Electric power material intelligent warehouse checking RFID tag self-adaptive sorting scanning method and electric power material intelligent warehouse checking RFID tag self-adaptive sorting scanning system

Abstract

The invention belongs to the technical field of intelligent warehouse checking, and provides an electric power material intelligent warehouse checking RFID tag adaptive sorting scanning method and system, and the method comprises the steps: obtaining adaptive sorting factors of a plurality of tag data through the weighted summation of signal intensity, phase stability, polarization matching degree and misreading compensation factors; sorting is carried out according to the self-adaptive sorting factors, the label data with the self-adaptive sorting factor values higher than a preset value are preferentially scanned, and then other label data are scanned. A self-adaptive sorting factor calculation method is designed, self-adaptive regulation and control of a label response time sequence are realized by sorting self-adaptive sorting factors, preferentially scanning label data with a self-adaptive sorting factor value higher than a preset value and then scanning other label data, the signal collision probability among multiple labels is effectively reduced, and the accuracy of the label response time sequence is improved. The problems of signal interference and missed reading during centralized identification of multiple labels are solved, and the integrity and accuracy of batch identification are improved.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of intelligent warehouse inventory, and particularly relates to an RFID tag self-adaptive sorting scanning method and system for inventory of an intelligent warehouse of electric power materials. BACKGROUND

[0002] The RFID-based inventory of electric power materials in and out of a warehouse is a solution for efficient management of materials by using wireless radio frequency identification technology, and through wireless signal interaction between electronic tags and readers, non-contact data acquisition is realized, and the precision and efficiency of electric power warehouse management are significantly improved.

[0003] When batch identification of electric power equipment is performed in the warehouse in and out process, multi-tag centralized identification is prone to signal interference and missed reading problems, and the types of equipment, emergency situations and positions in different electric power warehouse areas are different, which increases the difficulty of processing of identification signals. SUMMARY

[0004] To solve the above problems, the application provides an RFID tag self-adaptive sorting scanning method and system for inventory of an intelligent warehouse of electric power materials, which realizes adaptive regulation of the response timing sequence of the tags by sorting the self-adaptive sorting factors and preferentially scanning the tag data with a self-adaptive sorting factor value higher than a preset value, and then scanning other tag data, effectively reduces the signal collision probability between multiple tags, solves the signal interference and missed reading problems in multi-tag centralized identification, and improves the integrity and accuracy of batch identification.

[0005] To achieve the above purpose, the application is implemented by the following technical solutions: In a first aspect, the application provides an RFID tag self-adaptive sorting scanning method for inventory of an intelligent warehouse of electric power materials, comprising: Obtaining a plurality of tag data in a region; Obtaining a plurality of tag data in a region; According to the self-adaptive sorting factors, sorting is performed, and tag data with a self-adaptive sorting factor value higher than a preset value is preferentially scanned, and then other tag data is scanned.

[0006] Further, the self-adaptive sorting factor is: ; wherein, is a signal strength standard value; is a phase stability standard value; is a polarization matching degree standard value; is a missed reading compensation factor standard value; , , and are weights corresponding to signal strength, phase stability, polarization matching degree and missed reading compensation factor respectively.

[0007] Further, for non-metallic packaging equipment, ; for transformer accessories, metal cabinets and metal trays, ; for emergency distribution of spare parts, ; for automatic warehouse-in and warehouse-out electric power equipment, .

[0008] Further, for the equipment with a missed reading compensation factor standard value greater than a preset value and the tag that fails to read for the first time, an additional retry round is performed.

[0009] Further, when the signal strength of multiple unmatched materials is detected, the transmission power is reduced and a close-range priority reading strategy is started.

[0010] Further, according to the minimum and maximum values of the readable signal, the signal strength standard value is obtained by proportional conversion to 0~1, the closer to the maximum value, the closer to 1 the signal strength standard value is; the stability or change rate of the tag signal phase is determined, and the stability or change rate is compressed to 0~1 by a function to obtain the phase stability standard value, the more stable the phase is, the higher the score is; the matching degree of the tag direction and the antenna polarization direction is judged, and the matching degree is mapped to 0~1 to obtain the polarization matching degree standard value, the more consistent the direction is, the higher the score is; the number of the most recent unreadings of the tag is counted, and the missed reading compensation factor standard value is determined in 0~1, the more the missed readings are, the closer to 1 it is.

[0011] In a second aspect, the present application further provides an intelligent electric power warehouse inventory RFID tag self-adaptive sorting scanning system, comprising: a data acquisition module configured to acquire a plurality of tag data in a region; an adaptive sorting factor determination module configured to obtain adaptive sorting factors of the plurality of tag data by weighted summation of signal strength, phase stability, polarization matching degree and missed reading compensation factor; wherein the weights corresponding to signal strength, phase stability, polarization matching degree and missed reading compensation factor are adjusted according to different types of electric power equipment in the electric power warehouse; a scanning module configured to sort according to the adaptive sorting factors, and to perform priority scanning on the tag data with an adaptive sorting factor value higher than a preset value, and to perform scanning on other tag data.

[0012] In a third aspect, the present application further provides a computer readable storage medium, having stored thereon a computer program, which, when executed by a processor, implements the steps of the power material intelligent warehouse inventory RFID tag adaptive sorting scanning method of the first aspect.

[0013] In a fourth aspect, the present application further provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and capable of running on the processor, wherein the processor implements the steps of the power material intelligent warehouse inventory RFID tag adaptive sorting scanning method of the first aspect when executing the program.

[0014] In a fifth aspect, the present application further provides a computer program product, comprising a computer program, which, when executed by a processor, implements the steps of the power material intelligent warehouse inventory RFID tag adaptive sorting scanning method of the first aspect.

[0015] Compared with the prior art, the present application has the following beneficial effects: 1. The present application creatively provides a power material intelligent warehouse inventory RFID tag adaptive sorting scanning method, designs an adaptive sorting factor calculation method, sorts the adaptive sorting factor, preferentially scans the corresponding label data with an adaptive sorting factor value higher than a preset value, and then scans other label data, thereby realizing adaptive regulation of label response timing, effectively reducing the signal collision probability between multiple labels, solving the problems of signal interference and missed reading during multiple label centralized identification, and improving the integrity and accuracy of batch identification.

[0016] 2. The present application creatively provides an adaptive sorting factor calculation weight adjustment method, adjusts the weight according to different power equipment types in the power warehouse, realizes determination of adaptive sorting factors of different equipment types in the power warehouse area, improves the integrity and accuracy of batch identification, and solves the problem of increased identification signal processing difficulty. BRIEF DESCRIPTION OF DRAWINGS

[0017] The drawings constituting a part of this embodiment are used to provide further understanding of the embodiment, and the schematic embodiment and its description are used to explain the embodiment, and do not constitute an improper limitation on the embodiment.

[0018] Figure 1 The method flowchart of the present application embodiment 1. DETAILED DESCRIPTION

[0019] The present application will be further described below in combination with the drawings and embodiments.

[0020] It should be noted that the following detailed descriptions are exemplary and intended to provide further explanation of this application. Unless otherwise specified, 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.

[0021] Example 1: like Figure 1 As shown, this embodiment provides an adaptive sorting and scanning method for RFID tags in an intelligent warehouse for inventorying power materials, as well as a judgment and management method based on the scanning; specifically: S1. Automatic barcode scanning and recognition.

[0022] Optionally, scanning tasks can be automatically triggered by infrared sensors, and RFID readers can be used to quickly identify the physical ID electronic tags of power materials, conduct real-time inventory of power materials entering and leaving the warehouse, and upload key information.

[0023] To address signal interference and missed reads issues that easily occur during centralized identification of multiple tags in the inbound and outbound process, the tag identification mechanism has been optimized: By adaptively adjusting the tag response timing and signal characteristics, orderly responses and efficient differentiation of multiple tags within the same identification area are achieved, prioritizing the scanning of high-priority tags; combined with a signal strength discrimination and dynamic tag response status management mechanism, the probability of signal collisions between multiple tags can be effectively reduced, improving the completeness and accuracy of batch identification. The reader's transmission power is dynamically adjusted to suppress long-distance tag interference. (Tag quantity) The estimate is: ; in, Number of idle time slots; This represents the total number of time slots. This represents the number of successful time slots.

[0024] Optimal frame length Adjusted to: ; in, Find the minimum value of the expression; This refers to any frame length value from the candidate set of selectable frame lengths for the system, such as 64, 128, 256, 512, etc. The initial frame length is 64 time slots; the maximum frame length is 512 time slots; and the tag recognition rate is ≥99%.

[0025] Within the same identification area, differentiation is achieved by quantifying and scoring tag feature parameters. Feature factors selected include Signal Strength Indicator (RSSI), Carrier Phase Stability (Phase), Polarization Matching Degree (pol), and Historical Unread Tag Marks (misstag). RSSI is used to differentiate between near and far obstructions, improving identification priority; Phase Stability is used to assess tag response reliability and location visibility; pol assesses the spatial attitude compatibility between the antenna and the tag; and misstags are used to prioritize compensation for tags not identified in the previous round.

[0026] S1.1 Constructing a multi-dimensional weighted priority score and a multi-label adaptive ranking factor. : ; in, This is the standard value for signal strength. This is the standard value for phase stability; This represents the standard value for polarization matching. This is the standard value for the missed reading compensation factor; , , and These are the weights corresponding to signal strength, phase stability, polarization matching degree, and missed read compensation factor, respectively.

[0027] When determining the standard value, the collected feature factors are normalized: The method for normalizing RSSI signal strength to a standard signal strength value S (0~1) involves linear scaling and truncation. A minimum and maximum readable signal value (RSSI_min and RSSI_max) are set, and the signal is proportionally converted to a range of 0~1: the closer to the maximum value, the closer to 1. Optional. → ,For example dBm, dBm.

[0028] Phase stability is normalized to a standard phase stability value Ph (0~1) using a phase fluctuation mapping method. The stability or rate of change of the tag signal's phase is calculated, and then compressed to 0~1 using a function. The more stable the phase (the smaller the error), the higher the score. Optional, → (Map phase stability or phase change rate to [0, 1], the higher the stability, the closer it is to 1).

[0029] The method for normalizing polarization matching to a standard value Po (0~1) involves using directional consistency mapping to determine the degree of matching between the tag orientation and the antenna polarization orientation. Mapping the matching degree to 0~1: the more consistent the orientation, the higher the readout efficiency and the higher the score. Optional, → (Polarization matching degree is mapped to [0, 1]).

[0030] The missed read compensation factor is normalized to a standard value M (0~1) using the following method: weighted by the number of missed reads, the most recent unread count (miss_count) of a tag is counted, and the priority of unidentified tags is increased: the more missed reads, the closer the value is to 1. Optional, → (The weight of unread history is closer to 1 the more times it has not been identified recently;) (regularity coefficient).

[0031] Standard weight normalization: ,and .

[0032] S1.2, Selection of weighting coefficients: Scenario A: Conventional power warehouse inbound and outbound operations (most materials are non-metallic packaging, moderately concealed); optional. Scenario B: High metal interference or densely packed scenarios (transformer accessories, large metal cabinets, metal trays); optional. Reduce the weight of pure RSSI and increase the weight of phase and polarization matching to prioritize the identification of "reliable tags". Scenario C: Emergency / replenishment priority (urgent delivery or critical spare parts, priority should be given to identifying tags that have not been read for a long time or critical tags); optional, Significantly increase the MissTag weight to prevent critical materials from being missed for extended periods. Scenario D: High-speed access (ETC-style warehouse entry and exit, sparse tags but requiring extremely high throughput); optional. Optional, prioritize speed and throughput, tolerate short-term read latency.

[0033] Sort all tags by adaptive sorting factor Sort, take the first (or (This is a fast-track read, with subsequent reads in batches.) A standard value for the missed read compensation factor is specified. High value (e.g.) For tags that fail to be read on the first attempt, additional retry rounds and adjustments to the transmission power are arranged. When a large amount of strong far-end signal clutter (a large number of unmatched materials with extremely high RSSI) is detected, the transmission power is reduced and a near-field priority reading strategy is activated to suppress far-end interference. The relationship between quantization sorting and collision handling is shown in Table 1: Table 1. Relationship between quantization sorting and collision handling

[0034] S2, Full-process video monitoring.

[0035] Intelligent high-definition cameras are installed to collect images and videos of the entry and exit of electrical materials from multiple angles. Combined with image recognition algorithms, the cameras record and photograph the appearance, size, and packaging integrity of the electrical materials, and automatically generate photo and video archives.

[0036] To address the issues of high bandwidth consumption, high latency, and network fluctuations causing unsmooth monitoring during long-distance transmission of high-definition video, an adaptive video stream compression and transmission optimization mechanism is adopted. This mechanism dynamically predicts and differentially encodes content changes between adjacent video frames, transmitting only the key information of the changed portions, thereby significantly reducing data volume while maintaining image clarity. Simultaneously, the system adjusts the video bitrate and keyframe interval in real time based on network conditions, achieving intelligent allocation and balancing of bandwidth resources. When network congestion or increased packet loss rate is detected, forward error correction and redundancy compensation strategies are automatically activated to maintain the continuity and stability of the video stream. Through these optimized designs, the system maintains a stable average transmission bitrate under operating conditions of 2560×1440 resolution and 30 frames per second, achieving efficient compression of high-definition video and smooth remote playback, significantly improving the real-time performance and reliability of video surveillance.

[0037] Inter-frame prediction (motion estimation and compensation): Rate control model: .

[0038] When material movement / RFID response events are detected: Initiate high-precision acquisition of ROI (shelf / tag area), increase keyframe density, and improve frame difference sensitivity. ; With low activity levels, the GOP increases (reducing bandwidth); with high momentum, the GOP decreases (improving clarity); during inbound and outbound operations, it is linked with the RFID system. When the material tag is scanned, the ROI clarity is automatically increased, the event timestamp is automatically marked, and a traceable inventory video evidence file is generated.

[0039] S3, Logistics location tracking.

[0040] Optionally, a high-precision BeiDou positioning chip can be used to achieve real-time collection and dynamic tracking of the geographical location of materials. The location coordinate information is automatically bound to the material file, and the actual geographical location, storage location, and inbound / outbound flow of the materials can be matched and verified.

[0041] To address the challenge of determining location discrepancies in material entry / exit and construction site management, an intelligent comparison mechanism based on BeiDou positioning and geofence verification was designed. This mechanism calculates the spatial distance between the real-time coordinates of the material and the center coordinates of the target site, and dynamically determines the matching degree of the material's location by combining this with a preset tolerance threshold. When the material's location exceeds the effective range of the construction site or designated storage area, the system automatically triggers an anomaly warning, prompting management personnel to check for abnormal departures, misdeliveries, or unauthorized transfers.

[0042] The system can collect and update location data once per second, and supports automatic conversion between different coordinate systems to ensure the consistency and accuracy of the location data. The range and threshold of the geofence can be flexibly set according to the actual conditions of the storage or construction site. When a location deviation is detected to exceed the threshold (default 100 meters), the system automatically generates an alarm message and pushes it to the management terminal through the message service module, realizing real-time identification and response to location anomalies.

[0043] Two-point distance calculation (Haversine formula): havA = 1 / 2(1-cosA); Fence matching: Use the RedisGEO command GEORADIUS to query whether the coordinates of the material are within the radius of the construction site (default threshold: 100 meters). Positioning sampling frequency: 1Hz; Coordinate transformation: WGS-84 to GCJ-02 (National Bureau of Surveying and Mapping encrypted coordinates).

[0044] S4. Inventory and dynamic monitoring and early warning of materials entering and leaving the warehouse.

[0045] After the device completes the barcode scanning and identification, the system automatically connects to the materials management system to automatically verify data such as purchase orders and delivery notices. If any abnormality is found, an early warning will be automatically triggered, effectively reducing the risk of mis-recording, omission, and incorrect delivery.

[0046] The device features real-time monitoring and anomaly warning functions for incoming goods. It can continuously compare the actual quantity with the planned quantity during the material receiving process, automatically identify arrival deviations, and trigger alarms. To avoid false alarms caused by single data fluctuations, the system introduces a dynamic statistical mechanism based on a time sliding window. This mechanism continuously calculates and analyzes the arrival deviation rate over a period of time, thereby achieving smooth detection and accurate judgment of quantity anomalies.

[0047] Specifically, the system aggregates and statistically analyzes multiple batches of arrival data within a set time window (e.g., 10 minutes), calculates the average deviation rate within the window in real time, and continuously updates the calculation interval based on a sliding step size (e.g., 1 minute). If the deviation rate exceeds a set threshold (default 5%) for multiple consecutive windows, the system identifies it as an abnormal event and automatically triggers an early warning mechanism. Window data storage: Elasticsearch time-series index (compression ratio ≥ 80%). Window deviation rate calculation: .

[0048] Example 2: This embodiment provides an adaptive sorting and scanning system for RFID tags in an intelligent warehouse for the inventory of power materials, including: The data acquisition module is configured to acquire data from multiple tags within a given area. The adaptive sorting factor determination module is configured to obtain an adaptive sorting factor for multiple tag data by weighted summation of signal strength, phase stability, polarization matching degree, and missed read compensation factor; wherein the weights of signal strength, phase stability, polarization matching degree, and missed read compensation factor are adjusted according to the different types of power equipment in the power warehouse. The scanning module is configured to: sort according to an adaptive sorting factor, prioritize scanning label data with an adaptive sorting factor value higher than a preset value, and then scan other label data.

[0049] The working method of the system is the same as the adaptive sorting and scanning method of RFID tags for inventory of power materials in the intelligent warehouse of Embodiment 1, and will not be described again here.

[0050] Example 3: This embodiment provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the adaptive sorting and scanning method for RFID tags in an intelligent warehouse for power materials as described in Embodiment 1.

[0051] Example 4: This embodiment provides an electronic device, including a memory, a processor, and a computer program stored in the memory and capable of running on the processor. When the processor executes the program, it implements the steps of the adaptive sorting and scanning method for RFID tags in the intelligent warehouse inventory of power materials described in Embodiment 1.

[0052] Example 5: This embodiment provides a computer program product, which includes a computer program. When the computer program is executed by a processor, it implements the steps of the adaptive sorting and scanning method for RFID tags in the intelligent warehouse inventory of power materials described in Embodiment 1.

[0053] The above description is merely a preferred embodiment of this practice and is not intended to limit the scope of this practice. Various modifications and variations can be made to this practice by those skilled in the art. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of this practice should be included within the protection scope of this practice.

Claims

1. An intelligent warehouse inventory RFID tag adaptive sorting scanning method for electric power materials, characterized in that, The method comprises the following steps: acquiring a plurality of tag data in a region; obtaining an adaptive sorting factor of the plurality of tag data through a weighted sum of signal strength, phase stability, polarization matching degree and a missed reading compensation factor; wherein the weights corresponding to the signal strength, the phase stability, the polarization matching degree and the missed reading compensation factor are adjusted according to different types of power equipment in the power warehouse; sorting according to the adaptive sorting factor, and preferentially scanning tag data with an adaptive sorting factor value higher than a preset value, and then scanning other tag data.

2. The power asset intelligent warehouse inventory RFID tag adaptive sorting scanning method of claim 1, wherein, The adaptive ranking factor Is: ； wherein, is a signal strength criterion value; is a phase stability criterion value; is a polarization matching criterion value; is a missed reading compensation factor criterion value; , , and are weights corresponding to signal strength, phase stability, polarization matching, and missed reading compensation factor, respectively.

3. The power asset intelligent warehouse inventory RFID tag adaptive sorting scanning method of claim 2, wherein, For non-metallic packaging equipment, ; for transformer accessories, metallic cabinets and metallic trays, ; For emergency distribution of spare parts, ; for automatic in- and out- of stock electric power equipment, .

4. The power asset intelligent warehouse inventory RFID tag adaptive sorting scanning method of claim 1, wherein, For the equipment with a missed reading compensation factor standard value greater than a preset value and the tag that fails to read for the first time, an additional retry round is performed.

5. The power asset intelligent warehouse inventory RFID tag adaptive sorting scanning method of claim 1, wherein, When the signal strength of a plurality of unmatched materials is detected, the transmission power is reduced and a close-range priority reading strategy is started.

6. The power asset intelligent warehouse inventory RFID tag adaptive sorting scanning method of claim 1, wherein, According to the minimum and maximum values of the readable signal, the signal strength standard value is obtained by proportional conversion to 0-1, and the closer to the maximum value, the closer to 1 the signal strength standard value is; the stability or change rate of the tag signal phase is determined, and the stability or change rate is compressed to 0-1 through a function to obtain the phase stability standard value, and the more stable the phase is, the higher the score is; the matching degree of the tag direction and the antenna polarization direction is judged, and the matching degree is mapped to 0-1 to obtain the polarization matching degree standard value, and the more consistent the direction is, the higher the score is; The number of recent unreadings of the tag is counted, and the missed reading compensation factor standard value is determined in 0-1, and the more the missed readings are, the closer to 1.

7. The intelligent warehouse inventory RFID tag adaptive sorting scanning system of electric power materials, characterized in that, The method comprises the following steps: a data acquisition module configured to acquire a plurality of tag data in a region; an adaptive sorting factor determination module configured to obtain an adaptive sorting factor of the plurality of tag data through a weighted sum of signal strength, phase stability, polarization matching degree and a missed reading compensation factor; wherein the weights corresponding to the signal strength, the phase stability, the polarization matching degree and the missed reading compensation factor are adjusted according to different types of power equipment in the power warehouse; a scanning module configured to sort according to the adaptive sorting factor, and preferentially scan tag data with an adaptive sorting factor value higher than a preset value, and then scan other tag data.

8. A computer-readable storage medium having stored thereon a computer program, characterized in that, The program is executed by the processor to realize the steps of the power material intelligent warehouse inventory RFID tag adaptive sorting scanning method of any one of claims 1-6.

9. An electronic device comprising a memory, a processor, and a computer program stored on the memory and capable of running on the processor, characterized in that, The processor executes the program to realize the steps of the power material intelligent warehouse inventory RFID tag adaptive sorting scanning method of any one of claims 1-6.

10. A computer program product, characterised in that, The computer program product comprises a computer program, and the computer program is executed by the processor to realize the steps of the power material intelligent warehouse inventory RFID tag adaptive sorting scanning method of any one of claims 1-6.

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