A method and device for monitoring the status of smart metering boxes using multi-sensor fusion

Abstract

This application discloses a method and apparatus for monitoring the status of smart meters using multi-sensor fusion. The method divides multiple smart meters into multiple distance groups based on the distance relationships between their location information. It further divides these distance groups into multiple temporary energy consumption groups based on the magnitude relationships between energy consumption information within a preset time period. The method receives temperature information sent by communication modules within the temporary energy consumption groups to the communication modules of the multiple smart meters within the preset time period, and determines whether a temperature anomaly has occurred based on the differences between the multiple temperature information. In the multi-sensor fusion smart meter status monitoring method and apparatus provided by this invention, if the energy consumption of the smart meters in the temporary energy consumption groups is similar, then the self-heating of the multiple smart meters in the temporary energy consumption groups is similar. Therefore, the temperature differences between different smart meters in the temporary energy consumption groups reflect whether the temperature of a single smart meter is normal.

Description

Technical Field

[0001] This invention relates to the field of intelligent metering box control methods, and in particular to an intelligent metering box status monitoring method and device that integrates multiple sensors. Background Technology

[0002] In existing technologies, electricity metering boxes, as crucial equipment at the end of low-voltage power distribution systems, undertake multiple functions including electricity metering, power distribution, and operational status monitoring, and are widely deployed in residential communities, commercial buildings, and industrial plants. With the current rapid evolution of power grids towards intelligence and automation, the limitations of traditional metering boxes in terms of operational safety, real-time monitoring, and intelligent response are becoming increasingly prominent, making it difficult to meet the practical needs of increasingly complex power environments for fault early warning and data linkage. Most existing systems lack comprehensive perception capabilities of operational status and cannot achieve rapid response to fluctuations in the box's environment and electrical parameters, as well as physical intrusion behaviors, easily leading to fault propagation or amplification of safety hazards. Therefore, constructing a fusion monitoring system integrating multiple sensors to improve the real-time perception and linkage processing capabilities of metering box operational status has become a core direction for the development of intelligent power distribution terminals. Researching monitoring instruments with edge computing capabilities and multi-source information fusion functions has significant technical value and practical significance for realizing intelligent diagnosis and proactive protection of power distribution systems.

[0003] Currently, data from multiple sensors is only collected, with little fusion, thus hindering efficient and accurate monitoring. Summary of the Invention

[0004] The main objective of this invention is to provide a method and device for monitoring the status of smart metering boxes using multi-sensor fusion, aiming to solve the problem that current smart metering boxes have limited data fusion processing from multiple sensors, making efficient and accurate monitoring impossible.

[0005] To achieve the above objectives, the present invention provides a method for monitoring the status of a smart metering box using multi-sensor fusion. The smart metering box is equipped with a communication module, a positioning module, a temperature sensor, and a current transformer. The method for monitoring the status of the smart metering box includes:

[0006] S1. Receive location information sent by the communication modules in the multiple smart metering boxes, wherein the location information is obtained by the positioning module and transmitted to the communication module;

[0007] S2. Divide the multiple smart metering boxes into multiple distance groups according to the distance relationship between the location information;

[0008] S3. Receive energy consumption information sent by the communication modules of multiple smart metering boxes in the distance group, wherein the energy consumption information is obtained by the current transformer and transmitted to the communication module;

[0009] S4. Divide the distance grouping into multiple temporary energy consumption groups according to the magnitude relationship between energy consumption information within a preset time length.

[0010] S5. Receive temperature information sent by the communication modules of multiple smart metering boxes within a preset time period in the temporary energy consumption group, and determine whether a temperature abnormality has occurred based on the differences between the multiple temperature information. The temperature information is obtained by the temperature sensor and transmitted to the communication module.

[0011] In one embodiment, a height sensor is also installed in the smart metering box;

[0012] Step S1 further includes:

[0013] The system receives height information sent by the communication modules of multiple smart metering boxes, wherein the height information is obtained by the height sensor and transmitted to the communication module.

[0014] Step S2 includes:

[0015] The multiple smart metering boxes are divided into multiple distance groups based on the distance between their location and altitude information.

[0016] In one embodiment, a vibration sensor is also installed in the smart metering box, and step S2 is followed by:

[0017] When the vibration information of the smart metering box in the distance group exceeds the preset vibration threshold;

[0018] Based on the vibration information of multiple sets of smart metering boxes corresponding to multiple distance groups within the second preset time length, it is determined to be a single abnormality or a regional abnormality.

[0019] In one embodiment, the smart metering box is also equipped with a processing module;

[0020] Between steps S2 and S3, the following is included:

[0021] Select one of the processing modules of the smart meter box in a distance group as the edge processor center;

[0022] The steps in S3 include:

[0023] The edge processor receives energy consumption information sent by the communication modules of multiple smart metering boxes in the distance group;

[0024] The steps in S4 include:

[0025] The edge processor divides the distance grouping into multiple temporary energy consumption groups based on the magnitude relationship between energy consumption information within a preset time period.

[0026] The steps in S5 include:

[0027] The edge processor receives temperature information sent by the communication modules of multiple smart metering boxes within a preset time period in the temporary energy consumption group, and determines whether a temperature anomaly has occurred based on the differences between the multiple sets of temperature information.

[0028] In one embodiment, steps S4 and S5 include the following:

[0029] The magnitude relationship between energy consumption information within the next preset time period is used to re-divide temporary energy consumption groups in the distance grouping;

[0030] In one embodiment, the smart metering box is also equipped with a processing module;

[0031] Between steps S2 and S3, the following is included:

[0032] Select one of the processing modules of the smart meter box in a distance group as the edge processor center;

[0033] The steps in S3 include:

[0034] The edge processor receives energy consumption information sent by the communication modules of multiple smart metering boxes in the distance group;

[0035] The steps in S4 include:

[0036] The edge processor divides the distance group into multiple temporary energy consumption groups according to the magnitude relationship between energy consumption information within a preset time length. The edge processor selects the processing module of the smart meter box in the temporary energy consumption group as the temporary processor center.

[0037] The steps in S5 include:

[0038] The temporary processor center receives temperature information sent by the communication modules of multiple smart metering boxes within a preset time period in the temporary energy consumption group, and determines whether a temperature abnormality has occurred based on the differences between the multiple sets of temperature information.

[0039] In one embodiment, a humidity sensor is also installed in the smart metering box;

[0040] Step S1 further includes:

[0041] The device receives humidity information sent by the communication modules in multiple smart metering boxes, wherein the humidity information is obtained by the humidity sensor and transmitted to the communication module.

[0042] The step S3 is followed by:

[0043] S6. Receive humidity information sent by the communication modules in the multiple smart metering boxes;

[0044] S7. Receive multiple sets of humidity information corresponding to multiple smart metering boxes within a preset time length in the temporary energy consumption group, and determine whether humidity abnormality occurs based on the differences between the multiple sets of humidity information.

[0045] In one embodiment, step S5 includes:

[0046] S41. Receive temperature information sent by the communication modules of the multiple smart metering boxes within a preset time period in the temporary energy consumption group;

[0047] S42. Calculate the average operating temperature corresponding to multiple sets of temperature information;

[0048] S43. Calculate the average value among multiple average operating temperatures to obtain the rated temperature;

[0049] S44. If the average operating temperature of the intelligent metering box exceeds the approved temperature by a preset ratio, it is determined that the intelligent metering box has a temperature abnormality.

[0050] In one embodiment, step S2 is followed by:

[0051] The smart meter box is added to a distance group by receiving grouping information, wherein the grouping information is manually input.

[0052] The present invention also provides an apparatus for operating the above-described multi-sensor fusion-based intelligent metering box status monitoring method, comprising:

[0053] The first receiving module is used to receive location information blocks sent by the communication modules in the multiple smart metering boxes;

[0054] The first processing module is used to divide the multiple smart metering boxes into multiple distance groups according to the distance relationship between the location information;

[0055] The second receiving module is used to receive energy consumption information sent by the communication modules of the multiple smart metering boxes in the distance group;

[0056] The second processing module is used to divide the distance group into multiple temporary energy consumption groups according to the magnitude relationship between energy consumption information within a preset time length.

[0057] The third processing module is used to receive temperature information sent by the communication modules of multiple smart metering boxes within a preset time period in the temporary energy consumption group, and to determine whether a temperature abnormality has occurred based on the differences between the multiple temperature information.

[0058] The present invention provides a method and apparatus for monitoring the status of smart meters by multi-sensor fusion. Based on location information, multiple smart meters are clustered into multiple distance groups. Based on the energy consumption information of each smart meter in the distance group, the smart meters in the distance group are further divided into multiple temporary energy consumption groups. Since the energy consumption of the smart meters in the temporary energy consumption groups is similar, the self-heating of multiple smart meters in the temporary energy consumption groups is similar. At this time, the temperature information difference of different smart meters in the temporary energy consumption groups reflects whether the temperature of a single smart meter is normal. Attached Figure Description

[0059] Figure 1 This is a schematic diagram of a multi-sensor fusion-based intelligent metering box status monitoring method according to an embodiment of the present invention;

[0060] Figure 2 This is a schematic diagram of an apparatus for monitoring the status of a smart metering box using multi-sensor fusion, according to an embodiment of the present invention. Detailed Implementation

[0061] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0062] Those skilled in the art will understand that, unless specifically stated otherwise, the singular forms “a,” “an,” “the,” “the,” and “the” used herein may also include the plural forms. It should be further understood that the term “comprising” as used in this specification means the presence of the stated features, integers, steps, operations, elements, units, modules, and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, units, modules, components, and / or groups thereof. It should be understood that when we say an element is “connected” or “coupled” to another element, it can be directly connected or coupled to the other element, or there may be intermediate elements. Furthermore, “connected” or “coupled” as used herein can include wireless connection or wireless coupling. The term “and / or” as used herein includes all or any of the units and all combinations of one or more associated listed items.

[0063] It will be understood by those skilled in the art that, unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. It should also be understood that terms such as those defined in general dictionaries should be understood to have the same meaning as in the context of the prior art and should not be interpreted in an idealized or overly formal sense unless specifically defined as herein.

[0064] Reference Figure 1 In one embodiment of the present invention, a method for monitoring the status of a smart metering box using multi-sensor fusion is provided. The smart metering box is equipped with a communication module, a positioning module, a temperature sensor, and a current transformer. The method for monitoring the status of the smart metering box includes:

[0065] S1. Receive location information sent by the communication modules in the multiple smart metering boxes, wherein the location information is obtained by the positioning module and transmitted to the communication module;

[0066] S2. Divide the multiple smart metering boxes into multiple distance groups according to the distance relationship between the location information;

[0067] S3. Receive energy consumption information sent by the communication modules of multiple smart metering boxes in the distance group, wherein the energy consumption information is obtained by the current transformer and transmitted to the communication module;

[0068] S4. Divide the distance grouping into multiple temporary energy consumption groups according to the magnitude relationship between energy consumption information within a preset time length.

[0069] S5. Receive temperature information sent by the communication modules of multiple smart metering boxes within a preset time period in the temporary energy consumption group, and determine whether a temperature abnormality has occurred based on the differences between the multiple temperature information. The temperature information is obtained by the temperature sensor and transmitted to the communication module.

[0070] In existing technologies, electricity metering boxes, as crucial equipment at the end of low-voltage power distribution systems, undertake multiple functions including electricity metering, power distribution, and operational status monitoring, and are widely deployed in residential communities, commercial buildings, and industrial plants. With the current rapid evolution of power grids towards intelligence and automation, the limitations of traditional metering boxes in terms of operational safety, real-time monitoring, and intelligent response are becoming increasingly prominent, making it difficult to meet the practical needs of increasingly complex power environments for fault early warning and data linkage. Most existing systems lack comprehensive perception capabilities of operational status and cannot achieve rapid response to fluctuations in the box's environment and electrical parameters, as well as physical intrusion behaviors, easily leading to fault propagation or amplification of safety hazards. Therefore, constructing a fusion monitoring system integrating multiple sensors to improve the real-time perception and linkage processing capabilities of metering box operational status has become a core direction for the development of intelligent power distribution terminals. Researching monitoring instruments with edge computing capabilities and multi-source information fusion functions has significant technical value and practical significance for realizing intelligent diagnosis and proactive protection of power distribution systems.

[0071] Currently, data from multiple sensors is only collected, with little fusion, thus hindering efficient and accurate monitoring.

[0072] In this invention, the intelligent metering box is equipped with a communication module, a positioning module, a temperature sensor, a humidity sensor, and a current transformer. The positioning module, temperature sensor, humidity sensor, and current transformer respectively detect and obtain location information, temperature information, humidity information, and energy consumption information, and transmit them to the communication module. The communication module can transmit all information to a cloud server, or the intelligent metering boxes can exchange information with each other. The intelligent metering box has access control status detection, which can use a magnetic Hall sensor to achieve non-contact monitoring of door opening and closing, with a response delay of no more than 200 milliseconds and a false alarm rate of less than 1 per thousand operations. All sensor modules must support local event judgment and edge output alarm signals while reducing dependence on the main station. The status perception module not only improves the physical security level of the equipment but also provides support for subsequent maintenance decisions and helps to achieve intelligent and proactive operation and maintenance.

[0073] This invention provides a multi-sensor fusion-based intelligent metering box status monitoring method:

[0074] In step S1, location and energy consumption information are received from communication modules in multiple smart metering boxes. Specifically, this information can be received by a cloud server or the smart metering box's own processor.

[0075] In step S2, multiple smart meter boxes are divided into multiple distance groups based on the distance relationships between their locations. For example, K-means, DBSCAN, or hierarchical clustering can be used to divide smart meter boxes within a set distance range (e.g., 100 meters). K-means is a partitioning-based clustering algorithm that requires specifying the number of clusters k; DBSCAN is a density-based clustering algorithm that automatically identifies cluster boundaries; hierarchical clustering is a hierarchical clustering algorithm that does not require specifying the number of clusters. By setting distance groups, the local environment is considered.

[0076] In step S3, energy consumption information is received from communication modules in multiple smart metering boxes within the distance group. Specifically, this information can be received by a cloud server or the smart metering box's own processor.

[0077] In step S4, temporary energy consumption groups are created within the distance grouping based on the magnitude relationship between energy consumption information within a preset time period (e.g., 5, 10, 30 minutes). Specifically, multiple smart metering boxes with similar accumulated internal energy within the preset time period are aggregated into multiple temporary energy consumption groups. These temporary energy consumption groups can also be formed using K-means, DBSCAN, or hierarchical clustering methods, or by sorting the energy consumption information of all smart metering boxes in the distance group by magnitude and then sequentially dividing them into multiple temporary energy consumption groups.

[0078] In step S5, temperature information sent by communication modules in multiple smart metering boxes within a preset time period from the temporary energy consumption group is received, and the difference between the multiple temperature information is used to determine whether a temperature anomaly has occurred. The temperature information is obtained by a temperature sensor and transmitted to the communication module. In the above steps, the temperature sensor covers an ambient temperature range of -40 to 85 degrees Celsius, and the sampling time interval can be set as needed, such as a ten-second interval. The temperature information can be received by a cloud server or the smart metering box's own processor.

[0079] During operation, the system receives multiple sets of temperature information corresponding to various smart metering boxes within a preset time period from temporary energy consumption groups. It calculates multiple average operating temperatures for each set of temperature information, and then calculates the average of these average operating temperatures as the set temperature. If the average operating temperature of a corresponding smart metering box exceeds the set temperature by a preset percentage, the smart metering box is considered to have a temperature anomaly. Throughout this process, smart metering boxes with similar energy consumption information (work intensity) within the temporary energy consumption groups are compared to determine if the temperature of a single smart metering box is normal. For example, if the energy consumption information of all smart metering boxes in the temporary energy consumption group is 0, the temperature of the smart metering box will be the same as the ambient temperature; if the energy consumption information of all smart metering boxes in the temporary energy consumption group is high, the temperature of the smart metering box will be significantly higher than the ambient temperature.

[0080] In summary, based on location information, multiple smart meter boxes are clustered into multiple distance groups. Based on the energy consumption information of each smart meter box in the distance group, the smart meter boxes in the distance group are further divided into multiple temporary energy consumption groups. Since the energy consumption of smart meter boxes in the temporary energy consumption groups is similar, the self-heating of multiple smart meter boxes in the temporary energy consumption groups is similar. At this time, the temperature information difference of different smart meter boxes in the temporary energy consumption groups reflects whether the temperature of a single smart meter box is normal.

[0081] In one embodiment, a height sensor is also installed in the smart metering box;

[0082] Step S1 further includes:

[0083] The system receives height information sent by the communication modules of multiple smart metering boxes, wherein the height information is obtained by the height sensor and transmitted to the communication module.

[0084] Step S2 includes:

[0085] The multiple smart metering boxes are divided into multiple distance groups based on the distance between their location and altitude information.

[0086] In the aforementioned embodiments, distance grouping was determined solely based on horizontal distance relationships. In this embodiment, considering the typically high ceilings in modern residential buildings, height sensors are added to provide a vertical basis for distance grouping. For example, multiple smart metering boxes within a horizontal range of 50 meters and a vertical range of 30 meters are divided into distance groups, thus forming approximate groups. This introduction of height-based distance grouping makes the grouping process more accurate.

[0087] In one embodiment, a vibration sensor is also installed in the smart metering box, and step S2 is followed by:

[0088] When the vibration information of the smart metering box in the distance group exceeds the preset vibration threshold;

[0089] Based on the vibration information of multiple sets of smart metering boxes corresponding to multiple distance groups within the second preset time length, it is determined to be a single abnormality or a regional abnormality.

[0090] In this embodiment, the vibration sensor is based on a triaxial accelerometer to detect sudden displacements or continuous shaking exceeding 0.5g. This allows for timely identification of equipment disturbances caused by external forces, abnormal handling, or construction interference, further triggering safety protection signals. When the vibration information collected by a single smart meter exceeds a vibration threshold, the vibration information of all smart metering boxes in a distance group within a second preset time period is acquired. If only the vibration information of that single smart metering box is abnormal, it is determined to be a single anomaly, and relevant alarm information can be sent to prompt inspection. If the vibration information of multiple smart metering boxes is abnormal, it is determined to be a regional anomaly, such as caused by renovations, elevator operation, or severe weather.

[0091] In one embodiment, the smart metering box is also equipped with a processing module;

[0092] Between steps S2 and S3, the following is included:

[0093] Select one of the processing modules of the smart meter box in a distance group as the edge processor center;

[0094] The steps in S3 include:

[0095] The edge processor receives energy consumption information sent by the communication modules of multiple smart metering boxes in the distance group;

[0096] The steps in S4 include:

[0097] The edge processor divides the distance grouping into multiple temporary energy consumption groups based on the magnitude relationship between energy consumption information within a preset time period.

[0098] The steps in S5 include:

[0099] The edge processor receives temperature information sent by the communication modules of multiple smart metering boxes within a preset time period in the temporary energy consumption group, and determines whether a temperature anomaly has occurred based on the differences between the multiple sets of temperature information.

[0100] In this embodiment, the cloud processing center selects or manually selects a smart metering box as the core, and the processing module within it acts as an edge processor center. The processing module of the core smart metering box receives and processes relevant information from distance groups (thus controlling multiple temporary energy consumption groups). This edge computing approach reduces the computational burden on the cloud.

[0101] In one embodiment, steps S4 and S5 include the following:

[0102] The magnitude relationship between energy consumption information within the next preset time period is used to re-divide temporary energy consumption groups in the distance grouping;

[0103] In this embodiment, temporary energy consumption groups are updated at preset time intervals based on energy consumption information, making the reference value between various smart metering boxes greater.

[0104] In one embodiment, the smart metering box is also equipped with a processing module;

[0105] Between steps S2 and S3, the following is included:

[0106] Select one of the processing modules of the smart meter box in a distance group as the edge processor center;

[0107] The steps in S3 include:

[0108] The edge processor receives energy consumption information sent by the communication modules of multiple smart metering boxes in the distance group;

[0109] The steps in S4 include:

[0110] The edge processor divides the distance group into multiple temporary energy consumption groups according to the magnitude relationship between energy consumption information within a preset time length. The edge processor selects the processing module of the smart meter box in the temporary energy consumption group as the temporary processor center.

[0111] The steps in S5 include:

[0112] The temporary processor center receives temperature information sent by the communication modules of multiple smart metering boxes within a preset time period in the temporary energy consumption group, and determines whether a temperature abnormality has occurred based on the differences between the multiple sets of temperature information.

[0113] In this embodiment, in addition to setting an edge processor center in the distance group, a temporary processor center is set in the temporary energy consumption group. The temporary processor center receives and processes relevant information in the temporary energy consumption group, which reduces the computing power requirements and improves the computing speed.

[0114] In one embodiment, a humidity sensor is also installed in the smart metering box;

[0115] Step S1 further includes:

[0116] The device receives humidity information sent by the communication modules in multiple smart metering boxes, wherein the humidity information is obtained by the humidity sensor and transmitted to the communication module.

[0117] The step S3 is followed by:

[0118] S6. Receive humidity information sent by the communication modules in the multiple smart metering boxes;

[0119] S7. Receive multiple sets of humidity information corresponding to multiple smart metering boxes within a preset time length in the temporary energy consumption group, and determine whether humidity abnormality occurs based on the differences between the multiple sets of humidity information.

[0120] In this embodiment, the humidity sensor ranges from 10%RH to 95%RH, with a relative error controlled within ±0.3℃ and ±2%RH. It is used to determine condensation inside the smart metering box, overheating of electrical appliances, or abnormal external environment. Multiple sets of humidity information corresponding to multiple smart metering boxes within a preset time period from a temporary energy consumption group are received, and the differences between these sets of humidity information are used to determine whether a humidity anomaly has occurred. For example, multiple sets of humidity information corresponding to multiple smart metering boxes within a preset time period from a temporary energy consumption group are received. Multiple average operating humidity values ​​corresponding to the multiple sets of humidity information are calculated. The average value among these multiple average operating humidity values ​​is the rated humidity. If the average operating humidity of the corresponding smart metering box exceeds the rated humidity by a preset proportion, then the smart metering box is determined to have a humidity anomaly. In the above process, smart metering boxes with similar operating intensities are used for comparison to reflect whether the humidity of a single smart metering box is normal.

[0121] In one embodiment, step S5 includes:

[0122] S41. Receive temperature information sent by the communication modules of the multiple smart metering boxes within a preset time period in the temporary energy consumption group;

[0123] S42. Calculate the average operating temperature corresponding to multiple sets of temperature information;

[0124] S43. Calculate the average value among multiple average operating temperatures to obtain the rated temperature;

[0125] S44. If the average operating temperature of the intelligent metering box exceeds the approved temperature by a preset ratio, it is determined that the intelligent metering box has a temperature abnormality.

[0126] In this embodiment, in step S41, within a preset time period (e.g., half an hour), the temperature information of all smart metering boxes in the temporary energy consumption group is received. The temperature information is then matched with the smart metering boxes.

[0127] In step S42, multiple average operating temperatures corresponding to multiple sets of temperature information are calculated. For example, if 30 temperature values ​​are acquired within half an hour, the average of these 30 temperature values ​​is calculated as the average operating temperature.

[0128] In step S43, the average of multiple average operating temperatures is calculated as the rated temperature. The rated temperature is obtained based on the average operating temperature of all smart metering boxes in the temperature group.

[0129] In step S44, if the average operating temperature of the smart metering box is greater than the rated temperature by more than a preset percentage (e.g., exceeding by 10 to 20%), it is determined that the smart metering box has a temperature abnormality.

[0130] In one embodiment, step S2 is followed by:

[0131] The smart meter box is added to a distance group by receiving grouping information, wherein the grouping information is manually input.

[0132] In this embodiment, manually input grouping information is received to add specific smart meter boxes to distance groups. This can compensate for omissions in distance groups under certain circumstances, and also allows for manual addition of specific smart meter boxes to appropriate distance groups.

[0133] Reference Figure 2 In one embodiment, the present invention also provides an apparatus for operating the above-described multi-sensor fusion intelligent metering box status monitoring method, comprising:

[0134] The first receiving module 10 is used to receive location information blocks sent by the communication modules in the multiple smart metering boxes;

[0135] The first processing module 20 is used to divide the multiple smart metering boxes into multiple distance groups according to the distance relationship between the location information;

[0136] The second receiving module 30 is used to receive energy consumption information sent by the communication modules of the multiple smart metering boxes in the distance group;

[0137] The second processing module 40 is used to divide the distance group into multiple temporary energy consumption groups according to the magnitude relationship between energy consumption information within a preset time length.

[0138] The third processing module 50 is used to receive temperature information sent by the communication modules of multiple smart metering boxes within a preset time period in the temporary energy consumption group, and to determine whether a temperature abnormality has occurred based on the differences between the multiple temperature information.

[0139] In this embodiment, the operation of the device is the same as in the aforementioned embodiment, and will not be repeated here.

[0140] In summary, the multi-sensor fusion-based smart metering box status monitoring method and device provided by this invention divides multiple smart metering boxes into multiple distance groups based on location information, and further divides the smart metering boxes in the distance groups into multiple temporary energy consumption groups based on the energy consumption information of each smart metering box in the distance groups. Since the energy consumption of the smart metering boxes in the temporary energy consumption groups is similar, the self-heating of multiple smart metering boxes in the temporary energy consumption groups is similar. At this time, the temperature information difference of different smart metering boxes in the temporary energy consumption groups reflects whether the temperature of a single smart metering box is normal.

[0141] The above description is merely a preferred embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural or procedural transformations made based on the content of the present invention's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A method for monitoring the status of a smart metering box using multi-sensor fusion, wherein the smart metering box is equipped with a communication module, a positioning module, a temperature sensor, and a current transformer, characterized in that, The method for monitoring the status of the intelligent metering box includes: S1. Receive location information sent by the communication modules in the multiple smart metering boxes, wherein the location information is obtained by the positioning module and transmitted to the communication module; S2. Divide the multiple smart metering boxes into multiple distance groups according to the distance relationship between the location information; S3. Receive energy consumption information sent by the communication modules of multiple smart metering boxes in the distance group, wherein the energy consumption information is obtained by the current transformer and transmitted to the communication module; S4. Divide the distance grouping into multiple temporary energy consumption groups according to the magnitude relationship between energy consumption information within a preset time length. S5. Receive temperature information sent by the communication modules of multiple smart metering boxes within a preset time period in the temporary energy consumption group, and determine whether a temperature abnormality has occurred based on the differences between the multiple temperature information. The temperature information is obtained by the temperature sensor and transmitted to the communication module.

2. The method for monitoring the status of a smart metering box using multi-sensor fusion according to claim 1, characterized in that, The intelligent metering box is also equipped with a height sensor; Step S1 further includes: The system receives height information sent by the communication modules of multiple smart metering boxes, wherein the height information is obtained by the height sensor and transmitted to the communication module. Step S2 includes: The multiple smart metering boxes are divided into multiple distance groups based on the distance between their location and altitude information.

3. The method for monitoring the status of a smart metering box using multi-sensor fusion according to claim 2, characterized in that, The intelligent metering box is also equipped with a vibration sensor, and step S2 is followed by: When the vibration information of the smart metering box in the distance group exceeds the preset vibration threshold; Based on the vibration information of multiple sets of smart metering boxes corresponding to multiple distance groups within the second preset time length, it is determined to be a single abnormality or a regional abnormality.

4. The method for monitoring the status of a smart metering box using multi-sensor fusion according to claim 1, characterized in that, The intelligent metering box is also equipped with a processing module; Between steps S2 and S3, the following is included: Select one of the processing modules of the smart meter box in a distance group as the edge processor center; The steps in S3 include: The edge processor receives energy consumption information sent by the communication modules of multiple smart metering boxes in the distance group; The steps in S4 include: The edge processor divides the distance grouping into multiple temporary energy consumption groups based on the magnitude relationship between energy consumption information within a preset time period. The steps in S5 include: The edge processor receives temperature information sent by the communication modules of multiple smart metering boxes within a preset time period in the temporary energy consumption group, and determines whether a temperature anomaly has occurred based on the differences between the multiple sets of temperature information.

5. The method for monitoring the status of a smart metering box using multi-sensor fusion according to claim 4, characterized in that, The steps between S4 and S5 include: The magnitude relationship between energy consumption information within the next preset time period is used to re-divide temporary energy consumption groups in the distance grouping.

6. The method for monitoring the status of a smart metering box using multi-sensor fusion according to claim 1, characterized in that, The intelligent metering box is also equipped with a processing module; Between steps S2 and S3, the following is included: Select one of the processing modules of the smart meter box in a distance group as the edge processor center; The steps in S3 include: The edge processor receives energy consumption information sent by the communication modules of multiple smart metering boxes in the distance group; The steps in S4 include: The edge processor divides the distance group into multiple temporary energy consumption groups according to the magnitude relationship between energy consumption information within a preset time length. The edge processor selects the processing module of the smart meter box in the temporary energy consumption group as the temporary processor center. The steps in S5 include: The temporary processor center receives temperature information sent by the communication modules of multiple smart metering boxes within a preset time period in the temporary energy consumption group, and determines whether a temperature abnormality has occurred based on the differences between the multiple sets of temperature information.

7. The method for monitoring the status of a smart metering box using multi-sensor fusion according to any one of claims 1 to 6, characterized in that, The intelligent metering box is also equipped with a humidity sensor; Step S1 further includes: The device receives humidity information sent by the communication modules in multiple smart metering boxes, wherein the humidity information is obtained by the humidity sensor and transmitted to the communication module. The step S3 is followed by: S6. Receive humidity information sent by the communication modules in the multiple smart metering boxes; S7. Receive multiple sets of humidity information corresponding to multiple smart metering boxes within a preset time length in the temporary energy consumption group, and determine whether humidity abnormality occurs based on the differences between the multiple sets of humidity information.

8. The multi-sensor fusion-based intelligent metering box status monitoring method according to any one of claims 1 to 6, characterized in that, The steps in S5 include: S41. Receive temperature information sent by the communication modules of the multiple smart metering boxes within a preset time period in the temporary energy consumption group; S42. Calculate the average operating temperature corresponding to multiple sets of temperature information; S43. Calculate the average value among multiple average operating temperatures to obtain the rated temperature; S44. If the average operating temperature of the intelligent metering box exceeds the approved temperature by a preset ratio, it is determined that the intelligent metering box has a temperature abnormality.

9. The multi-sensor fusion-based intelligent metering box status monitoring method according to any one of claims 1 to 6, characterized in that, Step S2 is followed by: The smart meter box is added to a distance group by receiving grouping information, wherein the grouping information is manually input.

10. An apparatus for operating the multi-sensor fusion intelligent metering box status monitoring method according to any one of claims 1 to 9, characterized in that, include: The first receiving module is used to receive location information blocks sent by the communication modules in the multiple smart metering boxes; The first processing module is used to divide the multiple smart metering boxes into multiple distance groups according to the distance relationship between the location information; The second receiving module is used to receive energy consumption information sent by the communication modules of the multiple smart metering boxes in the distance group; The second processing module is used to divide the distance group into multiple temporary energy consumption groups according to the magnitude relationship between energy consumption information within a preset time length. The third processing module is used to receive temperature information sent by the communication modules of multiple smart metering boxes within a preset time period in the temporary energy consumption group, and to determine whether a temperature abnormality has occurred based on the differences between the multiple temperature information.

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