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CN-121981387-A - Production management identification method and system for safe AI (advanced technology attachment) glasses equipment

CN121981387ACN 121981387 ACN121981387 ACN 121981387ACN-121981387-A

Abstract

The invention discloses a production management identification method and a system of safe AI (advanced technology attachment) glasses equipment, and relates to the technical field of AI glasses equipment safety management, comprising the following steps of firstly, acquiring basic information of each equipment in a factory and generating an equipment serial number, wherein the equipment serial number comprises a basic code and a check bit, and the check bit comprises a first check bit C1 and a second check bit C2; the first check bit C1 is obtained by taking the modulus of a preset check module after weighting and summing the numerical values of all the basic codes according to forward position weights, the second check bit C2 is obtained by taking the modulus of the preset check module after weighting and summing the numerical values of all the basic codes according to reverse position weights, and the check bit of the equipment serial number is expanded from a self-check function to a key derivation factor, so that the replacement or deletion of any piece of equipment can cause the mismatch of a verification key and a decryption key, the tamper-proof verification of an equipment list is realized, and the equipment list can be switched between an online mode and an offline mode, so that the equipment can work in both network-available and network-free environments.

Inventors

  • WU WENHUI
  • LIANG YONG

Assignees

  • 深圳市形意智能科技有限公司

Dates

Publication Date
20260505
Application Date
20260120

Claims (10)

  1. 1. A production management identification method of a secure AI eyeglass device, characterized by comprising: The method comprises the steps of obtaining basic information of each device in a factory and generating a device serial number, wherein the device serial number comprises a basic code and check bits, and the check bits comprise a first check bit C1 and a second check bit C2, wherein the first check bit C1 is obtained by taking a preset check module after weighting and summing numerical values of each basic code according to forward position weights, and the second check bit C2 is obtained by taking a preset check module after weighting and summing numerical values of each basic code according to reverse position weights; Extracting a device list related to a task to be processed, adding corresponding values of first check bits C1 of all devices in the device list to obtain a first check bit accumulation sum S1, adding corresponding values of second check bits C2 of all devices to obtain a second check bit accumulation sum S2, calculating to obtain a decryption key K according to the first check bit accumulation sum S1, the second check bit accumulation sum S2 and the number N of the devices, and packaging the task to be processed, the device list and the decryption key K into a task execution end; step three, after the task execution end is started, self-checking and task timeliness verification are carried out, and after verification, equipment list data are loaded; Step four, an operator scans the identification of each execution device through AI glasses to obtain a device serial number, calculates check bits of all the scanned devices according to the mode of the step two to obtain a verification key V, compares the verification key V with a decryption key K, and generates a device list identification correct identification if the verification key V is equal to the decryption key K; generating an operation record containing the equipment serial number, the operation time and the operation result after generating the equipment list identification correct identification, and connecting a plurality of records in series to form a record chain; And step six, receiving the record chain data, updating the equipment state after verification is passed, and archiving to complete the data closed loop.
  2. 2. The method for manufacturing, managing and identifying the safe AI glasses equipment according to claim 1, wherein the equipment serial number is generated by adopting a compound coding rule, and the specific format is that a 3-bit equipment type code, a 2-bit year code, a 4-bit batch number, a 5-bit serial number and 2-bit check bits are spliced in sequence to form a 16-bit complete equipment serial number, wherein the first 14 bits are based on coding, the 15 th bit is a first check bit C1, and the 16 th bit is a second check bit C2.
  3. 3. The method for identifying the production management of the safe AI spectacle apparatus according to claim 2, wherein the first check bit C1 is calculated by: Multiplying the 1 st digit value of basic coding by weight 1, multiplying the 2 nd digit value by weight 2, and so on until the 14 th digit value is multiplied by weight 14, taking a module for 36 after all products are added, converting a module operation result into a corresponding character as a first check bit C1 according to a 36-system rule, wherein numbers 0 to 9 correspond to numbers 0 to 9, letters A to Z correspond to numbers 10 to 35, and a preset check module is 36.
  4. 4. The method for manufacturing management and identification of a safety AI spectacle apparatus according to claim 3, wherein the second check bit C2 is calculated by: Multiplying the 1 st digit value of basic coding by weight 14, multiplying the 2 nd digit value by weight 13, and so on until the 14 th digit value is multiplied by weight 1, adding all products in a reverse weighting mode, taking a module on 36, and converting the module operation result into corresponding characters as a second check bit C2 according to a 36-system rule.
  5. 5. The production management identification method of a secure AI spectacle apparatus according to claim 1, wherein the decryption key K is calculated by: The first check bit accumulation sum S1 is multiplied by the number of devices N, and the second check bit accumulation sum S2 is added to obtain a decryption key original value, the decryption key original value is subjected to modulus of a preset key modulus to obtain a decryption key K, and the preset key modulus is a prime number 9973.
  6. 6. The method for identifying the production management of the safe AI glasses equipment according to claim 1 is characterized in that the method further comprises the steps of calculating a hash value of the whole to be executed, which is composed of a task to be processed, an equipment list and a decryption key K, and embedding the hash value into a task execution end program as an expected hash value, wherein the self-checking in the step three is specifically that the task execution end is started to calculate a current hash value of the whole to be executed, the current hash value is compared with the expected hash value, if the current hash value is consistent, the self-checking is passed, and if the current hash value is inconsistent, the program is tampered and the operation is terminated.
  7. 7. The method for identifying the production management of the safe AI glasses equipment according to claim 1, wherein in the third step, after verification, an operation mode is selected according to a network state, a detection request is sent to the background, if a response is received, the online state is determined, the online mode is selected, the latest equipment list data is requested to be acquired from the background, if no response is received, the offline state is determined, the offline mode is selected, and the data is loaded from the equipment list embedded in the task execution end.
  8. 8. The method for manufacturing management and identification of a secure AI glasses apparatus according to claim 1, wherein in the fifth step, a plurality of records are connected in series to form a record chain, wherein each operation record includes a hash value of a previous operation record as a pre-hash value, the pre-hash value of the first operation record is set as a hash value of a task identifier, and the pre-hash values of the 2 nd and subsequent operation records are hash values of the previous operation record, thereby forming a tandem chain structure.
  9. 9. The method for manufacturing management and identification of a safety AI eyeglass device according to claim 8, wherein in step six, the specific manner of passing the verification includes: And if the front hash value of each record is consistent with the hash value of the previous record, judging that the integrity verification of the record chain is passed, verifying the equipment serial number in each record, extracting the basic code of the equipment serial number, respectively calculating a first verification bit and a second verification bit according to the mode in the step one, comparing the calculation result with the verification bit in the equipment serial number, and judging that the equipment serial number verification is passed if the calculated first verification bit is consistent with the 15 th bit of the equipment serial number and the calculated second verification bit is consistent with the 16 th bit of the equipment serial number, and judging that the equipment serial number verification is passed if the integrity verification of the record chain is passed and all the equipment serial numbers are passed.
  10. 10. A production management identification system of a secure AI spectacle apparatus, characterized in that the system is realized by a production management identification method of a secure AI spectacle apparatus as claimed in any one of claims 1 to 8, comprising: The equipment serial number generation module is used for acquiring an equipment type code, a year code, a batch number and a serial number of each equipment to form a 14-bit basic code, adopting a forward weighting summation pair 36 to modulo calculate a first check bit C1, adopting a reverse weighting summation pair 36 to modulo calculate a second check bit C2, and adding 2 check bits to the basic code to generate a 16-bit complete equipment serial number; The task packaging and key generating module is used for extracting a device list related to a task to be processed, calculating a first check bit accumulation sum and a second check bit accumulation sum according to a first check bit C1 and a second check bit C2 of each device in the device list, further calculating to obtain a decryption key K, packaging the task to be processed, the device list, the validity period and the decryption key as a whole to be executed, and embedding the whole hash value to be executed as an expected hash value into a production line execution end program; The double-layer verification and mode selection module is used for calculating the comparison of the whole hash value to be executed and the expected hash value to perform self-verification when the production line execution end is started, obtaining the comparison of the current time and the task validity period to perform timeliness verification, sending a detection request to the background, selecting an online mode according to the response condition to obtain the latest equipment list from the background or selecting an offline mode to load data from the program embedded list; The AI glasses identification and key verification module is used for establishing communication connection with AI glasses worn by an operator, receiving equipment serial numbers acquired by scanning two-dimensional codes by the AI glasses, verifying the equipment serial numbers of each equipment, calculating a verification key V according to verification bits after all the equipment are scanned, comparing the verification key V with a decryption key K, and generating an equipment list identification correct mark if the verification key V is equal to the decryption key K; The record chain generation and return module is used for generating operation records containing equipment serial numbers, operation time and operation results one by one after the equipment list identification correct identification is generated, each record contains a hash value of the previous record to form a record chain, the record chain is transmitted to a background in real time in an online mode, and the record chain is packed in an offline mode to generate an offline data packet with a packet check code for export; The background verification and state updating module is used for receiving the operation record transmitted online or importing the offline data packet, verifying the integrity of the packet verification code and the record chain, verifying the verification code of the equipment serial number of each record, and updating the equipment state after all the verification passes.

Description

Production management identification method and system for safe AI (advanced technology attachment) glasses equipment Technical Field The invention belongs to the technical field of safety management of AI (advanced technology attachment) glasses equipment, and particularly relates to a production management identification method and system of safe AI glasses equipment. Background In a modern intelligent production environment, accurate identification, state tracking and compliance management of equipment assets are core links for guaranteeing production safety and efficiency. Traditional equipment management methods mainly rely on paper work sheets, handheld code scanning guns or simple mobile application programs to complete equipment information acquisition and recording. With the development of the augmented reality technology, AI glasses are gradually introduced into the production management field, and workers are assisted in equipment identification and operation guidance through an augmented reality interface and machine vision capability. At present, an equipment management scheme based on AI glasses generally stores equipment list data at a glasses end or a matched terminal, an operator obtains an equipment number through a two-dimensional code or a bar code mark on glasses scanning equipment, and then the number and the list are compared one by one to confirm equipment identity. In terms of generating device numbers, the existing schemes mostly adopt simple sequential coding or coding rules of single check bits. In terms of task execution, the existing scheme generally stores a device list directly in an execution terminal, and an operator records an operation result of a system after finishing scanning and returns the operation result to a background management system. However, the conventional AI glasses device management identification scheme has insufficient anti-counterfeiting verification capability on the device serial number, a simple coding rule or a single check bit is difficult to effectively detect errors generated in the transmission, input or manual tampering process of the serial number, the identification of a single device is difficult to be found by a system after being counterfeited or replaced, meanwhile, the whole integrity of a device list is lack of an effective verification mechanism, the conventional scheme adopts a comparison-by-comparison mode to verify the device, when part of devices in the list are replaced, deleted or added, the system cannot identify the fact that the list is tampered as long as the number format of the replaced device is correct, and the program and the data of a task execution end lack anti-tampering protection, so that the system cannot automatically detect after the program or the embedded data of the execution end are maliciously modified, and potential safety hazards exist. Disclosure of Invention The present invention is directed to a method and a system for production management and identification of a safe AI glasses device, so as to solve the above-mentioned problems in the background art. A production management identification method and system of safe AI glasses equipment comprises the following steps: The method comprises the steps of obtaining basic information of each device in a factory and generating a device serial number, wherein the device serial number comprises a basic code and check bits, and the check bits comprise a first check bit C1 and a second check bit C2, wherein the first check bit C1 is obtained by taking a preset check module after weighting and summing numerical values of each basic code according to forward position weights, and the second check bit C2 is obtained by taking a preset check module after weighting and summing numerical values of each basic code according to reverse position weights; Extracting a device list related to a task to be processed, adding corresponding values of first check bits C1 of all devices in the device list to obtain a first check bit accumulation sum S1, adding corresponding values of second check bits C2 of all devices to obtain a second check bit accumulation sum S2, calculating to obtain a decryption key K according to the first check bit accumulation sum S1, the second check bit accumulation sum S2 and the number N of the devices, and packaging the task to be processed, the device list and the decryption key K into a task execution end; step three, after the task execution end is started, self-checking and task timeliness verification are carried out, and after verification, equipment list data are loaded; Step four, an operator scans the identification of each execution device through AI glasses to obtain a device serial number, calculates check bits of all the scanned devices according to the mode of the step two to obtain a verification key V, compares the verification key V with a decryption key K, and generates a device list identification correct identification if the ve