Dynamic risk management and control method and system for operation process and field interaction equipment

Abstract

The invention discloses a dynamic risk management and control method and system for an operation process and field interaction equipment, and relates to the technical field of industrial internet, machine vision and intrinsic safety control. The invention aims to solve the technical problems that the physical state and the digital approval in the existing job management are disjointed, the existing job management is easily attacked by multimedia data fraud (such as screen copying and historical photo forgery), and the control instruction is lagged in a dynamic environment. The method comprises the following steps: a system and a field controller establish bidirectional heartbeat monitoring based on a hardware watchdog, and equipment is set in a physical locking state by default; responding to the operation request, and acquiring multimedia evidence containing a bottom hardware level tamper-proof space-time fingerprint by utilizing a hardware security unit (SE) of the field interaction equipment; the authenticity and the space-time legality of hardware fingerprints are verified at first, and then moire detection, reflection analysis and semantic comparison are conducted through an AI algorithm; and only when the anti-counterfeiting and the content verification are both passed, generating an encryption driving signal to unlock. During operation, a state competition processing mechanism is introduced, if the environment is suddenly changed, the system preferentially suspends the authority through high-priority hardware interruption, and fault-oriented security (Fail-Safe) is achieved. According to the invention, through deep fusion of software and hardware, active defense and millisecond-level dynamic fusing of operation risks are realized.

Description

Technical Field

[0001] This invention relates to the fields of industrial internet, artificial intelligence, edge computing and intrinsically safe control technology, and in particular to a hardware linkage risk management method, system and equipment based on AI machine vision for pre-emptive anti-counterfeiting access control, in-process dynamic monitoring and fault-safe mechanism. Background Technology

[0002] In high-risk industries such as petrochemicals, power energy, and coal mining, work permit (certificate) management is a core system for ensuring production safety. However, existing technical solutions face serious pain points in practical applications, namely a disconnect between hardware and software and a crisis of trust.

[0003] 1. Disconnect between physical status and digital workflow (information silos): Existing electronic work permit systems primarily focus on software-level workflow approval. The start-up and shutdown control of high-risk equipment on-site (such as welding machines, confined space access control systems, and high-voltage cabinets) often relies entirely on manual operation by on-site personnel. System approval is merely a "digital signal," lacking mandatory technical means to ensure that on-site physical equipment is locked without authorization, and also failing to guarantee that on-site personnel strictly adhere to safety measures after approval.

[0004] 2. Evidence forgery and lack of anti-counterfeiting measures: In actual work sites, numerous violations occur. For example, workers may upload expired historical photos to the system, reuse photos of "standard operations," or even directly photograph compliant images displayed on the computer screen to deceive the system into passing inspection. Most existing systems only perform simple identification of image content (such as the presence of a safety helmet) and lack robust technical verification methods to verify the authenticity of photo content (whether it was copied) and the consistency of the shooting time and location (whether it was taken in real-time on-site).

[0005] 3. Lack of dynamic response and fail-safe mechanisms: In traditional systems, once authorized, permissions are typically valid for a fixed period. However, industrial environments are dynamically changing (e.g., sudden wind speed changes, toxic gas leaks), or system communication networks may be interrupted. In existing technologies, when the environment deteriorates or the network is down, field equipment often remains in its last "operating" state, unable to automatically switch to a safer state (i.e., automatic shutdown or reset), which violates the inherent safety principle of "fail-safe." Furthermore, when sudden environmental changes require updated control measures, there is a time lag between the system generating new instructions and issuing them. Race conditions within this time window may lead to uncontrolled hazards.

[0006] Therefore, there is an urgent need for a closed-loop management system that can deeply integrate hardware-level anti-counterfeiting technology, AI machine vision content verification, spatiotemporal fingerprint constraints and industrial hardware control to achieve "no action if insecure" and "fault-oriented safety". Summary of the Invention

[0007] This invention aims to solve the above-mentioned technical problems by introducing a hardware security unit (SE) to ensure the underlying trustworthiness of data, combining multi-level AI verification (anti-counterfeiting + content) as an "intelligent referee", and using a two-way heartbeat monitoring mechanism and hardware interlocking technology to establish a strong logical mapping from "digital verification" to "physical execution".

[0008] The technical solution adopted in this invention is as follows:

[0009] A dynamic risk management method for a work process mainly includes the following logical steps:

[0010] Initialization and heartbeat establishment: Upon system startup, the system implements hardware interlocking of key production equipment through the field intelligent controller and establishes a "watchdog"-style two-way heartbeat monitoring to ensure the real-time reliability of the communication link.

[0011] Anti-counterfeiting evidence collection: When collecting evidence, the on-site interactive device does not rely on the operating system time, but directly reads the hardware clock and positioning module data through the built-in hardware security unit (SE) to generate an anti-tampering spatiotemporal fingerprint embedded in the evidence.

[0012] Multi-level intelligent verification: After receiving evidence, the system does not directly identify the content, but first performs "authenticity verification" (geofencing, time window, hardware ID), and then performs "AI content semantic verification" (including anti-fraud detection: moiré pattern recognition, screen reflection analysis; and content comparison: instrument readings, protective equipment wearing).

[0013] AI-driven logical authorization: The system will only issue an encrypted command to drive the field relay to act and release the lockout when all the above verification steps are "true".

[0014] Dynamic race condition handling and circuit breaking: Establish a dynamic update mechanism driven by environmental data. When a sudden change in the environment necessitates the generation of new control measures, a high-priority hardware interrupt instruction is sent first to suspend device permissions (to resolve the state race problem). At the same time, once a communication failure or violation identification occurs, the hardware automatically executes fault-oriented safety logic and resets to the locked state.

[0015] A dynamic risk management system for a work process includes a communication and heartbeat management module, a work permit processing module, an intelligent multi-level verification module, an authorization and security control module, and a field intelligent controller deployed on-site. The field intelligent controller includes a watchdog timer and a physical execution interface to ensure automatic reset in the event of a disconnection.

[0016] An interactive device integrating a stabilization camera module, a positioning module, and a hardware security unit (SE) has the ability to perform trusted signatures on the collected data at the underlying level and lock the screen in response to forced interrupt commands.

[0017] The beneficial effects of this invention are:

[0018] 1. Strong anti-fraud capabilities: By introducing a hardware security unit (SE) to collect tamper-proof spatiotemporal fingerprints, and combining AI anti-reproduction (moiré pattern, reflection) and background feature comparison technologies, a tight anti-counterfeiting defense line is built, effectively preventing the use of historical photos, photos from other locations, or reproduced photos to deceive people.

[0019] 2. High level of intrinsic safety: Introduces industrial-grade fail-safe logic. Through heartbeat monitoring and watchdog mechanisms, it ensures that in extreme abnormal situations such as system crashes, network outages, and sensor failures, field devices can automatically reset to a safe state of power failure or lockout, eliminating control blind spots.

[0020] Dynamic Adaptability and Race Condition Handling: An innovative dynamic update mechanism for handling state race conditions is proposed. Before new measures are generated due to environmental risks, permissions are suspended by hardware interruption, which solves the time window risk of "new requirements not being issued while old permissions are still valid" in traditional processes, and achieves millisecond-level risk response. Attached Figure Description

[0021] Figure 1 This is an overall flowchart of the dynamic risk management method for work processes provided in the embodiments of the present invention;

[0022] Figure 2 This is a schematic diagram of the dynamic risk management system provided in the embodiments of the present invention;

[0023] Figure 3 This is a timing logic diagram of the state contention handling mechanism provided in an embodiment of the present invention;

[0024] Figure 4 This is a logical diagram of the multi-level automated verification process in an embodiment of the present invention. Detailed Implementation

[0025] The present invention will now be described in further detail with reference to the accompanying drawings and specific embodiments.

[0026] Example 1: Intelligent interlocking and rescue linkage in confined space operations

[0027] This embodiment demonstrates the application of the present invention in confined spaces within chemical industrial parks (such as dredging inside underground storage tanks).

[0028] 1. Hardware initialization and heartbeat establishment

[0029] See Figure 1 Before the operation begins, the system sends an initialization command to the "portable intelligent control box" (field intelligent controller) deployed at the tank opening. The microcontroller (MCU) inside the control box drives a normally open relay to disconnect, cutting off the power supply to the axial fan and lighting entering the confined space (hardware interlock). Simultaneously, the backend system establishes an encrypted long-term MQTT connection with the control box via a 4G / 5G network, with a heartbeat interval set to 500ms. The control box activates a hardware watchdog timer with a timeout set to 1500ms. If three consecutive heartbeats are lost, the watchdog timer resets the MCU, ensuring the relay remains disconnected, achieving physical-level fault-oriented safety.

[0030] 2. Collection of anti-counterfeiting evidence

[0031] The operator applies for work using the field interaction device (explosion-proof handheld terminal) of this invention. During the data collection phase, the operator takes photos of the tank opening. The hardware security element (SE) within the terminal directly reads the GPS / BeiDou coordinates and RTC (real-time clock) time from the baseband processor through the hardware abstraction layer (HAL), bypassing the Android / iOS operating system layer to prevent data tampering via "location simulation" software. The SE uses a pre-set device private key to digitally sign the aforementioned data and photo hash value, generating a spatiotemporal fingerprint and embedding it into the photo's Exif data.

[0032] 3. Multi-level intelligent verification

[0033] See Figure 4 After receiving the evidence, the system performs multi-level verification:

[0034] Level 1 (Authenticity): The system decrypts the fingerprint and verifies whether the coordinates are within a 20-meter radius of the storage tank's center, and whether the timestamp's time error with the server's time is within 30 seconds. If the coordinates show an office building, the system determines it as "signed on behalf of someone else from another location" and rejects it directly.

[0035] Level Two (Anti-fraud and Semantic): If Level One passes, the AI ​​engine first performs anti-fraud detection, identifying whether the image contains moiré patterns (screen copy features) or unnatural reflections. Subsequently, it uses a semantic segmentation algorithm to identify the gas detector screen reading (e.g., oxygen content 20.9%) and whether the ventilation duct is correctly connected.

[0036] 4. Encryption Authorization and Actions

[0037] After all verifications pass, the system generates an authorization command containing a dynamic key and its validity period. The control box receives the command, decrypts and verifies it, then activates a relay to turn on the ventilation fan and lighting power, and unlocks the electronic access lock to allow personnel to enter.

[0038] 5. Dynamic monitoring and emergency circuit breaker

[0039] During the operation, the UWB positioning tags worn by personnel and the gas sensors continuously transmit data.

[0040] Scenario: The sensor detects that the hydrogen sulfide concentration suddenly increases from 0 ppm to 15 ppm (close to the alarm value).

[0041] Response: The system immediately triggers a high-priority interrupt.

[0042] (1) The system sends a hardware fuse command to the control box, triggering the high-frequency sound and light alarm to sound.

[0043] (2) The system sends a forced interrupt packet to the handheld terminal. The terminal's underlying driver uses system-level broadcast to forcibly take over the screen displaying "Evacuate immediately" and activates the maximum vibration mode.

[0044] (3) At this time, the control box control logic keeps the ventilation fan running at full speed (special configuration: keep exhaust when there is a toxic gas leak), but controls the lighting to switch to SOS flashing mode.

[0045] Example 2: Fraud Prevention and Competitive Condition Handling in High-Voltage Substation Maintenance

[0046] This embodiment focuses on demonstrating the mechanism for preventing the use of historical photos and handling state races in dynamic environments. Figure 3 ).

[0047] 1. Background feature comparison to prevent cheating

[0048] During the grounding wire connection verification process, the workers upload photos of the successfully connected grounding wires. The intelligent verification module in the background not only identifies the physical grounding wire but also extracts SIFT / SURF features from the background of the photo, such as the texture of the tower, the degree of insulator contamination, and the color of the surrounding vegetation. These features are then compared with the "Today's Baseline Image" or "Previous Work Period Image" for that tower in the database. If the background vegetation is found to be withered and yellow (a winter characteristic) while it is currently summer, the system determines this as "historical photo cheating" and refuses to unlock the next maintenance equipment cabinet door.

[0049] 2. Dynamically updated race condition handling

[0050] During the operation, meteorological data showed that a strong thunderstorm cloud cluster would arrive at the operation site in 5 minutes. At this point, a state competition occurred: the system needed to revoke the operation permit, but generating a detailed "evacuation list" and new rules required processing time (let's assume 2 seconds). During these 2 seconds, the operators still had operational privileges.

[0051] To eliminate this safety hazard, the present invention executes the following logic:

[0052] (1) Priority interrupt: At the moment when the dynamic risk triggering model outputs the "thunderstorm warning" signal, the system does not wait for the new list to be generated, but directly generates the highest priority hardware interrupt instruction (Priority=Level 0).

[0053] (2) Queue interruption: This interruption command is interrupted to the first position in the communication transmission queue and sent to the on-site smart lock or power cabinet to physically cut off the maintenance power supply or lock the operating mechanism (suspend permissions).

[0054] (3) Suspension and Resumption: Subsequently, new control measures (such as "stop work and evacuate to a safe area") are generated and pushed to the terminal. At this time, the equipment is already in a locked state. Only when the operator confirms "evacuated" on the terminal and uploads an empty scene photo after evacuation (confirmed by AI that no one is there) will the system record the closed loop. If the thunderstorm warning is lifted, the operator needs to go through the pre-verification process for the new environment again and restore power through the handshake protocol.

[0055] As can be seen from the above embodiments, the present invention constructs a robust physical and digital defense through technical means. By utilizing SE hardware root of trust, AI anti-fraud algorithms, and fault-oriented security hardware control logic, it effectively solves the problems of management and on-site disconnect, easy falsification of evidence, and lack of dynamic security response mechanisms in the prior art.

Claims

1. A method for dynamic risk management of a work process, characterized in that, Includes the following steps: Step S1: Initialize the physical control state of the work site. Cut off the power supply or control circuit of the production equipment or access control facilities associated with the work task through the field intelligent controller, so that they are in a hardware lockout state. Establish an encrypted two-way communication heartbeat monitoring mechanism between the background system and the field intelligent controller. The hardware lockout state refers to the state in which the actuator automatically resets to the safety side in the event of no valid authorization signal, communication interruption or heartbeat timeout. Step S2: Receive a job license request containing job task description information; Step S3: Based on the job task description information and obtain the associated real-time environmental monitoring data, generate a dynamic risk control list containing multiple pre-control measures using a preset risk rule model; Step S4: Send the dynamic risk control list to the on-site interactive device bound to the task through an encrypted channel; Step S5: Receive the confirmation data packet uploaded by the field interaction device. The data packet contains on-site image or video data collected for each pre-control measure in the list. When the data packet is collected, the hardware security unit (SE) embedded in the field interaction device directly reads the time and geographic coordinate data from the underlying hardware, and uses the device private key to perform digital signature to generate a tamper-proof spatiotemporal fingerprint. The spatiotemporal fingerprint is then embedded in the metadata of the image or video data. Step S6: Execute a multi-level automated verification process: The first level performs authenticity verification: parsing the spatiotemporal fingerprint, verifying the integrity of the digital signature, whether the collection location is within the geofence of the work area, whether the collection time is within the valid work window, and verifying the consistency of the device hardware ID; The second level performs AI content semantic verification: If the first level verification passes, the AI ​​inference engine is used to analyze the image or video data, extract physical state features, and perform a logical comparison with the preset security standard threshold. Step S7: Only when the authenticity verification and semantic verification results of all the pre-control measures in the dynamic risk control list are both "true", the system generates a job authorization encryption control signal with a timestamp and dynamic key; Step S8: Send the work authorization encryption control signal to the field intelligent controller. After the controller decrypts and verifies the signal, it drives the relay to engage or the electromagnetic lock to release the hardware lockout state and simultaneously initiates real-time dynamic risk monitoring of the work site. Step S9: During operation, if the two-way communication heartbeat monitoring mechanism detects that the heartbeat loss exceeds the preset threshold, or the real-time status of any pre-control measure deviates from the safety threshold, the system or the field intelligent controller immediately triggers the Fail-Safe logic to forcibly disconnect the control loop and restore the hardware lockout state.

2. The method according to claim 1, characterized in that, The method of using an artificial intelligence inference engine to perform content-level semantic verification on image or video data specifically includes the following parallel detection steps for anti-fraud and compliance: For measures involving the confirmation of instrument readings, optical character recognition (OCR) and pointer angle recognition algorithms are used to extract values, and moiré detection and spectrum analysis algorithms are used to detect whether the image has screen pixel grid features to eliminate the possibility of fraud by photographing the screen. Then the extracted values ​​are compared with the preset safe value range. For measures involving on-site scene confirmation, background texture feature points (SIFT / SURF features) of the image are extracted and their feature matching degree is calculated with the pre-stored benchmark environmental image of the work area in the current season or time period. The real-time performance of the shooting scene is verified by background consistency to prevent the reuse of historical photos. For measures involving the configuration of safety facilities, object detection algorithms are used to identify entities, and monocular ranging or geometric constraint algorithms are used to calculate the relative distance between the entity and the work point to determine whether it is within the effective coverage area.

3. The method according to claim 1, characterized in that, The step of generating a dynamic risk control list based on the task description information further includes a dynamic update mechanism for handling race conditions. During the operation execution phase, environmental sensor data of the work area is continuously collected at a preset frequency and input into the dynamic risk triggering model; When the environmental sensor data meets the risk triggering conditions, the system immediately generates an interrupt command with the highest transmission priority and initiates the generation process of new control measures in parallel. The interrupt command is inserted at the head of the communication transmission queue and sent to the field intelligent controller before the current job authorization control signal. This triggers the controller to immediately cut off the output, enter a hardware lockout state, and suspend the current permissions to cover the time window required for the generation and issuance of new control measures. The new control measures are pushed to the field interactive equipment. Once the confirmation data packet for the new measures passes the multi-level automated verification process, the job authorization encryption control signal is regenerated through the handshake protocol to restore permissions.

4. The method according to claim 1, characterized in that, The dynamic risk monitoring steps include: Acquire real-time video streams from cameras at the work site and time-series data from environmental sensors; The video stream is subjected to frame-by-frame reasoning using a video structured analysis algorithm to detect whether there are preset features of illegal behavior or dangerous conditions. Perform multimodal data fusion analysis. When the feature confidence level extracted from the video stream and the normalized value of the environmental sensor data simultaneously meet the preset alarm logic, a risk warning event is generated. The risk warning event includes a manual intervention interface, allowing authorized personnel to send an over-control command after confirming a false alarm. The over-control command, alarm data, and operation log will be written to an immutable blockchain storage node to form an audit evidence chain.

5. The method according to claim 4, characterized in that, It also includes hardware-linked fuse-breaking steps: In response to the aforementioned risk warning event and if no over-control command is received within a preset time, the system generates a hardware-linked circuit breaker command. The hardware-linked fuse-breaking command is used to trigger the following physical actions: Send a power-off command to the on-site intelligent controller, which physically cuts off the power supply to the control coil to release the contactor, thereby cutting off the power supply to the process equipment; Drive the on-site audible and visual alarm to flash and sound at a specific frequency; A forced interrupt control packet is sent to the field interactive device. The control packet contains a system-level interrupt call instruction, which is used to lock the device screen and trigger a high-frequency vibration warning until the risk clearance instruction is issued.

6. A dynamic risk management system for a work process, characterized in that, include: The communication and heartbeat management module is used to establish an encrypted long-term connection channel with the field intelligent controller and maintain the sending and receiving of bidirectional heartbeat packets and timeout detection, serving as the underlying security link guarantee; The work permit processing module is used to generate or update a risk control list that includes anti-counterfeiting requirements by combining real-time environmental data, and to handle status competition logic. The intelligent multi-level verification module includes an authenticity verification unit and a semantic verification unit; the authenticity verification unit is used to verify the legality of the spatiotemporal fingerprint signed by the security element (SE); the semantic verification unit is used to verify the compliance and originality of the physical content, including moiré pattern detection and background feature comparison. The authorization and security control module is used to generate encrypted authorization instructions after verification, and to send interrupt instructions to execute fault-oriented security logic when risks, abnormal heartbeats, or sudden environmental changes are detected. The field intelligent controller, deployed at the work site, includes a decryption unit, a watchdog timer, and a physical execution interface. It is used to parse instructions and drive the on / off of external devices, and the watchdog timer triggers an automatic reset lockout when communication is interrupted.

7. The system according to claim 6, characterized in that, The intelligent multi-level verification module also includes: The environmental feature comparison library stores baseline panoramic image data of the work site, which is used to assist in verifying the background consistency of uploaded images. The anti-fraud detection unit is used to analyze the imaging characteristics of uploaded images and identify screen re-photographing moiré patterns, PS tampering traces, or timestamp forgery traces.

8. The system according to claim 6, characterized in that, Also includes: The blockchain evidence storage module is used to package and upload job application metadata, hash digests of original evidence, AI inference results, control command records, and manual over-control logs to the blockchain in chronological order.

9. A field interactive device, comprising a processor, a memory, a display screen, a communication module, a camera module with image stabilization, a positioning module, and a hardware security unit (SE), wherein the memory stores a computer program, and when the processor executes the computer program, it performs the following steps: Receive the dynamic risk control list issued by the back-end system; When collecting evidence, the trusted time and geographic coordinates of the underlying hardware are directly read through the hardware security unit (SE) and embedded as an immutable digital watermark into the image data stream. Upload evidence data packets with digital watermarks through an encrypted channel; In response to a forced interrupt control packet sent from the background, regardless of the current interface or running process, the system uses an interrupt mechanism to forcibly switch to an alert state, locks the screen operation, and issues a tactile alarm via a vibration motor.

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