Electric equipment quantity detection system based on electric meter display content

Abstract

The invention relates to an electricity meter display content-based electric equipment quantity detection system, which comprises a state identification mechanism, a detection mechanism and a display mechanism, the method is used for adopting a BP neural network model based on each piece of equipment data corresponding to each set electric equipment of the industrial park. Setting electric meter readings corresponding to the electric meters of the industrial park in all moments at uniform intervals in the latest time interval and setting rated current of the electric meters of the industrial park to intelligently identify and set on-state code values corresponding to all electric devices of the industrial park in the latest time interval; and the data transmission interface is used for transmitting the opening state coding numerical values of all the copies. According to the invention, an artificial intelligence mode can be adopted to intelligently identify the reading of each moment of the electric meter of the industrial park, and the on-state corresponding to each electric device in the industrial park can be determined, so that visual and effective field data can be provided for park device management network elements, and the technical difficulty of park device management is reduced.

Description

Technical Field

[0001] The invention relates to the field of electric meters, and in particular to a system for detecting the number of electric equipment based on electric meter display content. Background Art

[0002] Generally speaking, the specific impact of common meter load size is as follows: Meter damage: When the current exceeds the maximum current of the meter, it will not affect the measurement in a short time, but it will damage the meter in a long time. There are two current numbers on the meter, one of which allows a larger current. If it lasts longer, the meter will burn out.

[0003] Data reading error: If the purchased meter has a voltage greater than the rated voltage of your own circuit, the meter may have burnt components or circuits, and there may be errors in the data reading.

[0004] Circuit and line safety: High-load operation will cause the current transformer and electric energy meter to be seriously overloaded, the error will shift to the negative direction, and the metering will be greatly reduced. In addition, the excessive load of the circuit and line connected to the meter may cause a safety hazard of fire.

[0005] Obviously, for the meter load manager of an industrial park, in order to determine whether the above-mentioned dangerous situation will occur and provide expectations for future management, it is necessary not only to understand which load devices exist inside the industrial park, but also to understand which of these load devices are in the on state and which are in the off state. However, since the meter load manager is at the remote end of the industrial park, even by setting up cameras on site, it is difficult to fully determine the on state of each load device in each time interval, which makes it difficult for the meter load manager to provide expectations for future management. Summary of the invention

[0006] In order to solve the technical problems in the related fields, the present invention provides a system for detecting the number of electric equipment based on the display content of an electric meter. By adopting an artificial intelligence mode, the system intelligently identifies the readings of the electric meters of a set industrial park at various times, and determines the corresponding start-up states of the electric equipment in the set industrial park, thereby providing more intuitive and effective field data for the remote park equipment management network element. The BP neural network model adopted is a BP neural network obtained after multiple trainings are performed on the BP neural network to complete multiple reconstructions of the BP neural network. The number of trainings of the BP neural network is proportional to the total number of electric equipment in the set industrial park, thereby constructing different artificial intelligence models for different industrial parks. In order to ensure the effectiveness and stability of the intelligent identification results, sufficient and comprehensive multiple basic data are selected for the BP neural network model, including the equipment data corresponding to the electric equipment in the set industrial park and the meter readings corresponding to the electric meters of the set industrial park at various times evenly spaced within the latest time interval, wherein the single equipment data corresponding to each electric equipment is the resistance value, inductance value, working current and working voltage of the electric equipment.

[0007] According to the present invention, a system for detecting the number of electric devices based on the display content of an electric meter is provided, the system comprising: The first collection device is used to collect the equipment data corresponding to each electrical equipment in the set industrial park, and the single equipment data corresponding to each electrical equipment is the resistance value, inductance value, working current and working voltage of the electrical equipment; The second collection device is used to collect the meter readings of the electric meters in the set industrial park corresponding to each time at even intervals within the latest time interval, wherein the latest time interval ends at the current time and the duration is positively correlated with the total number of each electric device in the set industrial park; A network reconstruction device, used for performing multiple trainings on the BP neural network to complete multiple reconstructions of the BP neural network, and outputting the BP neural network after completing multiple trainings as a BP neural network model, wherein the number of trainings of the BP neural network is proportional to the total number of electrical equipment in the set industrial park; The state identification mechanism is connected to the first acquisition device, the second acquisition device and the network reconstruction device respectively, and is used to adopt the BP neural network model to intelligently identify the respective opening state code values ​​corresponding to the respective electrical equipment in the industrial park within the latest time interval based on the respective equipment data corresponding to the respective electrical equipment in the industrial park, the respective meter readings corresponding to the respective moments evenly spaced in the latest time interval of the electric meters in the industrial park, and the rated current of the electric meters in the industrial park; A data transmission interface, connected to the state identification mechanism, for transmitting the respective start-up state code values ​​corresponding to the respective electrical equipment in the set industrial park within the latest time interval to a remote park equipment management network element via a wireless communication link; Among them, the BP neural network model is used to intelligently identify the various power-on status code values ​​corresponding to the various electrical equipment in the industrial park in the latest time interval based on the various equipment data corresponding to the various electrical equipment in the industrial park, the various meter readings corresponding to the various moments evenly spaced in the latest time interval of the electric meters in the industrial park, and the rated current of the electric meters in the industrial park. The values ​​include: for each electrical equipment in the set industrial park, when it is turned on in the latest time interval, the single power-on status code value corresponding to it in the latest time interval is the ASCII value of its name plus a single digit with a value of 1.

[0008] It can be seen that the present invention has at least the following important inventive concepts: Invention concept 1: Using artificial intelligence mode to intelligently identify the readings of electric meters at various times in a set industrial park, determine the corresponding start-up status of each electric device in the set industrial park, and the artificial intelligence mode is based on a BP neural network model, thereby providing more intuitive and effective field data for remote park equipment management network elements; Inventive concept 2: The BP neural network model used is a BP neural network obtained by performing multiple training on the BP neural network to complete multiple reconstructions of the BP neural network. The number of trainings of the BP neural network is proportional to the total number of electrical equipment in the set industrial park, so as to construct different artificial intelligence models for different industrial parks. Inventive concept three: In order to ensure the effectiveness and stability of the intelligent identification results, sufficient and comprehensive basic data are selected for the BP neural network model, including setting each set of equipment data corresponding to each electrical equipment in the industrial park and setting each set of meter readings corresponding to each time period evenly spaced between the electric meters in the industrial park within the latest time interval, wherein the single set of equipment data corresponding to each electrical equipment is the resistance value, inductance value, working current and working voltage of the electrical equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] The embodiments of the present invention will be described below with reference to the accompanying drawings, wherein:

[0010] Figure 1 The figure is a schematic diagram of the internal structure of a system for detecting the number of electrical appliances based on the display content of an electric meter according to the first embodiment of the present invention.

[0011] Figure 2The figure is a schematic diagram of the internal structure of a system for detecting the number of electrical appliances based on the display content of an electric meter according to a second embodiment of the present invention.

[0012] Figure 3 Schematic diagram of the internal structure of a system for detecting the number of electrical appliances based on the display content of an electric meter according to a third embodiment of the present invention. DETAILED DESCRIPTION

[0013] The following will describe in detail an embodiment of the system for detecting the number of electrical equipment based on the display content of the electric meter according to the present invention with reference to the accompanying drawings.

[0014] Figure 1 This is a schematic diagram of the internal structure of a system for detecting the number of electrical devices based on the display content of an electric meter according to a first embodiment of the present invention, wherein the system comprises: The first collection device is used to collect the equipment data corresponding to each electrical equipment in the set industrial park, and the single equipment data corresponding to each electrical equipment is the resistance value, inductance value, working current and working voltage of the electrical equipment; The second collection device is used to collect the meter readings of the electric meters in the set industrial park corresponding to each time at even intervals within the latest time interval, wherein the latest time interval ends at the current time and the duration is positively correlated with the total number of each electric device in the set industrial park; A network reconstruction device, used for performing multiple trainings on the BP neural network to complete multiple reconstructions of the BP neural network, and outputting the BP neural network after completing multiple trainings as a BP neural network model, wherein the number of trainings of the BP neural network is proportional to the total number of electrical equipment in the set industrial park; Specifically, the network reconstruction device is used to perform multiple trainings on the BP neural network to complete multiple reconstructions of the BP neural network, and output the BP neural network after the multiple trainings as a BP neural network model, and the number of trainings of the BP neural network is proportional to the total number of various electrical equipment in the set industrial park. The method includes: using a MATLAB toolbox to complete the simulation and testing of a modeling process in which multiple trainings are performed on the BP neural network to complete multiple reconstructions of the BP neural network, and the BP neural network after the multiple trainings is output as a BP neural network model, and the number of trainings of the BP neural network is proportional to the total number of various electrical equipment in the set industrial park; The state identification mechanism is connected to the first acquisition device, the second acquisition device and the network reconstruction device respectively, and is used to adopt the BP neural network model to intelligently identify the respective opening state code values ​​corresponding to the respective electrical equipment in the industrial park within the latest time interval based on the respective equipment data corresponding to the respective electrical equipment in the industrial park, the respective meter readings corresponding to the respective moments evenly spaced in the latest time interval of the electric meters in the industrial park, and the rated current of the electric meters in the industrial park; A data transmission interface, connected to the state identification mechanism, for transmitting the respective start-up state code values ​​corresponding to the respective electrical equipment in the set industrial park within the latest time interval to a remote park equipment management network element via a wireless communication link; Among them, the BP neural network model is used to intelligently identify the respective opening state code values ​​corresponding to the respective electrical equipment in the industrial park in the latest time interval based on the respective equipment data corresponding to the respective electrical equipment in the industrial park, the respective meter readings corresponding to the respective moments evenly spaced in the latest time interval of the electric meter in the industrial park, and the rated current of the electric meter in the industrial park. The opening state code values ​​corresponding to the respective electrical equipment in the industrial park in the latest time interval include: for each electrical equipment in the set industrial park, when it is turned on in the latest time interval, the single opening state code value corresponding to it in the latest time interval is the ASCII value of its name plus a single digit with a value of 1; The electric meter readings corresponding to each time period evenly spaced in the latest time interval of the electric meter in the set industrial park are collected, and the latest time interval ends at the current time and the duration is positively correlated with the total number of each electric device in the set industrial park, including: the number of each time period evenly spaced in the latest time interval is proportional to the total number of each electric device in the set industrial park; Among them, the BP neural network model is used to intelligently identify the various power-on status code values ​​corresponding to the various electrical equipment in the industrial park in the latest time interval based on the various equipment data corresponding to the various electrical equipment in the industrial park, the various meter readings corresponding to the various moments evenly spaced in the latest time interval of the electric meters in the industrial park, and the rated current of the electric meters in the industrial park. It also includes: for each electrical equipment in the set industrial park, when it is turned on in the latest time interval, the single power-on status code value corresponding to it in the latest time interval is the ASCII value of its name plus a single digit with a value of 0.

[0015] Figure 2 The figure is a schematic diagram of the internal structure of a system for detecting the number of electrical appliances based on the display content of an electric meter according to a second embodiment of the present invention.

[0016] and Figure 1 different, Figure 2 The electric device quantity detection system based on the electric meter display content in the invention may also include the following components: A timing server component is connected to the state identification mechanism, the first acquisition device, the second acquisition device and the network reconstruction device respectively, and is used to provide the state identification mechanism, the first acquisition device, the second acquisition device and the network reconstruction device with the timing services required by each of them; The timing server is connected to the state identification mechanism, the first acquisition device, the second acquisition device and the network reconstruction device respectively, and is used to provide the state identification mechanism, the first acquisition device, the second acquisition device and the network reconstruction device with the timing services required by each of them, including: the timing server uses the same timing clock to provide the state identification mechanism, the first acquisition device, the second acquisition device and the network reconstruction device with the timing services required by each of them; Among them, the timing server uses the same timing clock to provide the timing services required by the state identification mechanism, the first acquisition device, the second acquisition device and the network reconstruction device respectively, including: the timing server uses the same timing clock to provide the state identification mechanism, the first acquisition device, the second acquisition device and the network reconstruction device respectively with reference clock signals of various changing waveforms of the same timing clock.

[0017] Figure 3 Schematic diagram of the internal structure of a system for detecting the number of electrical appliances based on the display content of an electric meter according to a third embodiment of the present invention.

[0018] and Figure 1 different, Figure 3 The electric device quantity detection system based on the electric meter display content in the invention may also include the following components: A parallel data bus, connected to the state identification mechanism, the first acquisition device, the second acquisition device and the network reconstruction device respectively, for providing a parallel data communication link between any two devices of the state identification mechanism, the first acquisition device, the second acquisition device and the network reconstruction device; Wherein, the parallel data bus is respectively connected to the state identification mechanism, the first acquisition device, the second acquisition device and the network reconstruction device, and is used to provide a parallel data communication link between two devices of the state identification mechanism, the first acquisition device, the second acquisition device and the network reconstruction device, including: providing a 64-bit parallel data communication link between two devices of the state identification mechanism, the first acquisition device, the second acquisition device and the network reconstruction device; Wherein, the parallel data bus is respectively connected to the state identification mechanism, the first acquisition device, the second acquisition device and the network reconstruction device, and is used to provide a parallel data communication link between two devices of the state identification mechanism, the first acquisition device, the second acquisition device and the network reconstruction device, including: providing a parallel data communication link between two devices of the state identification mechanism, the first acquisition device, the second acquisition device and the network reconstruction device is a 32-bit parallel data communication link; Wherein, the parallel data bus is respectively connected to the state identification mechanism, the first acquisition device, the second acquisition device and the network reconstruction device, and is used to provide a parallel data communication link between two devices of the state identification mechanism, the first acquisition device, the second acquisition device and the network reconstruction device, including: providing a 16-bit parallel data communication link between two devices of the state identification mechanism, the first acquisition device, the second acquisition device and the network reconstruction device; And wherein, a parallel data bus is respectively connected to the state identification mechanism, the first acquisition device, the second acquisition device and the network reconstruction device, and is used to provide a parallel data communication link between each two devices of the state identification mechanism, the first acquisition device, the second acquisition device and the network reconstruction device, and also includes: the distance between each two of the state identification mechanism, the first acquisition device, the second acquisition device and the network reconstruction device is less than or equal to a set distance threshold.

[0019] In addition, in the electric equipment quantity detection system based on the meter display content, the BP neural network model is used to intelligently identify the start-up state code values ​​corresponding to the electric equipment in the industrial park in the latest time interval based on the equipment data corresponding to the electric equipment in the industrial park, the meter readings corresponding to the electric meters in the industrial park at each moment evenly spaced within the latest time interval, and the rated current of the electric meters in the industrial park. It also includes: performing binary value conversion on the equipment data corresponding to the electric equipment in the industrial park, the meter readings corresponding to the electric meters in the industrial park at each moment evenly spaced within the latest time interval, and the rated current of the electric meters in the industrial park, and then inputting them into the BP neural network model.

[0020] The system for detecting the number of electrical equipment based on the meter display content of the present invention is used to solve the problem in the prior art that since the meter load manager is located at the remote end of the industrial park, even by setting up cameras on site, it is difficult to completely determine the power-on status of each load device in each time interval, which makes it difficult for the meter load manager to provide expected technical problems for future management. By adopting an artificial intelligence model, the readings of the meters of the set industrial park at each moment can be intelligently identified, and the corresponding power-on status of each electrical equipment in the set industrial park can be determined, thereby providing intuitive and effective on-site data for the park equipment management network element, reducing the technical difficulty of park equipment management.

[0021] It will be appreciated by those skilled in the art that various modifications and changes may be made without departing from the scope and spirit of the present invention. It should therefore be understood that the above embodiments are for illustration only and are not intended to be limiting. Because the scope of the present invention is defined by the claims rather than the foregoing description, any changes and modifications that fall within the scope and boundaries of the claims or the equivalents of these scopes and boundaries are subject to the claims.

Claims

1. A system for detecting the number of electrical equipment based on the display content of an electric meter, characterized in that: The system comprises: The first collection device is used to collect the equipment data corresponding to each electrical equipment in the set industrial park, and the single equipment data corresponding to each electrical equipment is the resistance value, inductance value, working current and working voltage of the electrical equipment; The second collection device is used to collect the meter readings of the electric meters in the set industrial park corresponding to each time at even intervals within the latest time interval, wherein the latest time interval ends at the current time and the duration is positively correlated with the total number of each electric device in the set industrial park; A network reconstruction device, used for performing multiple trainings on the BP neural network to complete multiple reconstructions of the BP neural network, and outputting the BP neural network after completing multiple trainings as a BP neural network model, wherein the number of trainings of the BP neural network is proportional to the total number of electrical equipment in the set industrial park; The state identification mechanism is connected to the first acquisition device, the second acquisition device and the network reconstruction device respectively, and is used to adopt the BP neural network model to intelligently identify the respective opening state code values ​​corresponding to the respective electrical equipment in the industrial park within the latest time interval based on the respective equipment data corresponding to the respective electrical equipment in the industrial park, the respective meter readings corresponding to the respective moments evenly spaced in the latest time interval of the electric meters in the industrial park, and the rated current of the electric meters in the industrial park; A data transmission interface, connected to the state identification mechanism, for transmitting the respective start-up state code values ​​corresponding to the respective electrical equipment in the set industrial park within the latest time interval to a remote park equipment management network element via a wireless communication link; Among them, the BP neural network model is used to intelligently identify the various power-on status code values ​​corresponding to the various electrical equipment in the industrial park in the latest time interval based on the various equipment data corresponding to the various electrical equipment in the industrial park, the various meter readings corresponding to the various moments evenly spaced in the latest time interval of the electric meters in the industrial park, and the rated current of the electric meters in the industrial park. The values ​​include: for each electrical equipment in the set industrial park, when it is turned on in the latest time interval, the single power-on status code value corresponding to it in the latest time interval is the ASCII value of its name plus a single digit with a value of 1.

2. The system for detecting the number of electric devices based on the electric meter display content according to claim 1, characterized in that: Collecting the meter readings corresponding to each time period evenly spaced in the latest time interval of the electric meter in the set industrial park, wherein the latest time interval ends at the current time period and the duration thereof is positively correlated with the total number of each electric-using equipment in the set industrial park, including: the number of each time period evenly spaced in the latest time interval is proportional to the total number of each electric-using equipment in the set industrial park; Among them, the BP neural network model is used to intelligently identify the various power-on status code values ​​corresponding to the various electrical equipment in the industrial park in the latest time interval based on the various equipment data corresponding to the various electrical equipment in the industrial park, the various meter readings corresponding to the various moments evenly spaced in the latest time interval of the electric meters in the industrial park, and the rated current of the electric meters in the industrial park. It also includes: for each electrical equipment in the set industrial park, when it is turned on in the latest time interval, the single power-on status code value corresponding to it in the latest time interval is the ASCII value of its name plus a single digit with a value of 0.

3. The system for detecting the number of electric devices based on the electric meter display content according to claim 2, characterized in that: The system further comprises: A timing server component is connected to the state identification mechanism, the first acquisition device, the second acquisition device and the network reconstruction device respectively, and is used to provide the state identification mechanism, the first acquisition device, the second acquisition device and the network reconstruction device with the timing services required by each of them; Among them, the timing server component is respectively connected to the state identification mechanism, the first acquisition device, the second acquisition device and the network reconstruction device, and is used to provide the state identification mechanism, the first acquisition device, the second acquisition device and the network reconstruction device with the timing services they need respectively, including: the timing server component uses the same timing clock to provide the state identification mechanism, the first acquisition device, the second acquisition device and the network reconstruction device with the timing services they need respectively.

4. The system for detecting the number of electric devices based on the electric meter display content according to claim 3, characterized in that: The timing server uses the same timing clock to provide the state identification mechanism, the first acquisition device, the second acquisition device and the network reconstruction device with the timing services they need, including: the timing server uses the same timing clock to provide the state identification mechanism, the first acquisition device, the second acquisition device and the network reconstruction device with reference clock signals of various changing waveforms of the same timing clock.

5. The system for detecting the number of electric devices based on the electric meter display content according to claim 3, characterized in that: The system further comprises: A parallel data bus is connected to the state identification mechanism, the first acquisition device, the second acquisition device and the network reconstruction device respectively, and is used to provide a parallel data communication link between any two devices of the state identification mechanism, the first acquisition device, the second acquisition device and the network reconstruction device.

6. The system for detecting the number of electric devices based on the electric meter display content according to claim 5, characterized in that: A parallel data bus is connected to the state identification mechanism, the first acquisition device, the second acquisition device and the network reconstruction device respectively, and is used to provide a parallel data communication link between each two devices of the state identification mechanism, the first acquisition device, the second acquisition device and the network reconstruction device, including: providing a parallel data communication link between each two devices of the state identification mechanism, the first acquisition device, the second acquisition device and the network reconstruction device is a 64-bit parallel data communication link.

7. The system for detecting the number of electric devices based on the electric meter display content according to claim 5, characterized in that: A parallel data bus is respectively connected to the state identification mechanism, the first acquisition device, the second acquisition device and the network reconstruction device, and is used to provide a parallel data communication link between each two devices of the state identification mechanism, the first acquisition device, the second acquisition device and the network reconstruction device, including: providing a parallel data communication link between each two devices of the state identification mechanism, the first acquisition device, the second acquisition device and the network reconstruction device is a 32-bit parallel data communication link.

8. The system for detecting the number of electric devices based on the electric meter display content according to claim 5, characterized in that: A parallel data bus is connected to the state identification mechanism, the first acquisition device, the second acquisition device and the network reconstruction device respectively, and is used to provide a parallel data communication link between each two devices of the state identification mechanism, the first acquisition device, the second acquisition device and the network reconstruction device, including: providing a parallel data communication link between each two devices of the state identification mechanism, the first acquisition device, the second acquisition device and the network reconstruction device is a 16-bit parallel data communication link.

9. The system for detecting the number of electric devices based on the electric meter display content according to claim 5, characterized in that: A parallel data bus is connected to the state identification mechanism, the first acquisition device, the second acquisition device and the network reconstruction device respectively, and is used to provide a parallel data communication link between the state identification mechanism, the first acquisition device, the second acquisition device and the network reconstruction device. It also includes: the distance between the state identification mechanism, the first acquisition device, the second acquisition device and the network reconstruction device is less than or equal to a set distance threshold.

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