仪速安电子科技有限公司 | Instrument after-sale service management system and method based on Internet of things |
| CN113487189A (en) * | 2021-07-08 | 2021-10-08 | 广东石油化工学院 | Petrochemical equipment fault probability risk assessment system and assessment method |
| CN113605877A (en) * | 2021-05-14 | 2021-11-05 | 浙江微科机电有限公司 | Intelligent monitoring and fault diagnosis system and processing method of offshore oil platform lift pump based on Internet of things |
| CN114331217A (en) * | 2022-01-20 | 2022-04-12 | 上海纳宇电气有限公司 | Remote maintenance method based on Internet of things equipment |
| CN114777841A (en) * | 2022-04-17 | 2022-07-22 | 贵州新思维科技有限责任公司 | Intelligent sensing system for managing and maintaining electromechanical equipment on highway based on Internet of things |
| CN115206066A (en) * | 2022-07-06 | 2022-10-18 | 深圳市第二人民医院(深圳市转化医学研究院) | Hospital electromechanical equipment fault alarm closed-loop management method and terminal thereof |
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Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN112379618A (en) * | 2020-11-06 | 2021-02-19 | 上海好卓机电工程有限公司 | Electromechanical device data acquisition and analysis method |
| CN112233407A (en) * | 2020-11-10 | 2021-01-15 | 四川富沃得机电设备有限公司 | Well cementation construction monitoring method and system |
| CN112837073A (en) * | 2020-12-31 | 2021-05-25 | 广州仪速安电子科技有限公司 | Instrument after-sale service management system and method based on Internet of things |
| CN113605877A (en) * | 2021-05-14 | 2021-11-05 | 浙江微科机电有限公司 | Intelligent monitoring and fault diagnosis system and processing method of offshore oil platform lift pump based on Internet of things |
| CN113605877B (en) * | 2021-05-14 | 2022-04-19 | 浙江微科机电有限公司 | Intelligent monitoring and fault diagnosis system and processing method of offshore oil platform lift pump based on Internet of things |
| CN113487189A (en) * | 2021-07-08 | 2021-10-08 | 广东石油化工学院 | Petrochemical equipment fault probability risk assessment system and assessment method |
| CN114331217A (en) * | 2022-01-20 | 2022-04-12 | 上海纳宇电气有限公司 | Remote maintenance method based on Internet of things equipment |
| CN114777841A (en) * | 2022-04-17 | 2022-07-22 | 贵州新思维科技有限责任公司 | Intelligent sensing system for managing and maintaining electromechanical equipment on highway based on Internet of things |
| CN115206066A (en) * | 2022-07-06 | 2022-10-18 | 深圳市第二人民医院(深圳市转化医学研究院) | Hospital electromechanical equipment fault alarm closed-loop management method and terminal thereof |
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Application publication date: 20200522 |
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