A fault detection and self-recovery method of a multi-state fusion low-voltage intelligent switch

Abstract

The present application relates to the technical field of low-voltage line protection, and particularly relates to a fault detection and self-healing method of a multi-state fusion low-voltage intelligent switch, which comprises the following steps: deploying the low-voltage intelligent switch on a low-voltage line, monitoring electrical parameters of the low-voltage circuit through the low-voltage intelligent switch, and recording electrical parameter data before and after a fault of the low-voltage line; establishing a data connection between the low-voltage intelligent switch and a fault monitoring APP, and transmitting the line electrical parameters to the fault monitoring APP; processing the received electrical parameter data by the fault monitoring APP, predicting a line fault, positioning the low-voltage intelligent switch according to an identification ID, and facilitating a power maintenance personnel to troubleshoot; setting a sampling frequency of the electrical parameter data of the low-voltage intelligent switch through the fault monitoring APP, and automatically recovering the line according to the automatically collected electrical parameter data after troubleshooting.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of low-voltage line protection, in particular to a fault detection and self-healing method of a multi-state fusion low-voltage intelligent switch. BACKGROUND

[0002] At present, the technology of distribution transformer and terminal electric energy meter is mainly focused on the technical requirements of the first terminal transformer and the terminal electric energy meter, however, the informatization demand of the middle layer of the transformer area, i.e. the distribution line, is still insufficient.

[0003] In addition, the terminal switch device at the total outgoing line side of the transformer area currently only has the basic overcurrent tripping protection function, and still lacks the ability of real-time electrical parameter monitoring and fault waveform recording. Such limitations not only increase the difficulty of fault analysis, but also make the monitoring of grid-connected power quality parameters of energy storage power stations, charging piles and new energy power stations a challenge. SUMMARY

[0004] The present application can accurately capture and record the change of electrical parameters within the key period before and after the fault occurs, thereby providing strong data support for subsequent fault analysis, and predicting the fault by monitoring the line through the voltage monitoring model and the current monitoring model, and timely controlling the action of the low-voltage intelligent switch.

[0005] The technical scheme provided by the present application is as follows: a fault detection and self-healing method of a multi-state fusion low-voltage intelligent switch, the method comprising:

[0006] The low-voltage intelligent switch is deployed on the low-voltage line, the low-voltage intelligent switch monitors the electrical parameters of the low-voltage circuit, and records the electrical parameter data before and after the fault of the low-voltage line;

[0007] The data connection between the low-voltage intelligent switch and the fault monitoring APP is established, and the line electrical parameters are transmitted to the fault monitoring APP;

[0008] The fault monitoring APP processes the received electrical parameter data and predicts the line fault, and locates the low-voltage intelligent switch according to the identification ID, so as to facilitate the fault elimination of the power maintenance personnel;

[0009] The sampling frequency of the electrical parameter data of the low-voltage intelligent switch is set through the fault monitoring APP, and after the fault is eliminated, the line is actively recovered according to the automatically collected electrical parameter data;

[0010] The low-voltage intelligent switch comprises a main control module and a power module, a metering module, a communication module and a split control module connected with the main control module;

[0011] The fault monitoring APP stores an identification ID matched with each low-voltage intelligent switch, and the sampling frequency comprises a current sampling frequency f1 and a voltage sampling frequency f2.

[0012] Preferably, the master module comprises a master chip and a touch master chip connected with the master chip, a memory and a plurality of recording wave master chips; the metering module comprises a metering chip and a voltage sampling circuit and a current sampling circuit connected with the metering chip, and the recording wave master chip is used to control the voltage sampling circuit and the current sampling circuit to collect voltage and current data of the circuit.

[0013] Preferably, the low-voltage intelligent switch monitors the electrical parameters of the low-voltage circuit and records the electrical parameter data before and after the low-voltage line fault, comprising the following steps:

[0014] Collecting voltage and current data of the low-voltage circuit through the voltage collection circuit and the current collection circuit;

[0015] Processing the input voltage and current data through the metering chip to obtain current and voltage values;

[0016] Controlling the collection time of the voltage collection circuit and the current collection circuit through the recording wave master chip; the collection time includes a collection start time point T1 and a collection end time point T2;

[0017] The master chip generates a RAM address corresponding to the identification ID according to the stored identification ID, and stores the collected current and voltage waveform data in the storage area corresponding to the RAM address in the memory.

[0018] Preferably, the low-voltage intelligent switch and the fault monitoring APP data connection are established, and the circuit electrical parameters are transmitted to the fault monitoring APP, comprising the following steps:

[0019] Establishing data connection between the communication module and the fault monitoring APP through a preset communication protocol;

[0020] The master chip retrieves the collected voltage and current waveform data from the memory;

[0021] Sending the voltage, current waveform data and the corresponding identification ID to the fault monitoring APP through the communication module.

[0022] Preferably, the fault monitoring APP processes the received electrical parameter data and predicts the line fault reason, comprising:

[0023] Reading the voltage, current waveform data and the corresponding identification ID, extracting the voltage characteristic value and the current characteristic value, and respectively forming the voltage characteristic value set and the current characteristic value set corresponding to the identification ID;

[0024] The current characteristic value includes one or more of the maximum current value, the minimum current value, the average current value and the current frequency;

[0025] The voltage characteristic value includes one or more of a maximum voltage value, a minimum voltage value, an average voltage value, and a voltage frequency.

[0026] The elements in the voltage characteristic value set are preprocessed and normalized as input variables and input into a preset voltage monitoring model to output a voltage prediction value at a future time;

[0027] The elements in the current characteristic value set are preprocessed and normalized as input variables and input into a preset current monitoring model to output a current prediction value at a future time;

[0028] The voltage prediction value and the current prediction value are analyzed, and a control instruction is output by a fault monitoring APP according to an analysis result to control the opening and closing actions of the low-voltage intelligent switch; a state value of the low-voltage intelligent switch is fed back, and the state value is 0 or 1.

[0029] Preferably, the voltage characteristic value set is preprocessed and normalized as an input variable and input into a preset voltage monitoring model to output a voltage prediction value at a future time, and specifically includes:

[0030] The elements in the voltage characteristic set are preprocessed and normalized, and a voltage monitoring characteristic set corresponding to the identification ID is generated in combination with the identification ID: ;

[0031] The voltage monitoring model is set as: wherein, is an intercept, represents the first regression coefficient, is an error term, ; ;

[0032] The are respectively input into the voltage monitoring model, and the output represents a prediction value of the voltage at a future time;

[0033] The elements in the current characteristic value set are preprocessed and normalized as input variables and input into a preset current monitoring model to output a current prediction value at a future time, and specifically includes:

[0034] The elements in the current characteristic set are preprocessed and normalized, and a current monitoring characteristic set corresponding to the identification ID is generated in combination with the identification ID: ; The preprocessed and normalized maximum current value, minimum current value, average current value, and current frequency are respectively represented by

[0035] The current monitoring model is set as: wherein, is an intercept, represents the first regression coefficient, is an error term,

[0036] are respectively input into the voltage monitoring model, and the output represents a predicted value of the current at a future time.

[0037] Preferably, the voltage prediction value and the current prediction value are analyzed, and the fault monitoring APP outputs a control instruction according to the analysis result to control the opening and closing actions of the low-voltage intelligent switch, including:

[0038] a voltage action threshold and a current action threshold

[0039] The state value of the low-voltage intelligent switch corresponding to the identification ID is obtained, and the state value of 1 indicates that the corresponding low-voltage intelligent switch is in a closed state, and the state value of 0 indicates that the corresponding low-voltage intelligent switch is in an open state.

[0040] If the state value is 1 and or , the fault monitoring APP generates an open control instruction and sends the open control instruction to the low-voltage intelligent switch corresponding to the identification ID, and the main control chip in the low-voltage intelligent switch drives the opening and closing control module after analyzing the open control instruction to execute the opening action; wherein are respectively a voltage threshold correction variable and a current threshold correction variable;

[0041] If the state value is 0 and and , the fault monitoring APP generates a closing control instruction and sends the closing control instruction to the low-voltage intelligent switch corresponding to the identification ID, and the main control chip in the low-voltage intelligent switch drives the opening and closing control module after analyzing the open control instruction to execute the closing action.

[0042] If the state value is 1 and and , it is judged that the circuit is normal, and the fault monitoring APP does not send a control instruction.

[0043] If the state value is 0 and or , it is judged that the low-voltage intelligent switch has a fault of not feeding back a state value normally or not opening normally, and the fault monitoring APP generates a switch fault alarm information, and the switch alarm information includes the identification ID of the fault low-voltage intelligent switch.

[0044] ​​​​Preferably, the sampling frequency of the electrical parameter data of the low-voltage intelligent switch is set by the fault monitoring APP, and after troubleshooting, the line is actively restored according to the automatically collected electrical parameter data, including:

[0045] Obtain the state value;

[0046] Determine whether the state value is 0;

[0047] If the state value is 0, then:

[0048] The fault monitoring APP calls the pre-stored f1 and f2 and sends f1 and f2 to the low-voltage intelligent switch;

[0049] The master control chip sends f1 and f2 to the wave recording chip, and the wave recording chip controls the voltage sampling circuit and the current sampling circuit to sample the line according to f1 and f2;

[0050] Obtain a plurality of voltage values and current values through the metering chip and feed back to the master control chip, and the master control chip compares the collected voltage values and current values with the preset normal current values and normal voltage values respectively;

[0051] If and , it is determined that the circuit current and voltage are normal, a closing instruction is generated to drive the opening and closing control module to perform closing operation, wherein, and are the current correction normal number and the voltage correction normal number respectively, , ;

[0052] If the state value is 1, go to the step of obtaining the state value.

[0053] The application also provides an electronic device for executing the fault detection and self-healing method of the multi-state fusion low-voltage intelligent switch.

[0054] The application also provides a computer readable storage medium storing a computer program, wherein the computer program is executed by a processor to realize the fault detection and self-healing method of the multi-state fusion low-voltage intelligent switch.

[0055] The application has the following beneficial effects:

[0056] 1. The low-voltage intelligent switch is installed on the low-voltage line of the key node, so that it can monitor the electrical parameters such as current and voltage flowing in the circuit, and continuously monitor and record the electrical parameter data before and after normal operation and failure through the intelligent switch, so as to analyze the failure. Data connection between intelligent switch and fault monitoring APP, real-time or scheduled upload of monitored electrical parameters to fault monitoring APP, fault monitoring APP processes and analyzes the uploaded electrical parameter data, diagnoses the fault cause, and determines the specific location of the fault according to the unique identification ID of each intelligent switch. The fault point and cause are reported to the power maintenance personnel, so that they can quickly and accurately troubleshoot. After troubleshooting, whether the power supply can be safely restored is evaluated by using the automatically collected electrical parameter data, and the intelligent switch is controlled by the fault monitoring APP to actively restore the line operation, so as to realize efficient and automated management of the low-voltage power grid, reduce manual intervention, and improve the reliability and self-healing ability of the power grid.

[0057] 2. The present application can predict that the line where the low-voltage intelligent switch is located will fail at a future time t, and the wave recording control module controls the voltage acquisition circuit and the current acquisition circuit to acquire the voltage waveform and the current waveform in the time period of t-1s to t+1s, that is, the waveform data within 2 seconds before and after the fault time point. The acquired waveform data is stored in the memory in the low-voltage intelligent switch to realize the function of fault recording. In addition, the main control chip sends f1 and f2 to the wave recording chip, and the wave recording chip controls the voltage sampling circuit and the current sampling circuit to sample the line according to f1 and f2 to realize the function of triggering recording.

[0058] 3. The present application obtains a plurality of voltage values and current values through the metering chip, and feeds back to the main control chip, and the main control chip compares the acquired voltage values and current values with the preset normal current values and normal voltage values respectively; if the circuit current and voltage are normal, a closing instruction is generated to drive the opening and closing control module to perform closing operation to restore power supply to the line that has been excluded from failure.

[0059] 4, If it is judged that the low-voltage intelligent switch has no normal feedback state value or no normal disconnection failure, the switch failure alarm information is generated by the fault monitoring APP, the switch alarm information includes the identification ID of the fault low-voltage intelligent switch, and the reset instruction is sent to the low-voltage intelligent switch, the main control chip of the low-voltage intelligent switch receives and analyzes the reset instruction, and then executes the reset operation. After resetting, the switch will try to disconnect again, and feed back the new state value to the fault monitoring APP, and the fault monitoring APP receives the feedback state value, and verifies whether the low-voltage intelligent switch has returned to the normal working state. If yes, the alarm is cancelled; if not, manual intervention or repair is carried out. BRIEF DESCRIPTION OF DRAWINGS

[0060] Figure 1 It is a schematic diagram of the low-voltage intelligent switch module of the present application.

[0061] Figure 2 It is a flow chart of the method of the present application. DETAILED DESCRIPTION

[0062] The following description is provided to disclose the present application so that those skilled in the art can implement the present application. The preferred embodiments in the following description are only examples, and other obvious modifications can be made by those skilled in the art. The basic principles defined in the following description can be applied to other embodiments, modifications, improvements, equivalents and other technical solutions without departing from the spirit and scope of the present application.

[0063] It can be understood that the term "one" should be understood as "at least one" or "one or more", that is, in one embodiment, the number of one element can be one, and in another embodiment, the number of the element can be multiple, and the term "one" cannot be understood as a limitation on the number.

[0064] Referring to the accompanying drawings Figure 1 In the present application, a low-voltage intelligent switch is provided, which is composed of a main control module and a power supply module, a metering module, a communication module and a switching control module connected with the main control module. The main control module includes a main control chip and a touch control chip, a memory and a plurality of wave recording control chips connected with the main control chip; the metering module includes a metering chip and a voltage sampling circuit and a current sampling circuit connected with the metering chip, and the wave recording control chip is used to control the voltage and current data collected by the voltage sampling circuit and the current sampling circuit. The communication module includes an RS485 communication unit and an infrared communication unit.

[0065] In addition, in some preferred embodiments, human-computer interaction units such as display module and input module can be connected outside the low-voltage intelligent switch as needed, for example, display screen and keyboard.

[0066] In combinationFigure 2 The application provides a fault detection and self-recovery method for a multi-state fusion low-voltage intelligent switch, comprising the following steps:

[0067] Step one, deploying the low-voltage intelligent switch on the low-voltage line, monitoring the electrical parameters of the low-voltage circuit through the low-voltage intelligent switch, and recording the electrical parameter data before and after the low-voltage line fault, specifically comprising:

[0068] Step 1.1, collecting the voltage and current data of the low-voltage circuit through the voltage acquisition circuit and the current acquisition circuit;

[0069] Step 1.2, processing the input voltage and current data through the metering chip to obtain the current value and voltage value;

[0070] Step 1.3, controlling the acquisition time of the voltage acquisition circuit and the current acquisition circuit through the wave recording master control chip; the acquisition time includes the acquisition start time point T1 (1 second before the fault occurs) and the acquisition end time point T2 (1 second after the fault occurs);

[0071] Step 1.4, the master control chip generates a RAM address corresponding to the identification ID according to the stored identification ID, and stores the collected current and voltage waveform data in the storage area corresponding to the RAM address in the storage.

[0072] Step two, establishing data connection between the low-voltage intelligent switch and the fault monitoring APP, transmitting the line electrical parameters to the fault monitoring APP, specifically comprising:

[0073] Step 2.1, establishing data connection between the communication module and the fault monitoring APP through the preset communication protocol; according to the actual situation, selecting RS485 communication protocol and wireless communication protocol.

[0074] Step 2.2, the master control chip retrieves the collected voltage and current waveform data from the storage;

[0075] Step 2.3, sending the voltage, current waveform data and the corresponding identification ID to the fault monitoring APP through the communication module.

[0076] Step three, the fault monitoring APP processes the received electrical parameter data and predicts the line fault, and locates the low-voltage intelligent switch according to the identification ID, so as to facilitate the fault elimination of the power maintenance personnel, specifically comprising:

[0077] Step 3.1, reading the voltage, current waveform data and the corresponding identification ID, extracting the voltage characteristic value and the current characteristic value, and respectively forming the voltage characteristic value set and the current characteristic value set corresponding to the identification ID;

[0078] Step 3.2, the elements in the voltage feature value set are input into the preset voltage monitoring model after preprocessing and normalization as input variables, and the voltage prediction value at the next time is output, including the following steps:

[0079] Step 3.2.1, the elements in the voltage feature set are preprocessed and normalized, and the voltage monitoring feature set corresponding to the identification ID is generated in combination with the identification ID: ; The maximum voltage value, the minimum voltage value, the average voltage value and the voltage frequency after preprocessing and normalization are represented;

[0080] Step 3.2.2, the voltage monitoring model is: Wherein, is the intercept, represents the th regression coefficient, is the error term, ;

[0081] Step 3.2.3, the are input into the voltage monitoring model respectively, and the output represents the prediction value of the voltage at the next time.

[0082] Step 3.3, the elements in the current feature value set are input into the preset current monitoring model after preprocessing and normalization as input variables, and the current prediction value at the next time is output, including the following steps:

[0083] Step 3.3.1, the elements in the current feature set are preprocessed and normalized, and the current monitoring feature set corresponding to the identification ID is generated in combination with the identification ID: ; The maximum current value, the minimum current value, the average current value and the current frequency after preprocessing and normalization are represented respectively;

[0084] Step 3.3.2, the current monitoring model is: Wherein, is the intercept, represents the th regression coefficient, is the error term, ;

[0085] Step 3.3.3, the are input into the voltage monitoring model respectively, and the output represents the prediction value of the current at the next time.

[0086] Step 3.4, analyzing the voltage prediction value and the current prediction value, and outputting a control instruction according to the analysis result by the fault monitoring APP, to control the opening and closing action of the low-voltage intelligent switch; and feeding back the state value of the low-voltage intelligent switch, the state value being 0 or 1, specifically including the following steps:

[0087] Step 3.4.1, setting the voltage action threshold value and the current action threshold value ;

[0088] Step 3.4.2, acquiring the state value of the low-voltage intelligent switch corresponding to the identification ID, the state value being 1 indicating that the corresponding low-voltage intelligent switch is in a closed state, and the state value being 0 indicating that the corresponding low-voltage intelligent switch is in an open state;

[0089] Step 3.4.3, if the state value is 1 and or , it is predicted that a fault will occur in the line where the low-voltage intelligent switch is located at a future time point, if the predicted time point is t, the fault monitoring APP sends the predicted fault time point t to the low-voltage intelligent switch, and the wave recording control module controls the voltage acquisition circuit and the current acquisition circuit to acquire the voltage waveform and the current waveform in the time period of t-1s to t+1s, that is, the waveform data in the period of 2 seconds before and after the fault time point, in this embodiment, the frequency of the wave recording is not less than 10k / s, the wave recording frequency can be written into the low-voltage intelligent switch remotely by the fault monitoring APP, or can be manually input into the low-voltage intelligent switch by the keyboard connected to the low-voltage intelligent switch. The acquired waveform data is stored in the memory in the low-voltage intelligent switch for later analysis;

[0090] Then, the fault monitoring APP generates an opening control instruction, and sends the opening control instruction to the low-voltage intelligent switch corresponding to the identification ID, and the main control chip in the low-voltage intelligent switch analyzes the opening control instruction to drive the opening and closing control module to execute the opening action; wherein, are respectively a voltage threshold correction variable and a current threshold correction variable;

[0091] Step 3.4.4, if the state value is 0 and and , the fault monitoring APP generates a closing control instruction, and sends the closing control instruction to the low-voltage intelligent switch corresponding to the identification ID, and the main control chip in the low-voltage intelligent switch analyzes the closing control instruction to drive the opening and closing control module to execute the closing action.

[0092] Step 3.4.5, if the state value is 1 and and , it is judged that the circuit is normal, and the fault monitoring APP does not send a control instruction;

[0093] Step 3.4.6, if the state value is 0 and or , it is judged that the low-voltage intelligent switch has a fault of no normal feedback state value or no normal disconnection, the fault monitoring APP generates a switch fault alarm information, the switch alarm information includes the identification ID of the fault low-voltage intelligent switch, and sends a reset instruction to the low-voltage intelligent switch, the main control chip of the low-voltage intelligent switch receives and analyzes the reset instruction, and then performs a reset operation. After resetting, the switch will try to disconnect again, and feed back a new state value to the fault monitoring APP. After receiving the feedback state value, the fault monitoring APP will verify whether the low-voltage intelligent switch has returned to a normal working state. If yes, the alarm will be cancelled; if not, further manual intervention or repair may be required.

[0094] Step four, set the sampling frequency of the electrical parameter data of the low-voltage intelligent switch through the fault monitoring APP, and automatically restore the line according to the automatically collected electrical parameter data after troubleshooting, which specifically includes the following steps:

[0095] Step 4.1, get the state value;

[0096] Step 4.2, judge whether the state value is 0;

[0097] Step 4.3, if it is 0, then:

[0098] The fault monitoring APP calls the pre-stored f1 and f2 and sends f1 and f2 to the low-voltage intelligent switch;

[0099] Step 4.4, the main control chip sends f1 and f2 to the wave recording chip, and the wave recording chip controls the voltage sampling circuit and the current sampling circuit to sample the line according to f1 and f2;

[0100] Step 4.5, get a plurality of voltage values and current values through the metering chip and feed back to the main control chip, and the main control chip compares the collected voltage values and current values with the pre-set normal current values and normal voltage values respectively;

[0101] Step 4.6, if and , it is judged that the circuit current and voltage are normal, then a closing instruction is generated to drive the on-off control module to perform closing operation, wherein, and are the current correction normal number and the voltage correction normal number respectively, , ;

[0102] Step 4.7, if 1, then enter step 4.1 to reacquire the state value.

[0103] The fault monitoring APP stores an identification ID matched with each low-voltage intelligent switch, and the sampling frequency includes a current sampling frequency f1 and a voltage sampling frequency f2, both of which can be set remotely by the upper computer or locally, and the set f1 and f2 are stored locally.

[0104] When current leakage occurs due to line insulation aging, damage, etc., and when a person or an animal directly touches, the low-voltage intelligent switch can be safely and reliably tripped and the power supply can be quickly cut off through the electric shock master control module controlling the on-off control module.

[0105] The application further provides an electronic device for executing the fault detection and self-recovery method of the multi-state fusion low-voltage intelligent switch.

[0106] The application further provides a computer readable storage medium storing a computer program, and the computer program is executed by a processor to realize the fault detection and self-recovery method of the multi-state fusion low-voltage intelligent switch.

[0107] It should be noted that the current monitoring model and the voltage monitoring model in the embodiment are pre-trained and functionally verified.

[0108] The processes described above with reference to the flowcharts can be implemented as computer software programs in accordance with embodiments of the present disclosure. Embodiments of the present disclosure include a computer program product comprising a computer program carried on a computer readable medium, the computer program comprising program code for performing the methods illustrated by the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication section, and / or installed from a detachable medium. When the computer program is executed by a central processing unit (CPU), the above-described functions defined in the methods of the present application are performed. It should be noted that the computer readable medium of the present application can be a computer readable signal medium or a computer readable storage medium or any combination of the two. The computer readable storage medium may, for example, but not limited to, be an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus or device, or any suitable combination of the above. More specific examples of the computer readable storage medium can include, but are not limited to, an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, the computer readable storage medium can be any tangible medium that contains or stores a program that can be used by or in connection with an instruction execution system, apparatus or device. In the present application, the computer readable signal medium can include a data signal carried in a baseband or as part of a carrier wave, in which the computer readable program code is carried. Such a propagated data signal can take many forms, including but not limited to, an electromagnetic signal, an optical signal or any suitable combination of the above. The computer readable signal medium can also be any computer readable medium that can send, propagate or transfer a program for use by or in connection with an instruction execution system, apparatus or device. The program code contained on the computer readable medium can be transmitted by any suitable medium, including but not limited to, wireless, wire, optical cable, RF or the like, or any suitable combination of the above.

[0109] The computer program product of the present application can be a computer program product comprising a computer-readable medium bearing computer program code embodied therein for use with a computer. The computer program code can be code defining and / or implementing the present application. The computer program code can be written in any suitable computer readable programming language. The computer program code can be stored in a computer- readable storage medium, such as, but not limited to, any type of disk including an optical disk, a CD-ROM, a CD-R, a CD-RW, a DVD, a flash memory, a ROM, a RAM, a magnetic disk or hard drive, or any other suitable type of medium including a medium that holds the software for a particular or specialized computing purpose, or any suitable combination of media. The computer program product can be a computer program product distributed to end users, whether as a stand-alone program, as part of a physical system, or as a software download. The computer program product can be distributed on a physical medium, such as, but not limited to, a floppy disk, a CD-ROM, a CD-R, a CD-RW, a DVD, a flash memory, a ROM, a RAM, a magnetic disk or hard drive, or any other suitable type of medium, or any suitable combination of media. The computer program product can be distributed from a program distribution center, either as a tangible medium or via electronic delivery, such as from a Web site via the Internet, or from one computer to another via electronic transfer, such as by e-mail. The computer program product can be distributed in an encrypted manner, such as via encryption or via password protection.

[0110] Those skilled in the art will understand that the application described above and illustrated in the accompanying drawings is presented by way of example only and is not limiting as to the present application. The intent is to cover all modifications and alternatives of the present application falling within the scope of the application.

Claims

1. A fault detection and self-healing method for a multi-state fusion low-voltage intelligent switch, characterized in that, The method comprises: The low-voltage intelligent switch is arranged on the low-voltage line, the low-voltage circuit electrical parameter is monitored through the low-voltage intelligent switch, and the electrical parameter data before and after the low-voltage line fault is recorded; The data connection between the low-voltage intelligent switch and the fault monitoring APP is established, and the line electrical parameter is transmitted to the fault monitoring APP; The fault monitoring APP processes the received electrical parameter data and predicts the line fault, and positions the low-voltage intelligent switch according to the identification ID, so as to facilitate the fault elimination of the power maintenance personnel; The fault monitoring APP processes the received electrical parameter data and predicts the line fault, and positions the low-voltage intelligent switch according to the identification ID, so as to facilitate the fault elimination of the power maintenance personnel; The fault monitoring APP processes the received electrical parameter data and predicts the line fault, and positions the low-voltage intelligent switch according to the identification ID, so as to facilitate the fault elimination of the power maintenance personnel; The voltage characteristic value set and the current characteristic value set corresponding to the identification ID are respectively constituted by reading the voltage and current waveform data and the corresponding identification ID, extracting the voltage characteristic value and the current characteristic value. The current characteristic value includes one or more of the maximum current value, the minimum current value, the average current value and the current frequency. The voltage characteristic value includes one or more of the maximum voltage value, the minimum voltage value, the average voltage value and the voltage frequency. The elements in the voltage characteristic value set are input into the preset voltage monitoring model as input variables after preprocessing and normalization, and the voltage prediction value at a future time is output. The elements in the current characteristic value set are input into the preset current monitoring model as input variables after preprocessing and normalization, and the current prediction value at a future time is output. The voltage prediction value and the current prediction value are analyzed, the fault monitoring APP outputs a control instruction according to the analysis result, controls the opening and closing action of the low-voltage intelligent switch, and feeds back the state value of the low-voltage intelligent switch, the state value being 0 or 1. The elements in the voltage feature set are preprocessed and normalized, and combined with the identification ID to generate a voltage monitoring feature set corresponding to the identification ID: ; Let the voltage monitoring model be: wherein, is the intercept, represents the first regression coefficient, is the error term, ; respectively represent the maximum voltage value, the minimum voltage value, the average voltage value and the voltage frequency after preprocessing and normalization. Will The inputs are respectively fed into the voltage monitoring model, and the outputs are... This represents the predicted voltage value at a future time. The elements in the voltage characteristic value set are input into the preset voltage monitoring model as input variables after preprocessing and normalization, and the voltage prediction value at a future time is output. The elements in the current feature set are preprocessed and normalized, and combined with the identification ID to generate a current monitoring feature set corresponding to the identification ID: ; Let the current monitoring model be: wherein, is an intercept, represents the first regression coefficient, is the second regression coefficient, is an error term, ; Will The inputs are respectively fed into the voltage monitoring model, and the outputs are... This represents the predicted value of the current at a future time. The elements in the current characteristic value set are input into the preset current monitoring model as input variables after preprocessing and normalization, and the current prediction value at a future time is output. Set a voltage action threshold and a current action threshold ; The voltage prediction value and the current prediction value are analyzed, the fault monitoring APP outputs a control instruction according to the analysis result, controls the opening and closing action of the low-voltage intelligent switch, and feeds back the state value of the low-voltage intelligent switch, the state value being 0 or 1. If the state value is 1 and or The fault monitoring APP generates a disconnection control instruction, and sends the disconnection control instruction to the low-voltage intelligent switch corresponding to the identification ID. The main control chip in the low-voltage intelligent switch analyzes the disconnection control instruction and drives the on-off control module to execute the disconnection action; wherein, are respectively a voltage threshold correction variable and a current threshold correction variable. If the state value is 0 and and The fault monitoring APP generates a closing control instruction, and sends the closing control instruction to the low-voltage intelligent switch corresponding to the identification ID. The main control chip in the low-voltage intelligent switch drives the opening and closing control module after analyzing the opening control instruction, and executes the closing action. If the state value is 1 and and the judgment circuit is normal, and the fault monitoring APP does not send control instructions; If the state value is 0 and or , it is judged that the low-voltage intelligent switch has a fault of no normal feedback state value or no normal disconnection, and the fault monitoring APP generates a switch fault alarm information, wherein the switch fault alarm information includes an identification ID of the fault low-voltage intelligent switch. The state value of the low-voltage intelligent switch corresponding to the identification ID is obtained, the state value being 1 indicating that the corresponding low-voltage intelligent switch is in a closed state, and the state value being 0 indicating that the corresponding low-voltage intelligent switch is in an open state. The sampling frequency of the low-voltage intelligent switch electrical parameter data is set through the fault monitoring APP, and after the fault is eliminated, the line is actively recovered according to the automatically collected electrical parameter data. The sampling frequency of the low-voltage intelligent switch electrical parameter data is set through the fault monitoring APP, and after the fault is eliminated, the line is actively recovered according to the automatically collected electrical parameter data. The state value is obtained. It is judged whether the state value is 0. If the state value is 0, then: The fault monitoring APP calls the pre-stored f1 and f2, and sends f1 and f2 to the low-voltage intelligent switch; The master chip sends f1 and f2 to the wave recording chip, and the wave recording chip controls the voltage sampling circuit and the current sampling circuit to sample the line according to f1 and f2; A plurality of voltage values are obtained by a metering chip and current values , and fed back to a master control chip, which compares the collected voltage values and current values with preset normal current values and normal voltage values respectively; If and , the judging circuit judges that the current and voltage are normal, generates a closing instruction, and drives the open-close control module to perform a closing operation, wherein, and are a current correction constant and a voltage correction constant, respectively, , ; If the state value is 1, enter the step of acquiring the state value; The low-voltage intelligent switch comprises a main control module and a power module, a metering module, a communication module and a switching control module connected with the main control module; The fault monitoring APP stores an identification ID matched with each low-voltage intelligent switch, and the sampling frequency comprises a current sampling frequency f1 and a voltage sampling frequency f2.

2. The fault detection and self-healing method of a multi-state fusion low-voltage intelligent switch according to claim 1, characterized in that, The main control module comprises a main control chip and a touch control chip, a memory and a plurality of wave recording control chips connected with the main control chip; the metering module comprises a metering chip and a voltage sampling circuit and a current sampling circuit connected with the metering chip, and the wave recording control chip is used for controlling the voltage sampling circuit and the current sampling circuit to collect voltage and current data.

3. The fault detection and self-healing method of a multi-state fusion low-voltage intelligent switch according to claim 2, characterized in that, The low-voltage intelligent switch is used for monitoring electrical parameters of a low-voltage circuit and recording electrical parameter data before and after a low-voltage line fault, and comprises the following steps: Waveform data of voltage and current of the low-voltage circuit are collected by the voltage collection circuit and the current collection circuit; The metering chip processes the input voltage and current data to obtain current and voltage values; The wave recording control chip controls the collection time of the voltage collection circuit and the current collection circuit; the collection time comprises a collection start time point T1 and a collection end time point T2; The main control chip generates a RAM address corresponding to the identification ID according to the stored identification ID, and stores the collected current and voltage waveform data in a storage area corresponding to the RAM address in the memory.

4. The fault detection and self-healing method of a multi-state fusion low-voltage intelligent switch according to claim 3, characterized in that, The low-voltage intelligent switch is connected with the fault monitoring APP, and the circuit electrical parameters are transmitted to the fault monitoring APP, comprising the following steps: A data connection between the communication module and the fault monitoring APP is established through a preset communication protocol; The main control chip retrieves the collected voltage and current waveform data from the memory; The voltage and current waveform data and the corresponding identification ID are sent to the fault monitoring APP through the communication module.

5. An electronic device, comprising: The electronic device is used for executing the fault detection and self-recovery method of the multi-state fusion low-voltage intelligent switch according to any one of claims 1-4.

6. A computer readable storage medium characterized by, The computer readable storage medium stores a computer program, and the computer program is executed by the processor to realize the fault detection and self-recovery method of the multi-state fusion low-voltage intelligent switch according to any one of claims 1-4.

Images