An intelligent control system for extreme environment high-mobility all-terrain emergency equipment

Abstract

The application discloses an extreme environment high-maneuverability all-terrain emergency equipment intelligent control system and relates to the technical field of intelligent control.The application comprises an extreme environment data acquisition module, an emergency equipment adaptation analysis module and an emergency equipment intelligent control module.The application collects extreme environment and topographic and geomorphic data through a plurality of types of environment sensors and terrain detection equipment, realizes accurate identification of the type of extreme environment in combination with similarity matching, further evaluates the health state and performance of equipment based on the type of environment and data, generates an environment adaptation index and an alternative operation scheme, and makes real-time intelligent decisions for the equipment according to the operation scheme, collects multi-dimensional feedback data and dynamically corrects the scheme, realizes intelligent regulation and control of the equipment and operation optimization, solves the problems of poor adaptability of emergency equipment and untimely adjustment of operation schemes in an extreme environment, improves the operation safety, stability and efficiency of the equipment in a complex extreme environment, and provides reliable technical support for emergency operation in an extreme environment.

Description

Technical Field

[0001] This invention relates to the field of intelligent control technology, specifically to an intelligent control system for highly mobile all-terrain emergency equipment in extreme environments. Background Technology

[0002] Intelligent management and control of emergency equipment is a core technological support for improving disaster emergency response efficiency, ensuring the safety of rescue operations, and reducing the operational risks for frontline rescue personnel. Against the backdrop of frequent various sudden disasters, emergency rescue operations place increasingly stringent demands on equipment. In recent years, with the rapid iteration and deep integration of technologies such as intelligent control, the Internet of Things, industrial automation, multi-sensor fusion, and wireless communication, emergency equipment has gradually broken free from the limitations of traditional manual operation and independent single-machine operation, rapidly developing towards intelligence, networking, and integration, providing fundamental intelligent technological support for emergency rescue operations in routine scenarios.

[0003] Current intelligent control technology systems for emergency equipment still have significant technical shortcomings and application limitations, failing to meet the actual operational needs of highly mobile all-terrain emergency equipment in extreme environments. Firstly, existing technologies focus only on data acquisition and command issuance under normal operating conditions, without conducting systematic quantitative assessments of the characteristics of different typical scenarios. This fails to provide a scientific environmental adaptation basis for operational decisions of highly mobile all-terrain equipment, leading to a significant decrease in the equipment's passability and operational stability in complex terrain. Secondly, existing technologies only achieve one-way acquisition and feedback of operating parameters, making it difficult to accurately predict equipment health degradation and performance adaptation risks, easily leading to operational interruptions or even safety accidents. Thirdly, existing technologies are primarily based on passive response control, unable to adjust equipment operating parameters in real time when facing dynamic changes in extreme environments, making it difficult to ensure the continuity and safety of emergency operations. Summary of the Invention

[0004] The main objective of this invention is to disclose an intelligent control system for highly mobile all-terrain emergency equipment in extreme environments, comprising: The extreme environment data acquisition module is used to collect extreme environment data and topographic data by deploying various types of environmental sensors and terrain detection equipment in the extreme environment operation area, and to analyze and identify the current extreme environment type based on the extreme environment data and topographic data. The extreme environment data includes ambient temperature and humidity, wind speed and direction, atmospheric pressure, rain and snow intensity, and altitude; the topographic data includes terrain slope, surface roughness, obstacle distribution dispersion, and geological stability. Furthermore, the extreme environment type is an accurate identification result achieved by constructing feature vectors based on normalization processing and using a similarity matching algorithm.

[0005] The emergency equipment compatibility analysis module analyzes the health status and performance of each emergency equipment based on extreme environment type, extreme environment data and terrain data, and generates an environmental compatibility index and alternative operation plans. The analysis of health status and performance refers to obtaining health assessment results and performance assessment results by comparing the rate of change of real-time operating parameters and baseline parameters with qualified thresholds; the alternative operation plan is to determine the high adaptation level, medium adaptation level or low adaptation level by setting grade thresholds to formulate corresponding plans. The health assessment results refer to determining whether the equipment is in a healthy or unhealthy state by comparing the rate of change of operational stability, the rate of change of equipment wear rate, and the rate of change of functional integrity of each component with their respective qualification thresholds. The performance assessment results refer to determining whether the performance assessment results are fully adapted or quantify the performance degradation by comparing the rate of change of power output efficiency, maneuverability, and operational accuracy with qualification thresholds. The environmental adaptability index is obtained by weighted summation of the health assessment results, performance assessment results, extreme environment data, and terrain data. The alternative operation schemes include efficient operation schemes, load reduction operation schemes, and hazard avoidance operation schemes. The efficient operation plan involves setting the equipment to full-load power output, conventional maneuvering speed, and standard operation accuracy. The load reduction operation plan involves lowering the power output threshold and limiting the maneuvering speed while meeting the basic functions and safety requirements of emergency operations, thereby expanding the allowable deviation range of operation accuracy. The risk avoidance operation plan involves controlling the equipment power output within a safe operating range, suspending conventional emergency operations, retaining the equipment's safe relocation, self-checking, and basic protection functions, and simultaneously triggering abnormal warnings.

[0006] The emergency equipment intelligent control module, based on the environmental adaptability index and alternative operation schemes, performs intelligent regulation and operation optimization of highly mobile all-terrain emergency equipment in extreme environments; The emergency equipment intelligent control module also includes an operation plan optimization unit and an intelligent decision execution unit. Furthermore, the operation plan optimization unit determines the optimal operation plan from the candidate operation plans based on the environmental adaptability index; the intelligent decision execution unit makes real-time intelligent decisions on emergency equipment based on the optimal operation plan, and collects multi-dimensional operation feedback data to dynamically correct the operation plan.

[0007] The dynamic correction operation plan refers to: calculating the deviation distance by constructing the Euclidean distance between the real-time feedback data vector and the optimal operation plan parameter vector, and comparing the deviation to the qualified threshold to determine whether it is necessary to correct the power output, maneuver speed and operation execution accuracy parameters.

[0008] According to this invention, extreme environment data and topographic data are collected collaboratively by multiple types of environmental sensors and terrain detection equipment. Normalization processing is used to construct feature vectors, which are then combined with similarity matching to achieve accurate identification of extreme environment types. A dual-dimensional evaluation system for equipment health and performance is constructed to quantify the equipment's health status and performance degradation. Differentiated alternative operational plans are generated based on environmental adaptability index classification. Through a dynamic correction intelligent control closed loop using plan matching and Euclidean distance deviation quantification, the system effectively addresses dynamic changes in extreme environments and equipment operational deviations. This solves the problems of poor adaptability of emergency equipment and untimely adjustment of operational plans in extreme environments, improving the safety, stability, and efficiency of equipment operations in complex and extreme environments. Attached Figure Description

[0009] Figure 1 This is a diagram of the intelligent control system architecture for highly mobile all-terrain emergency equipment in extreme environments, provided according to an embodiment of the present invention. Detailed Implementation

[0010] The specific implementation of the present invention will now be described in detail with reference to the accompanying drawings.

[0011] Figure 1 This is a diagram of the intelligent control system architecture for highly mobile all-terrain emergency equipment in extreme environments provided by the present invention, as shown below. Figure 1 As shown, it includes: The P100 extreme environment data acquisition module is used to collect extreme environment data and topographic data by deploying various types of environmental sensors and terrain detection equipment in extreme environment operation areas, and to analyze and identify the current extreme environment type based on the extreme environment data and topographic data. The extreme environment data acquisition module is equipped with various types of environmental sensors and terrain detection equipment, including: temperature and humidity sensors, wind speed and direction sensors, rain and snow intensity sensors, altitude sensors, ground-penetrating radar, and stress sensors. Specifically, the extreme environmental data includes ambient temperature and humidity, wind speed and direction, atmospheric pressure, rain and snow intensity, and altitude; the topographic data includes terrain slope, surface roughness, obstacle distribution dispersion, and geological stability. Furthermore, for extreme environment types, a feature vector construction based on normalization and a similarity matching algorithm are used to achieve accurate identification. The specific steps are as follows: Step 1: Normalize the collected extreme environment data and topographic data to eliminate the influence of different units and obtain standardized values; Step 2: Based on standardized numerical values, construct feature vectors for extreme environment data and topographic data respectively, and merge them to obtain a comprehensive feature vector for extreme environment. Step 3: Construct a data template library using historical extreme environment type data to store comprehensive feature vectors for various extreme environment types; Step 4: Calculate the similarity between the current extreme environment comprehensive feature vector and the comprehensive feature vectors of each type of extreme environment in the data template library. The similarity measure is cosine similarity or Euclidean distance. Step 5: Select the extreme environment type with the highest similarity that is greater than the set judgment threshold as the recognition result.

[0012] The P110 emergency equipment compatibility analysis module analyzes the health status and performance of each emergency equipment based on extreme environment type, extreme environment data and terrain data, and generates an environmental compatibility index and alternative operation plans. Specifically, the analysis of health status and performance refers to obtaining health assessment results and performance assessment results by comparing the rate of change of real-time operating parameters and baseline parameters with the qualified threshold. The health assessment result refers to determining whether the equipment is in a healthy or unhealthy state by comparing the rate of change of operational stability, the rate of change of equipment wear rate, and the rate of change of functional integrity with their respective qualification thresholds for each component. The performance assessment result refers to determining whether the performance assessment result is fully adapted or the magnitude of performance degradation by comparing the rate of change of power output efficiency, maneuverability, and operational accuracy with qualification thresholds.

[0013] 1) The specific steps for obtaining health assessment results are as follows: Step 1: Under the current extreme environment type, obtain the change rate of equipment operating status parameters of each emergency equipment under this type of extreme environment. The change rate of equipment operating status parameters includes the change rate of operating stability, the change rate of equipment wear rate, and the change rate of functional integrity. Step 2: Obtain the qualified threshold of the equipment operation status parameters corresponding to each type of emergency equipment under the current extreme environment, compare the change rate of each equipment operation status parameter with the corresponding qualified threshold, and construct a judgment status matrix; Step 3: The judgment rule is as follows: if the change rate of operational stability, the change rate of equipment wear rate, and the change rate of functional integrity are all within the corresponding qualified threshold range, the equipment is judged to be in a healthy state; if any change rate exceeds the corresponding qualified threshold range, the equipment is judged to be in an unhealthy state, and the components that exceed the threshold and the current degree of deviation are recorded.

[0014] 2) The specific steps for performance evaluation results are as follows: Step 1: Obtain operational performance parameters, including: rate of change, including the rate of change of power output efficiency, the rate of change of maneuverability, and the rate of change of operational execution accuracy; Step 2: Compare the rate of change of each performance parameter with the corresponding qualified threshold. If the rate of change of power output efficiency, the rate of change of maneuverability, and the rate of change of work execution accuracy are all within the corresponding qualified threshold range, the performance evaluation result is determined to be fully adapted. If any rate of change exceeds the corresponding qualified threshold range, the quantitative performance degradation magnitude is calculated and output.

[0015] The P120 emergency equipment intelligent control module, based on the environmental adaptability index and alternative operation schemes, intelligently regulates and optimizes the operation of highly mobile all-terrain emergency equipment in extreme environments. The emergency equipment intelligent control module includes a P121 operation plan optimization unit and a P122 intelligent decision execution unit.

[0016] The P121 operation plan optimization unit determines the optimal operation plan from the candidate operation plans based on the environmental adaptability index. When the environmental adaptability index is determined to be high adaptability level, the high-efficiency operation plan is preferred; when it is determined to be medium adaptability level, the load reduction operation plan is preferred; when it is determined to be low adaptability level, the risk avoidance operation plan is preferred. Specifically, the high-efficiency operation plan, the load reduction operation plan, and the hazard avoidance operation plan achieve a balance between emergency operation efficiency and equipment and personnel safety based on the working conditions of different environmental equipment adaptation levels, and realize flexible and safe adaptation of emergency operations in extreme environments.

[0017] The high-efficiency operation plan refers to setting the equipment to use full-load power output, conventional maneuver speed and standard operation accuracy, without the need to add additional operational constraints; it is suitable for high-adaptability level working conditions, where the equipment is in good health and extreme environmental constraints are weak, and the plan aims to maximize emergency operation efficiency. The load reduction operation plan refers to: under the premise of meeting the basic functions and safety requirements of emergency operation, lowering the power output threshold and limiting the maneuver speed, while expanding the allowable deviation range of operation execution accuracy, and monitoring the equipment operating conditions in real time; it is applicable to medium-adaptability level operating conditions, where the equipment or extreme environment has certain constraints and risks. The plan aims to balance efficiency and safety, avoiding equipment overload or expansion of environmental risks while meeting the basic functions of emergency operation, and strengthening the real-time monitoring of equipment operating conditions. The emergency response plan refers to controlling the equipment's power output within a safe operating range, suspending routine emergency operations, retaining the equipment's safe relocation, self-checking, and basic protection functions, and simultaneously triggering anomaly warnings. It is applicable to low-compatibility-level operating conditions, where there are serious safety hazards in the equipment or extreme environment. The plan takes ensuring the safety of equipment and personnel as its core objective, suspending routine emergency operations, and simultaneously triggering anomaly warnings to prevent accidents from occurring.

[0018] 1) The specific steps for the environmental adaptability index are as follows: Step 1: Set weighting coefficients for equipment health assessment results, performance assessment results, extreme environment data, and terrain data. Multiply the four types of data by their corresponding weighting coefficients and sum them to obtain the environmental adaptability index. ; The weight coefficients of the four types of data in the environmental adaptability index are set according to the priority of emergency operations. For example, in the rescue and relief scenario, the weight ratio of performance evaluation results and environmental impact index can be appropriately increased; in the evacuation and shelter scenario, the weight ratio of health evaluation results and terrain adaptability index can be appropriately increased to adapt to the decision-making needs under different emergency operation objectives. Step 2: Set the first-level threshold Second-level threshold The classification can be based on the equipment's maximum operational capability and its tolerance limit in extreme environments; for example, it can be... Set to 0.7 The value is set to 0.4, which corresponds to three levels: high compatibility, medium compatibility, and low compatibility, to clearly classify the degree of compatibility between the environment and equipment. Step 3: When When it is determined to be of a high compatibility level, an efficient operation plan is formulated; when When the condition is determined to be of medium compatibility level, a load reduction operation plan is formulated; when If the condition is deemed to be of low compatibility level, a risk avoidance operation plan should be formulated.

[0019] The P122 intelligent decision-making and execution unit makes real-time intelligent decisions on emergency equipment based on the optimal operation plan and issues control commands to each execution mechanism of the equipment. 1) The specific method for real-time intelligent decision-making is as follows: Step 1: Retrieve the predetermined operating parameters from the operation plan, generate corresponding operation control commands based on the operating parameters, and send them to each execution terminal of the emergency equipment to drive the equipment to enter the operation state according to the commands. The predetermined operating parameters include: equipment power output, maneuver speed, and operation execution accuracy. Step 2: Throughout the entire equipment operation process, continuously collect multi-dimensional feedback data from the equipment, including: real-time operating conditions, operation progress, and adaptability to extreme environments; Step 3: Compare and analyze the feedback data with the predetermined parameters and requirements of the optimal work plan, and dynamically revise the work plan based on the data deviation and analysis results.

[0020] 2) The specific method for dynamically correcting the work plan is as follows: Step 1: Based on the collected multi-dimensional feedback data, construct real-time feedback data vectors for power output, maneuver speed, and operational accuracy. ,in This is the measured value of power output. This is the measured value of the maneuver speed. This represents the measured value of the operation's execution accuracy. Step 2: Construct the corresponding parameter vector based on the optimal task plan. ,in The power output value specified in the optimal operation plan. The speed value specified in the optimal operation plan. This refers to the execution accuracy value specified in the optimal work plan. Step 3: Calculate the deviation distance between the two vectors using the Euclidean distance formula. The formula is as follows: In the Euclidean distance formula, the real-time feedback data vector and the optimal operation plan parameter vector correspond to the actual operating state of the equipment and the preset ideal state, respectively. By calculating the deviation distance between the two vectors, the overall deviation of multi-dimensional parameters can be quantified, avoiding misjudgment caused by the deviation of a single parameter, and improving the accuracy and pertinence of the plan correction. For example, when the real-time feedback data vector shows that the measured power output is 15% higher than the value specified in the optimal operation plan, and the deviations in maneuver speed and operation accuracy are both within 5%, it is determined that the deviation is mainly caused by the excessive power output. At this time, the power output parameter is lowered to 90%-95% of the optimal value, and the maneuver speed is finely adjusted to 98% of the original set value to match the power output change and avoid sudden changes in equipment load. Step 4: Extract the deviation acceptance threshold. If the deviation distance is less than or equal to the deviation acceptance threshold, maintain the current work plan and operating parameters. If the deviation distance is greater than the deviation acceptance threshold, adjust the power output, maneuver speed, and work execution accuracy parameters in the work plan according to the deviation distance and the deviation of each dimension parameter. The deviation acceptance threshold is set based on the equipment's operational accuracy requirements and safety redundancy standards. If the deviation is less than or equal to the acceptable threshold, the equipment is deemed to be in compliance with the requirements. If it exceeds the acceptable threshold, the power output, speed, and operational accuracy parameters need to be adjusted accordingly.

[0021] This invention, based on normalization processing, similarity matching, multi-dimensional quantitative scoring, and dynamic deviation correction technology, integrates multi-type sensor data and terrain detection data for extreme environments. During equipment operation, it continuously improves and optimizes by combining feedback data. This solves the problems of traditional methods for assessing the adaptability of emergency equipment in extreme environments, the extensive and tiered operation plans, the lag in dynamic adjustment response, and the lack of effective coordination between environmental changes and equipment operation deviations. It improves the equipment's operational adaptability and response speed in extreme environments, significantly enhances the intelligence level of emergency rescue and relief operations, and ensures the safety and efficiency of rescue operations.

[0022] The above-disclosed embodiments are merely a few specific examples of the present invention. However, the present invention is not limited thereto, and any variations that can be conceived by those skilled in the art should fall within the protection scope of the present invention.

Claims

1. An intelligent control system for highly mobile all-terrain emergency equipment in extreme environments, characterized in that, include: The extreme environment data acquisition module is used to collect extreme environment data and topographic data by deploying various types of environmental sensors and terrain detection equipment in the extreme environment operation area, and to analyze and identify the current extreme environment type based on the extreme environment data and topographic data. The emergency equipment compatibility analysis module analyzes the health status and performance of each emergency equipment based on extreme environment type, extreme environment data and terrain data, and generates an environmental compatibility index and alternative operation plans. The emergency equipment intelligent control module, based on the environmental adaptability index and alternative operation schemes, performs intelligent regulation and operation optimization of highly mobile all-terrain emergency equipment in extreme environments; The emergency equipment intelligent control module also includes an operation plan selection unit and an intelligent decision execution unit.

2. The intelligent control system for highly mobile all-terrain emergency equipment in extreme environments according to claim 1, characterized in that, The operation plan selection unit determines the operation plan from the candidate operation plans based on the environmental adaptability index.

3. The intelligent control system for highly mobile all-terrain emergency equipment in extreme environments according to claim 2, characterized in that, The intelligent decision-making and execution unit makes real-time intelligent decisions on emergency equipment based on the operation plan, and collects multi-dimensional operation feedback data to dynamically correct the operation plan.

4. The intelligent control system for highly mobile all-terrain emergency equipment in extreme environments according to claim 3, characterized in that, The dynamic correction operation plan refers to: by constructing the Euclidean distance between the real-time feedback data vector and the operation plan parameter vector, calculating the deviation distance, and comparing it with the deviation qualification threshold to determine whether it is necessary to correct the power output, maneuver speed and operation execution accuracy parameters.

5. The intelligent control system for highly mobile all-terrain emergency equipment in extreme environments according to claim 1, characterized in that, The extreme environment data includes ambient temperature and humidity, wind speed and direction, atmospheric pressure, rain and snow intensity, and altitude; the topographic data includes terrain slope, surface roughness, obstacle distribution dispersion, and geological stability.

6. The intelligent control system for highly mobile all-terrain emergency equipment in extreme environments according to claim 1, characterized in that, The extreme environment type is an accurate identification result achieved by constructing feature vectors based on normalization processing and using a similarity matching algorithm.

7. The intelligent control system for high-mobility all-terrain emergency equipment in extreme environments according to claim 1, characterized in that, The analysis of health status and performance refers to obtaining health assessment results and performance assessment results by comparing the rate of change of real-time operating parameters with the baseline parameters and the qualified threshold. The health assessment result refers to determining whether the equipment is in a healthy or unhealthy state by comparing the rate of change of operational stability, the rate of change of equipment wear rate, and the rate of change of functional integrity of each component with their respective qualification thresholds. The performance assessment result refers to determining whether the performance assessment result is fully adapted or the quantified performance degradation range by comparing the rate of change of power output efficiency, maneuverability, and operational accuracy with the qualification thresholds.

8. The intelligent control system for highly mobile all-terrain emergency equipment in extreme environments according to claim 1, characterized in that, The environmental adaptability index is obtained by weighted summation of health assessment results, performance assessment results, extreme environment data, and topographic data.

9. The intelligent control system for highly mobile all-terrain emergency equipment in extreme environments according to claim 1, characterized in that, The alternative operation plan is determined by setting a grading threshold to determine the high adaptation level, medium adaptation level, or low adaptation level in order to formulate a corresponding plan.

10. The intelligent control system for highly mobile all-terrain emergency equipment in extreme environments according to claim 1, characterized in that, The alternative operating schemes include efficient operating schemes, load reduction operating schemes, and risk avoidance operating schemes; The efficient operation plan involves setting the equipment to full-load power output, conventional maneuvering speed, and standard operation accuracy. The load reduction operation plan involves lowering the power output threshold and limiting the maneuvering speed while meeting the basic functions and safety requirements of emergency operations, thereby expanding the allowable deviation range of operation accuracy. The risk avoidance operation plan involves controlling the equipment power output within a safe operating range, suspending conventional emergency operations, retaining the equipment's safe relocation, self-checking, and basic protection functions, and simultaneously triggering abnormal warnings.

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