Calibration method, system and device for multi-protocol data of power Internet of Things and medium

Abstract

The invention discloses a power Internet of Things multi-protocol data calibration method, system, device and medium, and the method comprises the steps: receiving device state data reported by a plurality of communication protocols in the power Internet of Things, and analyzing the device state data to determine a gear switching critical value representing the operation state of the device under each communication protocol; based on each gear switching critical value, determining a plurality of numerical intervals used for dividing different gears under each communication protocol, and comparing the numerical intervals defined by different communication protocols for the operation state of the same equipment so as to determine conflict intervals among the plurality of communication protocols in gear division, drift point sets which are divided to different gears under different communication protocols are identified from the conflict interval; and on the basis of the numerical value distribution characteristics of the drift point set, each gear switching critical value is calibrated to obtain a calibration result of the multi-protocol data, so that the calibration accuracy of the multi-protocol data of the power Internet of Things can be improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of data processing, in particular to a power internet of things multi-protocol data calibration method, system, device and medium. BACKGROUND

[0002] In the power internet of things, in order to realize comprehensive monitoring of various power equipment, the system will usually access intelligent devices supporting different communication protocols (such as IEC61850, Modbus, DNP3). These protocols are formulated by different organizations and have their own independent state definition system in design, resulting in differences in the division standards and gear boundary thresholds of the same device operating state. When these heterogeneous data converge to the internet of things platform for fusion analysis, a fundamental contradiction will arise, that is, the same device measured value at the same time may be interpreted as different operating states (for example, one protocol determines "normal" and the other determines "warning") by different protocols, thereby directly causing subsequent data analysis confusion, false alarms, control command conflicts and a series of problems, seriously threatening the reliability and decision accuracy of power grid monitoring.

[0003] The prior art tries to refine the classification level of device state as much as possible, trying to improve the judgment accuracy within a single protocol through finer granularity, but this method ignores the environment of multiple protocols coexisting. The finer the state division, the more likely the state definition boundaries between different protocols will overlap and become ambiguous, thereby amplifying the conflict area when matching across protocols. Therefore, the existing calibration method often cannot effectively identify and process the ambiguous boundary problem between protocols, and the accuracy of the calibrated data in cross-protocol state alignment is limited, and even new systematic biases may be introduced. SUMMARY

[0004] The present application provides a power internet of things multi-protocol data calibration method, system, device and medium, which can improve the accuracy of power internet of things multi-protocol data calibration.

[0005] The present application provides a power internet of things multi-protocol data calibration method, comprising: receiving device state data reported by several communication protocols in the power internet of things, analyzing the device state data to determine the gear switching critical value representing the device operating state under each communication protocol; based on each gear switching critical value, determining a plurality of numerical intervals used to divide different gears under each communication protocol, comparing the numerical intervals defined by different communication protocols for the same device operating state to determine the conflict interval between a plurality of communication protocols in gear division, and identifying a set of drift points divided into different gears under different communication protocols from the conflict interval; Based on the numerical distribution characteristics of the drift point set, the switching threshold values ​​of each gear position are calibrated to obtain the calibration results of multi-protocol data.

[0006] This invention, through standardized parsing of raw device status data reported by multiple communication protocols, accurately extracts key parameters and defined gear switching thresholds implicit in each protocol message that characterize the operating status of the same device. This avoids confusion and errors caused by direct comparison due to protocol format differences, and is a prerequisite for improving calibration accuracy. By actively comparing the definition intervals of the same state by different protocols, conflict intervals with semantic conflicts between protocols can be automatically and accurately identified. By filtering the set of drift points that were divided into different gears in actual historical data due to protocol differences from the conflict intervals, the focus can be on real data points that have drifted, excluding non-critical areas that have theoretical interval overlap but have never been touched in actual operation. By analyzing the statistical characteristics of drift points, the derived calibration offset can truly reflect the typical performance and fluctuation range of the state quantity under specific operating conditions, making the calibrated thresholds or interval divisions closer to the actual operating characteristics and conditions of the device. Thus, when fusing multi-protocol data, it can more accurately reflect the consistency of the device's state, significantly reducing the risk of misjudgment and omission due to protocol differences. Compared with existing technologies, this invention can improve the accuracy of multi-protocol data calibration in the power Internet of Things.

[0007] Furthermore, the step of parsing the device status data to determine the gear switching thresholds representing the device operating status under each communication protocol includes: According to the protocol specifications of each communication protocol, the device status data is parsed to obtain data packets; Extract the identification field used to characterize the device's operating status from the data packet; According to the respective protocol specifications, the identification field is mapped to a preset numerical range, and the threshold value for switching gears of each communication protocol is determined based on the boundary value of the preset numerical range.

[0008] By standardizing and parsing the raw device status data reported by various communication protocols, we can accurately extract the key parameters and their defined gear switching thresholds hidden in each protocol message that characterize the operating status of the same device. This avoids the confusion and errors caused by direct comparison due to differences in protocol formats, and is a prerequisite for improving calibration accuracy.

[0009] Furthermore, the step of determining several numerical ranges for dividing different gears under each communication protocol based on the gear shifting threshold values ​​includes: The gear switching thresholds of each communication protocol are sorted by numerical value to obtain the sorting result; Based on the sorting results, adjacent critical values ​​are determined, and several numerical intervals characterizing the operating states of different devices are determined using the adjacent critical values ​​as boundaries.

[0010] This method of constructing numerical ranges for each protocol based on extracted critical values ​​facilitates the automatic and accurate identification of conflict ranges where semantic conflicts exist between protocols.

[0011] Furthermore, the comparison of numerical ranges defined by different communication protocols for the same device operating state to determine the conflict ranges in the grade division between several communication protocols includes: The numerical ranges defined by different communication protocols for the same device operating state are compared. If the numerical ranges defined by different communication protocols overlap in terms of numerical range, then the overlapping portion is determined as a conflicting range in the gear division of several communication protocols.

[0012] By actively comparing the definition ranges of the same state in different protocols, conflict ranges where semantic conflicts exist between protocols can be automatically and accurately identified.

[0013] Furthermore, identifying the set of drift points that are divided into different levels under different communication protocols from the conflict interval includes: Obtain several state data points that fall into each of the aforementioned conflict intervals within a preset historical time period; Based on the gear shifting threshold corresponding to each communication protocol, determine the first interval where each state data point is located under the first communication protocol and the second interval where it is located under the second communication protocol. If the first interval and the second interval are different, the corresponding state data point is determined as a drift point, until all state data points are identified and a drift point set is obtained.

[0014] By filtering out the drift point set that was classified into different levels in actual historical data due to protocol differences from the conflict interval, we can focus on the real data points that have drifted and exclude non-critical areas that have theoretical interval overlap but have never been touched in actual operation.

[0015] Furthermore, the calibration of each gear shifting threshold based on the numerical distribution characteristics of the drift point set to obtain the calibration result of the multi-protocol data includes: Statistical analysis was performed on the values ​​of all state data points in the drift point set to obtain the centroid and dispersion of the numerical distribution. Based on the centroid of the numerical distribution and the degree of dispersion, the target calibration offset for coordinating gear conflicts is calculated. Based on the target calibration offset, the gear shifting threshold of at least one communication protocol related to the conflict interval is offset and adjusted to obtain a multi-protocol data calibration result.

[0016] By analyzing the statistical characteristics of drift points, the derived calibration offset can truly reflect the typical performance and fluctuation range of the state quantity under specific operating conditions. This makes the calibrated critical value or interval division closer to the actual operating characteristics and conditions of the equipment. Thus, when multi-protocol data is fused, it can more accurately reflect the consistency of the equipment's state and significantly reduce the risk of misjudgment or omission caused by protocol differences.

[0017] Further, the step of calculating the target calibration offset for coordinating gear shift conflicts based on the centroid of the numerical distribution and the degree of dispersion includes: Calculate the distance between the centroid of the numerical distribution and at least one of the gear shifting thresholds within the conflict interval; If the distance is less than a preset confidence threshold, the distance is used as the target calibration offset; otherwise, the confidence threshold is used as the target calibration offset, wherein the confidence threshold is set based on the degree of dispersion.

[0018] Another embodiment of the present invention provides a calibration system for multi-protocol data of the power Internet of Things, comprising: The parsing module is used to receive device status data reported by several communication protocols in the power Internet of Things, parse the device status data, and determine the gear switching threshold value that represents the device operating status under each communication protocol. The partitioning module is used to determine several numerical intervals for partitioning different gears under each communication protocol based on the gear switching threshold value, compare the numerical intervals defined by different communication protocols for the same device operating state, determine the conflict intervals between several communication protocols in gear partitioning, and identify the drift point set that is partitioned into different gears under different communication protocols from the conflict intervals. The calibration module is used to calibrate the gear shifting thresholds based on the numerical distribution characteristics of the drift point set, and obtain the calibration results of the multi-protocol data.

[0019] Another embodiment of the present invention provides a terminal device, including: a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, it implements the steps of the calibration method for multi-protocol data of the power Internet of Things as described in the present invention.

[0020] Another embodiment of the present invention provides a computer-readable storage medium item, including: a stored computer program, which, when the computer program is running, controls the device where the computer-readable storage medium is located to perform the calibration method for multi-protocol data of the power Internet of Things as described in the present invention. Attached Figure Description

[0021] To more clearly illustrate the technical solution of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0022] Figure 1 This is a flowchart illustrating an embodiment of the calibration method for multi-protocol data in the power Internet of Things provided in this application; Figure 2 This is a flowchart illustrating one embodiment of steps S201 to S202 provided in this application; Figure 3 This is a flowchart illustrating one embodiment of steps S301 to S303 provided in this application; Figure 4 This is a flowchart illustrating one embodiment of steps S401 to S403 provided in this application; Figure 5 This is a schematic diagram of the structure of one embodiment of the calibration system for multi-protocol data of the power Internet of Things provided in this application. Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0024] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the application; the terms “comprising” and “having”, and any variations thereof, in the specification, claims, and foregoing description of the drawings are intended to cover non-exclusive inclusion.

[0025] In the description of the embodiments of this application, technical terms such as "first" and "second" are used only to distinguish different objects and should not be construed as indicating or implying relative importance or implicitly specifying the number, specific order, or primary and secondary relationship of the indicated technical features. In the description of the embodiments of this application, "multiple" means two or more, unless otherwise explicitly defined.

[0026] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0027] In the description of the embodiments in this application, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this document generally indicates that the preceding and following related objects have an "or" relationship.

[0028] In the description of the embodiments of this application, the term "multiple" refers to two or more (including two), similarly, "multiple sets" refers to two or more (including two sets), and "multiple pieces" refers to two or more (including two pieces).

[0029] In the description of the embodiments of this application, unless otherwise expressly specified and limited, technical terms such as "installation," "connection," "joining," and "fixing" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. For those skilled in the art, the specific meaning of the above terms in the embodiments of this application can be understood according to the specific circumstances.

[0030] In the Internet of Things (IoT) for power systems, to achieve comprehensive monitoring of various power equipment, the system typically connects smart devices supporting different communication protocols. These protocols differ in their criteria for classifying the operating status of the same device and their threshold values ​​for different speed ranges, directly leading to confusion in subsequent data analysis. Existing technologies attempt to improve the accuracy of judgments within a single protocol through finer granularity, but this approach offers limited improvement in accuracy.

[0031] See Figure 1To improve the accuracy of multi-protocol data calibration in the power Internet of Things (IoT), an embodiment of the present invention provides a calibration method for multi-protocol data in the power IoT, comprising steps S101 to S103: Step S101: Receive device status data reported by several communication protocols in the power Internet of Things, parse the device status data, and determine the gear switching threshold value that represents the device operating status under each communication protocol. In some embodiments, receiving device status data reported by several communication protocols in the power Internet of Things (IoT) involves the following steps: First, for each communication protocol to be calibrated (such as IEC 61850, Modbus, and DNP3), the corresponding protocol stack and communication interface are configured on the access platform side to establish a communication session with the field device to receive the original protocol messages. For example, for the IEC 61850 protocol, an MMS client is configured to establish a connection with the intelligent electronic device and subscribe to relevant datasets or report control blocks to receive reports containing device status information. For the Modbus TCP protocol, a Socket connection is established between the master station and the slave device, and data areas such as holding registers are read through function codes. For the DNP3 protocol, the protocol stack is initialized and a link layer session is established with the slave station to receive response messages containing analog inputs, binary status, and other data. Then, through the established communication channel, original communication messages from the device are received in real time or at preset intervals. These original communication messages are raw byte streams containing device operating status information, and their format and encoding strictly adhere to the specifications of their respective protocols. Then, the received raw messages undergo preliminary processing to separate them from the communication frames and extract the application layer message segments carrying valid data. Subsequently, these preliminarily extracted data messages, along with their source protocol identifiers, timestamps, and other information, are stored in the platform's raw data buffer or historical database to form device status data available for subsequent processing.

[0032] In some embodiments, parsing the device status data to determine the gear switching thresholds representing the device operating status under each communication protocol includes: parsing the device status data according to the protocol specifications of each communication protocol to obtain data packets; extracting an identification field representing the device operating status from the data packets; and mapping the identification field to a preset numerical range according to the protocol specifications, so as to determine the gear switching thresholds for each communication protocol based on the boundary values ​​of the preset numerical range. Specifically, firstly, the received device status data is parsed by a parsing engine. During the parsing process, the compliance of the data format is verified, and redundant information such as protocol headers and trailers is removed. Finally, a structured data packet is output, wherein the data packet contains readable key-value pairs or a list of data points. Finally, based on the dimension conversion rules defined in the protocol specifications of each communication protocol, the original values ​​of the extracted identifier fields are mapped to a preset, unified numerical range by applying the conversion formula in the specifications. The boundary values ​​of this numerical range are then used to directly determine the gear switching threshold values ​​that characterize the device's operating status under each communication protocol. The preset numerical range is set by domain knowledge or configuration and usually covers the possible value range of the device status (such as voltage 0-15kV). The initial boundary values ​​of the numerical range are derived from the thresholds defined by the protocol specifications or expert experience.

[0033] It should be noted that the parsing engine embeds dedicated parsing modules for each communication protocol (such as IEC 60870-5-104, MQTT, etc.). Each module strictly adheres to the official specifications of its corresponding protocol (such as the transmission frame structure of IEC 60870-5-104, the payload format of MQTT, and the PDU definition of Modbus TCP) to decode data. For example, for the IEC 60870-5-104 protocol, the parsing engine will unpack the data according to the ASDU (Application Service Data Unit) structure, identifying type identifiers, variable structure qualifiers, and information object addresses; for the MQTT protocol, it will parse JSON or binary payloads to extract the subject and message body.

[0034] It should be noted that the mapping process needs to take into account protocol-specific scaling factors, offsets, and units. For example, one protocol may represent temperatures of 0-100°C in integer values ​​(range 0-2000), while another protocol may directly represent degrees Celsius in floating-point numbers.

[0035] It should be noted that the preset numerical range is usually selected from the standard physical quantity unit range (such as kilovolts kV for voltage, degrees Celsius ℃ for temperature). The purpose is to uniformly convert the original encoded values ​​(such as integer values, values ​​with scaling factors) used by different protocols into a comparable numerical system with the same physical meaning. This is the basis for subsequent cross-protocol range comparisons.

[0036] It should be noted that the gear shift threshold refers to one or more key numerical thresholds used in the specifications of a specific communication protocol to distinguish different operating states (gears) of a device.

[0037] By standardizing and parsing the raw device status data reported by various communication protocols, we can accurately extract the key parameters and their defined gear switching thresholds hidden in each protocol message that characterize the operating status of the same device. This avoids the confusion and errors caused by direct comparison due to differences in protocol formats, and is a prerequisite for improving calibration accuracy.

[0038] Step S102: Based on the gear switching threshold values, determine several numerical intervals for dividing different gears under each communication protocol, compare the numerical intervals defined by different communication protocols for the same device operating state, determine the conflict intervals between several communication protocols in gear division, and identify the drift point set that is divided into different gears under different communication protocols from the conflict intervals. In some embodiments, determining several numerical intervals for dividing different gears under each communication protocol based on each gear switching threshold includes: sorting the gear switching thresholds of each communication protocol according to their numerical values ​​to obtain a sorting result; determining adjacent thresholds based on the sorting result, and using the adjacent thresholds as boundaries to determine several numerical intervals characterizing different device operating states. Specifically, firstly, after obtaining the gear switching thresholds under each communication protocol, one or more thresholds of a protocol itself (for example, protocol A defines a threshold C1 between "normal" and "overload" and a threshold C2 between "overload" and "danger") and thresholds defined by different protocols for the same device state (such as the corresponding thresholds C3 and C4 of protocol B) are aggregated into a temporary data structure (such as an array or list). Subsequently, the system invokes a numerical sorting algorithm (such as quicksort or mergesort) to perform a global, ascending sort based on numerical size for all collected threshold values. During the sorting process, the system uses a preset numerical tolerance ε (e.g., ε = 0.001, to handle floating-point precision issues or minor setting differences) to treat threshold values ​​with an absolute value difference less than ε as equal, and retains only one representative value. This ultimately generates a strictly monotonically increasing sequence of values ​​without repetition, which is the sorting result. Finally, every two adjacent values ​​in the sorting result (e.g., the i-th value) are... and the (i+1)th value The real number line is considered as the upper and lower boundaries of a continuous numerical interval. Assuming there are N different critical values ​​after sorting, the entire real number line is naturally divided into N+1 continuous numerical intervals.

[0039] It should be noted that, in mathematical terms, this refers to a semi-open interval (e.g., a left-closed, right-open interval). , ) or left-open right-closed interval ( , The rules are used to precisely define each interval, ensuring that the entire numerical domain is completely and non-overlappingly covered. Each such interval represents a specific operating state of the device, a "gear". For example, assuming the sorted threshold value is [100, 150], the intervals could be (-∞, 100), [100, 150), and [150, +∞), corresponding to the three states of "low gear", "medium gear", and "high gear", respectively.

[0040] This method of constructing numerical ranges for each protocol based on extracted critical values ​​facilitates the automatic and accurate identification of conflict ranges where semantic conflicts exist between protocols.

[0041] Please refer to Figure 2 In some embodiments, the step of comparing the numerical ranges defined by different communication protocols for the same device operating state to determine the conflict ranges in the grade division between several communication protocols includes steps S201 to S202: Step S201: Compare the numerical ranges defined by different communication protocols for the same device operating state; In some embodiments, an index structure is first established using device state as the key, aggregating several numerical ranges representing that state from different communication protocols. Then, an iterative comparison algorithm is used to perform a comprehensive pairwise comparison of these ranges. Specifically, for any two ranges from different protocols (such as ranges from protocol A...),... , The intervals of Protocol B and Protocol B [ , The system will accurately calculate whether their numerical ranges overlap.

[0042] Step S202: If the numerical ranges defined by different communication protocols overlap in numerical range, then the overlapping part is determined as a conflict range of several communication protocols in the grade division.

[0043] In some embodiments, firstly, set operations based on real number intervals are implemented by comparing boundary values—if and only if the condition " < and > When a region of protocol A contains a region of protocol B, it is determined that the two regions overlap. When an overlap is detected, the overlapping region is immediately identified as a conflicting region in the gear segmentation.

[0044] It should be noted that the specific range of the conflict interval is calculated by taking the maximum lower bound and the minimum upper bound of the two interval boundaries, that is, the conflict interval is [max( , ), min( , This interval represents the same physical quantity value, which is classified into different levels under different protocol standards (for example, it belongs to the "normal" level in protocol A, but to the "warning" level in protocol B), thus constituting a direct semantic conflict. At this time, all communication protocols associated with the conflict interval and their original level classification are recorded to form a conflict interval.

[0045] It should be noted that if the intervals of multiple protocols (more than two) have common overlap in the same numerical domain, pairwise comparisons and set intersection operations will be performed iteratively to determine the largest common overlapping sub-interval covering all relevant protocols as the conflict interval.

[0046] It should be noted that the conflict interval refers to the part where the numerical ranges defined by different communication protocols overlap when the same device is in operation.

[0047] By actively comparing the definition ranges of the same state in different protocols, conflict ranges where semantic conflicts exist between protocols can be automatically and accurately identified.

[0048] Please refer to Figure 3 In some embodiments, identifying the set of drift points that are divided into different levels under different communication protocols from the conflict interval includes steps S301 to S303: Step S301: Obtain several state data points that fall into each of the conflict intervals within a preset historical time period; In some embodiments, data for a pre-defined historical period (e.g., "the past 30 days") is selectively retrieved from a device status data warehouse that stores parsed data with timestamps, protocol tags, and standard physical unit values. The core retrieval condition is numerical filtering: the system iterates through each previously identified "conflict interval" and, for its precise numerical range (e.g., [100.5, 125.0)), writes and executes corresponding database query statements to filter out several status data points whose physical quantity values ​​fall into any conflict interval within that historical period.

[0049] Step S302: Based on the gear shifting threshold corresponding to each communication protocol, determine the first interval where each state data point is located under the first communication protocol and the second interval where it is located under the second communication protocol. In some embodiments, for the value V of the same state data point, firstly, based on a set of predetermined gear shifting threshold value sequences corresponding to the "first communication protocol" (i.e., the original source protocol of the data point), an interval matching algorithm (e.g., comparing V with the threshold value sorting sequence) is used to determine the specific numerical range that V falls into under the protocol standard, i.e., the first interval, and its corresponding gear identifier (e.g., gear A1) is recorded. Then, based on the threshold value sequence of the second communication protocol (i.e., another comparison protocol related to the conflict interval), the system performs the same interval matching logic again on the identical value V, thereby determining the second interval and gear identifier (e.g., "gear B2") that it falls into under the second protocol standard. This results in two gear determination results based on two independent protocol specifications.

[0050] Step S303: If the first interval and the second interval are different, the corresponding state data point is determined as a drift point until all state data points are identified and a drift point set is obtained.

[0051] In some embodiments, when the gear identifiers corresponding to the "first interval" and "second interval" obtained for each state data point are obtained, the two gear identifiers are compared. If the two identifiers are the same, it indicates that although the point is located within the conflict interval, it coincidentally belongs to the same gear according to the standards of the two protocols, and therefore is not considered a conflict instance. If the two identifiers are different (for example, "gear A1" is not equal to "gear B2"), it clearly indicates that the standards of the two communication protocols have made a divergent judgment for this specific physical quantity value V. Therefore, this state data point will be regarded as a drift point. At this time, its physical quantity value V, timestamp, and the corresponding two conflict gear information are collected, and this comparison and judgment logic is executed cyclically until all state data points in all conflict intervals are traversed. Finally, all marked drift points are summarized to form a structured drift point set.

[0052] It should be noted that a drift point refers to a single device status data point in historical or real-time data whose value falls within the conflict zone and is actually assigned to a different level when judged based on the level switching threshold of different communication protocols.

[0053] By filtering out the drift point set that was classified into different levels in actual historical data due to protocol differences from the conflict interval, we can focus on the real data points that have drifted and exclude non-critical areas that have theoretical interval overlap but have never been touched in actual operation.

[0054] Step S103: Based on the numerical distribution characteristics of the drift point set, the switching threshold values ​​of each gear position are calibrated to obtain the calibration results of the multi-protocol data.

[0055] Please refer to Figure 4 In some embodiments, the calibration of each gear shifting threshold based on the numerical distribution characteristics of the drift point set to obtain the calibration result of the multi-protocol data includes steps S401 to S403: Step S401: Perform statistical analysis on the values ​​of all state data points in the drift point set to obtain the centroid and dispersion of the numerical distribution; In some embodiments, after obtaining the complete set of drift points Set all state data points in the drift point cluster. The numerical sequence is used as the input sample, and its arithmetic mean is calculated by traversing it. This arithmetic mean is used as the centroid μ of the numerical distribution of the drift point set. The calculation formula is: ; Among them, the centroid μ reflects the central tendency of the data that causes gear conflicts on the numerical axis.

[0056] Simultaneously, calculate all state data. The sample standard deviation σ or variance As a measure of dispersion, to characterize how data points are dispersed around the centroid, the sample standard deviation σ is calculated using the following formula: ; The standard deviation σ quantifies the range of fluctuation of the data points around the centroid μ.

[0057] It should be noted that, in order to improve the processing efficiency of massive amounts of data, incremental calculation or batch processing algorithms can also be used to ensure efficiency, such as using the Welford method to update the mean and variance online.

[0058] Step S402: Based on the centroid of the numerical distribution and the degree of dispersion, calculate the target calibration offset for coordinating gear conflicts; In some embodiments, step S402 includes: calculating the distance between the centroid of the numerical distribution and at least one of the gear shifting thresholds within the conflict interval; if the distance is less than a preset confidence threshold, then the distance is used as the target calibration offset; otherwise, the confidence threshold is used as the target calibration offset, wherein the confidence threshold is set based on the degree of dispersion.

[0059] In some embodiments, after obtaining the centroid μ and the degree of dispersion σ, the location is determined to be relative to the set of drift points. Corresponding specific conflict interval A critical gear shifting threshold C is selected within a specific conflict interval I that directly leads to a divergence in gear allocation. C is the threshold value that constitutes the boundary of the specific conflict interval I, and whose gear definition in the protocol it belongs to does not match the data distribution trend (for example, if the center of gravity μ is clearly located within the gear defined by protocol B, then the boundary value of protocol A in the conflict interval is selected as C). Next, the absolute distance between the distribution center μ and this critical value C is calculated using the formula: d = |μ - C|. Then, a confidence threshold θ is dynamically generated based on the degree of dispersion (standard deviation σ), calculated using the formula: θ = k·σ, where k is a preset sensitivity coefficient (e.g., k = 1.5 or 2.0). Finally, the distance d and the confidence threshold θ are compared. If the distance d is less than the confidence threshold θ, it means that the drift points are relatively closely distributed and the center of gravity is close to the current critical value. The system directly identifies the distance d as the required target calibration offset Δ. If the distance d is greater than or equal to the confidence threshold θ, it means that the distribution is relatively scattered or the center of gravity is significantly deviated. For calibration robustness considerations, the system determines the confidence threshold θ as the calibration offset Δ.

[0060] It should be noted that the sensitivity coefficient k can be set based on the assumption or experience regarding the normality of the data distribution. For example, when it is assumed that the data is approximately normally distributed, k=2.0 roughly corresponds to a 95% confidence level, which is intended to limit the calibration offset within the main distribution range of the data and avoid excessive adjustments due to individual outliers.

[0061] Step S403: Based on the target calibration offset, adjust the gear shift threshold of at least one communication protocol related to the conflict interval to obtain multi-protocol data calibration results.

[0062] In some embodiments, when the target calibration offset is obtained Subsequently, based on the target calibration offset, the critical values ​​of protocols that are inconsistent with the direction μ of the centroid of the drift point distribution in the conflict interval are adjusted first. For example, it is determined which protocol's defined gear position the centroid μ of the distribution is located in within the conflict interval (e.g., μ falls within the gear position range defined by protocol B), and then the boundary critical value corresponding to the other protocol (protocol A) is adjusted accordingly. Perform offsetting and update the formula. Where `sign` is the sign function, ensuring movement towards the center of gravity. After adjustment, recheck whether the original conflict interval has been eliminated due to the critical value update (i.e., the intervals no longer overlap), and confirm that no new gear division conflicts have been triggered in other numerical ranges.

[0063] It should be noted that all updated gear shift thresholds constitute the final multi-protocol data calibration result. The system persists this result to the configuration library and synchronizes it to the real-time data parsing engine, so that subsequent homogeneous device status data from different protocols can be consistently and accurately divided based on a unified gear boundary.

[0064] By analyzing the statistical characteristics of drift points, the derived calibration offset can truly reflect the typical performance and fluctuation range of the state quantity under specific operating conditions. This makes the calibrated critical value or interval division closer to the actual operating characteristics and conditions of the equipment. Thus, when multi-protocol data is fused, it can more accurately reflect the consistency of the equipment's state and significantly reduce the risk of misjudgment or omission caused by protocol differences.

[0065] This invention, through standardized parsing of raw device status data reported by multiple communication protocols, accurately extracts key parameters and defined gear switching thresholds implicit in each protocol message that characterize the operating status of the same device. This avoids confusion and errors caused by direct comparison due to protocol format differences, and is a prerequisite for improving calibration accuracy. By actively comparing the definition intervals of the same state by different protocols, conflict intervals with semantic conflicts between protocols can be automatically and accurately identified. By filtering the set of drift points that were divided into different gears in actual historical data due to protocol differences from the conflict intervals, the focus can be on real data points that have drifted, excluding non-critical areas that have theoretical interval overlap but have never been touched in actual operation. By analyzing the statistical characteristics of drift points, the derived calibration offset can truly reflect the typical performance and fluctuation range of the state quantity under specific operating conditions, making the calibrated thresholds or interval divisions closer to the actual operating characteristics and conditions of the device. Thus, when fusing multi-protocol data, it can more accurately reflect the consistency of the device's state, significantly reducing the risk of misjudgment and omission due to protocol differences. Compared with existing technologies, this invention can improve the accuracy of multi-protocol data calibration in the power Internet of Things.

[0066] For ease of understanding, this application provides the following examples: The oil temperature of a main transformer in a substation is monitored by two different smart terminals, and the data is reported to an IoT platform via both Modbus TCP and IEC 60870-5-104 (hereinafter referred to as the 104 protocol). The IoT platform needs to fuse and analyze the oil temperature data reported by these two protocols, but it was found that the different protocols have inconsistent standards for classifying states such as "normal," "warning," and "alarm," leading to the same temperature value being potentially classified as different states. Therefore, the calibration method described in this application is required.

[0067] First, the platform receives a Modbus TCP message, parses it to obtain the original value of register address 30001 as 120, and maps it to the standard physical value according to the Modbus protocol specification (the range is known to be 0-200 corresponding to 0-100℃): (120 / 200) * 100 = 60.0℃. At the same time, the platform receives a 104 protocol message, parses the ASDU to obtain a floating-point type "oil temperature" information object with a value of 60.0 (unit is already in℃).

[0068] Subsequently, based on pre-defined knowledge (or protocol manual), the Modbus TCP protocol sets the threshold values ​​for the transformer oil temperature range as follows: 50℃ (normal / warning boundary) and 80℃ (warning / alarm boundary). The threshold values ​​for the 104 protocol are: 60℃ (normal / caution boundary) and 85℃ (caution / alarm boundary). Thus, the system determines the original threshold value set for the two protocols: {Modbus: [50, 80], 104: [60, 85]}.

[0069] Then, all critical values ​​were sorted into [50, 60, 80, 85], and the protocol ranges were divided according to the sorting results: Modbus: Normal (-∞, 50), Warning [50, 80), Alarm [80, +∞); 104 Protocol: Normal (-∞, 60), Caution [60, 85), Alarm [85, +∞). Comparison revealed that the Modbus "Warning" range [50, 80) and the 104 Protocol "Caution" range [60, 85) overlapped in the range [60, 80). This overlapping range [60, 80) was identified as a conflict zone. At this point, the system queried all historical data points within the past month whose oil temperature values ​​fell within the conflict zone [60, 80). Suppose we find a batch of data, with a typical data point V = 65℃. We re-evaluate this point using various protocol standards: under the Modbus standard, 65 ∈ [50, 80), belonging to the warning level; under the 104 protocol standard, 65 ∈ [60, 85), belonging to the caution level. Since the same temperature value of 65℃ is classified into different levels (warning vs. caution), this point is marked as a drift point. After traversing all historical data, suppose we identify m = 100 such drift points within the conflict interval [60, 80), forming a drift point set P.

[0070] Finally, the centroid of the drift point set P (100 temperature values) was calculated to be μ = 68℃, with a standard deviation σ = 4℃. This indicates that most of the conflicting data is concentrated around 68℃, with a fluctuation range of approximately ±4℃. Since the conflict interval [60, 80) is formed by the upper boundary 80 of Modbus and the lower boundary 60 of the 104 protocol, the centroid μ = 68 is closer to the Modbus boundary 80 (12℃ away) and much larger than the 104 boundary 60 (8℃ away). To minimize adjustments, a critical value is typically chosen that indicates "greater distance from the centroid" or "a more pronounced contradiction between the gear definition and the data's central trend." In this example, we chose to adjust the lower boundary C = 60℃ of the 104 protocol's "Caution" gear because a large amount of data indicates that the temperature is around 68℃ and should no longer be classified as a lower "Caution" gear starting point by the 104 protocol. The distance was calculated using the formula of this application, and the offset was determined to be 8. The lower boundary of the "Note" setting in the 104 protocol was calibrated from 60°C to 68°C (60+8). This completed the data calibration.

[0071] like Figure 5 As shown, based on the above method embodiments, corresponding apparatus embodiments are provided; An embodiment of the present invention provides a calibration system for multi-protocol data in the power Internet of Things, comprising: The parsing module 100 is used to receive device status data reported by several communication protocols in the power Internet of Things, parse the device status data, and determine the gear switching threshold value that represents the device operating status under each communication protocol. The partitioning module 200 is used to determine several numerical intervals for partitioning different gears under each communication protocol based on the gear switching threshold value, compare the numerical intervals defined by different communication protocols for the same device operating state, determine the conflict intervals between several communication protocols in gear partitioning, and identify the drift point set that is partitioned into different gears under different communication protocols from the conflict intervals. The calibration module 300 is used to calibrate the gear switching thresholds based on the numerical distribution characteristics of the drift point set, and obtain the calibration results of the multi-protocol data.

[0072] It is understood that the above-described device embodiments correspond to the method embodiments of the present invention, and can implement the calibration method for multi-protocol data of the power Internet of Things provided by any of the above-described method embodiments of the present invention.

[0073] It should be noted that the device embodiments described above are merely illustrative, and some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Furthermore, in the accompanying drawings of the device embodiments provided by this invention, the connection relationships between modules indicate that they have communication connections, which can specifically be implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement this without any creative effort.

[0074] Based on the above embodiments of the calibration method for multi-protocol data of the power Internet of Things, another embodiment of the present invention provides a terminal device, which includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the calibration method for multi-protocol data of the power Internet of Things according to any embodiment of the present invention.

[0075] For example, in this embodiment, the computer program can be divided into one or more modules, which are stored in the memory and executed by the processor to complete the present invention. The one or more modules may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program in the terminal device.

[0076] The terminal device may be a desktop computer, laptop, handheld computer, or cloud server, etc. The terminal device may include, but is not limited to, a processor and a memory.

[0077] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor. The processor is the control center of the terminal device, connecting all parts of the terminal device via various interfaces and lines.

[0078] Based on the above-described method embodiments, another embodiment of the present invention provides a computer-readable storage medium including a stored computer program, wherein, when the computer program is executed, it controls the device where the computer-readable storage medium is located to execute the power Internet of Things multi-protocol data calibration method described in any of the above-described method embodiments of the present invention.

[0079] The modules / units integrated in the device / terminal equipment, if implemented as software functional units and sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.

[0080] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A calibration method of power internet of things multi-protocol data, characterized in that, The application relates to a method for calibrating multi-protocol data, and a device state data analysis method. The method comprises the following steps: receiving device state data reported by several communication protocols in a power internet of things, analyzing the device state data to determine gear shift critical values representing device running states under each communication protocol; based on the gear shift critical values, determining several numerical interval ranges for dividing different gears under each communication protocol, comparing numerical interval ranges defined by different communication protocols for the same device running state to determine conflict interval ranges in gear division among several communication protocols, and identifying a set of drift points divided into different gears under different communication protocols from the conflict interval ranges; 2.The calibration method of power internet of things multi-protocol data according to claim 1, wherein, based on numerical distribution characteristics of the set of drift points, calibrating the gear shift critical values to obtain a calibration result of multi-protocol data. The analysis of the device state data to determine the gear shift critical values representing device running states under each communication protocol comprises the following steps: according to protocol specifications of each communication protocol, analyzing the device state data to obtain data messages; extracting an identification field representing device running states from the data messages; 3.The calibration method of power internet of things multi-protocol data according to claim 1, characterized in that, according to the protocol specifications, mapping the identification field to a preset numerical range to determine the gear shift critical values of each communication protocol based on boundary values of the preset numerical range. The determination of the several numerical interval ranges for dividing different gears under each communication protocol based on the gear shift critical values comprises the following steps: sorting the gear shift critical values of each communication protocol according to numerical values to obtain a sorting result; 4.The calibration method of power internet of things multi-protocol data according to claim 1, characterized in that, based on the sorting result, determining adjacent critical values and determining several numerical interval ranges representing different device running states with the adjacent critical values as boundaries. The comparison of the numerical interval ranges defined by different communication protocols for the same device running state to determine conflict interval ranges in gear division among several communication protocols comprises the following steps: comparing the numerical interval ranges defined by different communication protocols for the same device running state; 5.The calibration method of power internet of things multi-protocol data according to claim 1, characterized in that, if the numerical interval ranges defined by different communication protocols overlap in numerical range, the overlapping part is determined as a conflict interval range in gear division among several communication protocols. The identification of a set of drift points divided into different gears under different communication protocols from the conflict interval ranges comprises the following steps: obtaining several state data points falling into each conflict interval range within a preset historical period; based on the gear shift critical values corresponding to each communication protocol, determining a first interval of each state data point under a first communication protocol and a second interval of each state data point under a second communication protocol; 6.The calibration method of power internet of things multi-protocol data according to claim 1, characterized in that, if the first interval and the second interval are different, the corresponding state data point is determined as a drift point, and the identification of all state data points is completed to obtain a set of drift points. The calibration of the gear shift critical values based on numerical distribution characteristics of the set of drift points to obtain a calibration result of multi-protocol data comprises the following steps: statistically analyzing numerical values of all state data points in the set of drift points to obtain a numerical distribution center and a dispersion degree; based on the numerical distribution center and the dispersion degree, calculating a target calibration offset for coordinating gear conflicts; According to the target calibration offset, the gear shift threshold of at least one communication protocol related to the conflict interval is offset adjusted to obtain a multi-protocol data calibration result.

7. The calibration method of power internet of things multi-protocol data according to claim 6, characterized in that, The target calibration offset for coordinating gear conflicts is calculated based on the numerical distribution center of gravity and the dispersion degree, including: The distance between the numerical distribution center of gravity and at least one gear shift threshold in the conflict interval is calculated. If the distance is less than a preset confidence threshold, the distance is taken as the target calibration offset, otherwise, the confidence threshold is taken as the target calibration offset, wherein the confidence threshold is set based on the dispersion degree. 8.A calibration system for power internet of things multi-protocol data, characterized in that, Including: The analysis module is configured to receive device state data reported by a plurality of communication protocols in the power internet of things, analyze the device state data to determine gear shift thresholds representing device operating states under each communication protocol, and determine a plurality of numerical intervals for dividing different gears under each communication protocol. The division module is configured to compare numerical intervals defined by different communication protocols for the same device operating state based on the gear shift thresholds, determine conflict intervals between the communication protocols in gear division, and identify a set of drift points divided into different gears under different communication protocols from the conflict intervals. The calibration module is configured to calibrate the gear shift thresholds based on numerical distribution characteristics of the set of drift points to obtain a calibration result of multi-protocol data.

9. A terminal device, comprising: Including: One or more processors; Memory coupled to the processor for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the steps of the calibration method for multi-protocol data of the power internet of things according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, Including: A stored computer program, wherein when the computer program is running, the device where the computer readable storage medium is located executes the steps of the calibration method for multi-protocol data of the power internet of things according to any one of claims 1-7.

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