Electric energy metering box with temperature monitoring function and monitoring method

Abstract

The present invention relates to the technical field of electric fault monitoring, and in particular to an electric energy meter box with a temperature monitoring function and a monitoring method. Firstly, the relative abnormality of temperature is determined according to the characteristic that the corresponding temperature monitoring delay requirement should be shorter when the electric energy meter box is in an abnormal overheating condition at a terminal; further, the heat dissipation stability is determined according to the characteristic that when the heat dissipation of the electric energy meter box is relatively stable, the possibility of a large temperature fluctuation is small, so that the temperature monitoring delay requirement is shorter; further, the radiator temperature control capability value is determined according to the characteristic that when the temperature control capability of the radiator of the electric energy meter box is strong, the possibility of a normal temperature fluctuation exceeding a temperature threshold is small, so the temperature monitoring delay requirement should be shorter; finally, the temperature monitoring delay weight is comprehensively determined by combining the relative abnormality of temperature, the heat dissipation stability and the radiator temperature control capability value, so that the accuracy of temperature abnormality monitoring of the electric energy meter box according to the temperature monitoring delay weight is higher.

Description

Technical Field

[0001] The invention relates to the technical field of electric fault monitoring, and in particular to an electric energy metering box with a temperature monitoring function and a monitoring method. Background Art

[0002] In field applications, the wiring terminals of the energy meter box may overheat, causing the meter to burn or even cause a fire, because the wiring terminals and the wires are connected by bolts and hard pressure contact. There is contact resistance at the bolt connection of the wiring terminals, and the contact resistance at the overlap of the wiring terminals is not only related to the material, but even when different currents flow through the wiring terminals, the contact resistance value will be different. The contact resistance of the wiring terminals is related to the material. Different materials have different resistivities and their corresponding contact resistances are different. Because there are many uneven contact points on the contact surface area between the wiring terminals and the conductors, there are many gaps when the conductors contact the wiring terminals. When the current flows through the contact surface between the conductors and the wiring terminals, the current will gather to these contacts, causing the conductive channel to narrow and the contact resistance to increase. Therefore, overload use of the wiring terminals, installation quality, aging of the wiring terminals and long-term poor contact will cause the contact resistance to increase, generate a lot of heat, cause the terminals to overheat and fail, and cause the meter to burn or even a fire.

[0003] Therefore, it is necessary to monitor in real time whether the electric energy meter box has terminal overheating failure to prevent the meter from burning or fire. When the electric energy meter box has terminal overheating, a large amount of heat will be generated, causing the internal temperature of the electric energy meter box to be abnormally high. Therefore, the abnormal temperature inside the electric energy meter box can be detected by setting a temperature threshold, thereby monitoring the abnormal overheating of the electric energy meter box terminals. However, considering that during the daily use of the electricity meter box, normal temperature fluctuations that are not caused by terminal overheating may occur, causing the detected temperature to exceed the temperature threshold, but the normal temperature fluctuations will end after a period of time, causing the internal temperature of the electricity meter box to drop below the temperature threshold; so in order to more accurately monitor the internal temperature of the electricity meter box, the prior art usually sets a temperature monitoring delay, and issues an early warning after the internal temperature of the electricity meter box exceeds the temperature threshold for a period longer than the preset temperature monitoring delay, so as to avoid false alarms; however, the a priori temperature monitoring delay set in the prior art is a fixed duration, but the temperature monitoring delay required in different implementation environments is usually different. For example, in implementation environments with different radiator heat dissipation capacities and different stability conditions of the temperature data of the electricity meter box, the required monitoring delay usually needs to be longer or shorter, and setting a fixed temperature monitoring delay cannot adapt to temperature anomaly monitoring in different implementation environments, which reduces the detection accuracy of the internal temperature of the electricity meter box, and even causes false alarms or late alarms, resulting in low monitoring accuracy of the temperature anomaly monitoring of the electricity meter box. Summary of the invention

[0004] The present application provides an electric energy meter box with temperature monitoring function and a monitoring method. First, according to the characteristic that the temperature monitoring delay requirement corresponding to the overheating abnormality of the terminal of the electric energy meter box should be shorter, the relative abnormality of the temperature is determined according to the overall deviation and fluctuation of the terminal temperature data of each terminal; further, when the heat dissipation of the electric energy meter box is relatively stable, the possibility of large temperature fluctuations is small, which makes the temperature monitoring delay requirement shorter. According to the characteristic, the heat dissipation stability is determined according to the real-time power of the radiator, the stability of the temperature data in the box, and the relative deviation of the temperature data inside and outside the box; further, when the temperature control ability of the radiator of the electric energy meter box is strong, the normal temperature fluctuation The possibility of exceeding the temperature threshold is small, so the temperature monitoring delay requirement should be shorter. According to the matching delay between the temperature change in the box and the radiator power change, as well as the radiator power, the radiator temperature control capability value is determined; finally, the temperature monitoring delay weight is comprehensively determined based on the relative temperature abnormality, the heat dissipation stability and the radiator temperature control capability value, which solves the problem that the fixed temperature monitoring delay set in the prior art cannot adapt to temperature anomaly monitoring in different implementation environments, resulting in reduced detection accuracy of the internal temperature of the electric energy metering box, and even false alarms or late alarms, so that the accuracy of temperature anomaly monitoring of the electric energy metering box according to the temperature monitoring delay weight is higher.

[0005] The first aspect of the present application provides a method for monitoring an electric energy meter box with a temperature monitoring function, comprising:

[0006] At each sampling moment during the operation of the electric energy meter box, the internal temperature, external temperature, real-time power of the radiator and terminal temperature data of each wiring terminal corresponding to the electric energy meter box are collected;

[0007] According to the overall deviation of the terminal temperature data of each terminal and the fluctuation of the time series change, the relative abnormal degree of the temperature at each sampling moment is determined;

[0008] Based on the real-time power of the radiator of the electric energy metering box and the stability of the temperature data inside the box, the heat dissipation stability at each sampling moment is determined in combination with the relative deviation of the temperature data inside and outside the box in the historical data;

[0009] Determine the radiator temperature control capability value at each sampling moment according to the matching delay between the temperature change in the box and the radiator power change corresponding to each sampling moment and the real-time power of the radiator;

[0010] The temperature monitoring delay weight is determined according to the relative abnormality of the temperature, the heat dissipation stability and the temperature control capability value of the radiator; and the temperature abnormality monitoring of the electric energy metering box is performed according to the temperature monitoring delay weight.

[0011] Furthermore, the process of obtaining the relative abnormal degree of temperature includes:

[0012] In the time sequence, each sampling moment and the time period corresponding to the preset number of sampling moments before are taken as the local time period corresponding to each sampling moment;

[0013] The average value of the terminal temperature data of all sampling moments in the local time period corresponding to each sampling moment of each wiring terminal is used as the terminal temperature reference value of each wiring terminal at each sampling moment; the average value of the terminal temperature reference values ​​of all wiring terminals at each sampling moment is used as the terminal temperature standard value corresponding to each sampling moment; the difference between the terminal temperature reference value and the terminal temperature standard value is used as the terminal temperature standard deviation of each wiring terminal at each sampling moment;

[0014] The difference between the terminal temperature data of each terminal at each sampling moment and the terminal temperature data at the previous sampling moment is taken as the terminal temperature change value of each terminal at each sampling moment; the average of the terminal temperature change values ​​of each terminal at all sampling moments in the local time period corresponding to each sampling moment is taken as the terminal temperature change rate of each terminal at each sampling moment;

[0015] Determining the abnormal degree of terminal temperature of each terminal at each sampling moment according to the terminal temperature standard deviation and the terminal temperature change rate; wherein the terminal temperature standard deviation and the terminal temperature change rate are both positively correlated with the abnormal degree of terminal temperature;

[0016] The minimum value of the terminal temperature abnormality of all terminals at each sampling moment is taken as the relative temperature abnormality at each sampling moment.

[0017] Furthermore, the process of obtaining the abnormal degree of the terminal temperature includes:

[0018] The product of the terminal temperature standard deviation and the terminal temperature change rate is normalized to determine the abnormal degree of the terminal temperature of each terminal at each sampling time.

[0019] Furthermore, the process of obtaining the heat dissipation stability includes:

[0020] In terms of time sequence, the time period of the electric energy meter box with a preset time length before each sampling moment is used as the historical time period of each sampling moment;

[0021] Negative correlation mapping is performed on the variance of the box temperature at all sampling moments in the historical time period of each sampling moment to determine the stability of the box temperature data at each sampling moment;

[0022] Determine the reference temperature inside the box at each sampling moment according to the average of the temperatures inside the box at all sampling moments in the historical time period of each sampling moment; determine the reference temperature outside the box at each sampling moment according to the average of the temperatures inside the box at all sampling moments in the historical time period of each sampling moment; determine the temperature deviation inside and outside the box at each sampling moment according to the difference between the reference temperature inside the box and the reference temperature outside the box;

[0023] The heat dissipation stability at each sampling moment is determined according to the real-time power of the radiator, the stability of the temperature data inside the box, and the temperature deviation inside and outside the box at each sampling moment; the real-time power of the radiator is negatively correlated with the heat dissipation stability, and the stability of the temperature data inside the box and the temperature deviation inside and outside the box are positively correlated with the heat dissipation stability.

[0024] Furthermore, the process of determining the heat dissipation stability at each sampling moment according to the real-time power of the radiator at each sampling moment, the stability of the temperature data in the box, and the temperature deviation between the inside and outside of the box includes:

[0025] The product of the negative correlation mapping value of the real-time power of the radiator, the stability of the temperature data in the box and the real-time power of the radiator is normalized to determine the heat dissipation stability of the electric energy metering box at each sampling moment.

[0026] Furthermore, the process of obtaining the radiator temperature control capability value includes:

[0027] Arrange the in-box temperatures of all sampling moments in the historical time period of each sampling moment in time order to determine the in-box temperature data sequence of each sampling moment; arrange the real-time powers of the radiators of all sampling moments in the historical time period of each sampling moment in time order to determine the radiator power data sequence of each sampling moment; perform dynamic time regularization matching on the in-box temperature data sequence and the radiator power data sequence to determine the in-box temperature data that matches each radiator power data in the radiator power data sequence in the in-box temperature data sequence;

[0028] In the time sequence, the time difference between each radiator power data and the corresponding matched in-box temperature data in the radiator power data sequence is used as the heat dissipation effective local delay corresponding to each radiator power data; the average of the heat dissipation effective local delays corresponding to all radiator power data in the radiator power data sequence is used as the heat dissipation effective delay reference value corresponding to each sampling moment;

[0029] The ratio between the real-time power of the radiator at each sampling moment and the rated power of the radiator is used as the heat dissipation power saturation degree at each sampling moment;

[0030] The radiator temperature control capability value at each sampling moment is determined according to the heat dissipation effective delay reference value and the heat dissipation power saturation degree; the heat dissipation effective delay reference value and the heat dissipation power saturation degree are both negatively correlated with the radiator temperature control capability value.

[0031] Furthermore, the process of determining the radiator temperature control capability value at each sampling moment according to the heat dissipation effectiveness delay reference value and the heat dissipation power saturation degree includes:

[0032] The product of the heat dissipation effective delay reference value and the heat dissipation power saturation degree is negatively normalized to determine the heat sink temperature control capability value at each sampling moment.

[0033] Furthermore, the process of acquiring the temperature monitoring delay weight includes:

[0034] The product of the relative temperature abnormality, the heat dissipation stability and the radiator temperature control capability value is negatively normalized to determine the temperature monitoring delay weight at each sampling moment.

[0035] Furthermore, the process of performing temperature anomaly monitoring of the electric energy meter box according to the temperature monitoring delay weight includes:

[0036] The product of the positive correlation mapping value of the temperature monitoring delay weight and the prior temperature monitoring delay is used as the corrected temperature monitoring delay at each sampling moment; and real-time temperature anomaly monitoring is performed according to the corrected temperature monitoring delay.

[0037] The present application also proposes an electric energy meter box with a temperature monitoring function, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements any one of the steps of a method for monitoring an electric energy meter box with a temperature monitoring function.

[0038] This application has the following beneficial effects:

[0039] Normal temperature fluctuations will return to normal temperature state after a period of time. When the wiring terminals of the electricity meter box overheat abnormally, the temperature will continue to rise, causing the meter to burn or even cause a fire. Therefore, it is necessary to determine whether it is a normal temperature fluctuation or an overheating abnormality. For normal temperature fluctuations, the temperature monitoring delay needs to be extended to prevent false alarms. For overheating abnormalities, the temperature monitoring delay needs to be shortened to prevent late alarms.

[0040] First, the temperature abnormality characteristics of each terminal are analyzed, and the relative temperature abnormality is determined according to the overall deviation and fluctuation of the terminal temperature data of each terminal. The more abnormal the temperature characteristics of each terminal are, the more likely it is that the terminal will overheat abnormally, and the corresponding temperature monitoring delay should be smaller. Therefore, the relative temperature abnormality is negatively correlated with the temperature monitoring delay.

[0041] By further analyzing the stability of the heat dissipation of the electricity meter box, on the basis of the real-time power of the radiator of the electricity meter box and the stability of the temperature data inside the box, combined with the relative deviation of the temperature data inside and outside the box in the historical data, the heat dissipation stability at each sampling moment is determined; if the heat dissipation of the electricity meter box is relatively stable in the historical time period, it means that the heat dissipation demand is small, and the corresponding possibility of temperature fluctuations under normal circumstances is small, so it is also necessary to shorten the temperature monitoring delay, that is, the heat dissipation stability is negatively correlated with the temperature monitoring delay.

[0042] Further, by analyzing the temperature control capability of the radiator of the electric energy meter box, the temperature control capability value of the radiator at each sampling moment is determined according to the matching delay between the temperature change in the box and the power change of the radiator corresponding to each sampling moment and the real-time power of the radiator, so that the temperature control capability value of the radiator is obtained. When the temperature control capability of the radiator of the electric energy meter box is strong, normal temperature fluctuations are usually suppressed faster, so the frequency and duration of normal temperature fluctuations are reduced, so it is also necessary to shorten the temperature monitoring delay, so the temperature control capability value of the radiator is negatively correlated with the temperature monitoring delay.

[0043] Finally, the temperature monitoring delay weight is determined comprehensively based on the relative temperature abnormality, the heat dissipation stability and the temperature control capability value of the radiator. This solves the problem that the fixed temperature monitoring delay set in the prior art cannot adapt to temperature abnormality monitoring in different implementation environments, which reduces the detection accuracy of the internal temperature of the electric energy meter box and even causes false alarms or late alarms. This makes the temperature abnormality monitoring of the electric energy meter box based on the temperature monitoring delay weight more accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0045] Figure 1 A flow chart of a method for monitoring an electric energy meter box with a temperature monitoring function provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0046] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following is a detailed description of the specific implementation method, structure, characteristics and effects of an electric energy meter box and a monitoring method with a temperature monitoring function proposed by the present invention, in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment, and the specific features, structures or characteristics in one or more embodiments may be combined in any suitable form. In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as implying or suggesting relative importance or implicitly indicating the number of technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features.

[0047] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0048] The specific scheme of an electric energy metering box with temperature monitoring function and a monitoring method provided by the present invention is described in detail below with reference to the accompanying drawings.

[0049] The present application embodiment provides a method for monitoring an electric energy meter box with a temperature monitoring function. Figure 1 , which shows a flow chart of a method for monitoring an electric energy meter box with a temperature monitoring function provided by an embodiment of the present invention, the method comprising:

[0050] Step S101: at each sampling time during the operation of the electric energy meter box, the internal temperature, the external temperature, the real-time power of the radiator and the terminal temperature data of each wiring terminal corresponding to the electric energy meter box are collected.

[0051] In the prior art, the patent document with the publication number CN109616913A discloses a multifunctional electric energy meter box. In the embodiment of the present invention, the processing is performed on the basis of the patent document with the publication number CN109616913A disclosing a multifunctional electric energy meter box. At each sampling moment, the corresponding temperature sensor 14 is used to collect the box temperature corresponding to the electric energy meter box, and a temperature sensor is installed on the outer surface of the box of the electric energy meter box to collect the box temperature outside; the power of the cooling fan 11 is measured by a power analyzer and used as the real-time power of the radiator; a temperature sensor is installed on each terminal inside the electric energy meter box to collect the terminal temperature data of each terminal. In a specific implementation of the embodiment of the present invention, the sampling frequency is set to collect once every 30 seconds, that is, the time interval between two adjacent sampling moments is set to 30 seconds, and the sampling frequency can be adjusted according to the specific implementation environment.

[0052] Step S102: Determine the relative abnormality of the temperature at each sampling moment according to the overall deviation of the terminal temperature data of each connection terminal and the fluctuation of the time series variation.

[0053] Normal temperature fluctuations will return to normal temperature state after a period of time. When the wiring terminals of the electricity meter box overheat abnormally, the temperature will continue to rise, causing the meter to burn or even cause a fire. Therefore, it is necessary to determine whether it is a normal temperature fluctuation or an overheating abnormality. For normal temperature fluctuations, the temperature monitoring delay needs to be extended to prevent false alarms. For overheating abnormalities, the temperature monitoring delay needs to be shortened to prevent late alarms.

[0054] First, the temperature abnormality characteristics of each terminal are analyzed, and the relative temperature abnormality is determined according to the overall deviation and fluctuation of the terminal temperature data of each terminal. The more abnormal the temperature characteristics of each terminal are, the more likely it is that the terminal will overheat abnormally, and the corresponding temperature monitoring delay should be smaller. Therefore, the relative temperature abnormality is negatively correlated with the temperature monitoring delay.

[0055] Preferably, in some possible implementations of the embodiments of the present invention, the process of obtaining the relative abnormality degree of temperature includes:

[0056] In the time sequence, each sampling moment and the time period corresponding to the previous preset number of sampling moments are used as the local time period corresponding to each sampling moment. In a specific implementation of the embodiment of the present invention, the preset number is set to 9, that is, in the time sequence, the continuous time period including each sampling moment and the previous 9 sampling moments is used as the local time period, which can be adjusted according to the specific implementation environment.

[0057] The mean value of the terminal temperature data of all sampling moments in the local time period corresponding to each sampling moment of each terminal is taken as the terminal temperature reference value of each terminal at each sampling moment; the mean value of the terminal temperature reference values ​​of all terminal blocks at each sampling moment is taken as the terminal temperature standard value corresponding to each sampling moment; the difference between the terminal temperature reference value and the terminal temperature standard value is taken as the terminal temperature standard deviation of each terminal block at each sampling moment. The terminal temperature reference value is measured by the mean value of the terminal temperature data at all sampling moments in the local time period to reduce the influence of contingency. When the electric energy meter box is operating normally, the temperature difference of each terminal block inside should be small, so the terminal temperature reference value of each terminal block should be close to the terminal temperature standard value under normal circumstances; therefore, the larger the terminal temperature standard deviation obtained by the difference between the terminal temperature reference value and the terminal temperature standard value, the more likely the terminal block is to be abnormal, and the more likely the terminal block is to have abnormal operation.

[0058] In a specific implementation of the embodiment of the present invention, the process of obtaining the terminal temperature standard deviation is expressed by the formula: ;in, For the At the sampling time The terminal temperature standard deviation of each terminal block; For the The number of sampling moments in the local time period corresponding to the sampling moment; For the At the sampling time The terminal temperature reference value of the first terminal, that is, The terminal block is in The mean value of the terminal temperature data at all sampling moments in the local time period corresponding to the sampling moment; For the At the sampling time The terminal temperature reference value of the first terminal, that is, The terminal block is in The mean value of the terminal temperature data at all sampling moments in the local time period corresponding to the sampling moment; For the The terminal temperature standard value at each sampling moment; is the absolute value symbol.

[0059] The difference between the terminal temperature data of each terminal at each sampling moment and the terminal temperature data at the previous sampling moment is taken as the terminal temperature change value of each terminal at each sampling moment; the average of the terminal temperature change values ​​of each terminal at all sampling moments in the local time period corresponding to each sampling moment is taken as the terminal temperature change rate of each terminal at each sampling moment. When the electric energy meter box is operating normally, the terminal temperature of the terminal usually remains stable or shows a stable and slow linear change, and the corresponding temperature change rate is usually slow; therefore, the larger the average of the terminal temperature change values ​​of each terminal at all sampling moments in the local time period corresponding to each sampling moment, that is, the larger the terminal temperature change rate, the more likely the terminal is to have an abnormal operation at the corresponding sampling moment.

[0060] In a specific implementation of the embodiment of the present invention, the process of obtaining the terminal temperature change rate is expressed by the formula: ;in, For the At the sampling time The terminal temperature change rate of each terminal; For the The number of sampling moments in the local time period corresponding to the sampling moment; For the The terminal block is in The local time period corresponding to the sampling moment Terminal temperature data at each sampling moment; For the The terminal block is in The local time period corresponding to the sampling moment The terminal temperature data at the sampling time before the sampling time; For the The terminal block is in The terminal temperature change value at each sampling moment; for the first sampling moment, since there is no previous sampling moment, the corresponding terminal temperature change value is set to 0, so that the embodiment is more complete.

[0061] According to the terminal temperature standard deviation and the terminal temperature change rate, the terminal temperature abnormality degree of each terminal at each sampling moment is determined; since the larger the terminal temperature standard deviation and the larger the terminal temperature change rate, the more likely the corresponding terminal is to have abnormal operation, that is, abnormal terminal temperature, so the terminal temperature standard deviation and the terminal temperature change rate are both positively correlated with the terminal temperature abnormality degree. Preferably, in some possible implementations of the embodiments of the present invention, the process of obtaining the terminal temperature abnormality degree includes:

[0062] The product of the terminal temperature standard deviation and the terminal temperature change rate is normalized to determine the terminal temperature abnormality of each terminal at each sampling moment. The terminal temperature standard deviation and the terminal temperature change rate are positively correlated and normalized by multiplication, so that the value of the terminal temperature abnormality is limited to 0 to 1, making the temperature abnormality characterization of the terminal more intuitive. In a specific implementation of an embodiment of the present invention, the process of obtaining the terminal temperature abnormality is expressed by the formula: ;in, For the At the sampling time The abnormal degree of terminal temperature of each terminal; For the At the sampling time The terminal temperature change rate of each terminal; For the At the sampling time The terminal temperature standard deviation of each terminal block; It is a linear normalization function, and the implementer can adjust the normalization method according to the specific implementation environment. It should be noted that in addition to the normalized value of the product, the implementer can also calculate the degree of terminal temperature abnormality through other methods according to the correlation, such as the normalized value of the mean or the sum, etc., which will not be further elaborated here.

[0063] Finally, considering that as long as there is an abnormal operation or temperature abnormality in one terminal in the electricity meter box, the terminal will overheat and fail, the minimum value of the terminal temperature abnormality of all terminals at each sampling moment is further used as the relative temperature abnormality at each sampling moment. The greater the relative temperature abnormality, the greater the possibility of overheating abnormality, and the corresponding temperature monitoring delay should be smaller.

[0064] Step S103: Based on the real-time power of the radiator of the electric energy metering box and the stability of the temperature data inside the box, the heat dissipation stability at each sampling moment is determined in combination with the relative deviation of the temperature data inside and outside the box in the historical data.

[0065] By further analyzing the stability of the heat dissipation of the electricity meter box, on the basis of the real-time power of the radiator of the electricity meter box and the stability of the temperature data inside the box, combined with the relative deviation of the temperature data inside and outside the box in the historical data, the heat dissipation stability at each sampling moment is determined; if the heat dissipation of the electricity meter box is relatively stable in the historical time period, it means that the heat dissipation demand is small, and the corresponding possibility of temperature fluctuations under normal circumstances is small, so it is also necessary to shorten the temperature monitoring delay, that is, the heat dissipation stability is negatively correlated with the temperature monitoring delay.

[0066] Preferably, in some possible implementations of the embodiments of the present invention, the process of obtaining the heat dissipation stability includes:

[0067] In the time sequence, the time period of the electric energy meter box before each sampling moment is set as the historical time period of each sampling moment. In a specific implementation of the embodiment of the present invention, the preset time length is set to one hour, which can be adjusted according to the specific implementation environment.

[0068] The variance of the box temperature at all sampling moments in the historical time period of each sampling moment is negatively correlated and mapped to determine the stability of the box temperature data at each sampling moment; the larger the variance, the stronger the volatility of the box temperature in the historical time period. Therefore, the greater the stability of the box temperature data obtained by negatively correlating the variance, the more stable the temperature of the electric energy metering box is in the historical time period, and the possibility of temperature fluctuation under normal circumstances is small, which indirectly reflects that the corresponding heat dissipation effect is better and the heat dissipation is more stable.

[0069] According to the average of the box temperature at all sampling moments in the historical time period of each sampling moment, the reference box temperature at each sampling moment is determined; according to the average of the box temperature at all sampling moments in the historical time period of each sampling moment, the reference box temperature outside is determined at each sampling moment; according to the difference between the reference box temperature and the reference box temperature outside, the box temperature deviation at each sampling moment is determined. According to the principle of heat dissipation, the smaller the temperature difference between the inside and outside of the electric energy metering box, the worse the heat dissipation effect, and the more unstable the corresponding heat dissipation; therefore, when the temperature deviation between the inside and outside of the box is larger, the heat dissipation effect is better and the heat dissipation is more stable.

[0070] For the real-time power of the radiator at each sampling moment, the greater the real-time power of the radiator, the smaller the demand for heat dissipation, the smaller the possibility of large temperature fluctuations at this time, and the more stable the corresponding heat dissipation; on this basis, combined with the characteristics that the greater the temperature deviation inside and outside the box, the greater the stability of the temperature data inside the box, the more stable the heat dissipation, the heat dissipation stability at each sampling moment is determined according to the real-time power of the radiator at each sampling moment, the stability of the temperature data inside the box and the temperature deviation inside and outside the box; and the real-time power of the radiator is negatively correlated with the heat dissipation stability, and the stability of the temperature data inside the box and the temperature deviation inside and outside the box are positively correlated with the heat dissipation stability.

[0071] Preferably, according to the real-time power of the radiator at each sampling moment, the stability of the temperature data in the box, and the temperature deviation between the inside and outside of the box, the process of determining the heat dissipation stability at each sampling moment includes:

[0072] The product of the negative correlation mapping value of the radiator's real-time power, the stability of the temperature data inside the box and the real-time power of the radiator is normalized to determine the heat dissipation stability of the energy metering box at each sampling moment. Normalization can limit the value of the heat dissipation stability to within 0 to 1, making the characterization of the heat dissipation stability more intuitive.

[0073] In a specific implementation of the embodiment of the present invention, the process of obtaining the heat dissipation stability is expressed by the formula: ;in, For the The heat dissipation stability at each sampling moment; For the The variance of the temperature inside the box at all sampling moments in the historical time period of sampling moments; For the Stability of the temperature data in the box at each sampling moment; is an exponential function with a natural constant as base; For the The temperature in the reference box at the sampling time, that is, The average value of the temperature inside the box at all sampling moments in the historical time period of sampling moments; For the The reference temperature outside the box at the sampling time, that is, The average value of the temperature outside the box at all sampling moments in the historical time period of the sampling moment; For the The temperature deviation inside and outside the box at the sampling time, and in order to make the calculation result more objective in the embodiment of the present invention, When the corresponding value is less than or equal to 0, the temperature deviation inside and outside the box is replaced by a constant of 0.01 to participate in the calculation of heat dissipation stability; For the The real-time power of the radiator at the sampling moment; It is a preset adjustment parameter, which is set to 0.01 in the embodiment of the present invention to prevent the denominator from being 0, and can be adjusted according to the specific implementation environment; It is a linear normalization function, and the implementer can adjust the normalization method according to the specific implementation environment. It should be noted that in addition to the normalized value of the product, the implementer can also calculate the heat dissipation stability through other methods according to the correlation, such as the normalized value of the mean or the sum, etc., which will not be further elaborated here.

[0074] Step S104: Determine the radiator temperature control capability value at each sampling moment according to the matching delay between the temperature change in the box and the radiator power change corresponding to each sampling moment and the real-time power of the radiator.

[0075] By further analyzing the temperature control capability of the radiator of the electric energy meter box, the temperature control capability value of the radiator at each sampling moment is determined according to the matching delay between the temperature change in the box and the power change of the radiator and the real-time power of the radiator at each sampling moment, so that the temperature control capability value of the radiator is obtained. When the temperature control capability of the radiator of the electric energy meter box is strong, normal temperature fluctuations are usually suppressed faster, so the frequency and duration of normal temperature fluctuations are reduced, so it is also necessary to shorten the temperature monitoring delay, so the temperature control capability value of the radiator is negatively correlated with the temperature monitoring delay.

[0076] Preferably, in some possible implementations of the embodiments of the present invention, the process of obtaining the radiator temperature control capability value includes:

[0077] Arrange the in-box temperatures of all sampling moments in the historical time period of each sampling moment in time order to determine the in-box temperature data sequence of each sampling moment; arrange the real-time powers of the radiators of all sampling moments in the historical time period of each sampling moment in time order to determine the radiator power data sequence of each sampling moment; dynamically time warp the in-box temperature data sequence and the radiator power data sequence to determine the in-box temperature data that matches each radiator power data in the radiator power data sequence in the in-box temperature data sequence. It should be noted that dynamic time warping (DTW) is a technical means well known to those skilled in the art and will not be further limited or elaborated on here.

[0078] Taking into account that there is usually a certain delay in the power change of the radiator, after dynamic time warping matching, each radiator power data is affected or associated with its matching box temperature data, and the smaller the time difference between the two, the smaller the radiator effective delay and the stronger the corresponding regulation ability; therefore, further in the time sequence, the time difference between each radiator power data and the corresponding matching box temperature data in the radiator power data sequence is used as the heat dissipation effective local delay corresponding to each radiator power data; the average of the heat dissipation effective local delays corresponding to all radiator power data in the radiator power data sequence is used as the heat dissipation effective delay reference value corresponding to each sampling moment; the smaller the heat dissipation effective delay reference value, the smaller the corresponding heat dissipation effective delay and the stronger the corresponding radiator temperature regulation ability.

[0079] The ratio of the real-time power of the radiator at each sampling moment to the rated power of the radiator is taken as the saturation degree of the heat dissipation power at each sampling moment; the smaller the real-time power of the radiator is compared to the rated power of the radiator, the larger the power control space of the radiator is, and the stronger the corresponding temperature control capability is; therefore, the smaller the power saturation degree of the radiator is, the stronger the corresponding temperature control capability of the radiator is.

[0080] Furthermore, based on the characteristics that the smaller the heat dissipation effective delay reference value and the smaller the heat dissipation power saturation degree, the corresponding heat dissipation temperature control capability is stronger, the heat dissipation temperature control capability value at each sampling moment is determined according to the heat dissipation effective delay reference value and the heat dissipation power saturation degree; the heat dissipation effective delay reference value and the heat dissipation power saturation degree are negatively correlated with the heat dissipation temperature control capability value.

[0081] Preferably, in some possible implementations of the embodiments of the present invention, the process of determining the radiator temperature control capability value at each sampling moment according to the heat dissipation effectiveness delay reference value and the heat dissipation power saturation degree includes:

[0082] The product of the heat dissipation effective delay reference value and the heat dissipation power saturation degree is negatively normalized to determine the heat sink temperature control capability value at each sampling moment. Through normalization, the heat sink temperature control capability value can be limited to 0 to 1, making the representation of the heat sink temperature control capability more intuitive.

[0083] In a specific implementation of the embodiment of the present invention, the process of obtaining the radiator temperature control capability value is expressed by the formula: ;in, For the The radiator temperature control capability value at each sampling moment; For the The real-time power of the radiator at the sampling moment; is the rated power of the radiator of the electric energy meter box; For the The number of radiator power data in the radiator power data sequence at the sampling moment; For the The first sampling moment in the radiator power data series The time difference between the power data of the first radiator and the corresponding temperature data in the box, i.e. The first sampling moment in the radiator power data series The local delay of heat dissipation effectiveness corresponding to the power data of the first radiator, that is, The first sampling moment in the radiator power data series The time difference is obtained by subtracting the time corresponding to the radiator power data from the time corresponding to the matched box temperature data; For the The reference value of heat dissipation effective delay corresponding to each sampling moment; is a linear normalization function, and the implementer can adjust the normalization method according to the specific implementation environment. It should be noted that in addition to the product, the implementer can also calculate the radiator temperature control capability value through other methods according to the correlation, such as the mean, sum, etc., which will not be further elaborated here.

[0084] Step S105: Determine the temperature monitoring delay weight according to the relative abnormality of temperature, the heat dissipation stability and the radiator temperature control capability value; and perform temperature abnormality monitoring of the electric energy metering box according to the temperature monitoring delay weight.

[0085] Finally, the temperature monitoring delay weight is determined comprehensively based on the relative temperature abnormality, heat dissipation stability and radiator temperature control capability value. This solves the problem that the fixed temperature monitoring delay set in the prior art cannot adapt to temperature anomaly monitoring in different implementation environments, resulting in reduced detection accuracy of the internal temperature of the electric energy meter box, and even false alarms or late alarms. This makes the temperature anomaly monitoring of the electric energy meter box based on the temperature monitoring delay weight more accurate.

[0086] Preferably, in some possible implementations of the embodiments of the present invention, the process of acquiring the temperature monitoring delay weight includes:

[0087] Since the relative abnormality of temperature, the heat dissipation stability and the radiator temperature control capability value are all negatively correlated with the temperature monitoring delay, the product of the relative abnormality of temperature, the heat dissipation stability and the radiator temperature control capability value is further normalized to negative correlation, and the temperature monitoring delay weight at each sampling moment is determined, so that the larger the temperature monitoring delay weight, the longer the temperature monitoring delay at the corresponding sampling moment. In a specific implementation of an embodiment of the present invention, the process of obtaining the temperature monitoring delay weight is expressed by the formula: ;in, For the Temperature monitoring delay weight at each sampling moment; For the The radiator temperature control capability value at each sampling moment; For the The heat dissipation stability at each sampling moment; For the The relative abnormality of temperature at each sampling moment; is a linear normalization function. The implementer can adjust the normalization method according to the specific implementation environment. The implementer can adopt other negative correlation mapping methods according to the specific implementation environment, such as the inverse of the exponential function with a natural constant as the base, and the reciprocal, where is a hyperbolic tangent function, which will not be further described here.

[0088] Preferably, in some possible implementations of the embodiments of the present invention, the process of performing temperature anomaly monitoring of the electric energy meter box according to the temperature monitoring delay weight includes:

[0089] The product of the positive correlation mapping value of the temperature monitoring delay weight and the prior temperature monitoring delay is used as the corrected temperature monitoring delay at each sampling moment. In a specific implementation of an embodiment of the present invention, the prior temperature monitoring delay is set to 3 seconds, which can be adjusted according to the specific implementation environment. In a specific implementation of an embodiment of the present invention, the acquisition process of the corrected temperature monitoring delay is expressed by the formula: ;in, For the Corrected temperature monitoring delay at each sampling moment; Delay for a priori temperature monitoring; For the Temperature monitoring delay weight at each sampling moment; In order to preset the positive correlation mapping parameter, the embodiment of the present invention is set to 0.53, that is, when the temperature monitoring delay weight is greater than 0.47, the temperature monitoring delay is extended relative to the priori temperature monitoring delay at the corresponding sampling time; when the temperature monitoring delay weight is less than 0.47, the temperature monitoring delay is shortened relative to the priori temperature monitoring delay at the corresponding sampling time; when the temperature monitoring delay weight is equal to 0.47, the priori temperature monitoring delay is used as the corrected temperature monitoring delay for real-time temperature anomaly monitoring.

[0090] Finally, real-time temperature anomaly monitoring is performed according to the corrected temperature monitoring delay. Specifically, the time period from each sampling moment to the next sampling moment is used as the determination time period for each sampling moment. In the determination time period, when the temperature inside the box corresponding to the electric energy meter box is greater than the preset temperature threshold for a continuous period exceeding the corrected temperature monitoring delay of the corresponding sampling moment, a temperature anomaly alarm is issued; otherwise, no temperature anomaly alarm is issued. In a specific implementation of an embodiment of the present invention, the preset temperature threshold is set to 120 degrees Celsius, which can be adjusted according to the specific implementation environment.

[0091] To summarize, the present application first determines the relative abnormality of temperature based on the characteristic that the corresponding temperature monitoring delay requirement should be shorter when the terminal of the electric energy meter box is in an abnormal overheating situation, and according to the overall deviation and fluctuation of the terminal temperature data of each terminal; further, based on the characteristic that when the heat dissipation of the electric energy meter box is relatively stable, the possibility of large temperature fluctuations is small, which makes the temperature monitoring delay requirement shorter, and determines the heat dissipation stability according to the real-time power of the radiator, the stability of the temperature data inside the box, and the relative deviation of the temperature data inside and outside the box; further, when the temperature control ability of the radiator of the electric energy meter box is strong, the possibility of normal temperature fluctuations exceeding the temperature threshold is determined. The temperature monitoring delay requirement should be shorter due to the smaller temperature. The radiator temperature control capability value is determined according to the matching delay between the temperature change in the box and the radiator power change, as well as the radiator power. Finally, the temperature monitoring delay weight is determined comprehensively based on the relative temperature abnormality, the heat dissipation stability and the radiator temperature control capability value. This solves the problem that the fixed temperature monitoring delay set in the prior art cannot adapt to temperature anomaly monitoring in different implementation environments, which reduces the detection accuracy of the internal temperature of the electric energy metering box and even causes false alarms or late alarms. This makes the temperature anomaly monitoring of the electric energy metering box according to the temperature monitoring delay weight more accurate.

[0092] The present application also proposes an electric energy meter box with a temperature monitoring function, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements any one of the steps of a method for monitoring an electric energy meter box with a temperature monitoring function.

[0093] It should be noted that the sequence of the above embodiments of the present invention is only for description and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0094] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

Claims

1. A method for monitoring an electric energy meter box with a temperature monitoring function, characterized in that: The method comprises: At each sampling moment during the operation of the electric energy meter box, collect the box temperature, box temperature, radiator real-time power and terminal temperature data of each wiring terminal corresponding to the electric energy meter box; According to the overall deviation of the terminal temperature data of each terminal and the fluctuation of the time series change, the relative abnormal degree of the temperature at each sampling moment is determined; Based on the real-time power of the radiator of the electric energy metering box and the stability of the temperature data inside the box, the heat dissipation stability at each sampling moment is determined in combination with the relative deviation of the temperature data inside and outside the box in the historical data; Determine the radiator temperature control capability value at each sampling moment according to the matching delay between the temperature change in the box and the radiator power change corresponding to each sampling moment and the real-time power of the radiator; Determine the temperature monitoring delay weight according to the relative abnormality of the temperature, the heat dissipation stability and the temperature control capability value of the radiator; perform temperature abnormality monitoring of the electric energy metering box according to the temperature monitoring delay weight; The process of obtaining the relative abnormal degree of temperature includes: In the time sequence, each sampling moment and the time period corresponding to the preset number of sampling moments before are taken as the local time period corresponding to each sampling moment; The average value of the terminal temperature data of all sampling moments in the local time period corresponding to each sampling moment of each wiring terminal is used as the terminal temperature reference value of each wiring terminal at each sampling moment; the average value of the terminal temperature reference values ​​of all wiring terminals at each sampling moment is used as the terminal temperature standard value corresponding to each sampling moment; the difference between the terminal temperature reference value and the terminal temperature standard value is used as the terminal temperature standard deviation of each wiring terminal at each sampling moment; The difference between the terminal temperature data of each terminal at each sampling moment and the terminal temperature data at the previous sampling moment is taken as the terminal temperature change value of each terminal at each sampling moment; the average of the terminal temperature change values ​​of each terminal at all sampling moments in the local time period corresponding to each sampling moment is taken as the terminal temperature change rate of each terminal at each sampling moment; Determining the abnormal degree of terminal temperature of each terminal at each sampling moment according to the terminal temperature standard deviation and the terminal temperature change rate; wherein the terminal temperature standard deviation and the terminal temperature change rate are both positively correlated with the abnormal degree of terminal temperature; The minimum value of the abnormal degree of terminal temperature of all terminals at each sampling moment is taken as the relative abnormal degree of temperature at each sampling moment; The process of performing temperature anomaly monitoring of the electric energy meter box according to the temperature monitoring delay weight includes: The product of the positive correlation mapping value of the temperature monitoring delay weight and the prior temperature monitoring delay is used as the corrected temperature monitoring delay at each sampling moment; and real-time temperature anomaly monitoring is performed according to the corrected temperature monitoring delay.

2. The method for monitoring an electric energy meter box with a temperature monitoring function according to claim 1, characterized in that: The process of obtaining the abnormal degree of the terminal temperature includes: The product of the terminal temperature standard deviation and the terminal temperature change rate is normalized to determine the abnormal degree of the terminal temperature of each terminal at each sampling time.

3. The method for monitoring an electric energy meter box with a temperature monitoring function according to claim 1, characterized in that: The process of obtaining the heat dissipation stability includes: In terms of time sequence, the time period of the electric energy meter box with a preset time length before each sampling moment is used as the historical time period of each sampling moment; Negative correlation mapping is performed on the variance of the box temperature at all sampling moments in the historical time period of each sampling moment to determine the stability of the box temperature data at each sampling moment; Determine the reference temperature inside the box at each sampling moment according to the average of the temperatures inside the box at all sampling moments in the historical time period of each sampling moment; determine the reference temperature outside the box at each sampling moment according to the average of the temperatures inside the box at all sampling moments in the historical time period of each sampling moment; determine the temperature deviation inside and outside the box at each sampling moment according to the difference between the reference temperature inside the box and the reference temperature outside the box; The heat dissipation stability at each sampling moment is determined according to the real-time power of the radiator, the stability of the temperature data inside the box, and the temperature deviation inside and outside the box at each sampling moment; the real-time power of the radiator is negatively correlated with the heat dissipation stability, and the stability of the temperature data inside the box and the temperature deviation inside and outside the box are positively correlated with the heat dissipation stability.

4. The method for monitoring an electric energy meter box with a temperature monitoring function according to claim 3 is characterized in that: The process of determining the heat dissipation stability at each sampling moment according to the real-time power of the radiator at each sampling moment, the stability of the temperature data in the box, and the temperature deviation between the inside and outside of the box includes: The product of the negative correlation mapping value of the real-time power of the radiator, the stability of the temperature data in the box and the real-time power of the radiator is normalized to determine the heat dissipation stability of the electric energy metering box at each sampling moment.

5. The method for monitoring an electric energy meter box with a temperature monitoring function according to claim 3, characterized in that: The process of obtaining the radiator temperature control capability value includes: Arrange the in-box temperatures of all sampling moments in the historical time period of each sampling moment in time order to determine the in-box temperature data sequence of each sampling moment; arrange the real-time powers of the radiators of all sampling moments in the historical time period of each sampling moment in time order to determine the radiator power data sequence of each sampling moment; perform dynamic time regularization matching on the in-box temperature data sequence and the radiator power data sequence to determine the in-box temperature data that matches each radiator power data in the radiator power data sequence in the in-box temperature data sequence; In the time sequence, the time difference between each radiator power data and the corresponding matched in-box temperature data in the radiator power data sequence is used as the heat dissipation effective local delay corresponding to each radiator power data; the average of the heat dissipation effective local delays corresponding to all radiator power data in the radiator power data sequence is used as the heat dissipation effective delay reference value corresponding to each sampling moment; The ratio between the real-time power of the radiator at each sampling moment and the rated power of the radiator is used as the heat dissipation power saturation degree at each sampling moment; The radiator temperature control capability value at each sampling moment is determined according to the heat dissipation effective delay reference value and the heat dissipation power saturation degree; the heat dissipation effective delay reference value and the heat dissipation power saturation degree are both negatively correlated with the radiator temperature control capability value.

6. The method for monitoring an electric energy meter box with a temperature monitoring function according to claim 5, characterized in that: The process of determining the radiator temperature control capability value at each sampling moment according to the heat dissipation effectiveness delay reference value and the heat dissipation power saturation degree includes: The product of the heat dissipation effective delay reference value and the heat dissipation power saturation degree is negatively normalized to determine the heat sink temperature control capability value at each sampling moment.

7. The method for monitoring an electric energy meter box with a temperature monitoring function according to claim 1, characterized in that: The process of obtaining the temperature monitoring delay weight includes: The product of the relative temperature abnormality, the heat dissipation stability and the radiator temperature control capability value is negatively normalized to determine the temperature monitoring delay weight at each sampling moment.

8. An electric energy metering box with temperature monitoring function, characterized in that: It includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of a method for monitoring an electric energy meter box with a temperature monitoring function as described in any one of claims 1 to 7 when executing the computer program.

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