A meter reading method based on ammeter type learning, an intelligent fusion terminal and a medium

Abstract

The application relates to the technical field of terminal data acquisition, and particularly provides a meter reading method based on electric meter type learning, an intelligent fusion terminal and a medium, the method comprising the following steps: prioritizing electric meter types according to the number of data items supported by new three-phase meters, new single-phase meters, old three-phase meters and old single-phase meters; marking the electric meter type of a to-be-tested electric meter as a historical record and starting reading detection at a preset self-learning time; sending detection messages corresponding to the electric meter types to the to-be-tested electric meter in sequence to determine a detection result; determining the electric meter type of the to-be-tested electric meter based on the detection result and the historical record, and determining whether to perform data re-reading based on the priority of the electric meter type corresponding to the detection result and the priority of the electric meter type corresponding to the historical record. The detection is performed at a fixed time every day, the detection result is compared with a previous result, a reading strategy is selected according to the electric meter type priority and the detection message, and the electric meter type is automatically identified.

Description

Technical Field

[0001] This invention belongs to the field of terminal data acquisition technology, and particularly relates to a meter reading method based on meter type learning, an intelligent fusion terminal, and a medium. Background Technology

[0002] With the deepening of smart grid construction, electricity information collection terminals have been deployed on a large scale. Currently, power line carrier meters operating in the power grid are mainly divided into two categories based on their communication protocol: one is the electricity meter supporting the DL / T 698 protocol (hereinafter referred to as 698 meter), and the other is the electricity meter supporting the DL / T 645 protocol (hereinafter referred to as 645 meter). In the existing market and current bidding projects, 645 meters still occupy a large share, and their reading scheme directly affects the overall operating efficiency of the collection terminal.

[0003] The DL / T 645 protocol has undergone several evolutions since its introduction. Using 2013 as a dividing line, the load data format defined in versions of the protocol prior to 2013 is generally referred to in the field as load records (hereinafter collectively referred to as old loads), and its data organization method is relatively simple. After 2013, it is called load curves (hereinafter collectively referred to as new loads), and load curves are further refined into two organizational forms: block data (supporting batch transmission of multiple data items) and single-item data (supporting single data item reading). Meanwhile, from the perspective of meter phase line type, DL / T 645 meters are divided into three-phase meters and single-phase meters. The combination of these two dimensions forms four types of meters: new three-phase meters (supporting both new load block data and single-item data, as well as old load block data), new single-phase meters (supporting new load single-item data), old three-phase meters (not supporting new load data, supporting old load block data), and old single-phase meters (supporting old load block data). For the new three-phase meter, all three types of messages can be successfully responded to; for the new single-phase meter, only the new load single-item data can be successfully responded to; and for the old three-phase meter and the old single-phase meter, only the old load block data can be successfully responded to.

[0004] However, the DL / T 645 standard protocol does not define a universal command for querying or negotiating meter types. This means the data acquisition terminal cannot determine which of the four types a meter belongs to by sending a single query command. The master station system also cannot pre-determine the exact type of each meter connected to each data acquisition terminal through remote configuration or unified logic. Therefore, in actual meter reading operations, the data acquisition terminal cannot know which load data format each meter on site specifically supports.

[0005] The current common meter reading strategy is as follows: in each meter reading task, the data acquisition terminal attempts to send the three types of messages (new load block data message, new load single-item data message, and old load block data message) to each meter sequentially until a valid response is received. Since the data acquisition terminal cannot predict which messages the current meter supports before reading, in extreme cases, it needs to traverse all three types of messages to complete a valid reading, significantly extending the time required for single-meter reading. In large-scale data acquisition systems, the terminal often needs to manage hundreds or even thousands of meters. This multi-round, meter-by-meter approach severely limits the number of meters that can be read per unit time, resulting in low overall data acquisition efficiency.

[0006] Even more problematic is that data acquisition terminals typically operate using a multi-task scheduling mechanism. If a meter reading task hasn't completed traversing all three types of messages during execution, and the terminal scheduling strategy switches processing resources to other tasks, then the meter reading for that specific time will fail to obtain valid data, resulting in data deficiencies for that meter within the current reading cycle. In actual operation, this directly manifests as a decrease in the meter reading success rate. Since power data acquisition terminals have strict performance indicators for data integrity and reading success rate, the aforementioned issues directly impact the system's operational quality evaluation. Summary of the Invention

[0007] To address the problems existing in the prior art, this invention provides a meter reading method based on meter type learning, comprising the following steps: Step S1: Prioritize the meter types according to the number of data items supported by the new three-phase meter, the new single-phase meter, the old three-phase meter, and the old single-phase meter; Step S2: During the preset self-learning time, mark the meter type of the meter under test as a historical record and start the meter reading detection. Step S3: Send detection messages corresponding to each meter type to the meter under test in sequence, and determine the detection result based on the received meter response. The detection result is the meter type corresponding to the detection message that successfully responded in this test. Step S4: Determine the meter type of the meter to be tested based on the current detection result and the historical record, and determine whether to perform data re-reading based on the priority of the meter type corresponding to the current detection result and the priority of the meter type corresponding to the historical record.

[0008] Preferably, the detection messages in step S3 are, in sequence: a new load block data message corresponding to the new three-phase meter, a new load single-phase data message corresponding to the new single-phase meter, and an old load block data message corresponding to the old three-phase meter and the old single-phase meter.

[0009] Specifically, step S4 includes: If the current detection result is the same as the meter type in the historical record, then the current detection result will be recorded as the current meter type of the meter under test. If the current detection result is different from the meter type in the historical records, determine whether the priority of the meter type corresponding to the current detection result is higher than the priority of the meter type corresponding to the historical records; If so, then the data from the previous day should be copied according to the meter reading method corresponding to the current detection result, and the current detection result should be recorded as the current meter type of the meter to be tested; if not, then after waiting for a preset time, steps S3 to S4 should be executed again.

[0010] Based on the above scheme, if no valid response is received after sending all probe messages, it is determined that the communication link is abnormal, and an adaptive delay retry process based on the Fibonacci sequence is initiated.

[0011] Specifically, the adaptive delay retry process based on the Fibonacci sequence includes: The time delay sequence is generated sequentially according to the recursive relationship of the Fibonacci sequence; Delays are performed sequentially according to the delay time sequence, and probe messages are sent sequentially after each delay to perform the probe. If no valid response is received after the cumulative delay reaches the preset maximum delay time, the current meter will be marked as an abnormal meter.

[0012] Based on the above scheme, the detection result is obtained by delaying and retrying using the Fibonacci sequence. If the two detection results are consistent, the final meter type is locked; if there is a continuous conflict, the detection is delayed and retried until the result converges.

[0013] Specifically, in step S4, after waiting for a preset time, steps S3 to S4 are re-executed. During the re-execution process, if the detection result is the same as the historical record or any previous detection result, the repeated detection is stopped and the same detection result is recorded as the current meter type of the meter under test.

[0014] Preferably, the preset self-learning time is the free time in the early morning of each day. After determining the meter type of the meter to be tested in step S4, the reading is performed according to the reading method corresponding to the recorded meter type.

[0015] On the other hand, the present invention also provides an intelligent fusion terminal, comprising: The storage unit is used to store the historical records of the electricity meter and priority information for various electricity meter types. The priority information is sorted according to the number of data items supported by the new three-phase meter, the new single-phase meter, the old three-phase meter, and the old single-phase meter. The detection unit is used to initiate the meter reading detection at a preset self-learning time; it includes: sequentially sending detection messages corresponding to each meter type to the meter under test, determining the detection result based on the received meter response, and the detection result being the meter type corresponding to the detection message that successfully responded this time; The processing unit is used to determine the meter type of the meter under test based on the current detection result and the historical record, and to determine whether to perform data re-reading based on the priority of the meter type corresponding to the current detection result and the priority of the meter type corresponding to the historical record.

[0016] The present invention also provides a computer-readable storage medium having a computer program, which, when executed by a processor, implements the steps of the meter reading method based on meter type learning as described above.

[0017] Compared with the prior art, the present invention has the following beneficial effects: 1. Through a daily self-learning mechanism, the three types of messages are traversed only once a day, significantly shortening the reading time of a single table and greatly increasing the number of effective meter readings per unit time; 2. Prioritizing and sorting data by phenotypic order enables rapid completion within the time window of multi-task scheduling, fundamentally eliminating the problem of missing data caused by traversal interruption; at the same time, the Fibonacci adaptive delay retry mechanism achieves a balance between timely retries and congestion avoidance in the event of communication anomalies, improving the communication success rate in weak network environments. 3. When the meter type changes to a higher priority, the previous day's data is automatically re-read to ensure that historical data is not lost after the meter is upgraded or replaced; multiple detection and verification under low priority effectively avoids misjudgment caused by environmental interference and ensures the accuracy of data collection. 4. No modification is required to the communication protocol between the meter and the master station; only the terminal software needs to be upgraded, resulting in low modification costs and strong versatility. Attached Figure Description

[0018] Figure 1 This is an overall flowchart of the meter reading method based on meter type learning according to the present invention; Figure 2 This is a flowchart illustrating the meter reading method based on meter type learning according to the present invention. Detailed Implementation

[0019] The invention will be further described below with reference to specific embodiments.

[0020] In existing technologies, data acquisition terminals typically attempt to send multiple messages to each 645 meter sequentially until a valid response is received. The fundamental flaw in this approach is that the terminal cannot predict the meter type before reading the data, and each reading incurs the time cost of traversing multiple messages. In a multi-task scheduling environment, interruptions before completion are frequent, directly resulting in no valid data for that meter in the current cycle, thus significantly reducing the reading success rate.

[0021] Those skilled in the art should understand that the DL / T 645 standard protocol does not define a general instruction for querying or negotiating the meter type. Therefore, in cases where the meter type cannot be confirmed by querying the meter according to the existing standard protocol, the present invention determines the meter type by collecting data through trial and error.

[0022] To address the above problems, this invention provides a meter reading method based on meter type learning, such as... Figure 1 As shown, it includes the following steps: Step S1: Prioritize the meter types according to the number of data items supported by the new three-phase meter, the new single-phase meter, the old three-phase meter, and the old single-phase meter; In this embodiment, the meter under test is an energy meter that supports the DL / T 645 protocol. According to the protocol format and phase supported by the 645 meter, the 645 meter is divided into four types: new three-phase meter, old three-phase meter, new single-phase meter and old single-phase meter; the new and old correspond to the load format defined by the protocol versions around 2013.

[0023] Different table types have different capabilities in supporting the three types of read messages: new load block data, new load sub-item data, and old load block data. In this embodiment, the four types of 645 tables are prioritized based on the number of data items supported by different table types and the protocol type: new three-phase table > new single-phase table > old three-phase table > old single-phase table.

[0024] Step S2: During the preset self-learning time, mark the meter type of the meter under test as a historical record and start the meter reading detection. The preset self-learning time is preferably during the off-peak hours in the early morning. In one specific embodiment, 1:00 AM is selected as the self-learning time based on actual site conditions and safety checks. During this period, the communication load of the electricity information collection system is low, and the concentrator's processing resources are relatively abundant, making it suitable for performing meter type detection tasks. By periodically reading and detecting the meter at this time, the meter type is automatically identified.

[0025] Step S3: Send detection messages corresponding to each meter type to the meter under test in sequence. Determine the detection result based on the received meter response. The detection result is the meter type corresponding to the detection message that successfully responded this time. The detection messages are sent in the following order: new load block data message corresponding to the new three-phase meter, new load single-phase data message corresponding to the new single-phase meter, and old load block data message corresponding to the old three-phase meter and the old single-phase meter. The specific order of sending the detection messages is as follows: S3.1: Send a new load block data message for reading. If the reading is successful, record the detection result as a new three-phase meter. S3.2: If the new load block data is not successfully read, send the new load single-phase data for reading. If the reading is successful, record the detection result as a new single-phase meter. S3.3: If the new load data is not successfully copied, the old load block data is sent for copying. If the copying is successful, the detection result is recorded as the old 645 table.

[0026] Further, in step S4, the meter type of the meter to be tested is determined based on the current detection results and historical records, and whether to perform data re-reading is determined based on the priority of the meter type corresponding to the current detection results and the priority of the meter type corresponding to the historical records.

[0027] Specifically, such as Figure 2 As shown, step S4 includes: If the current detection result is the same as the meter type in the historical records, then the current detection result will be recorded as the current meter type of the meter under test. If the current detection result is different from the meter type in the historical records, determine whether the priority of the meter type corresponding to the current detection result is higher than the priority of the meter type corresponding to the historical records; If the current detection result has a higher priority, then the data from the previous day will be copied according to the meter reading method corresponding to the current detection result, and the current detection result will be recorded as the current meter type of the meter under test; if the historical record has a higher priority, then steps S3 to S4 will be executed again after a preset time.

[0028] A high priority in the detection results indicates that the previous day's detection results were incorrect, possibly due to communication failures during the detection period. Higher priority means that the table is newer and supports more complete data items for copying. The previous day's data may not have been fully retrieved when copied according to the old type, so it is necessary to re-copy the previous day's data according to the new type to ensure data integrity.

[0029] It should be noted that, since there is no individual data in the old load data, the old single-phase meter is read according to the load block data, and the data items read are the same.

[0030] Furthermore, to prevent erroneous detection results due to environmental issues, step S4 waits for a preset time before re-executing steps S3 to S4. During this re-execution, if the detection result is the same as the historical record or any previous detection result, the repeated detection stops, and the same detection result is recorded as the final meter type of the meter under test. Specifically, if the second detection result is the same as the previous detection result or the historical record, the second detection result is recorded as the current meter type of the meter under test; if the second detection result is different from both the previous detection result and the historical record (i.e., all three results are inconsistent), the process continues to wait and execute the detection procedure again until a detection result is the same as any previous detection result or the historical record, at which point the same meter type is recorded as the final identification result.

[0031] After determining the meter type of the meter to be tested in step S4, the 645 meter was read on the same day according to the reading method corresponding to the recorded meter type.

[0032] This invention uses daily self-learning to mark the meter type, eliminating the need for redundant attempts during daily meter readings, significantly shortening the single-meter reading time and increasing the number of meters read per unit time.

[0033] Furthermore, if no valid response is received after sending all probe messages, it is determined that the communication link is abnormal, and an adaptive delay retry process based on the Fibonacci sequence is initiated.

[0034] Adaptive delay retries effectively mitigate momentary interference and improve the success rate of copying. The adaptive delay retries process based on the Fibonacci sequence includes: The time delay sequence is generated sequentially according to the recursive relationship of the Fibonacci sequence; in this embodiment, the sequence is 1min, 1min, 2min, 3min, 5min, 8min, 13min, ...; Delays are performed sequentially according to the delay time sequence, and probe messages are sent sequentially after each delay to perform the probe. If no valid response is received after the cumulative delay reaches the preset maximum delay time, the current meter is marked as an abnormal meter. The preset maximum delay time is set according to actual needs to avoid invalid communication consuming system resources.

[0035] The detection results are obtained by adaptive delay retry using the Fibonacci sequence. If the two detection results are consistent, the final meter type is locked; if there is a continuous conflict, the delay retry is performed until the results converge.

[0036] The Fibonacci sequence is used as the delay sequence because its growth rate falls between linear and exponential backoff. During brief communication interruptions, the first few terms have shorter delays, allowing for rapid retries to capture the opportunity for channel recovery. During continuous congestion, subsequent terms gradually increase, avoiding increased link burden due to dense packet transmission. This balanced characteristic makes it particularly suitable for applications in power line carrier communication where channel quality fluctuates frequently.

[0037] In addition, when the detection results are inconsistent with the historical records, the adaptive delay retry process of the Fibonacci sequence can be used to re-execute the detection. If the results are consistent for two consecutive times, the final type is locked. If the conflict continues, the delay retry continues until the results converge, thereby ensuring that the phenotypic identification is accurate and reliable.

[0038] Based on the same technical concept, the present invention also provides an intelligent fusion terminal, comprising: The storage unit is used to store priority information for various meter types. The priority information is sorted according to the number of data items supported by the new three-phase meter, the new single-phase meter, the old three-phase meter, and the old single-phase meter. The detection unit is used to mark the current meter type of the meter under test as a historical record within a preset self-learning time and start the meter reading detection; including: sequentially sending detection messages corresponding to each meter type to the meter under test, determining the detection result based on the received meter response, and the detection result being the meter type corresponding to the detection message that successfully responded this time; The processing unit is used to determine the type of the meter to be tested based on the current detection result and the historical records, and to determine whether to perform data re-reading based on the priority of the meter type corresponding to the current detection result and the priority of the meter type corresponding to the historical records.

[0039] After completing the above detection and identification process, the processing unit stores the finally determined meter type in the storage unit as the current meter type.

[0040] During the subsequent periods of the day (i.e., from the start of this self-learning session to the next self-learning session), the terminal schedules all meter reading tasks according to the reading method corresponding to that meter type. For example, if the identification result is a new three-phase meter, the new load block data message will be sent directly for reading in subsequent readings of the day, without needing to try other messages sequentially; if the identification result is an old single-phase meter, the old load block data message will be sent directly for reading.

[0041] Furthermore, the meter reading method based on meter type learning according to the present invention can be recorded in a computer-readable recording medium. Specifically, according to the present invention, a computer-readable recording medium storing computer-executable instructions can be provided, which, when executed by a processor, causes the processor to execute the meter reading method based on meter type learning as described above.

[0042] It should be noted that the flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, program segment, or portion of code containing at least one executable instruction for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0043] In general, various exemplary embodiments of the present invention can be implemented in hardware or dedicated circuitry, software, firmware, logic, or any combination thereof. Some aspects can be implemented in hardware, while others can be implemented in firmware or software that can be executed by a controller, microprocessor, or other computing device. When aspects of embodiments of the present invention are illustrated or described as block diagrams, flowcharts, or represented using certain other images, it will be understood that the blocks, apparatuses, systems, techniques, or methods described herein can be implemented as non-limiting examples in hardware, software, firmware, dedicated circuitry or logic, general-purpose hardware or controllers or other computing devices, or certain combinations thereof.

[0044] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

[0045] While the specific embodiments of the present invention have been described above, they are not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of the present invention are still within the scope of protection of the present invention.

Claims

1. A meter reading method based on meter type learning, characterized in that, Includes the following steps: Step S1: Prioritize the meter types according to the number of data items supported by the new three-phase meter, the new single-phase meter, the old three-phase meter, and the old single-phase meter; Step S2: During the preset self-learning time, mark the meter type of the meter under test as a historical record and start the meter reading detection. Step S3: Send detection messages corresponding to each meter type to the meter under test in sequence, and determine the detection result based on the received meter response. The detection result is the meter type corresponding to the detection message that successfully responded in this test. Step S4: Determine the meter type of the meter to be tested based on the current detection result and the historical record, and determine whether to perform data re-reading based on the priority of the meter type corresponding to the current detection result and the priority of the meter type corresponding to the historical record. Step S4 specifically includes: If the current detection result is the same as the meter type in the historical record, then the current detection result will be recorded as the current meter type of the meter under test. If the current detection result is different from the meter type in the historical records, determine whether the priority of the meter type corresponding to the current detection result is higher than the priority of the meter type corresponding to the historical records; If so, then the data from the previous day should be copied according to the meter reading method corresponding to the current detection result, and the current detection result should be recorded as the current meter type of the meter to be tested; if not, then after waiting for a preset time, steps S3 to S4 should be executed again.

2. The meter reading method based on meter type learning according to claim 1, characterized in that, The detection messages in step S3 are, in sequence: new load block data message corresponding to the new three-phase meter, new load single-phase data message corresponding to the new single-phase meter, and old load block data message corresponding to the old three-phase meter and the old single-phase meter.

3. The meter reading method based on meter type learning according to claim 1, characterized in that, If no valid response is received after sending all probe messages, the communication link is determined to be abnormal, and an adaptive delay retry process based on the Fibonacci sequence is initiated.

4. The meter reading method based on meter type learning according to claim 3, characterized in that, The adaptive delay retry process based on the Fibonacci sequence includes: The time delay sequence is generated sequentially according to the recursive relationship of the Fibonacci sequence; Delays are performed sequentially according to the delay time sequence, and probe messages are sent sequentially after each delay to perform the probe. If no valid response is received after the cumulative delay reaches the preset maximum delay time, the current meter will be marked as an abnormal meter.

5. The meter reading method based on meter type learning according to claim 4, characterized in that, The detection result is obtained by delaying and retrying using the Fibonacci sequence. If the two detection results are consistent, the final meter type is locked. If there is a continuous conflict, the detection is delayed and retried until the result converges.

6. The meter reading method based on meter type learning according to claim 1, characterized in that, In step S4, after waiting for a preset time, steps S3 to S4 are re-executed. During the re-execution, if the detection result is the same as the historical record or any previous detection result, the repeated detection is stopped and the same detection result is recorded as the current meter type of the meter under test.

7. The meter reading method based on meter type learning according to claim 1, characterized in that, The preset self-learning time is the free time in the early morning of each day. After determining the meter type of the meter to be tested in step S4, the reading is performed according to the reading method corresponding to the recorded meter type.

8. A smart converged terminal, characterized in that, To implement the meter reading method based on meter type learning as described in claim 1, the method includes: The storage unit is used to store the historical records of the electricity meter and priority information for various electricity meter types. The priority information is sorted according to the number of data items supported by the new three-phase meter, the new single-phase meter, the old three-phase meter, and the old single-phase meter. The detection unit is used to initiate the meter reading detection at a preset self-learning time; it includes: sequentially sending detection messages corresponding to each meter type to the meter under test, determining the detection result based on the received meter response, and the detection result being the meter type corresponding to the detection message that successfully responded this time; The processing unit is used to determine the meter type of the meter under test based on the current detection result and the historical record, and to determine whether to perform data re-reading based on the priority of the meter type corresponding to the current detection result and the priority of the meter type corresponding to the historical record.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium has a computer program that, when executed by a processor, implements the meter reading method based on meter type learning as described in any one of claims 1-7.

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