A power consumption safety control method and system based on a current fingerprint recognition module

Abstract

The present invention discloses a method and system for power consumption safety control based on a current fingerprint recognition module, which relates to the technical field of power consumption safety control, and includes: obtaining power consumption device type data based on initial electrical signal data and a power consumption device recognition model, enabling the monitor to automatically identify the type of the power consumption device, and automatically configuring the parameters of the monitor according to the power consumption device type data, without the user adjusting the power consumption device monitor; obtaining the power consumption device quality index by calculating the mean value of the initial quality index of the power consumption device and the stable quality index of the power consumption device according to the real-time electrical signal data and the power consumption device quality evaluation model, reducing the influence caused by the unstable operation state of the power consumption device in the access line; obtaining system fault parameters based on the real-time electrical signal data and the real-time current fingerprint feature data, and enabling the user to more quickly and accurately find the faults of the power consumption device and the power consumption line through the system fault parameters.

Description

Technical Field

[0001] The present invention relates to the technical field of power consumption safety control, and specifically relates to a power consumption safety control method and system based on a current fingerprint recognition module. Background Art

[0002] With the development of technology, the types of electrical equipment are increasing and are deeply involved in each family, company, enterprise, etc. And with the process of intelligentization, the working modes of electrical equipment are also increasing. The working states of each electrical equipment are different, and even change continuously with the changes of environment and time, resulting in the continuous change of its current fingerprint.

[0003] When the existing power consumption safety control system is installed, it is necessary to dispatch special operation and maintenance personnel for installation and commissioning and pre-installation, and it is necessary to manually select the type of electrical equipment and configure it. However, users cannot flexibly adjust the electrical equipment during subsequent use, resulting in an increase in personnel costs and supervision costs. Therefore, it is necessary to provide a power consumption safety control method and system based on a current fingerprint recognition module to solve the above-mentioned problems. Summary of the Invention

[0004] To solve the above technical problems, the present technical solution solves the problem that when the existing power consumption safety control system is installed, it is necessary to dispatch special operation and maintenance personnel for installation and commissioning and pre-installation, and it is necessary to manually select the type of electrical equipment and configure it. However, users cannot flexibly adjust the electrical equipment during subsequent use, resulting in an increase in personnel costs and supervision costs as mentioned in the above background art.

[0005] To achieve the above purposes, the technical solution adopted by the present invention is as follows:

[0006] A power consumption safety control method based on a current fingerprint recognition module, comprising:

[0007] Collect initial electrical signal data;

[0008] Based on the initial electrical signal data, obtain electrical equipment type data and determine monitor calibration parameters;

[0009] Based on the monitor calibration parameters, calibrate and test the monitor to verify the accuracy and performance of the monitor;

[0010] Use the calibrated monitor to collect real-time electrical signal data;

[0011] According to the real-time electrical signal data, obtain the electrical equipment quality index;

[0012] Based on the analysis of the electrical equipment type, obtain the electrical equipment quality index threshold;

[0013] Judge whether the quality of the electrical equipment is qualified according to the quality index threshold of the electrical equipment. If not, send a warning message to the control center. If so, obtain the real-time current fingerprint feature data;

[0014] Obtain the system fault parameters based on the real-time electrical signal data and the real-time current fingerprint feature data;

[0015] Evaluate the operating state of the electrical equipment based on the system fault parameters, and obtain the system fault information;

[0016] Send the fault information to the control center based on the system fault information.

[0017] In an optional embodiment, based on the initial electrical signal data, obtain the electrical equipment type data and determine the monitor calibration parameters, specifically including:

[0018] Obtain the initial current characteristic information and the initial voltage characteristic information according to the initial electrical information data;

[0019] Obtain the initial electrical characteristic parameters based on the initial current characteristic information and the initial voltage characteristic information;

[0020] Input the initial electrical characteristic parameters into the electrical equipment identification model to obtain the electrical equipment type data;

[0021] Obtain the temperature coefficient and pressure parameters of the monitor;

[0022] Obtain the monitor calibration parameters based on the electrical equipment type data, the temperature coefficient and the pressure parameters;

[0023] Among them, the steps for obtaining the electrical equipment identification model are:

[0024] S201: Collect the electrical signal data of the electrical equipment;

[0025] S202: Extract the electrical equipment characteristic parameters according to the electrical signal data of the electrical equipment by using signal processing and data analysis techniques;

[0026] S203: Based on the machine learning method, input the extracted electrical equipment characteristic parameters into the classification model, and train the model to identify different types of electrical equipment;

[0027] S204: Optimize the trained classification model to obtain the electrical equipment identification model;

[0028] The calculation formula of the initial electrical characteristic parameters is:

[0029] ;

[0030] In the formula, Represents the initial electrical characteristic parameters of the electrical equipment, Represents the weight of the initial electrical characteristic parameters, Represents the Minimum current value of the electrical equipment at the th unit time node, Minimum voltage value of the electrical equipment at the th unit time node, Maximum current value of the electrical equipment at the th unit time node, Maximum voltage value of the electrical equipment at the Represents the total duration used for startup when the electrical equipment is first connected to the power line.

[0031] In an optional embodiment, according to the real-time electrical signal data, the quality index of the electrical equipment is obtained, which specifically includes:

[0032] Based on the real-time electrical signal data, the real-time current characteristic information and the real-time voltage characteristic information are obtained;

[0033] According to the real-time current characteristic information and the real-time voltage characteristic information, the real-time electrical characteristic parameters are obtained;

[0034] The real-time electrical characteristic parameters are input into the electrical equipment identification model to obtain the real-time electrical equipment type information;

[0035] According to the real-time electrical signal data and the real-time electrical equipment type information, the initial evaluation parameters of the electrical equipment are obtained;

[0036] The initial evaluation parameters of the electrical equipment are input into the electrical equipment quality evaluation model to obtain the initial quality index of the electrical equipment;

[0037] The stable electrical signal data of the electrical equipment is obtained;

[0038] Based on the stable electrical signal data of the electrical equipment, the stable current characteristic information and the stable voltage characteristic information are obtained;

[0039] Based on the stable current characteristic information and the stable voltage characteristic information, the stable evaluation parameters of the electrical equipment are obtained;

[0040] The stable evaluation parameters of the electrical equipment are input into the electrical equipment quality evaluation model to obtain the stable quality index of the electrical equipment;

[0041] Based on the initial quality index of the electrical equipment and the stable quality index of the electrical equipment, the quality index of the electrical equipment is obtained;

[0042] Among them, the obtaining steps of the electrical equipment quality evaluation model:

[0043] S401: Collect relevant electrical signal data and relevant quality assessment indices of different types of electrical equipment in the form of a time series using a monitor;

[0044] S402: Perform data preprocessing on the collected relevant electrical signal data and relevant quality assessment indices;

[0045] S402: Based on regression analysis techniques, establish a relationship model between the relevant electrical signal data and the relevant quality assessment indices;

[0046] S403: Extract the characteristic data from the relevant electrical signal data to obtain characteristic electrical signal data, and input the characteristic electrical signal data and the relevant quality assessment indices into the relationship model for training;

[0047] S404: Use the cross-validation method to evaluate the relationship model to obtain an electrical equipment quality assessment model;

[0048] The calculation formula for the initial evaluation parameters of the electrical equipment is as follows:

[0049] ;

[0050] In the formula, represents the initial evaluation parameters of the electrical equipment, represents the weight of the initial evaluation parameters of the electrical equipment, represents the th average power of the electrical equipment at the unit time node, represents the rated power of the electrical equipment, represents the total duration of startup after the electrical equipment is connected to the power circuit for a period of time;

[0051] The calculation formula for the stable evaluation parameters of the electrical equipment is as follows:

[0052] ;

[0053] In the formula, represents the stable evaluation parameters of the electrical equipment, represents the weight of the stable evaluation parameters of the electrical equipment, represents the average value of the fluctuating power when the electrical equipment is operating stably, represents the average power of the electrical equipment at the th unit time node after the electrical equipment operates stably, represents the rated power of the electrical equipment, represents the statistical duration.

[0054] In an alternative embodiment, based on the initial quality index of the electrical equipment and the stable quality index of the electrical equipment, obtain the quality index of the electrical equipment, specifically including:

[0055] Obtain the initial quality index and stable quality index of the electrical equipment for two electrical equipment connected to the power line in sequence.

[0056] Calculate the average value of the initial quality index and stable quality index of the a-th connected electrical equipment to obtain the first average value.

[0057] Calculate the average value of the initial quality index and stable quality index of the (a + 1)-th connected electrical equipment to obtain the second average value.

[0058] Connect the a-th electrical equipment and the (a + 1)-th electrical equipment to the power line at the same time, and respectively obtain the average values of the corresponding initial quality index and stable quality index of the electrical equipment to obtain the third average value and the fourth average value.

[0059] Based on the first average value, the second average value, the third average value and the fourth average value, obtain the electrical influence coefficient of the electrical equipment.

[0060] Based on the initial quality index of the electrical equipment, the stable quality index of the electrical equipment and the electrical influence coefficient of the electrical equipment, obtain the quality index of the electrical equipment.

[0061] Among them, the calculation formula for the quality index of the a-th electrical equipment is:

[0062] ;

[0063] In the formula, represents the quality index of the -th electrical equipment, represents the initial quality index of the -th electrical equipment when it is connected to the power line alone, represents the stable quality index of the -th electrical equipment when it is connected to the power line alone, represents the initial quality index of the -th electrical equipment when it is connected to the power line alone, represents the stable quality index of the -th electrical equipment when it is connected to the power line alone, represents the initial quality index of the -th electrical equipment when it is connected to the power line at the same time with the -th electrical equipment, represents the stable quality index of the -th electrical equipment when it is connected to the power line at the same time with the represents the -th electrical equipment when it is connected to the power line at the same time with the The initial quality index of electrical equipment when multiple electrical equipment are simultaneously connected to the electrical circuit Indicates the th electrical equipment and the th electrical equipment when they are simultaneously connected to the electrical circuit, the stable quality index of the electrical equipment

[0064] In an alternative embodiment, obtaining real-time current fingerprint feature data specifically includes:

[0065] Based on the electrical equipment type data output by the electrical equipment identification model, obtaining equipment combination information;

[0066] Based on the real-time current feature information and real-time voltage feature information, obtaining the load information and operating status information of different types of electrical equipment;

[0067] Combining the load information and operating status information of different types of electrical equipment with the equipment combination information to obtain real-time current fingerprint feature data.

[0068] In an alternative embodiment, based on the real-time electrical signal data and real-time current fingerprint feature data, obtaining system fault parameters specifically includes:

[0069] According to the real-time electrical signal data, obtaining the electrical circuit current information;

[0070] According to the electrical circuit current information, obtaining the total value of the electrical circuit current and the electrical circuit current index;

[0071] Based on the total value of the electrical circuit current, obtaining the electrical circuit current index threshold;

[0072] Based on the electrical circuit current index threshold, determining whether there is a leakage in the electrical circuit. If not, according to the real-time electrical signal data, obtaining the electrical circuit current information. If so, obtaining the electrical circuit leakage information;

[0073] Monitoring the load information and operating status information of different types of electrical equipment in the next operation cycle to obtain stable current fingerprint feature data;

[0074] Comparing the stable current fingerprint feature data with the real-time current fingerprint feature data to obtain the corresponding change information of different types of electrical equipment;

[0075] Based on the equipment combination information, the electrical circuit leakage information and the change information, obtaining system fault parameters.

[0076] Furthermore, a power consumption safety control system based on a current fingerprint recognition module is proposed for implementing the control method as described above, including:

[0077] A data acquisition module, which is used to collect initial electrical signal data, real-time electrical signal data and electrical signal data of electrical equipment, obtain the temperature coefficient and pressure parameters of the monitor, and collect relevant electrical signal data and relevant quality evaluation indexes of different types of electrical equipment by using the monitor in the form of time series;

[0078] A data processing module, which is used to extract characteristic parameters of electrical equipment according to the electrical signal data of electrical equipment by using signal processing and data analysis technologies, input the extracted characteristic parameters of electrical equipment into a classification model based on machine learning methods, train the model to identify different types of electrical equipment, obtain an electrical equipment identification model, establish a relationship model between relevant electrical signal data and relevant quality evaluation indexes based on regression analysis technology, extract characteristic data from relevant electrical signal data, obtain characteristic electrical signal data, and input the characteristic electrical signal data and relevant quality evaluation indexes into the relationship model for training to obtain an electrical equipment quality evaluation model, calibrate and test the monitor based on the monitor calibration parameters to verify the accuracy and performance of the monitor, judge whether the quality of the electrical equipment is qualified according to the electrical equipment quality index threshold, and judge whether there is a leakage in the electrical circuit based on the electrical circuit current index threshold;

[0079] A data transmission module, which is used to transmit the data obtained by the data acquisition module to the data processing module, and transmit the processed results in the data processing module to the display module;

[0080] A display module, which is used to display the training results of the electrical equipment identification model and the electrical equipment quality evaluation model, as well as display real-time electrical equipment type information, electrical equipment quality index and system fault information.

[0081] In an alternative embodiment, the data acquisition module includes:

[0082] A first acquisition unit, which is used to collect initial electrical signal data, real-time electrical signal data and electrical signal data of electrical equipment;

[0083] A second acquisition unit, which is used to obtain the temperature coefficient and pressure parameters of the monitor, and collect relevant electrical signal data and relevant quality evaluation indexes of different types of electrical equipment by using the monitor in the form of time series.

[0084] In an alternative embodiment, the data processing module includes:

[0085] A training unit, which is used to extract characteristic parameters of the electrical equipment according to the electrical signal data of the electrical equipment by using signal processing and data analysis techniques, input the extracted characteristic parameters of the electrical equipment into a classification model based on machine learning methods to train the model to identify different types of electrical equipment, obtain an electrical equipment identification model, establish a relationship model between relevant electrical signal data and relevant quality evaluation indexes based on regression analysis techniques, extract characteristic data from the relevant electrical signal data, obtain characteristic electrical signal data, and input the characteristic electrical signal data and relevant quality evaluation indexes into the relationship model for training to obtain an electrical equipment quality evaluation model;

[0086] An adjustment unit, which is used to calibrate and test the monitor based on the monitor calibration parameters to verify the accuracy and performance of the monitor;

[0087] A judgment unit, which is used to judge whether the quality of the electrical equipment is qualified according to the electrical equipment quality index threshold, and judge whether there is a leakage in the electrical circuit based on the electrical circuit current index threshold.

[0088] In an alternative embodiment, the display module includes:

[0089] A first display unit, which is used to display the training results of the electrical equipment identification model and the electrical equipment quality evaluation model;

[0090] A second display unit, which is used to display real-time electrical equipment type information, electrical equipment quality index and system fault information.

[0091] Compared with the prior art, the beneficial effects of the present invention are:

[0092] A method and system for electrical safety control based on a current fingerprint recognition module proposed by the present solution, based on the initial electrical signal data, uses the electrical equipment identification model to obtain electrical equipment type data, enables the monitor to automatically identify the type of the electrical equipment, and automatically configures the parameters of the monitor according to the electrical equipment type data, so that the user does not need to adjust the electrical equipment monitor during subsequent use. According to the real-time electrical signal data, uses the electrical equipment quality evaluation model to obtain the electrical equipment quality index, and obtains the electrical equipment quality index by calculating the average value of the initial quality index and the stable quality index of the electrical equipment, reducing the influence caused by the unstable operation state of the electrical equipment in the access line. Based on the real-time electrical signal data and real-time current fingerprint feature data, obtains system fault parameters, and through the system fault parameters, enables the user to find the faults of the electrical equipment and the electrical circuit more quickly and accurately. Description of the Drawings

[0093] Figure 1Flow chart of a power consumption safety control method based on a current fingerprint recognition module proposed by the present invention;

[0094] Figure 2 Flow chart for obtaining the quality index of electrical equipment in the present invention;

[0095] Figure 3 Flow chart for obtaining system fault parameters in the present invention;

[0096] Figure 4 System framework diagram of a power consumption safety control system based on a current fingerprint recognition module proposed by the present invention. Detailed implementation manners

[0097] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments in the following description are only examples, and those skilled in the art can think of other obvious variations.

[0098] Referring to Figure 1 - Figure 4 As shown, a power consumption safety control method based on a current fingerprint recognition module includes:

[0099] Collect initial electrical signal data;

[0100] Based on the initial electrical signal data, obtain electrical equipment type data and determine monitor calibration parameters;

[0101] Based on the monitor calibration parameters, calibrate and test the monitor to verify the accuracy and performance of the monitor;

[0102] Use the calibrated monitor to collect real-time electrical signal data;

[0103] According to the real-time electrical signal data, obtain the quality index of the electrical equipment;

[0104] Based on the analysis of the electrical equipment type, obtain the quality index threshold of the electrical equipment;

[0105] According to the quality index threshold of the electrical equipment, judge whether the quality of the electrical equipment is qualified. If not, send a warning message to the control center. If so, obtain the real-time current fingerprint feature data;

[0106] Based on the real-time electrical signal data and the real-time current fingerprint feature data, obtain system fault parameters;

[0107] Based on the system fault parameters, evaluate the operating state of the electrical equipment and obtain system fault information;

[0108] Based on the system fault information, send fault information to the control center.

[0109] Specifically, the initial electrical signal data is used to describe the electrical signals collected after the monitor is connected to the power line, including data such as the current, voltage, and power of the power line, as well as data such as the current, voltage, and power of the electrical equipment connected to the power circuit. The monitor calibration parameters are used to describe a set of parameters for adjusting or setting monitoring devices (such as power monitors, voltage monitors, etc.) to ensure their measurement accuracy and reliability. The real-time electrical signal data is used to describe the electrical signals collected after the monitor is connected to the power line and when determining the monitor calibration parameters according to the type of electrical equipment connected to the power line, including data such as the current, voltage, and power of the power line, as well as data such as the current, voltage, and power of the electrical equipment connected to the power circuit. The electrical equipment quality index is an indicator for measuring and evaluating the quality and reliability of different types of electrical equipment (such as motors, transformers, switchgear, etc.) connected to the power line.

[0110] Furthermore, based on the initial electrical signal data, electrical equipment type data is obtained, and the monitor calibration parameters are determined, specifically including:

[0111] According to the initial electrical information data, initial current characteristic information and initial voltage characteristic information are obtained;

[0112] Based on the initial current characteristic information and initial voltage characteristic information, initial electrical characteristic parameters are obtained;

[0113] The initial electrical characteristic parameters are input into the electrical equipment identification model to obtain electrical equipment type data;

[0114] The temperature coefficient and pressure parameters of the monitor are obtained;

[0115] Based on the electrical equipment type data, temperature coefficient, and pressure parameters, the monitor calibration parameters are obtained;

[0116] Among them, the steps for obtaining the electrical equipment identification model are:

[0117] S201: Collect the electrical signal data of the electrical equipment;

[0118] S202: According to the electrical signal data of the electrical equipment, use signal processing and data analysis techniques to extract the characteristic parameters of the electrical equipment;

[0119] S203: Based on the machine learning method, input the extracted characteristic parameters of the electrical equipment into the classification model, and train the model to identify different types of electrical equipment;

[0120] S204: Optimize the trained classification model to obtain the electrical equipment identification model;

[0121] The calculation formula for the initial electrical characteristic parameters is:

[0122] ;

[0123] Wherein, represents the initial electrical characteristic parameters of the electrical equipment, represents the weight of the initial electrical characteristic parameters, represents the minimum current value of the electrical equipment at the th unit time node, represents the th unit time node, minimum voltage value of the electrical equipment at the represents the th unit time node, maximum current value of the electrical equipment at the

[0124] Furthermore, according to the real-time electrical signal data, obtain the quality index of the electrical equipment, specifically including:

[0125] Based on the real-time electrical signal data, obtain the real-time current characteristic information and real-time voltage characteristic information;

[0126] According to the real-time current characteristic information and real-time voltage characteristic information, obtain the real-time electrical characteristic parameters;

[0127] Input the real-time electrical characteristic parameters into the electrical equipment identification model to obtain the real-time electrical equipment type information;

[0128] According to the real-time electrical signal data and real-time electrical equipment type information, obtain the initial evaluation parameters of the electrical equipment;

[0129] Input the initial evaluation parameters of the electrical equipment into the electrical equipment quality evaluation model to obtain the initial quality index of the electrical equipment;

[0130] Obtain the stable electrical signal data of the electrical equipment;

[0131] Based on the stable electrical signal data of the electrical equipment, obtain the stable current characteristic information and stable voltage characteristic information;

[0132] Based on the stable current characteristic information and stable voltage characteristic information, obtain the stable evaluation parameters of the electrical equipment;

[0133] Input the stable evaluation parameters of the electrical equipment into the electrical equipment quality evaluation model to obtain the stable quality index of the electrical equipment;

[0134] Based on the initial quality index of the electrical equipment and the stable quality index of the electrical equipment, obtain the quality index of the electrical equipment;

[0135] Among them, the steps for obtaining the electrical equipment quality evaluation model are as follows:

[0136] S401: In the form of a time series, use a monitor to collect relevant electrical signal data and relevant quality evaluation indices of different types of electrical equipment;

[0137] S402: Perform data preprocessing on the collected relevant electrical signal data and relevant quality evaluation indices;

[0138] S402: Based on regression analysis technology, establish a relationship model between the relevant electrical signal data and the relevant quality evaluation indices;

[0139] S403: Extract the characteristic data from the relevant electrical signal data to obtain characteristic electrical signal data, and input the characteristic electrical signal data and the relevant quality evaluation indices into the relationship model for training;

[0140] S404: Use the cross-validation method to evaluate the relationship model to obtain the electrical equipment quality evaluation model;

[0141] The calculation formula for the initial evaluation parameters of electrical equipment is:

[0142] ;

[0143] In the formula, represents the initial evaluation parameter of the electrical equipment, represents the weight of the initial evaluation parameter of the electrical equipment, represents the th average power of the electrical equipment at the unit time node, represents the rated power of the electrical equipment, represents the total duration of startup after the electrical equipment is connected to the electrical circuit for a period of time;

[0144] The calculation formula for the stable evaluation parameters of electrical equipment is:

[0145] ;

[0146] In the formula, represents the stable evaluation parameter of the electrical equipment, represents the weight of the stable evaluation parameter of the electrical equipment, represents the average value of the fluctuating power when the electrical equipment is operating stably, represents the th average power of the electrical equipment at the unit time node after the electrical equipment operates stably, represents the rated power of the electrical equipment, represents the statistical duration.

[0147] Specifically, when an electrical device is connected to an electrical circuit, due to the starting current impact and voltage fluctuation, the power supply voltage will drop instantaneously, affecting the normal operation of other devices, or triggering the protection device to cause a short power outage of the device, which will have a certain impact on the monitoring accuracy of the monitor. Therefore, the stable electrical signal data of the electrical device is the electrical data after the electrical device is connected to the electrical circuit and operates stably for a period of time after maintaining a certain state. The initial evaluation parameter of the electrical device is the comprehensive index of the electrical data generated when the electrical device is just connected to the electrical circuit, and the stable evaluation parameter of the electrical device is the comprehensive index of the electrical data after the electrical device maintains a certain state and operates stably for a period of time. represents the average value of the fluctuating power when the electrical device is operating stably. Inevitably, the electrical device will be affected by external factors during stable operation, resulting in fluctuations in the power spectrum diagram or waveform diagram generated by the monitor when monitoring the electrical device, so that the power represented by some unit time nodes is not on the waveform line. Therefore, is used to represent the error term.

[0148] It can be understood that based on the regression analysis technology, both the relevant electrical signal data and the relevant quality evaluation index in the relationship model established between the relevant electrical signal data and the relevant quality evaluation index are historical data. The relevant electrical signal data is the electrical signals generated by different types of electrical devices collected by the monitor, and the relevant quality evaluation index is the comprehensive index of the operating state of the electrical device itself when different types of electrical devices generate the relevant electrical signal data, including the output power of the electrical device, etc.

[0149] Furthermore, based on the initial quality index of the electrical device and the stable quality index of the electrical device, the quality index of the electrical device is obtained, specifically including:

[0150] Obtain the initial quality index of the electrical device and the stable quality index of the electrical device for two electrical devices connected to the electrical circuit in sequence;

[0151] Calculate the average value of the initial quality index of the a-th connected electrical device and the stable quality index of the electrical device to obtain the first average value;

[0152] Calculate the average value of the initial quality index of the (a + 1)-th connected electrical device and the stable quality index of the electrical device to obtain the second average value;

[0153] Connect the a-th electrical device and the (a + 1)-th electrical device to the electrical circuit at the same time, and respectively obtain the average values of the corresponding initial quality index of the electrical device and the stable quality index of the electrical device to obtain the third average value and the fourth average value;

[0154] Based on the first average value, the second average value, the third average value and the fourth average value, obtain the electrical influence coefficient of the electrical device;

[0155] Obtain the electrical equipment quality index based on the initial quality index of the electrical equipment, the stable quality index of the electrical equipment, and the electrical influence coefficient of the electrical equipment;

[0156] Among them, the calculation formula for the electrical equipment quality index of the a-th electrical equipment is:

[0157] ;

[0158] In the formula, represents the electrical equipment quality index of the -th electrical equipment, represents the initial quality index of the electrical equipment when the -th electrical equipment is separately connected to the electrical circuit, represents the stable quality index of the electrical equipment when the -th electrical equipment is separately connected to the electrical circuit, represents the initial quality index of the electrical equipment when the -th electrical equipment is separately connected to the electrical circuit, represents the stable quality index of the electrical equipment when the -th electrical equipment is separately connected to the electrical circuit, represents the initial quality index of the electrical equipment when the -th electrical equipment and the -th electrical equipment are simultaneously connected to the electrical circuit, represents the stable quality index of the electrical equipment when the -th electrical equipment and the -th electrical equipment are simultaneously connected to the electrical circuit, represents the initial quality index of the electrical equipment when the -th electrical equipment and the -th electrical equipment are simultaneously connected to the electrical circuit, represents the stable quality index of the electrical equipment when the -th electrical equipment and the -th electrical equipment are simultaneously connected to the electrical circuit.

[0159] It can be understood that is the initial quality index of the electrical equipment output by inputting the initial evaluation parameter of the -th electrical equipment into the electrical equipment quality evaluation model, is the stable quality index of the electrical equipment output by inputting the stable evaluation parameter of the -th electrical equipment into the electrical equipment quality evaluation model. The first mean, the second mean, the third mean, and the fourth mean are respectively expressed by the formulas 、 、 and , and the electrical influence coefficient of the electrical equipment is expressed by the formula .

[0160] Specifically, when the th electrical equipment is separately connected to the power line, the influence it receives is relatively small and can be ignored. Therefore, the quality index of the electrical equipment can be calculated separately. When the th and the +(1)th electrical equipment are simultaneously connected to the power line, since the total current and total voltage in the power line remain unchanged, the two electrical equipment will affect each other when connected to the power line, resulting in a decrease in the quality index of their respective electrical equipment, thus affecting the monitoring accuracy of the monitor. Therefore, it is necessary to consider the electrical influence coefficient between the two. The electrical influence coefficient of the electrical equipment is a comprehensive index of the mutual influence generated when the two equipment start simultaneously or within the same time period.

[0161] Furthermore, obtain real-time current fingerprint feature data, specifically including:

[0162] Based on the electrical equipment type data output by the electrical equipment identification model, obtain equipment combination information;

[0163] Based on the real-time current feature information and real-time voltage feature information, obtain the load information and operating status information of different types of electrical equipment;

[0164] Combine the load information and operating status information of different types of electrical equipment with the equipment combination information to obtain real-time current fingerprint feature data.

[0165] Furthermore, based on the real-time electrical signal data and real-time current fingerprint feature data, obtain system fault parameters, specifically including:

[0166] According to the real-time electrical signal data, obtain the power line current information;

[0167] According to the power line current information, obtain the total value of the current in the power consumption loop and the current index of the power consumption loop;

[0168] Based on the total value of the current in the power consumption loop, obtain the current index threshold of the power consumption loop;

[0169] Based on the current index threshold of the power consumption loop, determine whether there is a leakage in the power consumption loop. If not, according to the real-time electrical signal data, obtain the power line current information. If so, obtain the leakage information of the power consumption loop;

[0170] Monitor the load information and operating status information of different types of electrical equipment in the next operation cycle to obtain stable current fingerprint feature data;

[0171] Compare the steady - state current fingerprint feature data with the real - time current fingerprint feature data to obtain the change information corresponding to different types of electrical appliances.

[0172] Based on the equipment combination information, the leakage information of the power consumption circuit, and the change information, obtain the system fault parameters.

[0173] Specifically, the total current value of the power consumption circuit is the total current in the power consumption circuit. The power consumption circuit current index is the remaining current in the circuit after subtracting the sum of the real - time currents of the neutral line and the live line in the power consumption circuit from the total current value of the power consumption circuit. The power consumption circuit current index is used for trend analysis of the leakage situation in the power consumption circuit. The power consumption circuit current index threshold is generally set to 30 milliamperes. When the power consumption circuit current index exceeds the set threshold, a leakage alarm is triggered, and the leakage information of the power consumption circuit is obtained.

[0174] Furthermore, a power consumption safety control system based on a current fingerprint recognition module is proposed to implement the above control method, including:

[0175] A data acquisition module, which is used to collect initial electrical signal data, real - time electrical signal data, and electrical signal data of electrical appliances, obtain the temperature coefficient and pressure parameters of the monitor, and collect relevant electrical signal data and relevant quality evaluation indexes of different types of electrical appliances in the form of time series by using the monitor.

[0176] A data processing module, which is used to extract the characteristic parameters of electrical appliances according to the electrical signal data of electrical appliances by using signal processing and data analysis techniques. Based on machine learning methods, input the extracted characteristic parameters of electrical appliances into a classification model to train the model to identify different types of electrical appliances, obtain an electrical appliance identification model. Based on regression analysis techniques, establish a relationship model between relevant electrical signal data and relevant quality evaluation indexes, extract the characteristic data from the relevant electrical signal data, obtain characteristic electrical signal data, and input the characteristic electrical signal data and relevant quality evaluation indexes into the relationship model for training to obtain an electrical appliance quality evaluation model. Based on the monitor calibration parameters, calibrate and test the monitor to verify the accuracy and performance of the monitor. According to the electrical appliance quality index threshold, judge whether the quality of the electrical appliance is qualified. Based on the power consumption circuit current index threshold, judge whether there is a leakage in the power consumption circuit.

[0177] A data transmission module, which is used to transmit the data obtained by the data acquisition module to the data processing module, and transmit the processed results in the data processing module to the display module.

[0178] A display module, which is used to display the training results of the electrical appliance identification model and the electrical appliance quality evaluation model, as well as display the real - time electrical appliance type information, the electrical appliance quality index, and the system fault information.

[0179] Further, the data acquisition module includes:

[0180] The first acquisition unit is used to collect initial electrical signal data, real-time electrical signal data, and electrical signal data of electrical equipment;

[0181] The second acquisition unit is used to obtain the temperature coefficient and pressure parameters of the monitor, and in the form of a time series, use the monitor to collect relevant electrical signal data and relevant quality evaluation indexes of different types of electrical equipment.

[0182] Further, the data processing module includes:

[0183] The training unit is used to extract the characteristic parameters of electrical equipment according to the electrical signal data of electrical equipment, using signal processing and data analysis techniques. Based on machine learning methods, the extracted characteristic parameters of electrical equipment are input into a classification model to train the model to identify different types of electrical equipment, obtaining an electrical equipment identification model. Based on regression analysis techniques, a relationship model between relevant electrical signal data and relevant quality evaluation indexes is established, extracting characteristic data from the relevant electrical signal data, obtaining characteristic electrical signal data, and inputting the characteristic electrical signal data and relevant quality evaluation indexes into the relationship model for training to obtain an electrical equipment quality evaluation model;

[0184] The adjustment unit is used to calibrate and test the monitor based on the monitor calibration parameters to verify the accuracy and performance of the monitor;

[0185] The judgment unit is used to judge whether the quality of the electrical equipment is qualified according to the electrical equipment quality index threshold, and judge whether there is a leakage in the electrical circuit based on the electrical circuit current index threshold.

[0186] Further, the display module includes:

[0187] The first display unit is used to display the training results of the electrical equipment identification model and the electrical equipment quality evaluation model;

[0188] The second display unit is used to display real-time electrical equipment type information, electrical equipment quality index, and system fault information.

[0189] In summary, the advantages of the present invention are as follows: Through the initial electrical signal data, using the electrical equipment recognition model, the electrical equipment type data is obtained, enabling the monitor to automatically identify the type of electrical equipment, and automatically configuring the parameters of the monitor according to the electrical equipment type data. In subsequent use, there is no need for the user to adjust the electrical equipment monitor. According to the real-time electrical signal data, using the electrical equipment quality assessment model, the electrical equipment quality index is obtained. The electrical equipment quality index is obtained by calculating the average value of the initial quality index of the electrical equipment and the stable quality index of the electrical equipment, reducing the impact caused by the unstable operating state of the electrical equipment in the access line. Based on the real-time electrical signal data and the real-time current fingerprint feature data, the system fault parameters are obtained, and through the system fault parameters, the user can more quickly and accurately find the faults of the electrical equipment and the electrical circuit.

[0190] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art of this industry should understand that the present invention is not limited by the above embodiments. What is described in the above embodiments and the specification is only the principle of the present invention. Without departing from the spirit and scope of the present invention, the present invention will have various changes and improvements, and these changes and improvements all fall within the scope of the present invention claimed. The scope of protection required by the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for controlling electricity usage safety based on a current fingerprint recognition module, characterized in that, Including: Collecting initial electrical signal data; Based on the initial electrical signal data, obtaining initial current characteristic information and initial voltage characteristic information; Based on the initial current characteristic information and initial voltage characteristic information, obtaining initial electrical characteristic parameters; Inputting the initial electrical characteristic parameters into the electrical equipment identification model to obtain electrical equipment type data; Obtaining the temperature coefficient and pressure parameters of the monitor; Based on the electrical equipment type data, temperature coefficient and pressure parameters, determining the monitor calibration parameters; Based on the monitor calibration parameters, calibrating and testing the monitor to verify the accuracy and performance of the monitor; Using the calibrated monitor to collect real-time electrical signal data; According to the real-time electrical signal data, obtaining the electrical equipment quality index; Based on the analysis of the electrical equipment type, obtaining the electrical equipment quality index threshold; According to the electrical equipment quality index threshold, judging whether the quality of the electrical equipment is qualified. If not, sending a warning message to the control center. If so, obtaining real-time current fingerprint characteristic data; Based on the real-time electrical signal data and real-time current fingerprint characteristic data, obtaining system fault parameters; Based on the system fault parameters, evaluating the operating state of the electrical equipment to obtain system fault information; Based on the system fault information, sending fault information to the control center; Based on the initial quality index of the electrical equipment and the stable quality index of the electrical equipment, obtaining the electrical equipment quality index, specifically including: Obtaining the initial quality index of the electrical equipment and the stable quality index of the electrical equipment of two electrical equipment connected to the electrical circuit in sequence; Calculating the mean value of the initial quality index of the a-th connected electrical equipment and the stable quality index of the electrical equipment to obtain the first mean value; Calculating the mean value of the initial quality index of the (a + 1)-th connected electrical equipment and the stable quality index of the electrical equipment to obtain the second mean value; Connecting the a-th electrical equipment and the (a + 1)-th electrical equipment to the electrical circuit at the same time, and respectively obtaining the mean values of the corresponding initial quality index of the electrical equipment and the stable quality index of the electrical equipment to obtain the third mean value and the fourth mean value; Based on the first mean value, the second mean value, the third mean value and the fourth mean value, obtaining the electrical influence coefficient of the electrical equipment; Based on the initial quality index of the electrical equipment, the stable quality index of the electrical equipment and the electrical influence coefficient of the electrical equipment, obtaining the electrical equipment quality index; Wherein, the calculation formula of the electrical equipment quality index of the a-th electrical equipment is: ； Wherein, represents the electrical equipment quality index of the th electrical equipment, represents the initial quality index of the th electrical equipment when it is separately connected to the power line, represents the stable quality index of the th electrical equipment when it is separately connected to the power line, represents the initial quality index of the th electrical equipment when it is separately connected to the power line, represents the stable quality index of the th electrical equipment when it is separately connected to the power line, represents the initial quality index of the th electrical equipment and the th electrical equipment when they are simultaneously connected to the power line, represents the stable quality index of the th electrical equipment and the th electrical equipment when they are simultaneously connected to the power line, represents the initial quality index of the th electrical equipment and the th electrical equipment when they are simultaneously connected to the power line, represents the stable quality index of the th electrical equipment and the th electrical equipment when they are simultaneously connected to the power line.

2. The power consumption safety control method based on a current fingerprint recognition module according to claim 1, wherein The obtaining steps of the electrical equipment identification model are: S201: Collecting the electrical signal data of the electrical equipment; S202: According to the electrical signal data of the electrical equipment, using signal processing and data analysis techniques to extract the characteristic parameters of the electrical equipment; S203: Based on the machine learning method, inputting the extracted characteristic parameters of the electrical equipment into the classification model to train the model to identify different types of electrical equipment; S204: Optimizing the trained classification model to obtain the electrical equipment identification model; The calculation formula of the initial electrical characteristic parameters is: ； Wherein, represents the initial electrical characteristic parameters of the electrical equipment, represents the weight of the initial electrical characteristic parameters, represents the minimum current value of the electrical equipment at the th unit time node, represents the minimum voltage value of the electrical equipment at the th unit time node, represents the maximum current value of the electrical equipment at the th unit time node, represents the maximum voltage value of the electrical equipment at the th unit time node, represents the total startup duration when the electrical equipment is initially connected to the power line.

3. The power consumption safety control method based on a current fingerprint recognition module according to claim 1, characterized in that, According to the real-time electrical signal data, obtaining the electrical equipment quality index, specifically including: Based on the real-time electrical signal data, obtaining real-time current characteristic information and real-time voltage characteristic information; Obtain real-time electrical characteristic parameters according to real-time current characteristic information and real-time voltage characteristic information; Input the real-time electrical characteristic parameters into the electrical equipment identification model to obtain real-time electrical equipment type information; Obtain the initial evaluation parameters of the electrical equipment according to the real-time electrical signal data and the real-time electrical equipment type information; Input the initial evaluation parameters of the electrical equipment into the electrical equipment quality evaluation model to obtain the initial quality index of the electrical equipment; Obtain the stable electrical signal data of the electrical equipment; Based on the stable electrical signal data of the electrical equipment, obtain stable current characteristic information and stable voltage characteristic information; Based on the stable current characteristic information and the stable voltage characteristic information, obtain the stable evaluation parameters of the electrical equipment; Input the stable evaluation parameters of the electrical equipment into the electrical equipment quality evaluation model to obtain the stable quality index of the electrical equipment; Based on the initial quality index of the electrical equipment and the stable quality index of the electrical equipment, obtain the quality index of the electrical equipment; Among them, the obtaining steps of the electrical equipment quality evaluation model are as follows: S401: In the form of a time series, use a monitor to collect relevant electrical signal data and relevant quality evaluation indexes of different types of electrical equipment; S402: Perform data preprocessing on the collected relevant electrical signal data and relevant quality evaluation indexes; S402: Based on regression analysis technology, establish a relationship model between the relevant electrical signal data and the relevant quality evaluation indexes; S403: Extract the characteristic data from the relevant electrical signal data to obtain characteristic electrical signal data, and input the characteristic electrical signal data and the relevant quality evaluation indexes into the relationship model for training; S404: Use the cross-validation method to evaluate the relationship model to obtain the electrical equipment quality evaluation model; The calculation formula for the initial evaluation parameters of the electrical equipment is: ； In the formula, represents the initial evaluation parameter of the electrical equipment, represents the weight of the initial evaluation parameter of the electrical equipment, represents the average power of the electrical equipment at the nth unit time node, represents the total duration of startup after the electrical equipment is connected to the electrical circuit for a period of time; The calculation formula for the stable evaluation parameters of the electrical equipment is: ； Wherein, represents the stable evaluation parameter of the electrical equipment, represents the weight of the stable evaluation parameter of the electrical equipment, represents the mean value of the fluctuating power when the electrical equipment operates stably, represents the average power at the th unit time node after the electrical equipment operates stably, represents the rated power of the electrical equipment, represents the statistical duration.

4. A power consumption safety control method based on a current fingerprint recognition module according to claim 1, characterized in that Obtain real-time current fingerprint characteristic data, specifically including: Based on the electrical equipment type data output by the electrical equipment identification model, obtain equipment combination information; Based on the real-time current characteristic information and the real-time voltage characteristic information, obtain the load information and operating status information of different types of electrical equipment; Combine the load information and operating status information of different types of electrical equipment with the equipment combination information to obtain real-time current fingerprint characteristic data.

5. The power consumption safety control method based on a current fingerprint recognition module according to claim 1, characterized in that Based on the real-time electrical signal data and the real-time current fingerprint characteristic data, obtain system fault parameters, specifically including: According to the real-time electrical signal data, obtain the current information of the electrical circuit; According to the current information of the electrical circuit, obtain the total current value of the electrical circuit and the current index of the electrical circuit; Based on the total current value of the electrical circuit, obtain the current index threshold of the electrical circuit; Based on the current index threshold of the electrical circuit, judge whether there is electric leakage in the electrical circuit. If not, obtain the current information of the electrical circuit according to the real-time electrical signal data. If so, obtain the electric leakage information of the electrical circuit; Monitor the load information and operating status information of different types of electrical equipment in the next operation cycle to obtain stable current fingerprint characteristic data; Compare the stable current fingerprint characteristic data with the real-time current fingerprint characteristic data to obtain the corresponding change information of different types of electrical equipment; Obtain system fault parameters based on device combination information, power consumption loop leakage information, and change information.

6. An electricity consumption safety control system based on a current fingerprint recognition module for implementing the control method according to any one of claims 1-5, characterized in that, Including: A data acquisition module, which is used to collect initial electrical signal data, real-time electrical signal data, and electrical signal data of electrical equipment, obtain the temperature coefficient and pressure parameters of the monitor, and in the form of time series, use the monitor to collect relevant electrical signal data and relevant quality evaluation indexes of different types of electrical equipment; A data processing module, which is used to extract characteristic parameters of electrical equipment according to the electrical signal data of electrical equipment, using signal processing and data analysis techniques. Based on machine learning methods, input the extracted characteristic parameters of electrical equipment into a classification model, train the model to identify different types of electrical equipment, and obtain an electrical equipment identification model. Based on regression analysis techniques, establish a relationship model between relevant electrical signal data and relevant quality evaluation indexes, extract characteristic data from the relevant electrical signal data, obtain characteristic electrical signal data, and input the characteristic electrical signal data and relevant quality evaluation indexes into the relationship model for training to obtain an electrical equipment quality evaluation model. Based on the monitor calibration parameters, calibrate and test the monitor to verify the accuracy and performance of the monitor. According to the electrical equipment quality index threshold, judge whether the quality of the electrical equipment is qualified. Based on the power consumption loop current index threshold, judge whether there is leakage in the power consumption loop; A data transmission module, which is used to transmit the data obtained by the data acquisition module to the data processing module, and transmit the processed results in the data processing module to the display module; A display module, which is used to display the training results of the electrical equipment identification model and the electrical equipment quality evaluation model, as well as display real-time electrical equipment type information, electrical equipment quality index, and system fault information.

7. An electricity consumption safety control system based on a current fingerprint recognition module according to claim 6, characterized in that The data acquisition module includes: A first acquisition unit, which is used to collect initial electrical signal data, real-time electrical signal data, and electrical signal data of electrical equipment; A second acquisition unit, which is used to obtain the temperature coefficient and pressure parameters of the monitor, and in the form of time series, use the monitor to collect relevant electrical signal data and relevant quality evaluation indexes of different types of electrical equipment.

8. The power consumption safety control system based on a current fingerprint recognition module according to claim 6, wherein The data processing module includes: A training unit, which is used to extract characteristic parameters of electrical equipment according to the electrical signal data of electrical equipment, using signal processing and data analysis techniques. Based on machine learning methods, input the extracted characteristic parameters of electrical equipment into a classification model, train the model to identify different types of electrical equipment, and obtain an electrical equipment identification model. Based on regression analysis techniques, establish a relationship model between relevant electrical signal data and relevant quality evaluation indexes, extract characteristic data from the relevant electrical signal data, obtain characteristic electrical signal data, and input the characteristic electrical signal data and relevant quality evaluation indexes into the relationship model for training to obtain an electrical equipment quality evaluation model; An adjustment unit, which is used to calibrate and test the monitor based on the monitor calibration parameters to verify the accuracy and performance of the monitor; A judgment unit, which is used to judge whether the quality of the electrical equipment is qualified according to the electrical equipment quality index threshold, and judge whether there is a leakage in the electrical circuit based on the electrical circuit current index threshold.

9. The power consumption safety control system based on a current fingerprint recognition module according to claim 6, characterized in that The display module includes: A first display unit, which is used to display the training results of the electrical equipment identification model and the electrical equipment quality evaluation model; A second display unit, which is used to display the real-time electrical equipment type information, the electrical equipment quality index and the system fault information.

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