A method and system for generating a multi-stage safety control strategy of an industrial cleaning machine

Abstract

The application discloses a kind of multistage safety control strategy generation method and system of industrial cleaning machine, it is related to industrial equipment safety control technical field, including sensor group, configured to real-time acquisition reflects the multidimensional data of industrial cleaning machine operating state and potential risk;Risk grade assessment unit is connected with the sensor group, configured to based on the multidimensional data real-time calculation and output a comprehensive risk grade signal;Multistage safety strategy generation unit is connected with the risk grade assessment unit, configured to according to the comprehensive risk grade signal input, dynamically build a control strategy sequence comprising at least two levels progressive safety response;Output corresponding to the control instruction of the control strategy sequence;Execution unit is connected with the multistage safety strategy generation unit, configured to receive and execute the control instruction, the present application solves the problem of industrial cleaning risk control inaccuracy.

Description

Technical Field

[0001] This invention relates to the field of industrial equipment safety control technology, specifically to a method and system for generating multi-level safety control strategies for industrial cleaning machines. Background Technology

[0002] With the continuous improvement of industrial automation, industrial cleaning machines, as key equipment, have been widely used in various industries such as automobile manufacturing, aerospace, and precision electronics to efficiently clean oil stains, dust, and particulate residues from the surfaces of parts. Existing industrial cleaning equipment is generally equipped with a certain level of safety protection measures, such as emergency stop buttons, pressure monitoring, and leakage alarms.

[0003] However, existing industrial cleaning machines often employ a "one-size-fits-all" emergency stop strategy, halting all operations regardless of risk level. This not only risks production interruptions but, in high-pressure pipeline scenarios, can also trigger secondary hazards such as pressure surges and fluid backflow. Furthermore, existing industrial cleaning machine safety control logic is typically pre-programmed and fixed, failing to dynamically adjust response methods and intensity based on real-time risk levels, equipment operating stages, or specific task configurations, resulting in a lack of adaptability and specificity in the control strategy. Therefore, it is essential to design a method and system for generating multi-level safety control strategies for industrial cleaning machines that accurately identifies and implements graded responses. Summary of the Invention

[0004] The purpose of this invention is to provide a method and system for generating multi-level safety control strategies for industrial cleaning machines, so as to solve the problems mentioned in the background art.

[0005] To solve the above-mentioned technical problems, the present invention provides the following technical solution: a method and system for generating a multi-level safety control strategy for an industrial cleaning machine, including a sensor group configured to collect multi-dimensional data reflecting the operating status and potential risks of the industrial cleaning machine in real time;

[0006] A risk level assessment unit, connected to the sensor group, is configured to calculate and output a comprehensive risk level signal in real time based on the multidimensional data;

[0007] A multi-level security policy generation unit, connected to the risk level assessment unit, is configured to dynamically construct a control policy sequence containing at least two levels of progressive security responses based on the input comprehensive risk level signal; wherein the at least two levels of progressive security responses include:

[0008] Level 1 response refers to non-shutdown intervention measures triggered when the risk level is below a preset severity threshold.

[0009] Level 2 response refers to partial or complete shutdown interventions triggered when the risk level reaches or exceeds a preset severity threshold.

[0010] Output control commands corresponding to the control strategy sequence;

[0011] An execution unit, connected to the multi-level safety policy generation unit, is configured to receive and execute the control commands to drive the corresponding actuators of the industrial cleaning machine to achieve the progressive safety response.

[0012] According to the above technical solution, the risk level assessment unit is further configured as follows:

[0013] Establish a risk source mapping table to parse the multidimensional data into the following independent risk sources in real time:

[0014] (a) Sources of mechanical motion risk: including conveyor belt displacement deviation, robotic arm joint pressure, and abnormal clamping force of fixtures;

[0015] (b) Fluid dynamic risk sources: including main pump pressure pulsation value, pipeline flow rate change rate, and nozzle blockage index;

[0016] (c) Chemical exposure risk sources: including cleaning agent concentration gradient, vapor leakage threshold, and excessive emissions of exhaust gas;

[0017] Assign an independent risk weight coefficient to each risk source The weighting coefficients are dynamically adjusted based on the probability of an accident caused by the risk source in the historical fault database;

[0018] When the actual monitored value of any risk source exceeds its preset threshold When this occurs, a risk tracing command is triggered to identify the highest-risk source. ;

[0019] The multi-level security policy generation unit, in response to risk tracing instructions, is configured as follows:

[0020] according to The type matches a predefined response rule base to generate a targeted, progressive strategy sequence:

[0021] like If the mechanical motion risk source is the first level response, the robot arm motion trajectory smoothing algorithm will be forcibly inserted, and the second level response will trigger a regional shutdown instead of a complete power outage.

[0022] like If the source of fluid dynamic risk is identified, the first-level response will initiate the pressure buffer valve to gradually release pressure, and the second-level response will close the corresponding branch valve and maintain the main circulation.

[0023] like If the source is a chemical exposure risk, the first-level response activates the negative pressure suction system and triggers an alarm; the second-level response seals the chamber and injects a neutralizing agent.

[0024] Finally, hierarchical control instructions strongly correlated with the risk source type are output to the execution unit.

[0025] According to the above technical solution, the control strategy sequence contains three or more levels of progressive responses, and the responses at different levels support parallel and coordinated triggering.

[0026] When the comprehensive risk level signal simultaneously meets multiple independent risk conditions, the multi-level security policy generation unit generates a composite response instruction set.

[0027] All parallel instructions undergo logical verification through a conflict detector: if mutual exclusion is detected, priority arbitration is initiated: the instruction with the highest safety priority is executed immediately, and the next highest priority instruction is delayed until the conflict is resolved.

[0028] The execution unit is configured to synchronously process composite instruction sets using a multi-threaded control protocol.

[0029] According to the above technical solution, the system further includes an operation phase identification module, configured to determine the current operation phase based on a logical combination of at least two signals, specifically:

[0030] In response to the main motor start signal and the heater enable status, it is marked as the start-up preheating stage;

[0031] If the conveyor belt speed is greater than the preset value and the number of spray valves opened is greater than or equal to 2, it is marked as a normal cleaning stage;

[0032] If the drain pump current value continues to rise and the hatch position sensor triggers a signal, it is marked as the drain maintenance stage.

[0033] The multi-level security policy generation unit is further configured to: configure an independent risk level-response action mapping relationship for each operational phase, specifically including:

[0034] When the startup warm-up phase is in progress, a Level 2 comprehensive risk level will trigger a Level 2 response; the Level 1 response only includes audible and visual alarms.

[0035] During the normal cleaning phase, a Level 2 response is triggered only when the overall risk level reaches Level 3; the Level 1 response includes power regulation and flow compensation.

[0036] When the system is in the drainage maintenance phase, the first-level response is cancelled. If the overall risk level reaches Level 1, the second-level response is triggered. The second-level response forces the activation of the waste liquid recovery device.

[0037] According to the above technical solution, the non-shutdown intervention measures triggered by the first-level response specifically include gradient power adjustment, audible and visual alarm topology optimization, mechanical motion constraint, and chemical barrier activation.

[0038] According to the above technical solution, the intervention measures for triggering partial or complete shutdown in the second-level response include regional power supply cut-off, hydraulic system segmented locking, multi-dimensional emergency stop coordination, and chemical emergency neutralization.

[0039] According to the above technical solution, the risk level assessment unit includes a weight self-optimization engine:

[0040] Establish a mapping matrix between sensor data and historical accident database ;

[0041] When a new failure event occurs, the failure cause vector is calculated. ;

[0042] according to Update weights, where For learning rate, Contribute probability to the cause;

[0043] when If so, the adjustment will be frozen.

[0044] According to the above technical solution, the system is also equipped with a dual-channel command arbitrator, which includes an automatic decision-making channel and a manual intervention channel; wherein,

[0045] The automatic decision-making channel is used to receive the control instruction sequence output by the multi-level security policy generation unit;

[0046] The manual intervention channel is used to connect to the intelligent operation terminal and receive operator gesture commands or voice commands in real time.

[0047] The dual-channel command arbitrator is configured to execute hierarchical arbitration logic:

[0048] For Level 1 response commands, if the manual intervention channel is within the response window... If a "delay execution" instruction is received, the response will be suspended and a secondary risk assessment will be initiated; if no valid instruction is received within the time limit, the instruction from the automatic decision-making channel will be forcibly executed.

[0049] For Level 2 response commands, the manual intervention channel access is forcibly frozen, the automatic decision-making channel command is executed immediately, and after execution, an emergency event report and execution basis data packet are pushed to the operation terminal.

[0050] According to the above technical solution, the intelligent operation terminal is configured as follows:

[0051] When the manual intervention channel is activated, a three-dimensional model of the spatial location of the current risk source and its predicted evolution path are displayed.

[0052] A personalized response recommendation model is trained based on the operator's historical decision data, and priority response options are pushed during the arbitration window.

[0053] A method for generating a multi-level safety control strategy for an industrial cleaning machine includes the following steps:

[0054] Real-time data collection of industrial cleaning machine operating status and environmental risk data is achieved through multi-source sensors.

[0055] The data is processed based on a dynamic weighted fusion algorithm to output a comprehensive risk level signal.

[0056] Based on the comprehensive risk level signal, a control strategy sequence containing at least two levels of progressive safety response is dynamically generated;

[0057] The drive actuator executes a hierarchical safety response according to the control strategy sequence.

[0058] Compared with the prior art, the beneficial effects achieved by the present invention are: the present invention,

[0059] (1) By associating and matching risk source types with predefined response rule bases, the system can automatically generate corresponding graded intervention measures according to different risk scenarios, including flexible control, partial shutdown or emergency neutralization, and finally output strongly correlated and differentiated control instructions to achieve precise, flexible and highly adaptable safety control of industrial cleaning equipment. This effectively solves the problems of production interruption, control response lag and secondary safety hazards caused by "one-size-fits-all" emergency stop in the existing technology, and significantly improves the safety, continuity and intelligence level of equipment operation.

[0060] (2) By introducing a three-level or higher progressive security response mechanism and supporting the parallel collaborative triggering of multiple response strategies, a composite response instruction set can be generated. The built-in response conflict detector performs logical verification to ensure that there are no contradictions or execution interference between the instructions. This achieves the integration of security control logic, optimization of response strategy scheduling and stability assurance of the execution process under multiple risk concurrency conditions. It effectively improves the system's security decision-making ability and execution efficiency under complex working conditions and sudden multi-source risk situations, and avoids secondary hidden dangers or control failures caused by instruction conflicts.

[0061] (3) By introducing the operation phase identification module, and combining the logic of multi-dimensional signals such as main motor status, conveyor belt speed, heater start and stop, number of valves opened, pump current change and door position, the intelligent linkage and dynamic matching of safety strategy and equipment operation phase are realized, which effectively avoids problems such as false triggering, response delay or insufficient protection caused by fixed response logic, and significantly enhances the system's situational awareness, control flexibility and overall safety adaptability.

[0062] (4) Through the coordinated design and tiered deployment of non-stop and stop intervention measures, the principle of hierarchical execution, local control and minimal interference of risk response was realized, which not only enhanced the effectiveness and technical controllability of safety response, but also significantly improved the continuous operation capability and emergency response efficiency of industrial cleaning equipment under sudden risks.

[0063] (5) By setting up a dual-channel command arbitrator, the automatic decision-making channel and the manual intervention channel are connected to the control system in parallel, so that the "system intelligent judgment" and "operator active intervention" are organically combined in the safety response process, thereby realizing efficient coordination between automatic control and manual judgment, dynamic scheduling of permissions and transparent closed loop of decision-making, effectively improving the system's response credibility, flexible intervention capability and human-machine interaction intelligence level under complex working conditions. Attached Figure Description

[0064] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0065] Figure 1 This is a schematic diagram of the multi-level safety control strategy generation system for the industrial cleaning machine of the present invention.

[0066] Figure 2 This is a schematic diagram of the process for generating a multi-level safety control strategy for an industrial cleaning machine according to the present invention. Detailed Implementation

[0067] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0068] Example 1

[0069] like Figure 1As shown, a multi-level safety control strategy generation system for an industrial cleaning machine includes a sensor group configured to collect multi-dimensional data reflecting the operating status and potential risks of the industrial cleaning machine in real time.

[0070] A risk level assessment unit, connected to the sensor group, is configured to calculate and output a comprehensive risk level signal in real time based on the multidimensional data;

[0071] A multi-level security policy generation unit, connected to the risk level assessment unit, is configured to dynamically construct a control policy sequence containing at least two levels of progressive security responses based on the input comprehensive risk level signal; wherein the at least two levels of progressive security responses include:

[0072] Level 1 response refers to non-shutdown intervention measures triggered when the risk level is below a preset severity threshold.

[0073] Level 2 response refers to partial or complete shutdown interventions triggered when the risk level reaches or exceeds a preset severity threshold.

[0074] Output control commands corresponding to the control strategy sequence;

[0075] An execution unit, connected to the multi-level safety policy generation unit, is configured to receive and execute the control commands to drive the corresponding actuators of the industrial cleaning machine to achieve the progressive safety response.

[0076] The risk level assessment unit is further configured as follows:

[0077] Establish a risk source mapping table to parse the multidimensional data into the following independent risk sources in real time:

[0078] (a) Sources of mechanical motion risk: including conveyor belt displacement deviation, robotic arm joint pressure, and abnormal clamping force of fixtures;

[0079] (b) Fluid dynamic risk sources: including main pump pressure pulsation value, pipeline flow rate change rate, and nozzle blockage index;

[0080] (c) Chemical exposure risk sources: including cleaning agent concentration gradient, vapor leakage threshold, and excessive emissions of exhaust gas;

[0081] Assign an independent risk weight coefficient to each risk source The weighting coefficients are dynamically adjusted based on the probability of an accident caused by the risk source in the historical fault database;

[0082] When the actual monitored value of any risk source exceeds its preset threshold When this occurs, a risk tracing command is triggered to identify the highest-risk source. ;

[0083] The multi-level security policy generation unit, in response to risk tracing instructions, is configured as follows:

[0084] according to The type matches a predefined response rule base to generate a targeted, progressive strategy sequence:

[0085] like If the mechanical motion risk source is the first level response, the robot arm motion trajectory smoothing algorithm will be forcibly inserted, and the second level response will trigger a regional shutdown instead of a complete power outage.

[0086] like If the source of fluid dynamic risk is identified, the first-level response will initiate the pressure buffer valve to gradually release pressure, and the second-level response will close the corresponding branch valve and maintain the main circulation.

[0087] like If the source is a chemical exposure risk, the first-level response activates the negative pressure suction system and triggers an alarm; the second-level response seals the chamber and injects a neutralizing agent.

[0088] Finally, hierarchical control instructions strongly correlated with the risk source type are output to the execution unit;

[0089] This step, through the construction of a risk source mapping table and a real-time multi-dimensional monitoring mechanism, can accurately identify different types of risks generated during the operation of industrial cleaning machines. Based on dynamic weight assessment and risk level determination, it intelligently identifies the most threatening risk source, thereby generating multi-level safety control strategies with differentiated response levels and targeted response content. By associating and matching risk source types with a predefined response rule base, the system can automatically generate corresponding graded intervention measures according to different risk scenarios (such as mechanical anomalies, fluid fluctuations, or chemical leaks), including flexible control, partial shutdown, or emergency neutralization. Ultimately, it outputs strongly correlated and differentiated control commands, achieving precise, flexible, and highly adaptable safety control of industrial cleaning equipment. This step effectively solves the problems of production interruption, control response lag, and secondary safety hazards caused by "one-size-fits-all" emergency stops in existing technologies, significantly improving the safety, continuity, and intelligence level of equipment operation.

[0090] The control strategy sequence contains three or more levels of progressive responses, and the responses at different levels support parallel and coordinated triggering.

[0091] When the comprehensive risk level signal simultaneously meets multiple independent risk conditions, the multi-level security policy generation unit generates a composite response instruction set.

[0092] All parallel instructions undergo logical verification through a response conflict detector: if mutually exclusive instructions are detected (such as "open ventilation" and "seal the cabin"), priority arbitration is initiated: the instruction with the highest safety priority is executed immediately, and the next highest priority instruction is delayed until the conflict is resolved.

[0093] The execution unit is configured to synchronously process composite instruction sets using a multi-threaded control protocol. By introducing a three-level or higher progressive security response mechanism and supporting the parallel and collaborative triggering of multiple response strategies, it can generate composite response instruction sets when multiple independent risk conditions are simultaneously met in the comprehensive risk level. A built-in response conflict detector performs logical verification to ensure that there are no contradictions or execution interference between instructions. When a conflict exists, the system automatically determines the priority of the instructions based on a preset security priority arbitration mechanism and executes the highest priority instruction, while the remaining instructions are delayed until the conflict is resolved. The execution unit uses a multi-threaded control protocol to synchronously process composite response instructions, ensuring that various security responses are coordinated in time and do not interfere with each other functionally. This technical solution achieves the fusion of security control logic, optimization of response strategy scheduling, and stability assurance of the execution process under multi-risk concurrency conditions. It effectively improves the system's security decision-making capability and execution efficiency under complex operating conditions and sudden multi-source risk situations, avoiding secondary hidden dangers or control failures caused by instruction conflicts.

[0094] The system further includes an operation phase identification module, configured to determine the current operation phase based on a logical combination of at least two signals, specifically:

[0095] In response to the main motor start signal and the heater enable status, it is marked as the start-up preheating stage;

[0096] If the conveyor belt speed is greater than the preset value and the number of spray valves opened is greater than or equal to 2, it is marked as a normal cleaning stage;

[0097] If the drain pump current value continues to rise and the hatch position sensor triggers a signal, it is marked as the drain maintenance stage.

[0098] The multi-level security policy generation unit is further configured to: configure an independent risk level-response action mapping relationship for each operational phase, specifically including:

[0099] When the startup warm-up phase is in progress, a Level 2 comprehensive risk level will trigger a Level 2 response; the Level 1 response only includes audible and visual alarms.

[0100] During the normal cleaning phase, a Level 2 response is triggered only when the overall risk level reaches Level 3; the Level 1 response includes power regulation and flow compensation.

[0101] When the liquid drainage maintenance phase is underway, the first-level response is cancelled. If the overall risk level reaches Level 1, the second-level response is triggered. The second-level response will force the activation of the waste liquid recovery device.

[0102] In this embodiment of the invention, by introducing an operation phase identification module, and combining the logical combination of multi-dimensional signals such as main motor status, conveyor belt speed, heater start / stop, number of valves opened, pump current changes, and door position, the specific operation phase of the industrial cleaning machine can be accurately determined, such as the start-up preheating, normal cleaning, or drainage maintenance phase. On this basis, the multi-level safety strategy generation unit can dynamically switch the corresponding risk level-response action mapping relationship for different operation phases, ensuring that the safety strategy for each phase has phase adaptability and risk matching.

[0103] For example, the trigger threshold is lowered during the preheating phase to prevent cold-state damage, the response threshold is raised during the normal cleaning phase to ensure production continuity, and protection is strengthened in advance during the drainage maintenance phase to ensure personnel safety. This solution achieves intelligent linkage and dynamic matching between safety strategies and equipment operation phases, effectively avoiding problems such as false triggering, response delays, or insufficient protection caused by fixed response logic, and significantly enhancing the system's situational awareness, control flexibility, and overall operational safety adaptability.

[0104] The non-shutdown interventions triggered by the first-level response specifically include gradient power adjustment, audible and visual alarm topology optimization, mechanical motion constraints, and chemical barrier activation; among these...

[0105] Gradient power adjustment: Based on the linear relationship between risk level and equipment load, according to the formula... The motor power is dynamically adjusted, where k is the attenuation coefficient. As an increase in risk, This refers to the motor power under normal conditions. When the risk level is low to medium, the potential risk is mitigated by reducing the motor power instead of shutting down the machine. For example, if the risk level increases slightly, the system will automatically reduce the power appropriately to make the mechanical movements smoother and the load smaller, thereby reducing the probability of failure or accident.

[0106] Optimized audio-visual alarm topology: High-risk areas trigger a red rotating alarm + high-frequency buzzer, while low-risk areas trigger a yellow breathing light + intermittent alert sound;

[0107] Mechanical motion constraints: Generate dynamic no-go zones for the robotic arm in three-dimensional space, and correct joint angles in real time through inverse kinematics algorithms;

[0108] Chemical barrier activation: Deploy an air curtain around the leak point, with the air pressure value set according to... control, To adapt parameters for toxicity concentration, The formula is used to automatically adjust the jet pressure of the air curtain used to isolate leaked substances, based on the toxicity concentration of the chemical substance being monitored. The more toxic the chemical substance, the higher the jet pressure, ensuring a strong enough isolation effect to prevent the toxic gas from spreading to the work area.

[0109] By implementing the above measures, the risks can be kept within a controllable range. This can be achieved by dynamically reducing motor power, optimizing alarm methods, limiting the range of motion of the robotic arm, and activating local air curtain isolation. This will effectively mitigate the spread of risks, reduce the possibility of escalation of safety incidents, and maintain the continuous operation of equipment and production stability.

[0110] Level 2 response interventions that trigger partial or complete shutdown include regional power supply cutoff, segmented hydraulic system locking, multi-dimensional emergency stop coordination, and chemical emergency neutralization; among these...

[0111] Regionalized power supply cutoff: Based on the circuit topology map, identify the power supply branches of risky equipment and disconnect only the solid-state relays in the target area;

[0112] Segmented locking of hydraulic system: Insert physical isolation valves into the main pipeline and calculate the optimal locking point based on the fluid dynamics model;

[0113] Multi-dimensional emergency stop coordination: mechanical braking and electrical braking are triggered synchronously;

[0114] Chemical emergency neutralization: Precisely spray pH adjuster into the reaction chamber to achieve the required neutralization rate. The closed-loop control, in the formula This represents the rate of change of acidity over time. The neutral response coefficient, The formula represents the rate at which the neutralizing agent is injected. It indicates that the system automatically adjusts the injection speed of the neutralizing agent based on the rate of increase in acid concentration. If the acid concentration rises rapidly, the injection rate will also increase accordingly, ensuring that the neutralization reaction can promptly cover the risk, achieving precise neutralizing agent delivery, avoiding over- or under-dosing, and enhancing the emergency response effect under severe chemical risks.

[0115] These measures enable rapid, precise, and limited intervention in cases of runaway risks or severe events, avoiding the cascading impact of traditional system-wide power outages. In particular, circuit topology identification and fluid modeling allow for localized isolation and emergency response only in high-risk areas, minimizing disruption to the overall system operation.

[0116] Finally, through the coordinated design and tiered deployment of non-stop and stop intervention methods, the principles of hierarchical execution, local control, and minimal interference in risk response were achieved. This not only enhanced the effectiveness and technical controllability of safety response but also significantly improved the continuous operation capability and emergency response efficiency of industrial cleaning equipment under sudden risks.

[0117] The risk level assessment unit includes a weighted self-optimizing engine:

[0118] Establish a mapping matrix between sensor data and historical accident database ;

[0119] When a new failure event occurs, the failure cause vector is calculated. ;

[0120] according to Update weights, where For learning rate, Contribute probability to the cause;

[0121] when If necessary, the adjustment will be frozen.

[0122] In this embodiment of the invention, by introducing a weight self-optimization engine into the risk level assessment unit, dynamic learning and adaptive adjustment of the weight coefficients of different risk sources are achieved. The system constructs a mapping matrix between sensor data and historical accident events. When a new fault event occurs during actual operation, it can reverse-engineer the key cause vector leading to the fault and adjust the weight coefficients of each risk source according to the weight update formula. Incremental adjustments are made to gradually optimize the sensitivity and accuracy of the risk assessment model. Simultaneously, the system sets convergence criteria; when the change in the weight vector during continuous iterations falls below a preset threshold, the adjustment is automatically frozen to prevent overfitting or model oscillation. This significantly improves the system's adaptive learning capability and long-term accuracy stability of the risk level assessment model, enabling it to continuously optimize risk judgment criteria based on actual operational data and dynamically adapt to the real risk structure under different operating conditions. This enhances the intelligence, foresight, and environmental adaptability of the overall safety strategy generation process.

[0123] The system also features a dual-channel command arbitrator, which includes an automatic decision-making channel and a manual intervention channel; wherein,

[0124] The automatic decision-making channel is used to receive the control instruction sequence output by the multi-level security policy generation unit;

[0125] The manual intervention channel is used to connect to the intelligent operation terminal and receive operator gesture commands or voice commands in real time.

[0126] The dual-channel command arbitrator is configured to execute hierarchical arbitration logic:

[0127] For Level 1 response commands, if the manual intervention channel is within the response window... If a "delay execution" instruction is received, the response will be suspended and a secondary risk assessment will be initiated; if no valid instruction is received within the time limit, the instruction from the automatic decision-making channel will be forcibly executed.

[0128] For the second-level response command, the manual intervention channel access is forcibly frozen, and the automatic decision-making channel command is executed immediately. After execution, an emergency event report and execution basis data packet are pushed to the operation terminal. This achieves efficient collaboration between automatic control and manual judgment, dynamic permission scheduling, and transparent decision-making closed loop, effectively improving the system's response reliability, flexible intervention capability, and human-computer interaction intelligence level under complex working conditions.

[0129] The intelligent operating terminal is configured as follows:

[0130] When the manual intervention channel is activated, a three-dimensional model of the spatial location of the current risk source and its predicted evolution path are displayed.

[0131] A personalized response recommendation model is trained based on the operator's historical decision data, and priority response options are pushed out during the arbitration window.

[0132] Example 2

[0133] like Figure 2 As shown, the present invention also provides a method for generating a multi-level safety control strategy generation system for an industrial cleaning machine as described in Embodiment 1. The method includes the following steps:

[0134] Real-time data collection of industrial cleaning machine operating status and environmental risk data is achieved through multi-source sensors.

[0135] The data is processed based on a dynamic weighted fusion algorithm to output a comprehensive risk level signal.

[0136] Based on the comprehensive risk level signal, a control strategy sequence containing at least two levels of progressive safety response is dynamically generated;

[0137] The drive actuator executes a hierarchical safety response according to the control strategy sequence.

[0138] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0139] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0140] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0141] The embodiments of the present invention have been described above with reference to the accompanying drawings. However, the present invention is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of the present invention without departing from the spirit and scope of the claims. All of these forms are within the protection scope of the present invention.

Claims

1. A multi-level safety control strategy generation system for an industrial cleaning machine, characterized in that, include: The sensor array is configured to collect multidimensional data in real time reflecting the operating status and potential risks of the industrial cleaning machine; A risk level assessment unit, connected to the sensor group, is configured to calculate and output a comprehensive risk level signal in real time based on the multidimensional data; A multi-level security policy generation unit, connected to the risk level assessment unit, is configured to dynamically construct a control policy sequence containing at least two levels of progressive security responses based on the input comprehensive risk level signal; wherein the at least two levels of progressive security responses include: Level 1 response refers to non-shutdown intervention measures triggered when the risk level is below a preset severity threshold. Level 2 response refers to partial or complete shutdown interventions triggered when the risk level reaches or exceeds a preset severity threshold. Output control commands corresponding to the control strategy sequence; An execution unit, connected to the multi-level security policy generation unit, is configured to receive and execute the control commands to drive the corresponding actuators of the industrial cleaning machine to achieve the progressive security response; The risk level assessment unit is further configured as follows: Establish a risk source mapping table to parse the multidimensional data into the following independent risk sources in real time: (a) Sources of mechanical motion risk: including conveyor belt displacement deviation, robotic arm joint pressure, and abnormal clamping force of fixtures; (b) Fluid dynamic risk sources: including main pump pressure pulsation value, pipeline flow rate change rate, and nozzle blockage index; (c) Chemical exposure risk sources: including cleaning agent concentration gradient, vapor leakage threshold, and excessive emissions of exhaust gas; Assign an independent risk weight coefficient to each risk source The weighting coefficients are dynamically adjusted based on the probability of an accident caused by the risk source in the historical fault database; When the actual monitored value of any risk source exceeds its preset threshold When this occurs, a risk tracing command is triggered to identify the highest-risk source. ; The multi-level security policy generation unit, in response to risk tracing instructions, is configured as follows: according to The type matches a predefined response rule base to generate a targeted, progressive strategy sequence: like If the mechanical motion risk source is the first level response, the robot arm motion trajectory smoothing algorithm will be forcibly inserted, and the second level response will trigger a regional shutdown instead of a complete power outage. like If the source of fluid dynamic risk is identified, the first-level response will initiate the pressure buffer valve to gradually release pressure, and the second-level response will close the corresponding branch valve and maintain the main circulation. like If the source is a chemical exposure risk, the first-level response activates the negative pressure suction system and triggers an alarm; the second-level response seals the chamber and injects a neutralizing agent. Finally, hierarchical control instructions strongly correlated with the risk source type are output to the execution unit.

2. The multi-level safety control strategy generation system for an industrial cleaning machine according to claim 1, characterized in that: The control strategy sequence contains three or more levels of progressive responses, and the responses at different levels support parallel and coordinated triggering. When the comprehensive risk level signal simultaneously meets multiple independent risk conditions, the multi-level security policy generation unit generates a composite response instruction set. All parallel instructions undergo logical verification through a conflict detector: if mutual exclusion is detected, priority arbitration is initiated: the instruction with the highest safety priority is executed immediately, and the next highest priority instruction is delayed until the conflict is resolved. The execution unit is configured to synchronously process composite instruction sets using a multi-threaded control protocol.

3. The multi-level safety control strategy generation system for an industrial cleaning machine according to claim 1, characterized in that: The system further includes an operation phase identification module, configured to determine the current operation phase based on a logical combination of at least two signals, specifically: In response to the main motor start signal and the heater enable status, it is marked as the start-up preheating stage; If the conveyor belt speed is greater than the preset value and the number of spray valves opened is greater than or equal to 2, it is marked as a normal cleaning stage; If the drain pump current value continues to rise and the hatch position sensor triggers a signal, it is marked as the drain maintenance stage. The multi-level security policy generation unit is further configured to: configure an independent risk level-response action mapping relationship for each operational phase, specifically including: When the startup warm-up phase is in progress, a Level 2 comprehensive risk level will trigger a Level 2 response; the Level 1 response only includes audible and visual alarms. During the normal cleaning phase, a Level 2 response is triggered only when the overall risk level reaches Level 3; the Level 1 response includes power regulation and flow compensation. When the system is in the drainage maintenance phase, the first-level response is cancelled. If the overall risk level reaches Level 1, the second-level response is triggered. The second-level response forces the activation of the waste liquid recovery device.

4. The multi-level safety control strategy generation system for an industrial cleaning machine according to claim 1, characterized in that: The non-shutdown intervention measures triggered by the first-level response specifically include gradient power adjustment, audible and visual alarm topology optimization, mechanical motion constraints, and chemical barrier activation.

5. The multi-level safety control strategy generation system for an industrial cleaning machine according to claim 1, characterized in that: The second-level response triggers partial or complete shutdown intervention measures, including regional power supply cut-off, segmented locking of hydraulic systems, multi-dimensional emergency stop coordination, and chemical emergency neutralization.

6. The multi-level safety control strategy generation system for an industrial cleaning machine according to claim 1, characterized in that: The risk level assessment unit includes a weighted self-optimization engine: Establish a mapping matrix between sensor data and historical accident database ; When a new failure event occurs, the failure cause vector is calculated. ; according to Update weights, where For learning rate, Contribute probability to the cause; when If so, the adjustment will be frozen.

7. The multi-level safety control strategy generation system for an industrial cleaning machine according to claim 1, characterized in that: The system also features a dual-channel command arbitrator, which includes an automatic decision-making channel and a manual intervention channel; wherein, The automatic decision-making channel is used to receive the control instruction sequence output by the multi-level security policy generation unit; The manual intervention channel is used to connect to the intelligent operation terminal and receive operator gesture commands or voice commands in real time. The dual-channel command arbitrator is configured to execute hierarchical arbitration logic: For Level 1 response commands, if the manual intervention channel is within the response window... If a "delay execution" instruction is received, the response will be suspended and a secondary risk assessment will be initiated; if no valid instruction is received within the time limit, the instruction from the automatic decision-making channel will be forcibly executed. For Level 2 response commands, the manual intervention channel access is forcibly frozen, the automatic decision-making channel command is executed immediately, and after execution, an emergency event report and execution basis data packet are pushed to the operation terminal.

8. The multi-level safety control strategy generation system for an industrial cleaning machine according to claim 7, characterized in that: The intelligent operation terminal is configured as follows: When the manual intervention channel is activated, a three-dimensional model of the spatial location of the current risk source and its predicted evolution path are displayed. A personalized response recommendation model is trained based on the operator's historical decision data, and priority response options are pushed during the arbitration window.

9. A method for generating a multi-level safety control strategy for an industrial cleaning machine using the multi-level safety control strategy generation system as described in claim 1, characterized in that: Includes the following steps: Real-time data collection of industrial cleaning machine operating status and environmental risk data is achieved through multi-source sensors. The data is processed based on a dynamic weighted fusion algorithm to output a comprehensive risk level signal. Based on the comprehensive risk level signal, a control strategy sequence containing at least two levels of progressive safety response is dynamically generated; The drive actuator executes a hierarchical safety response according to the control strategy sequence.

Images