Electric energy meter sorting detection method and system of intelligent sorting platform

Abstract

The invention discloses an electric energy meter sorting detection method and system of an intelligent sorting platform, and relates to the technical field of electric power systems. The problem that existing electric energy meter sorting detection is low in accuracy is mainly solved. The method mainly comprises the steps of obtaining all pre-configured detection nodes in the intelligent sorting platform, and performing alignment processing on detection lag parameters, detection objects and detection trigger conditions in the detection nodes to obtain standardized detection nodes; when the sorting task list is received, a detection target of the electric energy meter in the sorting task list is analyzed, and the detection target is used for representing an extreme value or a numerical range of the detection object passing through the detection; when it is detected that the electric energy meter is placed on the sorting transmission equipment, sorting operation data and sorting image data of the detection node are obtained; and carrying out combined identification on the sorting operation data and the sorting image data according to the detection lag parameter, the detection object and the detection target to obtain a sorting detection result of the electric energy meter. The method is used for sorting and detecting electric energy meters.

Description

Technical Field

[0001] The present invention relates to the technical field of power systems, and in particular to an electric energy meter sorting and detection method and system for an intelligent sorting platform. Background Art

[0002] With the development of intelligent layout and intelligent identification technologies for energy meters in power systems, the energy meter sorting and identification platform is used to identify each energy meter in the power transmission network to ensure the safety and effectiveness of energy meter operation. To ensure the accuracy and effectiveness of energy meter sorting and identification, the entire sorting and identification process needs to be tested.

[0003] Currently, electricity meter sorting and detection are typically based on video data and collected sorting equipment operation data. However, the detection targets of video data and operation data are often different, which can lead to detection errors during sorting and detection, significantly affecting the accuracy of electricity meter sorting and detection. Summary of the Invention

[0004] In view of this, the present invention provides an electric energy meter sorting and detection method and system for an intelligent sorting platform, the main purpose of which is to solve the problem of low accuracy of existing electric energy meter sorting and detection.

[0005] According to one aspect of the present invention, a method for sorting and detecting electric energy meters on an intelligent sorting platform is provided, comprising:

[0006] Acquire all pre-configured detection nodes in the intelligent sorting platform, and align the detection hysteresis parameters, detection objects, and detection trigger conditions in the detection nodes to obtain standardized detection nodes;

[0007] When a sorting task list is received, parsing the detection target of the electric energy meter in the sorting task list, the detection target is used to represent the extreme value or value range of the detection object passing the detection;

[0008] When it is detected that the electric energy meter is placed on the sorting and transmission device, the sorting operation data and the sorting image data of the detection node are obtained;

[0009] The sorting operation data and the sorting image data are combined and identified according to the detection hysteresis parameter, the detection object, and the detection target to obtain a sorting detection result of the electric energy meter.

[0010] Querying a detection object that matches the detection function type based on the function-object mapping relationship, and retrieving an initial detection trigger condition that matches the detection object, wherein the detection trigger condition includes at least one of a time trigger condition, a signal trigger condition, and an identification trigger condition;

[0011] The initial detection trigger conditions of each sorting device are aligned according to the detection hysteresis parameter to obtain detection trigger conditions corresponding to different sorting devices.

[0012] Furthermore, the analyzing the detection targets of the electric energy meters in the sorting task list includes:

[0013] Parsing the row identifier and the column identifier in the sorting task list, wherein the row identifier is used to represent the identity of the electric energy meter, and the column identifier is used to represent the function parameter of the device;

[0014] Based on the numerical weight value between the row identifier and the column identifier, a detection object and a corresponding extreme value or numerical range are selected from the detection object library to be determined as the detection target.

[0015] Furthermore, the obtaining of the sorting operation data and the sorting image data of the detection node includes:

[0016] The target sensor of the detection node is determined, and the sorting operation data and the sorting image data collected by the target sensor are acquired according to the detection trigger condition in the detection node.

[0017] Furthermore, the combining and identifying the sorting operation data and the sorting image data according to the detection hysteresis parameter, the detection object, and the detection target to obtain the sorting detection result of the electric energy meter includes:

[0018] Determining the acquisition time and acquisition sequence of the sorting operation data and the sorting image data, and generating a detection data sequence based on the acquisition time and the acquisition sequence;

[0019] comparing the detection data sequence with the detection hysteresis parameter;

[0020] If the detection data sequence matches the detection hysteresis parameter, a one-to-one matching identification is performed based on the detection data sequence, the detection object, and the detection target to generate a sorting detection result;

[0021] If the detection data sequence does not match the detection hysteresis parameter, the detection data sequence is adjusted according to the detection hysteresis parameter, and a one-to-one matching and identification is performed between the adjusted detection data sequence and the detection target to generate a sorting detection result.

[0022] Furthermore, the method further comprises:

[0023] If the sorting detection result is an abnormality detection, the abnormality type is determined and warning information matching the abnormality type is output.

[0024] According to another aspect of the present invention, there is provided an electric energy meter sorting and detection system for an intelligent sorting platform, comprising:

[0025] An alignment module is used to obtain all pre-configured detection nodes in the intelligent sorting platform and align the detection hysteresis parameters, detection objects, and detection trigger conditions in the detection nodes to obtain standardized detection nodes;

[0026] a parsing module configured to, upon receiving a sorting task list, parse a detection target of an electric energy meter in the sorting task list, wherein the detection target is used to represent an extreme value or a numerical range of the detection object passing the detection;

[0027] an acquisition module, configured to acquire the sorting operation data and the sorting image data of the detection node after detecting that the electric energy meter is placed on the sorting and transmission device;

[0028] The recognition module is used to combine and recognize the sorting operation data and the sorting image data according to the detection hysteresis parameter, the detection object, and the detection target to obtain the sorting detection result of the electric energy meter.

[0029] Furthermore, the alignment module includes:

[0030] a first determining unit, configured to obtain the number of sorting devices of the same detection function type in the detection node and a sorting transmission distance, and determine the detection hysteresis parameter based on the number and the sorting transmission distance;

[0031] A query unit, configured to query a detection object matching the detection function type based on a function-object mapping relationship, and retrieve an initial detection trigger condition matching the detection object, wherein the detection trigger condition includes at least one of a time trigger condition, a signal trigger condition, and an identification trigger condition;

[0032] An alignment unit is configured to align the initial detection trigger conditions of the various sorting devices according to the detection hysteresis parameter to obtain detection trigger conditions corresponding to different sorting devices.

[0033] Furthermore, the analysis module includes:

[0034] a parsing unit, configured to parse a row identifier and a column identifier in the sorting task list, wherein the row identifier is used to represent the identity of the electric energy meter, and the column identifier is used to represent the function parameter of the device;

[0035] The second determining unit is configured to select a detection object and a corresponding extreme value or numerical range from a detection object library based on the numerical weight value between the row identifier and the column identifier, and determine the detection object as the detection target.

[0036] Furthermore, the acquisition module includes:

[0037] An acquisition unit is configured to determine a target sensor of the detection node and acquire the sorting operation data and the sorting image data collected by the target sensor according to a detection trigger condition in the detection node.

[0038] Furthermore, the identification module includes:

[0039] a third determining unit, configured to determine the acquisition time and acquisition sequence of the sorting operation data and the sorting image data, and generate a detection data sequence based on the acquisition time and the acquisition sequence;

[0040] a comparison unit, configured to compare the detection data sequence with the detection hysteresis parameter;

[0041] an identification unit, configured to, if the detection data sequence matches the detection hysteresis parameter, perform one-to-one matching and identification based on the detection data sequence, the detection object, and the detection target, to generate a sorting detection result;

[0042] an adjustment unit, configured to adjust the detection data sequence according to the detection hysteresis parameter if the detection data sequence does not match the detection hysteresis parameter, and perform one-to-one matching and identification between the adjusted detection data sequence and the detection target to generate a sorting detection result.

[0043] Furthermore, the system further comprises:

[0044] The early warning module is used to determine the abnormality type if the sorting detection result is an abnormality detection, and output early warning information matching the abnormality type.

[0045] According to another aspect of the present invention, a storage medium is provided, in which at least one executable instruction is stored. The executable instruction enables a processor to execute operations corresponding to the electric energy meter sorting and detection method of the above-mentioned intelligent sorting platform.

[0046] According to another aspect of the present invention, there is provided a terminal, comprising: a processor, a memory, a communication interface, and a communication bus, wherein the processor, the memory, and the communication interface communicate with each other via the communication bus;

[0047] The memory is used to store at least one executable instruction, and the executable instruction enables the processor to execute operations corresponding to the electric energy meter sorting and detection method of the above-mentioned intelligent sorting platform.

[0048] By means of the above technical solution, the technical solution provided by the embodiment of the present invention has at least the following advantages:

[0049] The present invention provides a method and system for sorting and detecting electric energy meters on an intelligent sorting platform. Compared with the prior art, the embodiment of the present invention obtains all pre-configured detection nodes in the intelligent sorting platform and aligns the detection hysteresis parameters, detection objects, and detection trigger conditions in the detection nodes to obtain standardized detection nodes. When a sorting task list is received, the detection target of the electric energy meter in the sorting task list is parsed, and the detection target is used to represent the extreme value or numerical range of the detection object through detection. When the electric energy meter is detected to be placed on a sorting transmission device, the sorting operation data and sorting image data of the detection node are obtained. The sorting operation data and sorting image data are combined and identified according to the detection hysteresis parameters, the detection objects, and the detection targets to obtain the sorting detection results of the electric energy meter. By aligning the detection hysteresis parameters and detection trigger conditions in the detection nodes before sorting detection, and identifying the sorting operation data and sorting image data according to the detection hysteresis parameters during the sorting operation data and sorting image data identification process, the matching of the sorting operation data and the sorting image data can be ensured, thereby ensuring the accuracy of the sorting detection results.

[0050] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are specifically listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Various other advantages and benefits will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiment below. The accompanying drawings are for illustration purposes only and are not to be considered as limiting the present invention. The same reference symbols are used throughout the drawings to represent the same components. In the drawings:

[0052] Figure 1 A flow chart of an electric energy meter sorting and detection method of an intelligent sorting platform provided by an embodiment of the present invention is shown;

[0053] Figure 2 A flow chart of an electric energy meter sorting and detection method of another intelligent sorting platform provided by an embodiment of the present invention is shown;

[0054] Figure 3 The following is a block diagram showing the composition of an electric energy meter sorting and detection system of an intelligent sorting platform provided by an embodiment of the present invention;

[0055] Figure 4 A schematic structural diagram of a terminal provided by an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0056] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0057] The embodiment of the present invention provides an electric energy meter sorting detection method for an intelligent sorting platform, such as Figure 1 As shown, the method includes:

[0058] 101. Acquire all pre-configured detection nodes in the intelligent sorting platform, and align detection hysteresis parameters, detection objects, and detection trigger conditions in the detection nodes to obtain standardized detection nodes.

[0059] In an embodiment of the present invention, multiple test items expected to be performed on an electricity meter are assigned to different test nodes for testing. All test nodes constitute the complete sorting and testing process for the current electricity meter, with each test node representing a node in the complete testing process. For example, if a batch of electricity meters requires testing, namely, testing targets including voltage, current, and fee control function testing, the complete testing process involves performing batch voltage testing on the electricity meters, followed by batch current testing on all the meters, and finally, batch fee control function testing on the electricity meters. Each batch voltage test, batch current test, and batch fee control function test corresponds to a separate test node. Each test node contains multiple sorting devices that perform the same test items. To ensure consistency in the testing operations performed by each sorting device within a test node and to ensure accurate matching between the collected sorting operation data and the sorting image data, before executing a specific test task, the current execution entity must retrieve all test nodes pre-configured by the operator through the intelligent sorting platform and analyze the test hysteresis parameters, test targets, and test trigger conditions for each test node. Among them, the current execution entity is the intelligent sorting platform server, which can be a local server or a cloud server, and the embodiment of the present invention does not make specific limitations.

[0060] By analyzing the test items that the sorting equipment in the detection node can perform, we can obtain the detection object—the test items that the sorting equipment needs to perform, such as voltage detection, current detection, fee control function detection, and meter type identification. Since energy meters are sequentially loaded into the sorting and transport equipment and arrive at their corresponding sorting equipment, there is a time difference between the time different energy meters are loaded into the sorting and transport equipment, and there is a time difference between the time different energy meters are transferred through the pipeline to their corresponding sorting equipment positions. This time difference is usually smaller than the time difference, so all energy meters cannot arrive at their corresponding sorting equipment positions at the same time. When the first energy meter arrives at the corresponding sorting equipment position, the remaining transmission distance or remaining transmission time of each other energy meter relative to the corresponding sorting equipment position is calculated. The sequence of these remaining transmission distances or remaining transmission times is the detection hysteresis parameter. The detection trigger condition is the condition that triggers the corresponding sorting equipment to begin the detection operation, such as a preset time point, a preset identification target, or the receipt of an execution instruction.

[0061] It should be noted that, when there are relatively few detection objects for electric energy meters, but a large number of electric energy meters need to be sorted and detected, in order to improve the efficiency of sorting and detection, multiple sorting devices can be configured to perform the same detection operation to achieve batch detection of multiple electric energy meters and the same detection objects. For example, there are 10 sorting devices distributed on a sorting and transmission device, and the detection object of each sorting device is configured to be voltage detection. Then, 10 electric energy meters are sequentially input into the input end of the sorting and transmission device. When the first electric energy meter is transmitted to the operating area of ​​the first sorting device, it is picked up by the first sorting device. When the second electric energy meter is transmitted to the operating area of ​​the second sorting device, it is picked up by the second sorting device. And so on. The tenth electric energy meter is transmitted from the position of the first sorting device along the assembly line to the operating area of ​​the tenth sorting device and is picked up by the tenth sorting device. There is a time misalignment between the collection of sorting operation data and the collection of sorting image data. By analyzing the detection lag parameters and adjusting them according to the detection trigger conditions, the synchronization and time alignment of the detection operations of each sorting device can be achieved from the device control dimension, thereby ensuring the accuracy of the subsequent recognition collected.

[0062] In one embodiment of the present invention, for further explanation and limitation, as Figure 2 As shown, the analysis of the detection hysteresis parameter, detection object, and detection trigger condition in the detection node includes:

[0063] 201. Obtain the number of sorting devices of the same detection function type in the detection node and the sorting transmission distance, and determine the detection hysteresis parameter based on the number and the sorting transmission distance;

[0064] 202. Query a detection object that matches the detection function type based on the function-object mapping relationship, and retrieve an initial detection trigger condition that matches the detection object.

[0065] 203. Align the initial detection trigger conditions of the various sorting devices according to the detection hysteresis parameter to obtain detection trigger conditions corresponding to different sorting devices.

[0066] In this embodiment of the present invention, the sorting equipment includes a robotic arm configured for sorting and transporting equipment and a detection device that cooperates with the robotic arm for detection. Each sorting device corresponds to one or more detection function types. The detection function type of the sorting device with the most corresponding detection function types in a detection node is used as the detection function type of the current detection node. The number of sorting devices capable of performing this detection function type is then determined, along with the sorting and transport distance between the sorting devices, that is, their relative positions on the assembly line.

[0067] The alignment method for the order in which the energy meters are placed and the sorting equipment can be to align the first-order energy meter with the farthest sorting equipment, or to align the first-order energy meter with the nearest sorting equipment. Different alignment methods determine the detection lag parameters in different ways based on the number of sorting equipment and the sorting transmission distance. The following uses the alignment detection of the first-order energy meter with the farthest sorting equipment as an example to determine the detection lag parameters. In the process of determining the detection lag parameters, it is necessary to assume the scenario of energy meter transmission. For example, five electricity meters, a, b, c, d, and e, are placed in sequence, and the sorting devices are arranged from near to far as 1, 2, 3, 4, and 5. When electricity meter e arrives at sorting device 1, the distance between electricity meter d and sorting device 2 is the difference between the transmission distance between sorting device 1 and sorting device 2 and the product of the time interval between d and e and the transmission speed; the distance between c and sorting device 3 is the difference between the transmission distance between sorting device 1 and sorting device 3 and the product of the time interval between c and e and the transmission speed. Similarly, when the first electricity meter to arrive at the sorting device is generated, the hysteresis transmission distance of each electricity meter to the corresponding sorting device is obtained, thereby obtaining the detection hysteresis parameter. In this sequence, the hysteresis transmission distance corresponding to electricity meter e is 0. Of course, the hysteresis transmission distance can also be converted into hysteresis time based on the transmission speed, which is not specifically limited in the embodiment of the present invention.

[0068] After determining the same detection function type, a detection object that has a mapping relationship with the same detection function type is searched from the function object mapping relationship and used as the detection object of this detection node. The function object mapping relationship is a pre-constructed mapping relationship between different detection function types and their corresponding detection objects. Different detection objects are also pre-configured with corresponding detection trigger conditions. Therefore, after determining the detection object, the detection trigger condition of the matching detection object is retrieved as the initial detection trigger condition of the current detection node. Taking the detection lag parameter as the lag time period as an example, for any sorting device, the initial detection trigger condition is adjusted based on the lag time period corresponding to the sorting device in the detection lag parameter to obtain the detection trigger condition corresponding to the different sorting devices. The detection trigger condition includes at least one of a time trigger condition, a signal trigger condition, and an identification trigger condition. The time trigger condition is to use a preset time node as an instruction condition to start the detection operation. The sum of the initial preset time node and the lag time period can be used as the adjusted time trigger condition. The signal trigger condition uses the receipt of a specified trigger signal as the command condition for initiating the detection operation. The identifier trigger condition uses the recognition of a specified identifier, such as the lighting of a green indicator light, as the command condition for initiating the detection operation. For both of these detection trigger conditions, the issuance of the detection trigger signal can be delayed based on a hysteresis period to adjust the initial detection trigger condition. By identifying the detection hysteresis parameters between sorting devices and aligning the detection trigger condition with the detection hysteresis parameters, it is possible to ensure that the collected sorting operation data matches the image data of the electricity meter's transportation and detection process when the detection is triggered.

[0069] 102. When a sorting task list is received, parse the detection targets of the electric energy meters in the sorting task list.

[0070] In an embodiment of the present invention, the sorting task list is a list of data entered or uploaded by an operator via the intelligent sorting platform. It stores at least one detection object corresponding to different electricity meters, as well as conditional data for detecting and identifying the detection object's data, such as thresholds and ranges. Since the electricity meters being sorted and inspected are mostly recycled, their device models and types are relatively diverse, and their device conditions and corresponding device functional parameters vary. Therefore, it is necessary to determine the detection objects and detection targets for the electricity meters based on the device conditions and functional parameters of the electricity meters in the sorting task list. For example, if the sorting task list includes electricity meters 1-10, where the device functional parameters of electricity meters 1-5 correspond to detection objects A, B, and C, the device functional parameters of electricity meters 6-8 correspond to detection objects B, C, D, and E, and the device functional parameters of electricity meters 9 and 10 correspond to detection objects B, D, and E, then B is determined as the detection object, and the detection conditions corresponding to the detection object are determined as the detection targets. The detection target is used to represent the extreme value or numerical range of the detection object through the detection, that is, the standard used to determine whether the data corresponding to the detection object is normal or abnormal, qualified or unqualified.

[0071] It should be noted that when the equipment situation of the electricity meter is relatively complex and the detection objects to be detected are difficult to unify, using the detection object as the unified dimension for batch processing, extracting the common detection objects of the electricity meter, and performing batch detection on each detection object can effectively improve the efficiency of sorting and detection of the electricity meter.

[0072] In one embodiment of the present invention, for further explanation and limitation, the step of parsing the detection target of the electric energy meter in the sorting task list includes:

[0073] Parsing the row identifiers and column identifiers in the sorting task list;

[0074] Based on the numerical weight value between the row identifier and the column identifier, a detection object and a corresponding extreme value or numerical range are selected from the detection object library to be determined as the detection target.

[0075] In an embodiment of the present invention, each row in the sorting task list corresponds to an identification identifier for an electric energy meter, i.e., the row identifier represents the identity of the electric energy meter. The row identifier includes information such as the corresponding electric energy meter's asset type code, asset code, and checksum. Each column in the sorting task list corresponds to an equipment function parameter of the electric energy meter, i.e., the column identifier represents the equipment function parameter. The data at the intersection of the row and column information represents an equipment function parameter corresponding to each electric energy meter. Each electric energy meter and each equipment function parameter is pre-assigned with a corresponding weight. This weight represents the importance or urgency of detection of the corresponding electric energy meter or equipment function parameter. For example, if a row corresponds to a large number of similar electric energy meters, the corresponding weight is higher. If a column corresponds to an equipment function parameter with a high probability of abnormality, the corresponding weight is higher; if a column corresponds to an equipment function parameter with a low probability of abnormality, the corresponding weight is lower. The weight of each row is multiplied by the weight of each column to obtain a numerical weight value between the row identifier and the column identifier. The equipment function parameter with the highest numerical weight value is selected from the detection object library to select a detection object and its corresponding detection target. The detection object library stores the corresponding numerical weights for different detection objects, detection ranges, and energy meter identifications. Using these numerical weights and their corresponding energy meter identifications, the detection object library can be used to match the corresponding extreme value or numerical range. The extreme value or numerical range corresponds to the detection target. By matching the detection object with the detection objects corresponding to all detection nodes, the detection node that currently needs to be executed can be determined.

[0076] It should be noted that after the selection of the detection target is completed, the largest numerical weight value in the current sorting task list is deleted, so that when the detection object and detection target are determined in the next round, different detection objects can be determined, and detection nodes that are different from the completed detection nodes can be matched from all detection nodes based on the detection objects.

[0077] 103. When it is detected that the electric energy meter is placed on the sorting and transmission equipment, the sorting operation data and the sorting image data of the detection node are obtained.

[0078] In an embodiment of the present invention, after determining the inspection target of an energy meter, the energy meters of different inspection targets are placed on the sorting and conveying equipment (sorting and inspection pipeline) at the inspection node corresponding to the inspection target. After detecting that the energy meter has been placed on the sorting and conveying equipment, i.e., the energy meter to be sorted and inspected has entered the sorting process of the current inspection node, sorting operation data and sorting image data are acquired from data acquisition equipment and image acquisition equipment configured on the sorting and conveying equipment. The data acquisition equipment includes sensors for detecting transmission data from the sorting and conveying equipment, sensors for collecting operational data from the sorting equipment, and equipment for performing corresponding functional tests on the energy meter. The image acquisition equipment includes equipment for capturing images of the operating areas corresponding to each sorting device. The captured sorting image data is used to display information such as the positional relationship between the energy meter and the alignment marker on the sorting and conveying equipment, the connection relationship between the energy meter and the inspection equipment, and the movement trajectory and rest position of the sorting equipment.

[0079] It should be noted that the sorting operation data and sorting image data can be a data sequence collected in real time at a preset data collection frequency. The acquisition of the sorting operation data and sorting image data by the current execution entity can be performed in response to a detection trigger condition. In other words, the sorting operation data and sorting image data acquired by the current execution entity are selective data acquisition processes, thus avoiding the generation of excessive data transmission.

[0080] In one embodiment of the present invention, for further explanation and limitation, the step of obtaining the sorting operation data and the sorting image data of the detection node includes:

[0081] The target sensor of the detection node is determined, and the sorting operation data and the sorting image data collected by the target sensor are acquired according to the detection trigger condition in the detection node.

[0082] In an embodiment of the present invention, the sorting and transmission equipment is equipped with numerous sensors. However, not every sensor collects data relevant to the current detection node. Therefore, before acquiring sorting operation data and sorting image data, it is necessary to determine the sensor whose data is relevant to the current detection node, i.e., the target sensor. This determination of the target sensor can be achieved through a list query. Specifically, a pre-built list of correspondences between sensors and detection objects is retrieved to identify sensors that match the detection object of the current detection node. For example, if the detection object of the current detection node is voltage detection, only the voltage detection sensor and the sensor used for voltage detection line wiring image acquisition need to be determined as target sensors; data from other sensors can be omitted. After determining the target sensor, monitoring is performed according to the detection trigger conditions. If the detection trigger conditions are met, sorting operation data and sorting image data are acquired from the target sensor. By determining the target sensor, the scope of data acquisition can be further narrowed, reducing the amount of data transmission and data processing.

[0083] 104. Combining and identifying the sorting operation data and the sorting image data according to the detection hysteresis parameter, the detection object, and the detection target to obtain a sorting detection result of the electric energy meter.

[0084] In an embodiment of the present invention, after executing each detection node, sorting operation data and sorting image data corresponding to all detection objects of each electric energy meter are obtained. The sorting operation data and sorting image data are then judged based on the threshold or numerical range represented by the detection target to determine whether the sorting detection result of the electric energy meter corresponding to the sorting operation data and sorting image data is normal or abnormal. If the sorting operation data and sorting image data meet the corresponding threshold or range, the sorting detection result of the corresponding electric energy meter is normal. Conversely, if at least one of the sorting operation data and sorting image data meets the corresponding threshold or range, the sorting detection result of the corresponding electric energy meter is abnormal. Before making a judgment based on the detection target, it is necessary to determine the consistency of the detection object corresponding to the sorting operation data and sorting image data. Specifically, the consistency of the sorting operation data and sorting image data can be verified using a detection hysteresis parameter and the detection object. If the verification passes, the sorting operation data and sorting image data are then identified based on the detection target corresponding to the detection object. If the verification result fails, the abnormal sorting detection result may also be output. That is to say, the abnormal sorting detection result may indicate abnormal detection data or abnormal operation of the sorting detection equipment.

[0085] It should be noted that because the detection lag parameters and detection trigger conditions used to guide the acquisition of sorting operation data and sorting image data are aligned, the timing of acquiring sorting operation data and sorting image data is accurate. Furthermore, during the identification process of sorting detection results, the detection lag parameters, the detection object, and the detection target serve as the identification basis, effectively ensuring the matching of sorting operation data and sorting image data, thereby ensuring the accuracy of the sorting detection results.

[0086] In one embodiment of the present invention, for further explanation and limitation, the step of combining and identifying the sorting operation data and the sorting image data according to the detection hysteresis parameter, the detection object, and the detection target to obtain the sorting detection result of the electric energy meter includes:

[0087] Determining the acquisition time and acquisition sequence of the sorting operation data and the sorting image data, and generating a detection data sequence based on the acquisition time and the acquisition sequence;

[0088] comparing the detection data sequence with the detection hysteresis parameter;

[0089] If the detection data sequence matches the detection hysteresis parameter, a one-to-one matching identification is performed based on the detection data sequence, the detection object, and the detection target to generate a sorting detection result;

[0090] If the detection data sequence does not match the detection hysteresis parameter, the detection data sequence is adjusted according to the detection hysteresis parameter, and a one-to-one matching and identification is performed between the adjusted detection data sequence and the detection target to generate a sorting detection result.

[0091] In an embodiment of the present invention, when the detection lag parameter is expressed in time, after acquiring the sorting image data and sorting operation data, the data is sorted according to their corresponding acquisition times and the acquisition order between each of the sorting image data and sorting operation data to obtain a detection data sequence. The detection data sequence includes the acquisition time intervals between each data point. This acquisition time interval is compared with the lag time period in the detection lag parameter. If a match is found, it indicates that the adjustment of the detection trigger conditions before the sorting detection is performed is effective, and the obtained sorting image data and sorting operation data match. Data anomalies can be determined using thresholds or ranges corresponding to the sorting image data and sorting operation data in the detection target. If the detection data sequence does not match the detection lag parameter, indicating a deviation between the actual data acquisition process and the expected time of the detection trigger condition, the time intervals in the detection data sequence are adjusted according to the time intervals in the detection lag parameter to obtain a detection data sequence that matches the detection lag parameter, i.e., the adjusted detection data sequence. The adjustment may be to shorten the time interval or to extend the time interval. Preferably, the time interval may be adjusted in a direction that minimizes the difference with the hysteresis period, which is not specifically limited in the embodiment of the present invention.

[0092] In one embodiment of the present invention, for further illustration and limitation, the method further includes:

[0093] If the sorting detection result is an abnormality detection, the abnormality type is determined and warning information matching the abnormality type is output.

[0094] In an embodiment of the present invention, if the sorting image data and the sorting operation data exceed corresponding thresholds or range values, for example, the distance between the voltage detection connector in the sorting image data and the detection port of the electric energy meter exceeds the corresponding distance threshold, or the voltage value in the sorting operation data exceeds the rated voltage value of the voltmeter, then it can be determined that the detection result is abnormal. For the above two abnormalities, they can be determined as sorting image data abnormality and sorting operation data abnormality respectively. Of course, abnormalities also include missing sorting image data and sorting operation data abnormalities. After determining the abnormality type, the warning information corresponding to the current abnormality type is matched from the pre-constructed warning information corresponding to different abnormality types, and then the warning information is sent to the production line terminal to prompt the production line inspection personnel to confirm.

[0095] The present invention provides a method for sorting and detecting electric energy meters on an intelligent sorting platform. Compared with the prior art, the embodiment of the present invention obtains all pre-configured detection nodes in the intelligent sorting platform and aligns the detection hysteresis parameters, detection objects, and detection trigger conditions in the detection nodes to obtain standardized detection nodes. When a sorting task list is received, the detection target of the electric energy meter in the sorting task list is parsed, and the detection target is used to represent the extreme value or numerical range of the detection object through detection. When the electric energy meter is detected to be placed on a sorting transmission device, the sorting operation data and sorting image data of the detection node are obtained. The sorting operation data and sorting image data are combined and identified according to the detection hysteresis parameters, the detection objects, and the detection targets to obtain the sorting detection results of the electric energy meter. By aligning the detection hysteresis parameters and detection trigger conditions in the detection nodes before sorting detection, and identifying the sorting operation data and sorting image data according to the detection hysteresis parameters during the sorting operation data and sorting image data identification process, the matching of the sorting operation data and the sorting image data can be ensured, thereby ensuring the accuracy of the sorting detection results.

[0096] Furthermore, as a response to the above Figure 1 The embodiment of the present invention provides an electric energy meter sorting detection system for an intelligent sorting platform, such as Figure 3 As shown, the system includes:

[0097] An alignment module 31 is used to obtain all pre-configured detection nodes in the intelligent sorting platform and align the detection hysteresis parameters, detection objects, and detection trigger conditions in the detection nodes to obtain standardized detection nodes;

[0098] The parsing module 32 is configured to, upon receiving a sorting task list, parse the detection target of the electric energy meter in the sorting task list, wherein the detection target is used to represent an extreme value or a value range of the detection object passing the detection;

[0099] An acquisition module 33 is configured to acquire the sorting operation data and sorting image data of the detection node after detecting that the electric energy meter is placed on the sorting and transmission device;

[0100] The identification module 34 is configured to perform combined identification on the sorting operation data and the sorting image data according to the detection hysteresis parameter, the detection object, and the detection target to obtain a sorting detection result of the electric energy meter.

[0101] Furthermore, the alignment module 31 includes:

[0102] a first determining unit, configured to obtain the number of sorting devices of the same detection function type in the detection node and a sorting transmission distance, and determine the detection hysteresis parameter based on the number and the sorting transmission distance;

[0103] A query unit, configured to query a detection object matching the detection function type based on a function-object mapping relationship, and retrieve an initial detection trigger condition matching the detection object, wherein the detection trigger condition includes at least one of a time trigger condition, a signal trigger condition, and an identification trigger condition;

[0104] An alignment unit is configured to align the initial detection trigger conditions of the various sorting devices according to the detection hysteresis parameter to obtain detection trigger conditions corresponding to different sorting devices.

[0105] Furthermore, the analysis module 32 includes:

[0106] a parsing unit, configured to parse a row identifier and a column identifier in the sorting task list, wherein the row identifier is used to represent the identity of the electric energy meter, and the column identifier is used to represent the function parameter of the device;

[0107] The second determining unit is configured to select a detection object and a corresponding extreme value or numerical range from a detection object library based on the numerical weight value between the row identifier and the column identifier, and determine the detection object as the detection target.

[0108] Furthermore, the acquisition module 33 includes:

[0109] An acquisition unit is configured to determine a target sensor of the detection node and acquire the sorting operation data and the sorting image data collected by the target sensor according to a detection trigger condition in the detection node.

[0110] Furthermore, the identification module 34 includes:

[0111] a third determining unit, configured to determine the acquisition time and acquisition sequence of the sorting operation data and the sorting image data, and generate a detection data sequence based on the acquisition time and the acquisition sequence;

[0112] a comparison unit, configured to compare the detection data sequence with the detection hysteresis parameter;

[0113] an identification unit, configured to, if the detection data sequence matches the detection hysteresis parameter, perform one-to-one matching and identification based on the detection data sequence, the detection object, and the detection target, to generate a sorting detection result;

[0114] an adjustment unit, configured to adjust the detection data sequence according to the detection hysteresis parameter if the detection data sequence does not match the detection hysteresis parameter, and perform one-to-one matching and identification between the adjusted detection data sequence and the detection target to generate a sorting detection result.

[0115] Furthermore, the system further comprises:

[0116] The early warning module is used to determine the abnormality type if the sorting detection result is an abnormality detection, and output early warning information matching the abnormality type.

[0117] The present invention provides an electric energy meter sorting and detection system for an intelligent sorting platform. Compared with the prior art, the embodiment of the present invention obtains all pre-configured detection nodes in the intelligent sorting platform and aligns the detection hysteresis parameters, detection objects, and detection trigger conditions in the detection nodes to obtain standardized detection nodes. When a sorting task list is received, the detection target of the electric energy meter in the sorting task list is parsed, and the detection target is used to represent the extreme value or numerical range of the detection object through detection. When the electric energy meter is detected to be placed on the sorting transmission device, the sorting operation data and sorting image data of the detection node are obtained. The sorting operation data and sorting image data are combined and identified according to the detection hysteresis parameters, the detection objects, and the detection targets to obtain the sorting detection results of the electric energy meter. By aligning the detection hysteresis parameters and detection trigger conditions in the detection nodes before sorting detection, and identifying the sorting operation data and sorting image data according to the detection hysteresis parameters during the sorting operation data and sorting image data identification process, the matching of the sorting operation data and the sorting image data can be ensured, thereby ensuring the accuracy of the sorting detection results.

[0118] According to one embodiment of the present invention, a storage medium is provided, wherein the storage medium stores at least one executable instruction. The computer executable instruction can execute the electric energy meter sorting and detection method of the intelligent sorting platform in any of the above method embodiments.

[0119] Figure 4 A schematic structural diagram of a terminal provided according to an embodiment of the present invention is shown. The specific embodiment of the present invention does not limit the specific implementation of the terminal.

[0120] like Figure 4 As shown, the terminal may include: a processor (processor) 402 , a communications interface (Communications Interface) 404 , a memory (memory) 406 , and a communication bus 408 .

[0121] The processor 402 , the communication interface 404 , and the memory 406 communicate with each other via a communication bus 408 .

[0122] The communication interface 404 is used for network communication with other devices such as a client or other servers.

[0123] The processor 402 is configured to execute the program 410 , and specifically to execute the relevant steps in the embodiment of the electric energy meter sorting and detection method of the intelligent sorting platform.

[0124] Specifically, the program 410 may include program codes, which include computer operation instructions.

[0125] Processor 402 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement embodiments of the present invention. The one or more processors included in the terminal may be processors of the same type, such as one or more CPUs, or processors of different types, such as one or more CPUs and one or more ASICs.

[0126] The memory 406 is used to store the program 410. The memory 406 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk storage.

[0127] The program 410 may be specifically configured to cause the processor 402 to perform the following operations:

[0128] Acquire all pre-configured detection nodes in the intelligent sorting platform, and align the detection hysteresis parameters, detection objects, and detection trigger conditions in the detection nodes to obtain standardized detection nodes;

[0129] When a sorting task list is received, parsing the detection target of the electric energy meter in the sorting task list, the detection target is used to represent the extreme value or value range of the detection object passing the detection;

[0130] When it is detected that the electric energy meter is placed on the sorting and transmission device, the sorting operation data and the sorting image data of the detection node are obtained;

[0131] The sorting operation data and the sorting image data are combined and identified according to the detection hysteresis parameter, the detection object, and the detection target to obtain a sorting detection result of the electric energy meter.

[0132] Obviously, those skilled in the art will appreciate that the various modules or steps of the present invention described above can be implemented using a general-purpose computing system. They can be centralized on a single computing system or distributed across a network of multiple computing systems. Alternatively, they can be implemented using program code executable by a computing system, and thus, they can be stored in a storage system and executed by the computing system. In some cases, the steps shown or described herein can be performed in a different order than that shown, or they can be fabricated into separate integrated circuit modules, or multiple modules or steps can be fabricated into a single integrated circuit module. Thus, the present invention is not limited to any particular combination of hardware and software.

[0133] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A method for sorting and detecting electric energy meters on an intelligent sorting platform, characterized in that: include: Acquire all pre-configured detection nodes in the intelligent sorting platform, and align the detection hysteresis parameters, detection objects, and detection trigger conditions in the detection nodes to obtain standardized detection nodes; When receiving the sorting task list, parsing the detection target of the electric energy meter in the sorting task list, the detection target is used to represent the extreme value or value range of the detection object through the detection; When it is detected that the electric energy meter is placed on the sorting and transmission device, the sorting operation data and the sorting image data of the detection node are obtained; The sorting operation data and the sorting image data are combined and identified according to the detection lag parameter, the detection object, and the detection target to obtain a sorting detection result of the electric energy meter.

2. The method according to claim 1, characterized in that The analysis of the detection hysteresis parameter, detection object, and detection trigger condition in the detection node includes: Acquire the number of sorting devices belonging to the same detection function type in the detection node and the sorting transmission distance, and determine the detection lag parameter based on the number and the sorting transmission distance; Based on the function-object mapping relationship, query the detection object matching the detection function type, and retrieve the initial detection trigger condition matching the detection object, wherein the detection trigger condition includes at least one of a time trigger condition, a signal trigger condition, and an identification trigger condition; The initial detection trigger conditions of each sorting device are aligned according to the detection hysteresis parameter to obtain detection trigger conditions corresponding to different sorting devices.

3. The method according to claim 2, characterized in that The analysis of the detection targets of the electric energy meters in the sorting task list includes: Parsing the row identifier and the column identifier in the sorting task list, wherein the row identifier is used to characterize the identity of the electric energy meter, and the column identifier is used to characterize the function parameter of the device; Based on the numerical weight value between the row identifier and the column identifier, a detection object and a corresponding extreme value or numerical range are selected from the detection object library to be determined as the detection target.

4. The method according to claim 3, characterized in that The obtaining of the sorting operation data and the sorting image data of the detection node comprises: The target sensor of the detection node is determined, and the sorting operation data and the sorting image data collected in the target sensor are acquired according to the detection trigger condition in the detection node.

5. The method according to claim 1, characterized in that The step of combining and identifying the sorting operation data and the sorting image data according to the detection hysteresis parameter, the detection object, and the detection target to obtain the sorting detection result of the electric energy meter includes: Determine the acquisition time and acquisition sequence of the sorting operation data and the sorting image data, and generate a detection data sequence based on the acquisition time and the acquisition sequence; comparing the detection data sequence with the detection hysteresis parameter; If the detection data sequence matches the detection hysteresis parameter, a one-to-one matching identification is performed based on the detection data sequence, the detection object, and the detection target to generate a sorting detection result; If the detection data sequence does not match the detection hysteresis parameter, the detection data sequence is adjusted according to the detection hysteresis parameter, and a one-to-one matching and identification is performed based on the adjusted detection data sequence and the detection target to generate a sorting detection result.

6. The method according to claim 1, characterized in that The method further comprises: If the sorting detection result is an abnormality detection, the abnormality type is determined, and warning information matching the abnormality type is output.

7. An electric energy meter sorting and detection system for an intelligent sorting platform, characterized in that: include: An alignment module is used to obtain all pre-configured detection nodes in the intelligent sorting platform, and align the detection hysteresis parameters, detection objects, and detection trigger conditions in the detection nodes to obtain standardized detection nodes; A parsing module, for parsing the detection target of the electric energy meter in the sorting task list when receiving the sorting task list, wherein the detection target is used to represent the extreme value or value range of the detection object through the detection; An acquisition module, used for acquiring the sorting operation data and the sorting image data of the detection node after detecting that the electric energy meter is placed on the sorting transmission device; The identification module is used to combine and identify the sorting operation data and the sorting image data according to the detection lag parameter, the detection object, and the detection target to obtain the sorting detection result of the electric energy meter.

8. The system according to claim 7, characterized in that The alignment module comprises: a determining unit, configured to obtain the number of sorting devices of the same detection function type in the detection node and the sorting transmission distance, and determine the detection lag parameter based on the number and the sorting transmission distance; A query unit is used to query the detection object matching the detection function type based on the function-object mapping relationship, and retrieve the initial detection trigger condition matching the detection object, wherein the detection trigger condition includes at least one of a time trigger condition, a signal trigger condition, and an identification trigger condition.

9. A storage medium, wherein at least one executable instruction is stored in the storage medium, and the executable instruction enables a processor to execute operations corresponding to the electric energy meter sorting detection method of the intelligent sorting platform as described in any one of claims 1-6.

10. A terminal, comprising: A processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface communicate with each other via the communication bus; The memory is used to store at least one executable instruction, and the executable instruction enables the processor to perform operations corresponding to the electric energy meter sorting detection method of the intelligent sorting platform as described in any one of claims 1-6.

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