Agv carrying monitoring method, system and equipment for underground garage

Abstract

The application discloses an AGV carrying monitoring method, system and equipment for an underground garage, and relates to the technical field of AGV carrying monitoring control. The AGV carrying monitoring method for the underground garage comprises the following steps: underground garage disaster identification; AGV response to visibility adjustment optimization is carried out according to comparative analysis of visibility; AGV response to high temperature adjustment optimization is carried out according to comparative analysis of AGV backboard temperature; AGV response to electromagnetic pulse adjustment optimization is carried out according to comparative analysis of electromagnetic intensity borne by the AGV backboard; the AGV judges to reach the underground garage safety house, and starts a closed fire extinguishing scheme. Through the butt joint, bearing and carrying of the AGV and the self-igniting vehicle, the environmental visibility, backboard temperature and electromagnetic interference are analyzed and adjusted in steps in the carrying process, so that the effect of improving the dynamic regulation and control adaptability of the AGV carrying the self-igniting vehicle in the underground garage is achieved, and the problem of insufficient dynamic regulation and control adaptability of the AGV carrying the self-igniting vehicle in the underground garage in the prior art is solved.

Description

Technical Field

[0001] This invention relates to the field of AGV handling monitoring and control technology, and in particular to AGV handling monitoring methods, systems and equipment for underground parking garages. Background Technology

[0002] The development of AGV (Automated Guided Vehicle) handling monitoring methods is primarily driven by the continuous improvement of global industrial automation levels, which has propelled the rapid development of AGV handling robots. With rising labor costs, enterprises have an increasingly urgent need to improve production efficiency and reduce costs. AGV handling robots, due to their high efficiency, stability, and safety, have become an important tool for achieving automated production. Furthermore, the development of applications in fire-fighting scenarios has also promoted the widespread use of AGVs in warehousing and logistics.

[0003] Existing AGV (Automated Guided Vehicle) handling monitoring methods in underground parking garages have the following main technical functions: Autonomous navigation is achieved through technologies such as LiDAR, visual navigation, and inertial navigation, requiring no human intervention. Optimal paths are planned based on task requirements and environmental conditions to ensure safe and efficient operation. Multiple AGVs can work collaboratively, achieving collective handling tasks through communication and coordination. Equipped with various sensors, they can perceive the surrounding environment in real time, including obstacles, pedestrians, vehicles, and the status of goods. They can automatically return to the charging station for charging when needed, without human intervention.

[0004] For example, the invention patent with publication number CN109656256A discloses an AGV-based automated handling system, including: an AGV ground control system, a communication module, an assignment unit, a sending unit, a receiving unit, a processing unit, and an AGV vehicle system. The AGV ground control system is signal-connected to the communication module, the communication module is signal-connected to the assignment unit, the assignment unit is signal-connected to the sending unit, the sending unit is signal-connected to the receiving unit, and the receiving unit is signal-connected to the processing unit. This system processes the transmitted instruction information through the AGV ground control system, communication module, assignment unit, sending unit, receiving unit, processing unit, and AGV vehicle system; it uses a GPS positioning system for real-time positioning of the handling system; it stores the machine's travel path through a storage module; and it uses an alarm system, battery monitoring unit, anti-collision protection system, self-test system, and interface module to monitor and control system stability in real time.

[0005] For example, the invention patent with publication number CN109885050A discloses a safety protection system for an AGV handling robot, comprising: a second plate fixed to the outer side of a turntable; a frame fixed to the outer side of the second plate; a U-shaped spring fixed to the inner side of the frame by screws; a movable plate fixed to the outer side of the U-shaped spring by screws; a protruding column fixed to the movable plate; a third plate fixed to the outer side of the protruding column; and an ultrasonic sensor fixed to the outer side of the third plate. A control system is located on the top of the vehicle body. The second plate is rotated by rollers, ensuring the ultrasonic sensor always measures the direction of travel. Laser rangefinders are distributed around the robot, and the control system monitors the robot's working status.

[0006] However, in the process of implementing the inventive technical solution in the embodiments of this application, it was found that the above-mentioned technology has at least the following technical problems:

[0007] In existing technologies, AGVs can be used to transport vehicles that spontaneously combust in underground parking garages to a safe location. However, due to factors such as reduced visibility caused by spontaneous combustion, high temperature fluctuations, and electromagnetic pulses caused by battery combustion, unexpected situations may occur during the transport of spontaneously combustible vehicles by AGVs. This indicates that the dynamic control adaptability of AGVs in transporting spontaneously combustible vehicles in underground parking garages is insufficient. Summary of the Invention

[0008] This application provides an AGV handling monitoring method, system, and equipment for underground parking garages, which solves the problem of insufficient dynamic control adaptability of AGVs transporting spontaneously combusting vehicles in underground parking garages in the prior art, and achieves the effect of improving the dynamic control adaptability of AGVs transporting spontaneously combusting vehicles in underground parking garages.

[0009] This application provides an AGV handling monitoring method for underground parking garages, including the following steps: disaster identification in the underground parking garage; if a vehicle on fire is detected, the AGV docks with, carries, and transports the vehicle; the AGV judges the environmental visibility during transport in real time, and adjusts and optimizes its response based on visibility comparison analysis; the AGV judges the temperature of its backplate during transport in real time, and adjusts and optimizes its response to high temperatures based on AGV backplate temperature comparison analysis; the AGV judges the electromagnetic intensity received by its backplate during transport in real time, and adjusts and optimizes its response to electromagnetic pulses based on electromagnetic intensity comparison analysis; the AGV determines that it has reached the underground parking garage safety room and activates the closed fire extinguishing plan.

[0010] Furthermore, the AGV's docking, carrying, and transporting of the spontaneously combusting vehicle specifically includes: real-time monitoring of fire warning data in the corresponding underground garage area through a distributed fire sensor array; if the local temperature of the vehicle in the fire warning data is less than the corresponding spontaneously combusting vehicle temperature threshold, no action is taken; if the local temperature of the vehicle in the fire warning data is equal to or greater than the corresponding spontaneously combusting vehicle temperature threshold, the corresponding vehicle is identified as a spontaneously combusting vehicle, the underground garage area where the spontaneously combusting vehicle is located is recorded, a predefined isolation procedure is initiated for the underground garage area where the spontaneously combusting vehicle is located, and the AGV is invoked to travel to the underground garage area where the spontaneously combusting vehicle is located through a predefined layered path planning scheme; the AGV unfolds its three-stage telescopic arm through a special AGV hydraulic lifting mechanism, grabs the vehicle chassis support point, and the AGV transports the corresponding spontaneously combusting vehicle to a predefined underground garage safety room.

[0011] Furthermore, the AGV's visibility adjustment and optimization based on visibility comparison analysis specifically includes: real-time acquisition of the visibility of the underground parking garage environment using the AGV's lidar; if the visibility of the underground parking garage environment is greater than a first visibility threshold, no adjustment is made; if the visibility of the underground parking garage environment is greater than a second visibility threshold but less than or equal to the first visibility threshold, air brush cleaning is activated through the AGV's built-in rotary air brush cleaning device; if the visibility of the underground parking garage environment is greater than a third visibility threshold but less than or equal to the second visibility threshold, the optical sensor is turned off, while the non-optical sensor remains on; if the visibility of the underground parking garage environment is less than or equal to the third visibility threshold, relevant personnel are notified for manual remote control.

[0012] Furthermore, the optimization of AGV response to high temperatures based on the comparative analysis of AGV backplate temperature specifically includes: real-time acquisition of AGV backplate temperature using AGV temperature sensors; if the AGV backplate temperature is less than or equal to the third threshold of AGV tolerance temperature, a high-temperature negative impact correction assessment and adjustment is performed; if the AGV backplate temperature is greater than the third threshold of AGV tolerance temperature but less than or equal to the second threshold of AGV tolerance temperature, infrared thermal imager thermal radiation compensation is performed; if the AGV backplate temperature is greater than the second threshold of AGV tolerance temperature but less than or equal to the first threshold of AGV tolerance temperature, a first cooling treatment is performed using the integrated thermoelectric cooling device built into the AGV; if the AGV backplate temperature is greater than the first threshold of AGV tolerance temperature, a second cooling treatment is performed using the nitrogen curtain protection device built into the edge of the AGV backplate.

[0013] Furthermore, the specific process for the high-temperature negative impact correction assessment and adjustment is as follows: The maximum temperature dispersion of the AGV backplate and the ambient temperature difference of the AGV path planning sensor optical lens are obtained through temperature sensor data acquisition and analysis; the average dark current of the avalanche photodiode of the APD detector of the AGV path planning sensor is acquired through a built-in current sampler; the predefined threshold of the AGV backplate temperature dispersion, the preset radius of curvature of the AGV path planning sensor optical lens, the preset thermal expansion coefficient of the AGV path planning sensor optical lens, the expansion difference between the metal bracket and the glass reflector, and the value of the avalanche photodiode of the APD detector are directly extracted from the underground parking garage AGV handling monitoring database. The standard value of dark current is used; the ratio analysis of the maximum temperature dispersion of the AGV backplane and the predefined threshold of the temperature dispersion of the AGV backplane is used to obtain the first variable of high temperature for the AGV path planning sensor; the preset thermal expansion coefficient of the AGV path planning sensor optical lens and the expansion difference between the metal bracket and the glass reflector are first superimposed, and then coupled with the preset radius of curvature of the AGV path planning sensor optical lens and the ambient temperature difference of the AGV path planning sensor optical lens respectively, to obtain the second variable of high temperature for the AGV path planning sensor; the ratio analysis of the average dark current of the avalanche photodiode of the APD detector and the standard value of the dark current of the avalanche photodiode of the APD detector is used to obtain the AGV path planning sensor... The high temperature of the AGV path planning sensor is the third variable; the high temperature of the AGV path planning sensor is corrected by the corresponding weight factor to obtain the first weight variable of the AGV path planning sensor high temperature, the second variable of the AGV path planning sensor high temperature is corrected by the corresponding weight factor to obtain the second weight variable of the AGV path planning sensor high temperature, and the third variable of the AGV path planning sensor high temperature is corrected by the corresponding weight factor to obtain the third weight variable of the AGV path planning sensor high temperature; combined with the first weight variable of the AGV path planning sensor high temperature, ... The second and third weighted variables of high temperature in the AGV path planning sensor are analyzed together to obtain the correction value for the negative impact of high temperature on the AGV path planning sensor. The correction value is used to describe the average dark current of the avalanche photodiode of the APD detector of the AGV path planning sensor, and the degree of quantification of the negative distortion of the AGV path planning sensor caused by external high temperature by the first and second variables of high temperature. If the correction value for the negative impact of high temperature on the AGV path planning sensor is less than the corresponding threshold for the negative impact of high temperature on the AGV path planning sensor, no adjustment is made.If the high-temperature negative impact correction value of the AGV path planning sensor is equal to or greater than the corresponding high-temperature negative impact threshold of the AGV path planning sensor, then the SiCMOSFET parallel drive of the AGV motor driver is activated, and thermal correction is performed using predefined software based on the temperature acquisition data built into the AGV path planning sensor.

[0014] Furthermore, the step of adjusting and optimizing the AGV's response to electromagnetic pulses based on the comparative analysis of the electromagnetic intensity received by the AGV's backplate specifically includes: real-time acquisition of the AGV's environmental electromagnetic intensity through the AGV's electromagnetic sensors; if the AGV's environmental electromagnetic intensity is less than or equal to the AGV's environmental electromagnetic intensity threshold, no adjustment is made; if the AGV's environmental electromagnetic intensity is greater than the AGV's environmental electromagnetic intensity threshold, a high electromagnetic interference negative impact correction assessment and adjustment is performed.

[0015] Furthermore, the aforementioned high electromagnetic interference negative impact correction assessment and adjustment specifically includes: real-time acquisition of the instantaneous maximum intensity and rise time of the electromagnetic pulse using the broadband electric field probe built into the AGV; recording the start time of the electromagnetic pulse rise time; if the electromagnetic pulse intensity is less than the electromagnetic pulse intensity attention threshold, recording the electromagnetic pulse termination time; and recording the difference between the electromagnetic pulse termination time and the electromagnetic pulse rise time start time as the electromagnetic pulse duration; directly extracting the allowable electromagnetic pulse intensity value from the underground parking garage AGV handling monitoring database; performing a ratio analysis between the instantaneous maximum intensity and the electromagnetic pulse rise time, coupling it with the electromagnetic pulse duration, and then performing a ratio analysis with the allowable electromagnetic pulse intensity value to obtain the electromagnetic negative impact component of the AGV path planning sensor; and then applying the high temperature negative impact correction value of the AGV path planning sensor to... The electromagnetic negative influence components of the AGV path planning sensor are coupled and analyzed to obtain the comprehensive value of the electromagnetic negative influence of the AGV path planning sensor. The comprehensive value of the electromagnetic negative influence of the AGV path planning sensor is used to quantify the degree of negative distortion influence of the AGV path planning sensor under external electromagnetic interference by the combination of the high temperature negative influence correction value and the electromagnetic negative influence components of the AGV path planning sensor. If the comprehensive value of the electromagnetic negative influence of the AGV path planning sensor is less than a second threshold, no adjustment is made. If the comprehensive value of the electromagnetic negative influence of the AGV path planning sensor is equal to or greater than the second threshold and less than the first threshold, generalized denoising processing is performed by a predefined first denoising software. If the comprehensive value of the electromagnetic negative influence of the AGV path planning sensor is equal to or greater than the first threshold, specific denoising processing is performed by a predefined second denoising software.

[0016] This application provides an AGV handling monitoring system for underground parking garages, including an underground parking garage disaster identification module, an AGV transport environment visibility analysis and adjustment module, an AGV transport temperature analysis and adjustment module, an AGV transport electromagnetic intensity analysis and adjustment module, and an underground parking garage safe room fire suppression module. The underground parking garage disaster identification module is used to identify disasters in the underground parking garage; if a vehicle on fire is detected, the AGV docks with, carries, and transports the vehicle. The AGV transport environment visibility analysis and adjustment module is used to determine the environmental visibility during the transport process in real time and compare the visibility data. The system includes: an AGV visibility adjustment module for monitoring visibility; an AGV transport temperature analysis and adjustment module for real-time monitoring of the AGV backplate temperature during transport and optimization of high-temperature response based on backplate temperature comparisons; an AGV transport electromagnetic intensity analysis and adjustment module for real-time monitoring of the electromagnetic intensity on the AGV backplate during transport and optimization of electromagnetic pulse response based on backplate temperature comparisons; and an underground parking garage safe room fire suppression module for activating a fire suppression system upon arrival at the underground parking garage safe room.

[0017] This application provides an AGV handling and monitoring device for underground parking garages, including a special high-temperature resistant AGV chassis, a special AGV hydraulic lifting mechanism, special AGV explosion-proof electrical hardware, and a special modular underground parking garage safety house with double-layer heat insulation, intelligent fire extinguishing equipment, and negative pressure smoke exhaust equipment. The special high-temperature resistant AGV chassis is used to resist the negative effects of high temperatures during the transport of spontaneously combusting vehicles. The special AGV hydraulic lifting mechanism is used to secure and transport spontaneously combusting vehicles. The special AGV explosion-proof electrical hardware is used to resist the negative effects of deflagration during the transport of spontaneously combusting vehicles. The special modular underground parking garage safety house with double-layer heat insulation is used to resist the negative effects of deflagration in spontaneously combusting vehicles. The special modular underground parking garage safety house with intelligent fire extinguishing equipment is used to quickly cool and extinguish spontaneously combusting vehicles. The special modular underground parking garage safety house with negative pressure smoke exhaust equipment is used to quickly exhaust smoke generated by spontaneously combusting vehicles under negative pressure.

[0018] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages:

[0019] 1. Disaster identification in underground parking garages; AGV response to visibility adjustments and optimizations based on visibility comparison analysis; AGV response to high temperatures adjustments and optimizations based on AGV backplate temperature comparison analysis; AGV response to electromagnetic pulse adjustments and optimizations based on electromagnetic intensity comparison analysis of the AGV backplate; AGV determines when it has reached the underground parking garage's safe room and activates the closed fire extinguishing plan, achieving the effect of improving the dynamic control adaptability of AGVs transporting spontaneously combusting vehicles in underground parking garages, and solving the problem of insufficient dynamic control adaptability of AGVs transporting spontaneously combusting vehicles in underground parking garages in existing technologies.

[0020] 2. Based on the temperature comparison analysis of the AGV backplate, the AGV is adjusted and optimized to cope with high temperatures. This graded temperature control scheme achieves a comprehensive improvement from data accuracy to system energy efficiency through the synergy of multi-band infrared sensing, directional cooling and dynamic protection. It can support the long-term stable operation of AGV in the high-temperature environment of underground parking garages, while reducing the total energy consumption, thus realizing the effectiveness of AGV's high-temperature adaptability adjustment for underground parking garages.

[0021] 3. Based on the comparative analysis of the electromagnetic intensity received by the AGV backplate, the AGV is adjusted and optimized to cope with electromagnetic pulses. On the basis of high temperature adjustment and optimization, the electromagnetic interference of the AGV path planning sensor is reduced to within ±2cm through real-time monitoring and graded noise reduction of electromagnetic sensors, ensuring its positioning accuracy in extreme electromagnetic environments. Combined with a closed fire extinguishing scheme, a triple protection system of "high temperature-electromagnetic-safety" is formed, thereby realizing the reliability of the AGV's adaptive adjustment to the high electromagnetic interference it receives when transporting self-igniting vehicles in underground garages. Attached Figure Description

[0022] Figure 1 A flowchart of an AGV handling monitoring method for underground parking garages provided in this application embodiment;

[0023] Figure 2 This is a structural diagram of an AGV handling monitoring system for an underground parking garage, provided as an embodiment of this application. Detailed Implementation

[0024] This application provides an AGV handling monitoring method, system, and equipment for underground parking garages, which solves the problem of insufficient dynamic control adaptability of AGVs transporting spontaneously combusting vehicles in underground parking garages in the prior art. By docking, carrying, and transporting the spontaneously combusting vehicle with the AGV, the system can judge and analyze the environmental visibility, back panel temperature, and electromagnetic interference in real time during the transport process and make step-by-step analysis and adjustments, thereby improving the dynamic control adaptability of AGVs transporting spontaneously combusting vehicles in underground parking garages.

[0025] To better understand the above technical solutions, the following will provide a detailed explanation of the technical solutions in conjunction with the accompanying drawings and specific implementation methods.

[0026] like Figure 1 The diagram shows a flowchart of an AGV handling monitoring method for underground parking garages provided in this application embodiment. This method is applied to an AGV handling monitoring system in an underground parking garage and includes the following steps: disaster identification in the underground parking garage; if a vehicle on fire is detected, the AGV docks with, carries, and transports the vehicle; the AGV judges the environmental visibility during transport in real time and adjusts and optimizes its response based on visibility comparison analysis; the AGV judges the temperature of its backplate during transport in real time and adjusts and optimizes its response to high temperatures based on AGV backplate temperature comparison analysis; the AGV judges the electromagnetic intensity received by its backplate during transport in real time and adjusts and optimizes its response to electromagnetic pulses based on electromagnetic intensity comparison analysis; the AGV determines it has reached the underground parking garage safety room and activates a closed fire extinguishing plan.

[0027] Furthermore, the AGV docks with, carries, and transports the spontaneously combusting vehicle. Specifically, this includes: real-time monitoring of fire warning data in the corresponding underground parking garage area through a distributed fire sensor array; if the local temperature of the vehicle in the fire warning data is lower than the corresponding spontaneously combusting vehicle temperature threshold, no action is taken; if the local temperature of the vehicle in the fire warning data is equal to or greater than the corresponding spontaneously combusting vehicle temperature threshold, the corresponding vehicle is identified as a spontaneously combusting vehicle, the underground parking garage area where the spontaneously combusting vehicle is located is recorded, a predefined isolation procedure is initiated for the underground parking garage area where the spontaneously combusting vehicle is located, and the AGV is invoked to travel to the underground parking garage area where the spontaneously combusting vehicle is located through a predefined layered path planning scheme; the AGV unfolds its three-stage telescopic arm through a special AGV hydraulic lifting mechanism, grabs the vehicle chassis support point, and the AGV transports the corresponding spontaneously combusting vehicle to a predefined underground parking garage safety room.

[0028] In this embodiment, the distributed fire sensor can be a dual-band infrared flame sensor (3-5μm and 8-14μm band) for different underground garage areas (e.g., under different parking spaces).

[0029] The thermal imaging system detected that the local temperature of the vehicle exceeded the 200°C threshold (different temperature thresholds are set for different vehicles, and are manually preset by identifying different vehicles).

[0030] The predefined isolation procedure involves the fireproof roller shutter door in the underground garage area where the spontaneously combusted vehicle is located descending. The fireproof roller shutter door has three sides, leaving one side open for the AGV to transport the spontaneously combusted vehicle.

[0031] The predefined hierarchical path planning scheme is the execution scheme of the AGV's built-in algorithm. Specifically, the predefined hierarchical path planning scheme includes global path planning (A* algorithm) and local path adjustment (Dynamic Window Method (DWA)). Global planning (A* algorithm): Generates a static optimal path from the starting point to the destination, avoiding fixed obstacles (such as walls and pillars). Local adjustment (DWA): Real-time perception of dynamic obstacles (such as pedestrians and vehicles), dynamically adjusting speed and path to ensure safe obstacle avoidance.

[0032] The steps for a predefined hierarchical path planning scheme are shown below:

[0033] Global phase (A* algorithm): Input a static map (raster map or topology map) of the garage.

[0034] The A* algorithm is used to calculate the shortest path from the starting point to the destination, with the following cost function:

[0035] f(n) = g(n) + h(n);

[0036] g(n): Actual movement cost (e.g., distance, turning penalty).

[0037] h(n): Heuristic estimate (e.g., endpoint Euclidean distance).

[0038] Output the global path (a sequence of path points).

[0039] Local stage (Dynamic Window Method DWA): Real-time sampling velocity space: Under the current speed and motion constraints of the AGV, generate multiple feasible velocity combinations (linear velocity, angular velocity).

[0040] Trajectory simulation: Predicts the trajectory of each velocity group within a short future time (e.g., 0.5 seconds).

[0041] Prioritize tracks that are close to the global path, far from obstacles, and have a relatively high speed.

[0042] Output the optimal local path and repeat until the destination is reached.

[0043] The optimal path planning for AGVs in underground parking garages requires a hierarchical strategy: the A* algorithm provides the globally optimal path; DWA adjusts the local trajectory in real time. This scheme strikes a balance between efficiency, safety, and computational resource consumption, making it suitable for the underground parking garage environment.

[0044] The AGV deploys its three-stage telescopic arm via a special hydraulic lifting mechanism to grip the vehicle's tires or chassis support points. Specifically, the AGV scans the burning vehicle 360° to select the optimal gripping point (avoiding deformed / burned areas). The hydraulic arm adjusts its telescopic stages according to the vehicle's height (1m for the first stage, 2m for the second, and 3m for the third). The gripper grips the vehicle's tires or chassis crossbeams with constant pressure (5-10kN) to prevent structural damage from compression. The three stages of the hydraulic arm lift synchronously, raising the vehicle off the ground at a low speed of 0.1m / s (lifting height 20-30cm). The gripper's built-in ratchet mechanism automatically locks, rigidly connecting the vehicle to the AGV chassis. The AGV lowers its center of gravity to its lowest mode (10cm from the ground), with speed control: straight sections: maximum speed 1m / s (speed limited in explosion-proof mode). Turning sections: speed reduced to 0.3m / s, and the hydraulic arm retracts one stage to minimize the turning radius.

[0045] The AGV deploys via a three-stage telescopic arm using a special AGV hydraulic lifting mechanism. After gripping the vehicle's chassis support point, the AGV unfolds a foldable high-temperature resistant explosion-proof cover, as shown in the example below: After the AGV completes vehicle gripping and lifts the vehicle by 20cm, it triggers the cover unfolding command. The hydraulic push rod extends at a speed of 20mm / s, with a stroke difference of <5mm between the four sets of push rods (anti-skew), and the cover initially closes. Pressure sensors monitor the air pressure inside the cover; if the pressure rise is <50Pa within 10 seconds, the skirt is extended a second time, and the cover is fully closed. Eight thermocouples (accuracy ±1℃) and two flame optical sensors are installed inside the cover, and the data is transmitted back to the AGV control system in real time. After arriving at the underground parking garage safety house, the AGV stops, and the hydraulic push rod retracts the cover at a speed of 15mm / s. Through the deep integration of the foldable high-temperature resistant explosion-proof cover with the AGV, the spread of fire and smoke from spontaneously combusting vehicles can be effectively controlled without significantly affecting the AGV's mobility.

[0046] It should be noted that throughout the entire process of the AGV transporting the self-ignited vehicle to the underground garage safety house, the self-ignited vehicle was inside a foldable high-temperature resistant explosion-proof cover.

[0047] Furthermore, based on visibility comparison analysis, the AGV is optimized to respond to visibility changes. Specifically, this includes: real-time collection of the visibility of the underground parking garage environment using the AGV's lidar; if the visibility of the underground parking garage environment is greater than the first visibility threshold, no adjustment is made; if the visibility of the underground parking garage environment is greater than the second visibility threshold but less than or equal to the first visibility threshold, the air brush cleaning device built into the AGV is activated; if the visibility of the underground parking garage environment is greater than the third visibility threshold but less than or equal to the second visibility threshold, the optical sensor is turned off, while the non-optical sensor remains on; if the visibility of the underground parking garage environment is less than or equal to the third visibility threshold, relevant personnel are notified for manual remote control.

[0048] In this embodiment, when the laser beam propagates in a smoke or dusty environment, its intensity attenuates due to scattering and absorption. According to the Beer-Lambert law, the attenuation of laser intensity is inversely proportional to visibility. Using the built-in calibration data of the lidar, the attenuation coefficient in the Beer-Lambert law formula is converted into a visibility value.

[0049] The air brush cleaning is initiated by the rotary air brush cleaning device built into the AGV, and the cooling is activated by the integrated thermoelectric cooling device built into the AGV. Specific example:

[0050] Equipped with a rotary air brush cleaning system (compressed air pressure 0.6MPa, cleaning cycle 10 seconds / time); integrated thermoelectric cooling device (TEC cooling plate, temperature difference AT=35℃); air brush cleaning is activated when the dust concentration is greater than 30mg / m³.

[0051] The rotary air brush cleaning device can be positioned above the optical sensor and the non-optical sensor.

[0052] Optical sensors are disabled, while non-optical sensors are retained. For example, optical cameras are disabled, while millimeter-wave radar, ultrasonic arrays, thermal imaging navigation modules, and lidar are retained. Sensor fusion logic priority: millimeter-wave radar > thermal imaging, thermal imaging > ultrasonic, ultrasonic > lidar.

[0053] If the visibility in the underground parking garage is less than or equal to the third threshold, the following example applies: When visibility is <0.5m, the AGV automatically requests manual remote control. The control panel uses GPS real-time visualization positioning combined with thermal imaging and millimeter-wave point cloud to assist driving. For example, an AR control panel built using the Unity engine supports FPV view and obstacle attribute labeling, and dual-channel communication (5G + Wi-Fi) ensures remote control latency of less than 200ms. When visibility is less than 0.3m, the AGV uses radar to detect electric vehicles that are not turned off and detours around them. At the same time, thermal imaging monitors the dynamic deceleration of personnel in the construction area, meeting the needs of the complex environment of the underground parking garage.

[0054] Furthermore, based on the comparative analysis of AGV backplate temperature, adjustments and optimizations are made to the AGV to cope with high temperatures. Specifically, this includes: real-time acquisition of the AGV backplate temperature using the AGV's temperature sensor; if the AGV backplate temperature is less than or equal to the third threshold of the AGV's tolerance temperature, a high-temperature negative impact correction assessment and adjustment are performed; if the AGV backplate temperature is greater than the third threshold of the AGV's tolerance temperature but less than or equal to the second threshold of the AGV's tolerance temperature, infrared thermal imager thermal radiation compensation is performed; if the AGV backplate temperature is greater than the second threshold of the AGV's tolerance temperature but less than or equal to the first threshold of the AGV's tolerance temperature, a first cooling treatment is performed using the integrated thermoelectric cooling device built into the AGV; if the AGV backplate temperature is greater than the first threshold of the AGV's tolerance temperature, a second cooling treatment is performed using the nitrogen curtain protection device built into the edge of the AGV backplate.

[0055] In this embodiment, if the AGV backplate temperature is greater than the third threshold of the AGV's tolerance temperature but less than or equal to the second threshold of the AGV's tolerance temperature, then infrared thermal imager thermal radiation compensation is performed. Infrared thermal imager thermal radiation compensation can be directly implemented using Python, as shown in the following example:

[0056]

[0057] Parameter description;

[0058] raw_data: Raw thermal imager data matrix (unit: W / m²) 2 ·sr);

[0059] emissivity: Target surface emissivity (0.0-1.0);

[0060] T_env: Ambient temperature (degrees Celsius);

[0061] T_ref: Thermal imager calibration reference temperature (default 25℃);

[0062] wavelength: center wavelength of the sensor (default 10μm);

[0063] bandwidth: Sensor bandwidth (default 1μm);

[0064] Temperature conversion (Celsius → Kelvin);

[0065]

[0066] Calculate the environmental radiation term (Stephen-Boltzmann law correction);

[0067]

[0068] Calculate the wavelength correlation correction factor for Planck's law;

[0069]

[0070] Radiant energy correction at a specific wavelength bandwidth;

[0071]

[0072] Integrate over the wavelength bandwidth;

[0073]

[0074] Obtain the sensor response coefficients (based on actual calibration data);

[0075]

[0076] Comprehensive compensation formula;

[0077]

[0078] Nonlinear calibration (example of polynomial fitting);

[0079]

[0080] If the AGV backplane temperature exceeds the third threshold of the AGV's tolerance temperature but is less than or equal to the second threshold, the AGV's built-in integrated thermoelectric cooling device will perform the first cooling process, which is called TEC cooling activation. TEC arrays are arranged in the core areas of the AGV's backplane that are susceptible to heat conduction (controller, battery compartment, hydraulic pump), with 3-5 arrays connected in parallel in each area. The cold end is attached to the component being cooled, and the hot end is connected to the heat dissipation system.

[0081] If the temperature of the AGV backplate exceeds the first threshold temperature that the AGV can withstand, a local nitrogen curtain protection is activated, and annular nitrogen injection pipes (0.5 mm orifice diameter, 50 mm spacing) are arranged along the edge of the AGV backplate. The nitrogen flow rate is 10 L / min, forming a positive pressure air curtain to isolate heat radiation.

[0082] Furthermore, the specific process for correcting and adjusting the negative impact of high temperature is as follows: The maximum temperature dispersion of the AGV backplate and the ambient temperature difference of the AGV path planning sensor's optical lens are obtained through temperature sensor data acquisition and analysis; the average dark current of the avalanche photodiode of the APD detector of the AGV path planning sensor is collected through the built-in current sampler; and the predefined threshold of the AGV backplate temperature dispersion, the preset radius of curvature of the AGV path planning sensor's optical lens, the preset thermal expansion coefficient of the AGV path planning sensor's optical lens, the expansion difference between the metal bracket and the glass reflector, and the dark current of the avalanche photodiode of the APD detector are directly extracted from the underground parking garage AGV handling monitoring database. The standard value of the current; by analyzing the ratio of the maximum temperature dispersion of the AGV backplane to the predefined threshold of the temperature dispersion of the AGV backplane, the first variable of high temperature for the AGV path planning sensor is obtained; by first superimposing the preset thermal expansion coefficient of the AGV path planning sensor optical lens and the expansion difference between the metal bracket and the glass reflector, and then coupling them with the preset radius of curvature of the AGV path planning sensor optical lens and the ambient temperature difference of the AGV path planning sensor optical lens respectively, the second variable of high temperature for the AGV path planning sensor is obtained; by analyzing the ratio of the average dark current of the APD detector avalanche photodiode to the standard value of the dark current of the APD detector avalanche photodiode, the AGV path planning sensor... The third variable for high temperature; the first variable for high temperature from the AGV path planning sensor is corrected using the corresponding weighting factor to obtain the first weighted variable for high temperature from the AGV path planning sensor; the second variable for high temperature from the AGV path planning sensor is corrected using the corresponding weighting factor to obtain the second weighted variable for high temperature from the AGV path planning sensor; the third variable for high temperature from the AGV path planning sensor is corrected using the corresponding weighting factor to obtain the third weighted variable for high temperature from the AGV path planning sensor; combined with the first weighted variable for high temperature from the AGV path planning sensor, ... The second and third weighted variables of high temperature in the AGV path planning sensor are analyzed together to obtain the correction value for the negative impact of high temperature on the AGV path planning sensor. The correction value is used to describe the average dark current of the avalanche photodiode of the APD detector of the AGV path planning sensor, and the degree of quantification of the negative distortion of the AGV path planning sensor caused by external high temperature by the first and second variables of high temperature. If the correction value for the negative impact of high temperature on the AGV path planning sensor is less than the corresponding threshold for the negative impact of high temperature on the AGV path planning sensor, no adjustment is made.If the high-temperature negative impact correction value of the AGV path planning sensor is equal to or greater than the corresponding high-temperature negative impact threshold of the AGV path planning sensor, then the SiCMOSFET parallel drive of the AGV motor driver is activated, and thermal correction is performed using predefined software based on the temperature acquisition data built into the AGV path planning sensor.

[0083] In this embodiment, the AGV path planning sensor function checkpoints are divided into sections. FG0 represents the number of AGV path planning sensor function checkpoints, where FG0 = 1, 2, 3..., FG, and FG represents the total number of AGV path planning sensor function checkpoints. AS0 represents the AGV path planning sensor detection time period number, where AS0 = 1, 2, 3..., AS, and AS represents the total number of AGV path planning sensor detection time period numbers.

[0084] This represents the high-temperature negative impact correction value of the AGV path planning sensor during the detection time period of the AS0th AGV path planning sensor at the FG0th AGV path planning sensor functional check point. The high-temperature negative impact correction value quantifies the degree of relative negative distortion caused by external high temperatures on the AGV path planning sensor. Specifically, the AGV path planning sensor monitors the degree of adverse negative distortion caused by changes in external temperature, affecting sensors such as LiDAR, millimeter-wave radar, and infrared scanners mounted on the AGV that directly impact path planning.

[0085]

[0086] e represents the natural constant.

[0087] This represents the maximum value of the AGV backplate temperature dispersion during the detection time period of the AS0th AGV path planning sensor at the FG0th AGV path planning sensor function check point. The AGV backplate temperature dispersion refers to the degree of dispersion between the AGV backplate temperature corresponding to the AGV path planning sensor function check point and the average AGV backplate temperature during the AGV path planning sensor detection time period. The maximum value of the dispersion is the maximum value of the AGV backplate temperature dispersion.

[0088] Temperature sensor type: Select high-precision, fast-response temperature sensors, such as: Thermistors: high sensitivity, suitable for small-area temperature monitoring. Infrared temperature sensors: non-contact measurement, suitable for mobile AGVs or high-temperature areas. Deploy multiple temperature sensors in key heat-sensitive areas of the AGV backplane (such as near the AGV path planning sensor motor, AGV path planning sensor power module, AGV path planning sensor heat sink, etc.). In practical applications, a combination of thermistors and infrared temperature sensors can be used for data acquisition; that is, the thermistor is used when the temperature range of the thermistor is within its applicable range, and the infrared temperature sensor is used when the temperature range of the thermistor is outside its applicable range.

[0089] This represents the predefined threshold for the AGV backplate temperature dispersion during the detection time period of the AS0th AGV path planning sensor at the FG0th AGV path planning sensor function check point. The predefined threshold for AGV backplate temperature dispersion is directly extracted from the underground garage AGV handling monitoring database and is used to represent the average degree of AGV backplate temperature dispersion when the AGV backplate temperature is running at rated power.

[0090] This indicates the preset curvature radius of the optical lens of the AGV path planning sensor during the detection time period of the AS0th AGV path planning sensor at the FG0th AGV path planning sensor function check point. The preset curvature radius of the optical lens of the AGV path planning sensor is directly extracted from the underground garage AGV handling monitoring database, specifically from the corresponding manufacturer's production log.

[0091] The preset thermal expansion coefficient of the optical lens of the AGV path planning sensor represents the detection time period of the AS0th AGV path planning sensor at the FG0th AGV path planning sensor function check point. The preset thermal expansion coefficient of the optical lens of the AGV path planning sensor is directly extracted from the underground garage AGV handling monitoring database, specifically from the corresponding manufacturer's production log.

[0092] This represents the ambient temperature difference of the optical lens of the AGV path planning sensor during the detection time period of the AS0th AGV path planning sensor at the FG0th AGV path planning sensor functional check point. The ambient temperature difference of the optical lens of the AGV path planning sensor refers to the difference between the average ambient temperature of the optical lens of the AGV path planning sensor during the current detection time period and the preset standard temperature. The preset standard temperature is directly extracted from the underground garage AGV handling monitoring database. The preset standard temperature can be set manually or obtained from the rated operating temperature in the corresponding factory production log.

[0093] Example: Sensor optical lenses often use silicon / germanium-based materials. When the ambient temperature is greater than 80℃, the radius of curvature of the window will change, causing the laser beam focus to shift by more than 0.1mm.

[0094] This represents the expansion difference value between the metal bracket and the glass reflector during the detection time period of the AS0th AGV path planning sensor at the FG0th AGV path planning sensor functional check point. The expansion difference value between the metal bracket and the glass reflector represents the absolute value of the difference between the expansion coefficient of the corresponding AGV optical accessory metal bracket and the expansion coefficient of the AGV optical accessory glass reflector. The expansion coefficients of the AGV optical accessory metal bracket, the expansion coefficients of the AGV optical accessory glass reflector, and the expansion difference value between the metal bracket and the glass reflector are directly extracted from the underground parking garage AGV handling monitoring database, specifically from the corresponding manufacturer's production logs.

[0095] For example, the expansion difference between the metal bracket and the glass reflector of the lidar causes a mirror tilt angle deviation greater than 0.02°, resulting in an increase of 1.5° in the point cloud angle measurement error.

[0096] The average dark current of the avalanche photodiode of the APD detector of the AGV path planning sensor during the detection time period of the AS0th AGV path planning sensor at the FG0th AGV path planning sensor functional check point is caused by electron-hole pairs generated by heat in the material. It is closely related to temperature and increases exponentially with temperature. The shot noise power of the dark current is proportional to the square root of the current, which has a negative impact on the signal-to-noise ratio. The average dark current of the avalanche photodiode of the APD detector is specifically obtained in real time through the built-in embedded ADC sampling and acquisition circuit.

[0097] This represents the dark current standard value of the avalanche photodiode of the APD detector of the AGV path planning sensor at the FG0th AGV path planning sensor function check point. The dark current standard value of the avalanche photodiode of the APD detector is directly extracted from the underground garage AGV handling monitoring database, specifically from the corresponding manufacturer's production log.

[0098] When starting the SiCMOSFET parallel drive architecture of the AGV motor driver, it should be noted that before this comparative analysis, under normal circumstances, the AGV motor driver can use traditional IGBTs, that is, the AGV motor driver uses two drive architectures. Generally, only traditional IGBTs are started. After comparative analysis and judgment, SiCMOSFETs are started as the motor driver to cope with external temperature changes.

[0099] The SiCMOSFET parallel drive architecture is implemented by using a parallel architecture of silicon carbide (SiC) MOSFETs and traditional IGBTs, increasing the temperature resistance to 200℃. It adopts a dual-module parallel topology, allowing automatic switching when a single module fails. The continuous output power at 85℃ is increased by 40%, which makes the frequency reduction trigger threshold of the AGV motor driver change from 80℃ to 110℃, and the speed can be maintained at 2m / s without decay.

[0100] The AGV path planning sensor's built-in temperature acquisition data undergoes thermal correction via predefined software. A specific example is as follows: Hardware dependency: Temperature ADC sampling is embedded within the AGV's LiDAR (every 5cm). 2 Deploy 1 instance), perform hotfix via Python, as shown in the example code below:

[0101] Real-time processing of simplified code;

[0102]

[0103] Update the temperature field and deformation model;

[0104]

[0105]

[0106] This code framework enables real-time point cloud correction of AGV LiDAR in environments with changing temperatures, further improving navigation accuracy.

[0107] The first variable weighting factor for high temperature of AGV path planning sensor during the detection time period of AGV path planning sensor at the FG0th AGV path planning sensor functional check point;

[0108] The weighting factor of the high temperature second variable of the AGV path planning sensor during the detection time period of the AS0th AGV path planning sensor at the FG0th AGV path planning sensor functional check point.

[0109] The third variable weighting factor for high temperature of AGV path planning sensor during the detection time period of AGV path planning sensor at the FG0th AGV path planning sensor functional check point;

[0110] The weighting factor acquisition process is exemplified as follows: by controlling the temperature of the AGV backplane, sensor data under different high-temperature scenarios are collected, a quantitative relationship between temperature and three high-temperature variables (stability risk, optical deformation, and dark current noise) is established, and the weighting factor is determined.

[0111] Setting up the simulation environment: Tools: Incubator / heating plate, high-precision temperature sensor (±0.5℃), laser interferometer, oscilloscope. Target temperatures: 25℃ (room temperature), 80℃ (high temperature), 100℃ (extreme high temperature). Data acquisition: Backplane temperature: per 5cm... 2 Arrange thermistors to record temperature distribution in real time. High-temperature variables: Stability risk (V1): Calculate the proportion of backplane temperatures exceeding 80℃ (e.g., V1 = 85% at 100℃). Optical deformation (V2): Measure lens curvature changes using a laser interferometer and calculate the degree of deformation based on the material expansion coefficient. Dark current noise (V3): Acquire APD detector dark current using an oscilloscope (e.g., dark current reaches 1000nA at 100℃). System performance: Record navigation path deviation (e.g., ±4.8cm) and point cloud distortion (e.g., -4.8dB). Step 3: Establish a mathematical model: Normalization: Scale V1, V2, and V3 to the range of 0-1 (e.g., V1 = 0.85). Linear regression equation: Substitute the data to solve for weighting factors (e.g., solve the equations for the 80℃ and 100℃ data sets to obtain ω1 = 45%, ω2 = 35%, ω3 = 20%). 100 sets of data were generated using Monte Carlo simulation to verify the stability of the weights (standard deviation <2%). The AGV was run in a real garage, collecting data over 200 kilometers, and the navigation accuracy reached ±2cm after correction. Weights were automatically adjusted based on real-time temperature (e.g., increasing the stability weight to 50% above 90℃). The first variable related to high temperature (stability) had the highest weight (45%), directly triggering the safety mechanism when the temperature exceeded the limit. Dark current noise had the lowest weight (20%), but it needs to be dynamically increased under extreme high temperatures. Through a four-step method of "temperature control - data collection - mathematical modeling - verification and optimization," the experiment quantitatively determined the weight relationship between the AGV backplate temperature and the three high-temperature variables, obtaining a weight factor mapping table. By inputting the real-time AGV backplate temperature, the corresponding weight factors for the first, second, and third high-temperature variables of the AGV path planning sensor were obtained.

[0112] Furthermore, based on the comparative analysis of the electromagnetic intensity received by the AGV backplate, the AGV is adjusted and optimized to cope with electromagnetic pulses. Specifically, this includes: real-time acquisition of the electromagnetic intensity of the AGV environment through the AGV's electromagnetic sensors; if the electromagnetic intensity of the AGV environment is less than or equal to the AGV environmental electromagnetic intensity threshold, no adjustment is made; if the electromagnetic intensity of the AGV environment is greater than the AGV environmental electromagnetic intensity threshold, a high electromagnetic interference negative impact correction assessment and adjustment is performed.

[0113] Further, the assessment and adjustment of the negative impact correction of high electromagnetic interference specifically includes: real-time acquisition of the instantaneous maximum intensity and rise time of the electromagnetic pulse using the broadband electric field probe built into the AGV; recording the start time of the rise time; if the electromagnetic pulse intensity is less than the electromagnetic pulse intensity attention threshold, recording the end time; and recording the electromagnetic pulse duration as the difference between the end time and the start time of the rise time. The allowable electromagnetic pulse intensity value is directly extracted from the AGV handling monitoring database in the underground parking garage. A ratio analysis is performed between the instantaneous maximum intensity and the rise time of the electromagnetic pulse, coupled with the electromagnetic pulse duration, and then a ratio analysis is performed with the allowable electromagnetic pulse intensity value to obtain the electromagnetic negative impact component of the AGV path planning sensor. The high-temperature negative impact correction value of the AGV path planning sensor is then compared with the electromagnetic pulse intensity. The electromagnetic negative influence component coupling analysis of the AGV path planning sensor yields the comprehensive value of the electromagnetic negative influence of the AGV path planning sensor. This comprehensive value quantifies the degree of negative distortion influence of the AGV path planning sensor caused by external electromagnetic interference, resulting from the combined effect of the high-temperature negative influence correction value and the electromagnetic negative influence component. If the comprehensive value of the electromagnetic negative influence of the AGV path planning sensor is less than a second threshold, no adjustment is made. If the comprehensive value is equal to or greater than the second threshold and less than the first threshold, generalized denoising is performed using a predefined first denoising software. If the comprehensive value is equal to or greater than the first threshold, specific denoising is performed using a predefined second denoising software.

[0114] In this embodiment, the electromagnetic pulse rise time specifically refers to the time it takes for the pulse to rise from 10% to 90% intensity. The shorter the electromagnetic pulse rise time, the stronger and more concentrated the electromagnetic pulse energy.

[0115] It should be noted that the general electromagnetic interference built into the AGV is sufficient to handle most situations. The electromagnetic interference correction and adjustment here occurs during the burning of the transport vehicle, which may be caused by a special electromagnetic pulse due to violent combustion or battery combustion and discharge. Therefore, the high electromagnetic interference negative impact correction and adjustment at this time is after the AGV has been adjusted and optimized to cope with high temperatures.

[0116] The electromagnetic sensor of an AGV can be a broadband electric field probe. Through the principle of capacitive coupling, the probe tip senses a charge, which is converted into a voltage signal and then into the ambient electromagnetic intensity.

[0117] This represents the comprehensive value of the electromagnetic negative influence of the AGV path planning sensor during the detection time period of the AS0th AGV path planning sensor at the FG0th AGV path planning sensor functional check point. It is used to quantify the degree of negative distortion of the AGV path planning sensor when it is subjected to external electromagnetic interference.

[0118]

[0119] This represents the high-temperature negative impact correction value of the AGV path planning sensor during the detection time period of the AS0th AGV path planning sensor at the FG0th AGV path planning sensor function check point.

[0120] e represents the natural constant.

[0121] This represents the instantaneous maximum intensity of the electromagnetic pulse at the FG0th AGV path planning sensor function check point.

[0122] This represents the rise time of the electromagnetic pulse at the FG0th AGV path planning sensor function checkpoint.

[0123] This is used to quantify the rate of energy release per unit time, helping to avoid relying solely on absolute intensity. For example, short-duration, high-intensity pulses may be underestimated due to their short duration. For instance, if two pulses have the same intensity, but one has a rise time of 1 μs and the other 10 μs, the former will have a 10-fold higher energy release rate and be more harmful.

[0124] This is used to scale the instantaneous energy release rate over a longer time scale, quantifying the cumulative energy released over a long period and the persistence of interference. For example, if the duration of an electromagnetic pulse is 100 ms, the energy release is 100 times the original value, significantly increasing the harm. It also prevents long-pulse interference (such as continuous electromagnetic noise) from being misjudged due to its low instantaneous intensity.

[0125] It is used to eliminate dimensions, convert absolute interference intensity into relative threshold excess, standardize thresholds in different scenarios, and is more suitable for quantitative evaluation in different environments.

[0126] This represents the duration of the electromagnetic pulse at the FG0th AGV path planning sensor function checkpoint.

[0127] This represents the allowable electromagnetic pulse intensity value for the FG0th AGV path planning sensor function check point. The allowable electromagnetic pulse intensity value is directly extracted from the underground garage AGV handling monitoring database. It can be set manually or obtained from the electromagnetic interference resistance setting value under rated power operation in the AGV production log.

[0128] The comprehensive value of electromagnetic negative influence of AGV path planning sensors represents the quantification level after the sensor has been subjected to electromagnetic interference and corrected by the high-temperature negative influence correction value. The quantification of the high-temperature negative influence correction value is due to the fact that high temperatures cause sensor material expansion or electronic component performance drift (such as changes in thermistor resistance), reducing the accuracy of electromagnetic signal detection. High temperatures also accelerate circuit aging and introduce additional thermal noise (such as localized temperature rise caused by poor substrate thermal conductivity). Simultaneously considering the instantaneous intensity and duration of the electromagnetic pulse, as well as the ambient temperature, avoids misjudgment based on a single indicator.

[0129] For example, when a battery burns, the high temperature may reduce the allowable value of the electromagnetic pulse intensity, but the electromagnetic component increases due to the short-term high energy release, resulting in a double risk. By monitoring the temperature in real time and dynamically adjusting the threshold and filtering parameters, the system can adapt to the changing operating conditions of the AGV from room temperature to high temperature (e.g., 70℃).

[0130] Example: In a battery combustion test of an AGV in an underground parking garage: Without correction: The calculated comprehensive value of the electromagnetic components triggers secondary denoising, but high temperature causes sensor misalignment, resulting in an actual path planning error of ±5cm. After correction: Primary denoising is triggered, reducing the path planning error to ±2cm. The correction mechanism quantifies the impact of high temperature on sensor performance, making interference assessment closer to the actual risk and improving path planning accuracy.

[0131] In AGV handling monitoring methods, environmental visibility, backplane temperature, and electromagnetic interference are interrelated sources of interference. For example, high temperatures may exacerbate electromagnetic interference (e.g., battery discharge generates more electromagnetic pulses), and the transient characteristics of electromagnetic pulses may affect the real-time performance of the navigation system, thereby impacting path planning accuracy. Therefore, the formula achieves multi-factor synergistic optimization through step-by-step adjustments, ultimately ensuring the AGV's adaptability in complex environments through comprehensive value coupling.

[0132] If the combined value of the electromagnetic negative influence of the AGV path planning sensor is equal to or greater than the second threshold and less than the first threshold, then denoising processing is performed using predefined denoising software. The predefined first denoising software can be MATLAB, and example code is as follows:

[0133]

[0134] It can be used for electromagnetic interference filtering in the 30-300MHz range.

[0135] For broadband / non-stationary interference, Matlab can be used for filtering.

[0136] The predefined second noise reduction software can be Python, as shown in the example code below:

[0137]

[0138] It can be used for electromagnetic interference filtering at 3GHz.

[0139] For narrowband / fixed-point interference, Python can be used for filtering.

[0140] By combining the two selection methods, AGV sensors can maintain stable navigation in complex electromagnetic environments, and the path planning error can be controlled within ±2cm.

[0141] Furthermore, the closed-loop fire extinguishing plan is activated, which includes: after the AGV determines that it has reached the safe house in the underground garage, it is unhooked and separated from the self-igniting vehicle; the safe house activates heptafluoropropane total flooding spray, fine water mist continuous cooling, exhaust gas treatment and automatic sewage discharge; the AGV returns to the standby position and starts the AGV self-check.

[0142] In this embodiment, after the AGV determines that it has reached the safe room in the underground garage, it triggers the cover retrieval command, and the AGV hydraulic arm slowly lowers the vehicle to the ground (at a speed of 0.05 m / s). The gripper pressure is released, and the AGV retreats 5 m to disengage.

[0143] The safe house initiates a closed fire suppression plan, including: Phase 1: Total flooding with heptafluoropropane (concentration reaches 10% within 30 seconds); Phase 2: Continuous cooling with fine water mist (flow rate 5L / min, lasting 3 minutes); Exhaust gas treatment: The catalytic oxidation device is activated to maintain the indoor negative pressure below -50Pa; Environmental monitoring: The closed system is released when the temperature is below 50℃ and the CO concentration is below 30ppm; Automatic wastewater discharge: Fire suppression wastewater is collected into a dedicated treatment tank. System reset: The AGV returns to the standby position, and the safe house's self-cleaning program is activated.

[0144] AGV self-test example: The high-temperature chassis cooling system is shut down, and the explosion-proof module is reset to normal mode. The hydraulic arm retracts to its storage position, and the sensors are calibrated in preparation for the next task.

[0145] like Figure 2As shown in the diagram, the AGV transport monitoring system for underground parking garages provided in this application embodiment includes: an underground parking garage disaster identification module, an AGV transport environment visibility analysis and adjustment module, an AGV transport temperature analysis and adjustment module, an AGV transport electromagnetic intensity analysis and adjustment module, and an underground parking garage safe room fire suppression module. The underground parking garage disaster identification module is used for disaster identification in the underground parking garage. If a vehicle on fire is detected, the AGV docks with, carries, and transports the vehicle. The AGV transport environment visibility analysis and adjustment module is used for real-time judgment of the transport process by the AGV. The system includes: an environmental visibility module for adjusting and optimizing AGV response based on visibility comparison analysis; an AGV transport temperature analysis and adjustment module for real-time AGV backplate temperature assessment during transport and optimization for high-temperature response based on backplate temperature comparison analysis; an AGV transport electromagnetic intensity analysis and adjustment module for real-time AGV backplate electromagnetic intensity assessment and optimization for electromagnetic pulse response based on backplate electromagnetic intensity comparison analysis; and an underground parking garage safe room fire suppression module for AGV arrival at an underground parking garage safe room and activation of the fire suppression plan.

[0146] This application provides an AGV handling and monitoring device for underground parking garages, characterized by comprising a special high-temperature resistant AGV chassis, a special AGV hydraulic lifting mechanism, special AGV explosion-proof electrical hardware, and a special modular underground parking garage safety house with double-layer heat insulation, intelligent fire extinguishing equipment, and negative pressure smoke exhaust equipment. The special high-temperature resistant AGV chassis is used to resist the negative effects of high temperatures during the transport of spontaneously combusting vehicles. The special AGV hydraulic lifting mechanism is used to secure and transport spontaneously combusting vehicles. The special AGV explosion-proof electrical hardware is used to resist the negative effects of deflagration during the transport of spontaneously combusting vehicles. The special modular underground parking garage safety house with double-layer heat insulation is used to resist the negative effects of deflagration in spontaneously combusting vehicles. The special modular underground parking garage safety house with intelligent fire extinguishing equipment is used to quickly cool and extinguish spontaneously combusting vehicles. The special modular underground parking garage safety house with negative pressure smoke exhaust equipment is used to quickly exhaust smoke generated by spontaneously combusting vehicles under negative pressure.

[0147] In this embodiment, the special AGV high-temperature resistant chassis is made of silicon carbide composite material, which can withstand a high temperature of 800°C for 5 minutes.

[0148] Special AGV hydraulic lifting mechanism: equipped with a three-stage telescopic boom, with a maximum lifting capacity of 3.5 tons.

[0149] Special AGV explosion-proof electrical hardware: conforms to ATEX Zne1 standard, IP67 protection level.

[0150] Special modular underground garage safety house double-layer heat insulation equipment: outer layer calcium silicate board (50mm thick) + inner layer aerogel coating.

[0151] Special modular underground garage safety house intelligent fire extinguishing equipment: heptafluoropropane + fine water mist dual-mode spray, flow control accuracy ±5%.

[0152] Special modular underground garage safety house negative pressure smoke exhaust equipment: equipped with a catalytic oxidation treatment unit, with a VC removal rate of more than 95%.

[0153] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-RM, optical storage, etc.) containing computer-usable program code.

[0154] 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.

[0155] 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.

[0156] 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 1The steps of the function specified in one or more boxes.

[0157] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0158] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A method for monitoring AGV transport in underground parking garages, characterized in that, Includes the following steps: In underground parking garage disaster detection, if a vehicle on fire is detected, the AGV will dock with the vehicle, carry it, and transport it. The AGV assesses the environmental visibility in real time during the transport process and adjusts and optimizes its response based on visibility comparison and analysis. The AGV monitors the back panel temperature in real time during the transport process and optimizes the AGV's response to high temperatures based on a comparative analysis of the AGV's back panel temperature. This optimization includes an assessment and adjustment to correct the negative impact of high temperatures. The AGV judges the electromagnetic intensity of the AGV backplate in real time during the transport process, and adjusts and optimizes the AGV to cope with electromagnetic pulses based on the comparative analysis of the electromagnetic intensity of the AGV backplate. The AGV determines that it has reached the underground parking garage safety room and initiates the closed fire extinguishing plan. The specific process for correcting and adjusting the negative impact of high temperature is as follows: The maximum temperature dispersion of the AGV backplate and the ambient temperature difference of the optical lens of the AGV path planning sensor are obtained by collecting and analyzing data from temperature sensors. The average dark current of the avalanche photodiode, the APD detector of the AGV path planning sensor, is collected by the built-in current sampler. The following data were directly extracted from the AGV transport monitoring database in the underground parking garage: the predefined threshold for temperature dispersion of the AGV backplate, the preset radius of curvature of the optical lens of the AGV path planning sensor, the preset coefficient of thermal expansion of the optical lens of the AGV path planning sensor, the expansion difference between the metal bracket and the glass reflector, and the standard value of the dark current of the avalanche photodiode of the APD detector. By performing a ratio analysis between the maximum temperature dispersion of the AGV backplate and the predefined threshold temperature dispersion of the AGV backplate, the first variable of high temperature for the AGV path planning sensor is obtained. The preset thermal expansion coefficient of the AGV path planning sensor optical lens and the expansion difference between the metal bracket and the glass reflector are first superimposed, and then coupled and analyzed with the preset radius of curvature of the AGV path planning sensor optical lens and the ambient temperature difference of the AGV path planning sensor optical lens, respectively, to obtain the second variable of high temperature of the AGV path planning sensor. The coupling means multiplying for correction. By comparing the average dark current of the avalanche photodiode in the APD detector with the standard value of the dark current of the avalanche photodiode in the APD detector, the high temperature third variable of the AGV path planning sensor is obtained. The high temperature first variable of the AGV path planning sensor is corrected by the corresponding weight factor of the high temperature first variable of the AGV path planning sensor to obtain the high temperature first weight variable of the AGV path planning sensor. The high temperature second variable of the AGV path planning sensor is corrected by the corresponding weight factor of the high temperature second variable of the AGV path planning sensor to obtain the high temperature second weight variable of the AGV path planning sensor. The high temperature third variable of the AGV path planning sensor is corrected by the corresponding weight factor of the high temperature third variable of the AGV path planning sensor to obtain the high temperature third weight variable of the AGV path planning sensor. By combining the first, second, and third weighted variables of high temperature in the AGV path planning sensor, a correction value for the negative impact of high temperature on the AGV path planning sensor is obtained. This correction value is used to describe the quantification of the degree of negative distortion of the AGV path planning sensor caused by external high temperature, based on the average dark current of the avalanche photodiode of the APD detector of the AGV path planning sensor, and the combined effect of the first and second variables of high temperature on the AGV path planning sensor. If the correction value for the negative impact of high temperature on the AGV path planning sensor is less than the corresponding threshold for the negative impact of high temperature on the AGV path planning sensor, then no adjustment is made; If the high temperature negative influence correction value of the AGV path planning sensor is equal to or greater than the corresponding high temperature negative influence threshold of the AGV path planning sensor, the SiCMOSFET parallel drive of the AGV motor driver is activated, and thermal correction is performed through predefined software using the temperature acquisition data built into the AGV path planning sensor.

2. The AGV handling monitoring method for underground parking garages as described in claim 1, characterized in that, The AGV docks with, carries, and transports the spontaneously combusting vehicle, specifically including: Real-time monitoring of fire early warning data in the corresponding underground parking garage area using a distributed fire sensor array; If the local temperature of a vehicle in the fire warning data is lower than the corresponding temperature threshold for a spontaneously combusting vehicle, no action will be taken. If the local temperature of a vehicle in the fire warning data is equal to or greater than the corresponding spontaneous combustion vehicle temperature threshold, then the corresponding vehicle is identified as a spontaneous combustion vehicle, the underground garage area where the spontaneous combustion vehicle is located is recorded, a predefined isolation procedure is initiated for the underground garage area where the spontaneous combustion vehicle is located, and the AGV is called to go to the underground garage area where the spontaneous combustion vehicle is located through a predefined hierarchical path planning scheme. The AGV unfolds its three-stage telescopic arm through a special AGV hydraulic lifting mechanism, grabs the vehicle's chassis support point, and transports the corresponding self-ignited vehicle to a predefined underground garage safety house.

3. The AGV handling monitoring method for underground parking garages as described in claim 1, characterized in that, The aforementioned optimization of AGVs based on visibility comparison analysis specifically includes: The visibility of the underground parking garage is collected in real time using the lidar of the AGV; If the visibility in the underground parking garage is greater than the first visibility threshold, no adjustment will be made. If the visibility in the underground parking garage is greater than the second visibility threshold and less than or equal to the first visibility threshold, then the air brush cleaning device built into the AGV will be activated. If the visibility in the underground parking garage is greater than the third visibility threshold and less than or equal to the second visibility threshold, then the optical sensor is turned off and the non-optical sensor is kept on. If the visibility in the underground parking garage is less than or equal to the third visibility threshold, relevant personnel will be notified to conduct manual remote control.

4. The AGV handling monitoring method for underground parking garages as described in claim 1, characterized in that, The optimization and adjustment of AGVs to cope with high temperatures based on the comparative analysis of AGV backplate temperatures specifically includes: The temperature of the AGV backplate is collected in real time using the AGV's temperature sensor. If the temperature of the AGV backplate is less than or equal to the third threshold of the AGV's tolerance temperature, then a high-temperature negative impact correction assessment and adjustment will be performed. If the temperature of the AGV backplate is greater than the third threshold of the AGV's tolerance temperature and less than or equal to the second threshold of the AGV's tolerance temperature, then infrared thermal imager thermal radiation compensation is performed. If the temperature of the AGV backplate is greater than the second threshold of the AGV's tolerance temperature and less than or equal to the first threshold of the AGV's tolerance temperature, then the first cooling treatment is carried out through the integrated thermoelectric cooling device built into the AGV. If the temperature of the AGV backplate exceeds the first threshold of the AGV's tolerance temperature, a second cooling treatment will be carried out through the nitrogen curtain protection device built into the edge of the AGV backplate.

5. The AGV handling monitoring method for underground parking garages as described in claim 1, characterized in that, The optimization of AGV response to electromagnetic pulses based on comparative analysis of electromagnetic intensity received by the AGV backplate specifically includes: The electromagnetic intensity of the AGV's environment is collected in real time by the AGV's electromagnetic sensors. If the electromagnetic intensity of the AGV environment is less than or equal to the electromagnetic intensity threshold of the AGV environment, no adjustment is made; If the electromagnetic intensity of the AGV environment is greater than the threshold of the electromagnetic intensity of the AGV environment, then a correction assessment and adjustment for the negative impact of high electromagnetic interference will be carried out.

6. The AGV handling monitoring method for underground parking garages as described in claim 5, characterized in that, The aforementioned adjustment and correction of the negative impact of high electromagnetic interference specifically includes: The maximum instantaneous intensity and rise time of the electromagnetic pulse are collected in real time by the broadband electric field probe built into the AGV. The start time of the rise time of the electromagnetic pulse is recorded. If the intensity of the electromagnetic pulse is less than the electromagnetic pulse intensity attention threshold, the end time of the electromagnetic pulse is recorded. The difference between the end time of the electromagnetic pulse and the start time of the rise time of the electromagnetic pulse is recorded as the duration of the electromagnetic pulse. The allowable electromagnetic pulse intensity value was directly extracted from the AGV handling monitoring database in the underground parking garage. The ratio analysis of the instantaneous maximum intensity of the electromagnetic pulse with the rise time of the electromagnetic pulse is coupled with the duration of the electromagnetic pulse, and then the ratio analysis is performed with the allowable value of the electromagnetic pulse intensity to obtain the electromagnetic negative influence component of the AGV path planning sensor. By coupling the high temperature negative influence correction value of the AGV path planning sensor with the electromagnetic negative influence component of the AGV path planning sensor, the comprehensive value of the electromagnetic negative influence of the AGV path planning sensor is obtained. The comprehensive value of the electromagnetic negative influence of the AGV path planning sensor is used to quantitatively represent the degree of negative distortion influence of the AGV path planning sensor under the influence of external electromagnetic interference by the combination of the high temperature negative influence correction value of the AGV path planning sensor and the electromagnetic negative influence component of the AGV path planning sensor. If the combined value of the electromagnetic negative influence of the AGV path planning sensor is less than the second threshold, no adjustment will be made; If the comprehensive value of the electromagnetic negative influence of the AGV path planning sensor is equal to or greater than the second threshold and less than the first threshold, then generalized denoising processing is performed through the predefined first denoising software. If the combined value of the electromagnetic negative influence of the AGV path planning sensor is equal to or greater than the first threshold, then specific denoising processing is performed using predefined second denoising software.

7. The AGV handling monitoring method for underground parking garages as described in claim 1, characterized in that, The activation of the closed-loop fire suppression plan specifically includes: After the AGV determines that it has reached the safe house in the underground garage, it detaches from the burning vehicle. The safe house initiates heptafluoropropane total flooding injection, continuous cooling with fine water mist, exhaust gas treatment, and automatic sewage discharge; The AGV returns to the standby position and initiates its self-check.

8. An AGV handling monitoring system for underground parking garages, employing the AGV handling monitoring method for underground parking garages as described in any one of claims 1-7, characterized in that, This includes a disaster identification module for underground parking garages, a visibility analysis and adjustment module for AGV transport environments, a temperature analysis and adjustment module for AGV transport, an electromagnetic intensity analysis and adjustment module for AGV transport, and a fire suppression module for enclosed safe rooms in underground parking garages. The underground parking garage disaster identification module is used to identify disasters in underground parking garages. If a vehicle is detected to be on fire, the AGV will dock with the vehicle, carry it, and transport it. The AGV transport environment visibility analysis and adjustment module is used to determine the environmental visibility during the transport process in real time, and to adjust and optimize the AGV's response to visibility based on visibility comparison analysis; The AGV transport temperature analysis and adjustment module is used to judge the AGV backplate temperature in real time during the transport process, and to adjust and optimize the AGV to cope with high temperatures based on the comparison and analysis of the AGV backplate temperature. The AGV transport electromagnetic intensity analysis and adjustment module is used to judge the electromagnetic intensity of the AGV backplate in real time during the transport process, and to adjust and optimize the AGV's response to electromagnetic pulses based on the comparative analysis of the electromagnetic intensity of the AGV backplate. The underground parking garage safety room fire suppression module is used by AGVs to determine when they arrive at the underground parking garage safety room and to activate the fire suppression plan.

9. An AGV handling monitoring device for an underground parking garage, employing the AGV handling monitoring method for an underground parking garage as described in any one of claims 1-7, characterized in that, This includes special AGV high-temperature resistant chassis, special AGV hydraulic lifting mechanism, special AGV explosion-proof electrical hardware equipment, special modular underground garage safety house double-layer heat insulation equipment, special modular underground garage safety house intelligent fire extinguishing equipment, and special modular underground garage safety house negative pressure smoke exhaust equipment; Special AGV high-temperature resistant chassis, used to resist the negative effects of high temperatures when transporting spontaneously combusting vehicles; Specialized AGV hydraulic lifting mechanism for securing and transporting spontaneously combusting vehicles; Specialized explosion-proof electrical hardware for AGVs, used to resist the negative effects of deflagration in transporting spontaneously combusting vehicles; Special modular underground garage safety house with double-layer heat insulation equipment is used to resist the negative effects of deflagration in spontaneously combusting vehicles; Special modular intelligent fire extinguishing equipment for underground garage safety houses, used for rapid cooling and extinguishing of spontaneously combusting vehicles; Special modular underground garage safety house negative pressure smoke exhaust equipment is used for rapid negative pressure smoke exhaust from vehicles that spontaneously combust.

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