CN114040002A - Internet of things-based state monitoring system, state monitoring method, electronic device and storage medium - Google Patents
Internet of things-based state monitoring system, state monitoring method, electronic device and storage medium Download PDFInfo
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Abstract
The application discloses condition monitoring system based on thing networking includes: the system comprises an artificial intelligence module, a big data cloud module, an Internet of things module, an edge data center module and a terminal module; the method comprises the following steps: monitoring data of all equipment to be monitored are respectively transmitted to the Internet of things module and the edge data center module through the terminal module; the edge data center module transmits the data obtained by state monitoring to the Internet of things module; the internet of things module transmits all data to the big data cloud module; the big data cloud module receives and stores the data transmitted by the Internet of things module; the artificial intelligence module calls various data and models stored in the big data cloud module, and the artificial intelligence algorithm is used for monitoring the state to obtain a new model or/and a monitoring result; and the big data cloud module receives and stores the new model or/and the monitoring result transmitted by the artificial intelligence module. The application also discloses a state monitoring method, electronic equipment and a storage medium. The method and the device improve the problem that the equipment state of the petrochemical enterprise is difficult to monitor.
Description
Technical Field
The invention belongs to the field of data processing, and particularly relates to a state monitoring system based on the Internet of things, a state monitoring method, electronic equipment and a storage medium.
Background
Condition monitoring is the process of monitoring and examining operating condition parameters (e.g., current, vibration, temperature, etc.) of the entire operating equipment or its components to identify significant changes that can indicate a potential defect in the operation of the equipment. The state monitoring of the electrical equipment, namely for the electrical equipment, carries on the state monitoring. The electrical equipment on-line monitoring lays a foundation for fault diagnosis by extracting the characteristic signals of the faults in real time, and the correct fault diagnosis provides a maintenance basis for state maintenance. The purpose of on-line monitoring is to analyze and predict maintenance by measuring the condition of the equipment in transit, identifying its existing and upcoming defects.
The existing petrochemical enterprises have the following characteristics: 1. the electrical equipment is huge in quantity, wide in distribution and difficult to manage, and whether the running state of the equipment is normal or not needs to be combined with running information in inspection and the running state of a process device, so that the equipment is difficult to manage. Taking a common-scale distribution substation as an example, about 20 running devices needing inspection and measurement are needed, and one hour is needed for finishing the power transformation according to the specified items. A large amount of workload is required to be invested in completing the daily routing inspection of all the operating electrical equipment of the whole plant. 2. The operation and maintenance personnel are few, the manual inspection efficiency is low, the operation and maintenance personnel which are actually invested are few corresponding to the inspection equipment with huge quantity, and the efficiency of manual work and process device operation communication is low. 3. The operation and maintenance of secondary equipment are not in place, the production hidden trouble cannot be eliminated as soon as possible, the situation that the unplanned shutdown of low-pressure pump equipment possibly occurs in the daily operation of a production field cannot be avoided, and the pump equipment is particularly a non-important link pump and the shutdown of the equipment which cannot directly cause serious faults can not be realized; the shutdown of these devices often reduces the operational reliability of critical links or is an inducing factor in the occurrence of major accidents. Due to the reasons, the problems cannot be found in time because the daily operation and maintenance work is difficult to be in place, so that the hidden production trouble cannot be eliminated as soon as possible, and the reliability of production and operation is greatly reduced.
In view of the above technical problems, there is no fast, simple and effective solution.
Disclosure of Invention
In order to overcome the defects in the prior art, the state monitoring system, the state monitoring method, the electronic equipment and the storage medium based on the Internet of things are provided, the state monitoring system is constructed based on an electric Internet of things architecture, a novel monitoring system of edge, pipe, end, network, cloud and intelligence is established, the problems of large quantity, wide distribution, few operation and maintenance personnel and improper operation and maintenance of secondary equipment of petrochemical enterprises are solved, and real-time state monitoring and fault early warning are realized.
In a first aspect, the present application provides a status monitoring system based on the internet of things, including: the system comprises an artificial intelligence module, a big data cloud module, an Internet of things module, an edge data center module and a terminal module;
the artificial intelligence module is connected with a big data cloud module, the big data cloud module is connected with the Internet of things module, the Internet of things is respectively connected with the edge data center module and the terminal module, and the edge data center module is connected with the terminal module;
the artificial intelligence module is used for calling various data and models stored in the big data cloud module, performing state monitoring by using an artificial intelligence algorithm to obtain a new model or/and a monitoring result, and transmitting the new model or/and the monitoring result to the big data cloud module;
the big data cloud module is used for receiving and storing various data transmitted by the Internet of things module and the new model or/and monitoring result transmitted by the artificial intelligence module;
the internet of things module is used for being connected with the edge data center module and the terminal module through a network, receiving edge data, an edge model and an edge state monitoring result transmitted by the edge data center, receiving various equipment data transmitted by the terminal module, and transmitting the edge data, the edge model, the edge state monitoring result and the various equipment data to the big data cloud module;
the edge data center module is used for monitoring the state of at least one device and transmitting edge data, an edge model and an edge state monitoring result obtained by state monitoring to the Internet of things module;
the terminal module is used for being connected with all the devices to be monitored and providing data transmission interfaces for monitoring data of all the devices to be monitored.
The state monitoring system based on the Internet of things allows a plurality of edge data center modules to exist, and allows a plurality of devices to be monitored to be connected with the same edge data center module.
The edge data center module has an independent alarm function, namely, when the edge state monitoring result exceeds a preset edge threshold value, an alarm is given, and edge alarm information is sent to a mobile phone of a related person or displayed on an alarm screen.
The edge data center module can receive alarm information transmitted by the Internet of things module, and the alarm information is obtained by comparing a monitoring result with a preset threshold value through the big data cloud module.
The alarm information and the edge alarm information are displayed by adopting a graph curve, and the alarm information and the edge alarm information display method have an alarm information inquiry function and a report generation function.
The network comprises but is not limited to optical fibers, super-five lines, RS485, 4G \5G, GPRS, ZigBee, WiFi, LoRa, M-BUS or Bluetooth; and supports the following communication protocols including TCP/IP, IEC61850, IEC60870, MODBUS, ProfiBus.
The big data cloud module stores various data transmitted by the internet of things module according to predefined indexes, wherein the predefined indexes comprise: time index, device name index, edge data center name index.
In a second aspect, the application provides a state monitoring method based on the internet of things, which includes the following steps:
monitoring data of all equipment to be monitored are transmitted to the Internet of things module and the edge data center module through the terminal module respectively;
the edge data center module transmits edge data, an edge model and an edge state monitoring result obtained by state monitoring to the Internet of things module;
the Internet of things module receives the edge data, the edge model and the edge state monitoring result transmitted by the edge data center, receives various equipment data transmitted by the terminal module, and transmits the edge data, the edge model, the edge state monitoring result and the various equipment data to the big data cloud module;
the big data cloud module receives and stores the edge data, the edge model, the edge state monitoring result and various equipment data transmitted by the Internet of things module;
the artificial intelligence module calls various data and models stored in the big data cloud module, carries out state monitoring by using an artificial intelligence algorithm to obtain a new model or/and a monitoring result, and transmits the new model or/and the monitoring result to the big data cloud module;
and the big data cloud module receives and stores the new model or/and the monitoring result transmitted by the artificial intelligence module.
In a third aspect, the present application provides an electronic device, comprising:
one or more processors;
a memory;
one or more applications stored in the memory and configured to be loaded and executed by the one or more processors to perform the internet of things based condition monitoring method.
In a fourth aspect, the present application provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the method for monitoring a state based on an internet of things according to the first aspect or any possible implementation manner of the first aspect.
The beneficial effect that this application reached:
the application provides a state monitoring system and method based on the Internet of things, electronic equipment and a storage medium, combines the characteristics of the petrochemical industry, applies the technologies of the Internet of things, cloud computing, edge computing, big data analysis and the like, establishes the state monitoring system based on the Internet of things, realizes comprehensive state sensing, data heterogeneous compatibility, efficient information processing and flexible platform expansion, and fundamentally solves the problem that equipment states of petrochemical enterprises are difficult to monitor due to the fact that the quantity of electrical equipment is large, the distribution is wide, operation and maintenance personnel are few, and operation and maintenance of secondary equipment are not in place.
Drawings
Fig. 1 is a schematic block diagram of a condition monitoring system based on the internet of things according to an embodiment of the present application;
FIG. 2 is a schematic diagram of an edge data center according to an embodiment of the present application;
fig. 3 is a flowchart of a state monitoring method based on the internet of things according to an embodiment of the present application;
FIG. 4 is an exemplary diagram of an electronic device according to an embodiment of the present application;
fig. 5 is a schematic diagram of a second edge data center failure prediction according to an embodiment of the present application.
Detailed Description
The present application is further described below with reference to the accompanying drawings. The following examples are only for illustrating the technical solutions of the present invention more clearly, and the protection scope of the present application is not limited thereby.
Example (b):
in recent years, primary and secondary equipment (especially secondary equipment) of petrochemical enterprises have the characteristics of large quantity, wide distribution, difficulty in operation and maintenance and the like in operation and maintenance. In operation and maintenance, hidden dangers are difficult to monitor, and faults and the occurrence of the hidden dangers are more difficult to predict. In the fine management operation, not only the hidden dangers need to be found and handled in time, but also the actual running conditions of the primary and secondary equipment can be known in real time, and the overall running conditions of the equipment need to be evaluated in time so as to take countermeasures as soon as possible. The on-line state monitoring system for the electrical equipment of the whole plant can effectively improve the operation and maintenance efficiency of the electrical equipment, ensure the safe and stable operation of a power supply system and bring huge direct economic benefits and indirect economic benefits. The system improves the power supply reliability of petrochemical enterprises, enhances the continuous power supply capacity of production, ensures safe and stable production and reduces the safety production accidents of enterprises.
In this embodiment, jinling petrochemical load is 266MW, as shown in table 1. The internal power grid comprises five links of power generation, power transformation, power transmission, power distribution and power utilization. Most of the electric loads are primary electric loads, a considerable part of the electric loads are important loads in the primary loads, the electric equipment mainly comprises an asynchronous motor, and the loads are relatively stable. In recent years, some nonlinear loads have been applied to inverters, UPSs, and dc power supplies.
TABLE 1 Electrical load situation throughout the plant
In a first aspect, the present application provides a status monitoring system based on the internet of things, as shown in fig. 1, including: the system comprises an artificial intelligence module, a big data cloud module, an Internet of things module, an edge data center module and a terminal module;
the artificial intelligence module is connected with a big data cloud module, the big data cloud module is connected with the Internet of things module, the Internet of things is respectively connected with the edge data center module and the terminal module, and the edge data center module is connected with the terminal module;
the artificial intelligence module is used for calling various data and models stored in the big data cloud module, performing state monitoring by using an artificial intelligence algorithm to obtain a new model or/and a monitoring result, and transmitting the new model or/and the monitoring result to the big data cloud module;
the big data cloud module is used for receiving and storing various data transmitted by the Internet of things module and the new model or/and monitoring result transmitted by the artificial intelligence module;
the internet of things module is used for being connected with the edge data center module and the terminal module through a network, receiving edge data, an edge model and an edge state monitoring result transmitted by the edge data center, receiving various equipment data transmitted by the terminal module, and transmitting the edge data, the edge model, the edge state monitoring result and the various equipment data to the big data cloud module;
the edge data center module is used for monitoring the state of at least one device and transmitting edge data, an edge model and an edge state monitoring result obtained by state monitoring to the Internet of things module;
in this embodiment, 3 edge data centers are adopted, as shown in fig. 2, the measurement and control device and the temperature measurement device are connected with the first edge data center, the high-voltage protection device (SEL-351) is connected with the second edge data center, and the low-voltage protection device (BDM-100 series of beidou galaxy) is connected with the third edge data center.
The second edge data center provides comprehensive self-checking information, fault prediction and timely processing can be performed on the relay protection device (belonging to secondary equipment) by using the information, and the provided information is shown in fig. 5. In addition, the method can also provide a fixed value reading function and can be used for fixed value checking.
The third edge data center provides the following key equipment management and self-checking information: CPU temperature, CPU load rate, sampling reference voltage, residual overheat protection delay action time, starting times, total running time, device power-on time, clock module state, fixed value storage area state, report storage area state, A/D sampling state and fixed value self-checking.
The first edge data center, the second edge data center and the third edge data center are all connected with the Internet of things module, and the measurement and control device, the temperature measuring device, the high-voltage protection device and the low-voltage protection device are all connected with the Internet of things module.
The terminal module is used for being connected with all the devices to be monitored and providing data transmission interfaces for monitoring data of all the devices to be monitored.
The state monitoring system based on the Internet of things allows a plurality of edge data center modules to exist, and allows a plurality of devices to be monitored to be connected with the same edge data center module.
The edge data center module has an independent alarm function, namely, when the edge state monitoring result exceeds a preset edge threshold value, an alarm is given, and edge alarm information is sent to a mobile phone of a related person or displayed on an alarm screen.
The edge data center module can receive alarm information transmitted by the Internet of things module, and the alarm information is obtained by comparing a monitoring result with a preset threshold value through the big data cloud module.
The alarm information and the edge alarm information are displayed by adopting a graph curve, and the alarm information and the edge alarm information display method have an alarm information inquiry function and a report generation function.
And (3) displaying a graph curve:
and a unified data comprehensive display interface is provided, so that important information and related information of substations in the jurisdiction can be quickly, conveniently, visually and effectively checked, and related quasi-real-time data pictures of power production can be displayed.
And (3) inquiring alarm information:
and multiple condition combination queries are supported, and fuzzy queries are supported. In the available future state overhaul advanced application, a maintenance information list can be customized, the fault information of various devices and devices in the station in the month and the week is designated in a centralized mode, a state evaluation program is started, each fault/abnormal device automatically enters a maintenance work plan flow, maintenance is finished, and automatic cancellation is performed after a feedback signal is obtained.
The report generation function is as follows:
the state monitoring application provides a self-defined report tool, and a user can customize various statistical reports according to business needs and generate/output the statistical reports in real time or at regular time.
The network consists of optical fibers, a super-five line, RS485, 4G \5G, GPRS, ZigBee, WiFi, LoRa, M-BUS or Bluetooth; and supports the following communication protocols including TCP/IP, IEC61850, IEC60870, MODBUS, ProfiBus.
The big data cloud module stores various data transmitted by the internet of things module according to predefined indexes, wherein the predefined indexes comprise: time index, device name index, edge data center name index.
The artificial intelligence algorithm includes, but is not limited to: an expert system method, an association analysis method, a neural network method, and a cluster analysis method. The above algorithms are all technical methods that can be realized by those skilled in the art, and are not described in detail in this application.
In a second aspect, the present application provides a status monitoring method based on the internet of things, as shown in fig. 3, including the following steps:
step S1: monitoring data of all equipment to be monitored are transmitted to the Internet of things module and the edge data center module through the terminal module respectively;
step S2: the edge data center module transmits edge data, an edge model and an edge state monitoring result obtained by state monitoring to the Internet of things module;
step S3: the Internet of things module receives the edge data, the edge model and the edge state monitoring result transmitted by the edge data center, receives various equipment data transmitted by the terminal module, and transmits the edge data, the edge model, the edge state monitoring result and the various equipment data to the big data cloud module;
step S4: the big data cloud module receives and stores the edge data, the edge model, the edge state monitoring result and various equipment data transmitted by the Internet of things module;
step S5: the artificial intelligence module calls various data and models stored in the big data cloud module, carries out state monitoring by using an artificial intelligence algorithm to obtain a new model or/and a monitoring result, and transmits the new model or/and the monitoring result to the big data cloud module;
step S6: and the big data cloud module receives and stores the new model or/and the monitoring result transmitted by the artificial intelligence module.
In a third aspect, the present application provides an electronic device, comprising:
one or more processors;
a memory;
one or more applications stored in the memory and configured to be loaded and executed by the one or more processors to perform the internet of things based condition monitoring method.
As shown in fig. 4, the electronic apparatus 100 includes: a processor 101 and a memory 103. Wherein the processor 101 is coupled to the memory 103, such as via a bus 102.
The structure of the electronic device 100 is not limited to the embodiment of the present application.
The processor 101 may be a CPU, general purpose processor, DSP, ASIC, FPGA or other programmable logic device, transistor logic device, hardware component, or any combination thereof. Which may implement or perform the various illustrative logical blocks, modules, and circuits described in connection with the disclosure. The processor 101 may also be a combination of computing functions, e.g., comprising one or more microprocessors, DSPs, and microprocessors.
The memory 103 may be, but is not limited to, a ROM or other type of static storage device that can store static information and instructions, a RAM or other type of dynamic storage device that can store information and instructions, an EEPROM, a CD-ROM or other optical disk storage, optical disk storage (including compact disk, laser disk, optical disk, digital versatile disk, blu-ray disk, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer.
In a fourth aspect, the present application provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the method for monitoring a state based on an internet of things according to the first aspect or any possible implementation manner of the first aspect.
The present applicant has described and illustrated embodiments of the present invention in detail with reference to the accompanying drawings, but it should be understood by those skilled in the art that the above embodiments are merely preferred embodiments of the present invention, and the detailed description is only for the purpose of helping the reader to better understand the spirit of the present invention, and not for limiting the scope of the present invention, and on the contrary, any improvement or modification made based on the spirit of the present invention should fall within the scope of the present invention.
Claims (10)
1. A condition monitoring system based on the Internet of things, comprising:
the system comprises an artificial intelligence module, a big data cloud module, an Internet of things module, an edge data center module and a terminal module;
the artificial intelligence module is connected with a big data cloud module, the big data cloud module is connected with the Internet of things module, the Internet of things is respectively connected with the edge data center module and the terminal module, and the edge data center module is connected with the terminal module;
the artificial intelligence module is used for calling various data and models stored in the big data cloud module, performing state monitoring by using an artificial intelligence algorithm to obtain a new model or/and a monitoring result, and transmitting the new model or/and the monitoring result to the big data cloud module;
the big data cloud module is used for receiving and storing various data transmitted by the Internet of things module and the new model or/and monitoring result transmitted by the artificial intelligence module;
the internet of things module is used for being connected with the edge data center module and the terminal module through a network, receiving edge data, an edge model and an edge state monitoring result transmitted by the edge data center, receiving various equipment data transmitted by the terminal module, and transmitting the edge data, the edge model, the edge state monitoring result and the various equipment data to the big data cloud module;
the edge data center module is used for monitoring the state of at least one device and transmitting edge data, an edge model and an edge state monitoring result obtained by state monitoring to the Internet of things module;
the terminal module is used for being connected with all the devices to be monitored and providing data transmission interfaces for monitoring data of all the devices to be monitored.
2. The internet of things based condition monitoring system of claim 1, wherein: the state monitoring system based on the Internet of things allows a plurality of edge data center modules to exist, and allows a plurality of devices to be monitored to be connected with the same edge data center module.
3. The internet of things based condition monitoring system of claim 1, wherein: the edge data center module has an independent alarm function, namely, when the edge state monitoring result exceeds a preset edge threshold value, an alarm is given, and edge alarm information is sent to a mobile phone of a related person or displayed on an alarm screen.
4. The internet of things based condition monitoring system of claim 1, wherein: the edge data center module can receive alarm information transmitted by the Internet of things module, and the alarm information is obtained by comparing a monitoring result with a preset threshold value through the big data cloud module.
5. The internet of things based condition monitoring system of claim 4, wherein: the alarm information and the edge alarm information are displayed by adopting a graph curve, and the alarm information and the edge alarm information display method have an alarm information inquiry function and a report generation function.
6. The internet of things based condition monitoring system of claim 1, wherein: the network is formed by, but not limited to: optical fiber, a super-five line, RS485, 4G \5G, GPRS, ZigBee, WiFi, LoRa, M-BUS or Bluetooth; and supports the following communication protocols including TCP/IP, IEC61850, IEC60870, MODBUS, ProfiBus.
7. The internet of things based condition monitoring system of claim 1, wherein: the big data cloud module stores various data transmitted by the internet of things module according to predefined indexes, wherein the predefined indexes comprise: time index, device name index, edge data center name index.
8. An Internet of things-based state monitoring method is realized by the Internet of things-based state monitoring system according to any one of claims 1 to 7, and is characterized in that: the method comprises the following steps:
monitoring data of all equipment to be monitored are transmitted to the Internet of things module and the edge data center module through the terminal module respectively;
the edge data center module transmits edge data, an edge model and an edge state monitoring result obtained by state monitoring to the Internet of things module;
the Internet of things module receives the edge data, the edge model and the edge state monitoring result transmitted by the edge data center, receives various equipment data transmitted by the terminal module, and transmits the edge data, the edge model, the edge state monitoring result and the various equipment data to the big data cloud module;
the big data cloud module receives and stores the edge data, the edge model, the edge state monitoring result and various equipment data transmitted by the Internet of things module;
the artificial intelligence module calls various data and models stored in the big data cloud module, carries out state monitoring by using an artificial intelligence algorithm to obtain a new model or/and a monitoring result, and transmits the new model or/and the monitoring result to the big data cloud module;
and the big data cloud module receives and stores the new model or/and the monitoring result transmitted by the artificial intelligence module.
9. An electronic device, comprising:
one or more processors;
a memory;
one or more applications stored in the memory and configured to be loaded and executed by the one or more processors to perform the internet of things based condition monitoring method of claim 8.
10. A computer-readable storage medium, characterized in that,
stored thereon is a computer program which can be loaded and run by a processor to perform the method for internet of things based condition monitoring as claimed in claim 8.
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