A method and system for detecting the distribution of harmful gases during battery disassembly.

Abstract

This invention relates to a method and system for detecting the distribution of harmful gases during battery disassembly. The detection method includes the following steps: S1, generating a rough distribution map of harmful gas concentration and extracting the rough edges of the harmful gas concentration in the rough distribution map; S2, controlling an inspection robot to perform inspections along the rough edges of the harmful gas concentration as the original inspection path, dynamically adjusting the original inspection path during the inspection process, and obtaining the precise edges of the harmful gas concentration through the inspection robot; S3, optimizing the rough distribution map of harmful gas concentration using the precise edges of the harmful gas concentration to obtain a precise distribution map of harmful gas concentration; S4, calculating the formation area of ​​the harmful gas pool based on the precise distribution map of harmful gas concentration, the flow velocity of the harmful gas, and the diffusion direction.

Description

Technical Field

[0001] This invention relates to the field of hazardous gas distribution detection, specifically to a method and system for hazardous gas distribution detection applicable to battery disassembly. Background Technology

[0002] A lithium battery is a type of battery that uses lithium metal or lithium compounds as the positive electrode material. It is primarily used to power vehicles such as new energy vehicles, hybrid vehicles, and electric bicycles. Currently, lithium batteries are the main power source for new energy vehicles. After the lifespan of a lithium battery declines, it needs to be disassembled and crushed to recover the lithium ions.

[0003] Since the electrolyte in batteries generally contains DMC, EMC, DEC, etc., when these substances leak and evaporate, they combine with water molecules in the air to form organic solvent vapors. Organic solvent vapors are denser than air, and after evaporation, they gradually settle to the ground and slowly diffuse, eventually accumulating in low-lying areas or corners of the room to form harmful gas pools.

[0004] Therefore, disassembly and real-time detection of hazardous gas leaks are necessary in enclosed equipment. Current technologies primarily employ: 1. Manual inspection: Due to the complex production processes, flammability, explosiveness, high concentrations of toxic and hazardous gases, and harsh operating environments in the battery disassembly industry, traditional manual inspection suffers from low efficiency, high risk, and delayed data acquisition; 2. Fixed sensor networks: These are costly to deploy and lack flexibility, typically only covering some key equipment or areas, failing to provide comprehensive coverage of the production area. Existing technologies are difficult to optimize based on the volatilization and diffusion characteristics of organic solvent vapors, relying solely on specific routes for inspection, ultimately failing to determine the distribution area of ​​hazardous gas pools.

[0005] The purpose of this invention is to design a method and system for detecting the distribution of harmful gases during battery disassembly, addressing the problems existing in the prior art. Summary of the Invention

[0006] In view of the problems existing in the prior art, the present invention provides a method and system for detecting the distribution of harmful gases in battery disassembly, which can effectively solve at least one of the problems existing in the prior art.

[0007] The technical solution of this invention is:

[0008] A method for detecting the distribution of harmful gases during battery disassembly, based on a harmful gas detection system, includes an inspection robot and several harmful gas sensors. The harmful gas sensors are arranged in an array centered on the corresponding disassembly equipment. The harmful gas sensors are placed on the ground. The inspection robot is used to walk around the disassembly equipment and detect harmful gases.

[0009] The detection method includes the following steps:

[0010] S1, after any of the harmful gas sensors detects a harmful gas, the concentrations of the harmful gas detected by multiple harmful gas sensors are obtained, a rough distribution map of the harmful gas concentration is generated, and the rough edges of the harmful gas concentration in the rough distribution map of the harmful gas concentration are extracted;

[0011] S2, control the inspection robot to perform inspections with the rough edge of the harmful gas as the original inspection path. During the inspection process, predict the flow speed and diffusion direction of the harmful gas based on the rough distribution map of the harmful gas concentration, and dynamically adjust the original inspection path according to the actual harmful gas concentration obtained by the inspection robot, so as to obtain the precise edge of the harmful gas through the inspection robot.

[0012] S3, optimize the rough distribution map of harmful gas concentration by the precise edge of the harmful gas to obtain the precise distribution map of harmful gas concentration;

[0013] S4. Calculate the formation area of ​​the harmful gas pool based on the accurate distribution map of the harmful gas concentration, the flow velocity of the harmful gas, and the diffusion direction of the harmful gas.

[0014] Further, in step S1, the concentrations of harmful gases detected by multiple harmful gas sensors are spatially interpolated and smoothed to generate a rough distribution map of harmful gas concentrations.

[0015] Furthermore, the flow velocity of the harmful gas is obtained using the following formula:

[0016] Where v is the flow velocity, dC is the change in the concentration of harmful gas, dt is the unit time, and Δx is the distance between adjacent harmful gas sensors;

[0017] The diffusion direction of harmful gases is obtained through the following steps: acquiring the concentration gradient obtained from the harmful gas sensor, constructing the gradient vector field of the gas flow, and taking the direction with the largest concentration gradient as the diffusion direction of the harmful gas.

[0018] Further, in step S2, based on the rough distribution map of harmful gas concentration, the flow velocity and diffusion direction of the harmful gas are predicted, and the actual harmful gas concentration obtained by the inspection robot, the original inspection path is dynamically adjusted to obtain the precise edge of the harmful gas, including:

[0019] S2.1, The harmful gas is coarsely discretized to obtain the original inspection path target point set of the inspection robot;

[0020] S2.2 Calculate the time point when the inspection robot reaches the next original path target point, predict the flow speed, diffusion direction and coordinates of the next original path target point based on the rough distribution map of the harmful gas concentration, and calculate the estimated offset position of the harmful gas at the next original path target point.

[0021] S2.3, control the inspection robot to reach the estimated offset position, obtain the actual concentration of harmful gas near the estimated offset position through the inspection robot, and take the coordinate of the sudden change in the concentration of harmful gas near the estimated offset position as the actual offset position.

[0022] S2.4, the coordinates of the subsequent original path target point and the offset of the actual offset position are weighted and added together to obtain the adjusted coordinates of the subsequent original path target point;

[0023] S2.5, repeat steps S2.2 to S2.4 until the inspection robot completes a closed path, connect the coordinates of all actual offset positions and perform smooth calculation to obtain the precise edge of the harmful gas.

[0024] Furthermore, the weighted sum of the coordinates of the subsequent original path target point and the offset of the actual offset position is achieved using the following formula:

[0025] ,

[0026] in This indicates the coordinates of the target point on the subsequent original path after adjustment. Indicates the coordinates of the target point on the subsequent original path. This represents the offset amount at the actual offset position. Indicates weight, It is a positive number less than 1, and It gradually decreases over time.

[0027] Furthermore, by optimizing the rough distribution map of harmful gas concentration using the precise edge of the harmful gas, a precise distribution map of harmful gas concentration is obtained, including:

[0028] The concentrations of harmful gases detected by multiple harmful gas sensors are interpolated using radial basis functions with the precise edge of the harmful gas as a constraint condition to obtain a precise distribution map of the harmful gas concentration.

[0029] Furthermore, based on the precise distribution map of the harmful gas concentration, the flow velocity of the harmful gas, and the diffusion direction, the formation area of ​​the harmful gas pool is calculated to include:

[0030] S4.1, Extract the streamlines and isoconcentration lines of the harmful gases from the accurate distribution map of harmful gas concentration;

[0031] S4.2, by using the streamlines and isoconcentration lines of the harmful gas, combined with the flow velocity and diffusion direction of the harmful gas, and the surrounding environment of the dismantling equipment, a hydrodynamic model of the harmful gas is performed, and the formation area of ​​the harmful gas pool is calculated through the hydrodynamic model of the harmful gas.

[0032] Furthermore, S4.2 includes:

[0033] S4.2.1, Establish a three-dimensional geometric model that includes the dismantling equipment, the surrounding environment, and obstacles;

[0034] S4.2.2, Obtain the air velocity, temperature and humidity around the dismantling equipment, as well as the physical properties of harmful gases;

[0035] S4.2.3, import the three-dimensional geometric model, the air velocity, temperature and humidity around the dismantling equipment, the physical properties of the harmful gases, and the accurate distribution map of the concentration of the harmful gases into the fluid dynamics system to establish a fluid dynamics model of the harmful gases;

[0036] S4.2.4, The formation area of ​​the harmful gas pool is obtained by calculating the area where harmful gas accumulates due to the presence of obstacles or the reduction of external wind speed through the harmful gas hydrodynamic model.

[0037] Furthermore, a hazardous gas distribution detection system suitable for battery disassembly is provided, which implements any one of the hazardous gas distribution detection methods for battery disassembly during operation.

[0038] Therefore, the present invention provides the following effects and / or advantages:

[0039] This application deploys multiple hazardous gas sensors and uses an inspection robot for dynamic path planning and detection, thereby obtaining an accurate distribution map of hazardous gas concentrations. Finally, the formation area of ​​the hazardous gas pool is calculated using the accurate distribution map of hazardous gas concentrations.

[0040] This application uses the edges of a rough distribution map of hazardous gas concentrations obtained from multiple hazardous gas sensors as the original path for an inspection robot. This allows for the recommendation of a closer edge path for the robot, improving its detection accuracy. Simultaneously, the actual offset position obtained by the robot iteratively optimizes its movement path. By weighting the coordinates of the subsequent original path target point with the actual offset position, the relationship between the robot's actual offset and the original path target point is balanced, thereby improving the robot's detection accuracy and work efficiency.

[0041] Other features and advantages of the invention will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention are realized and obtained through the structures particularly pointed out in the description and the drawings.

[0042] It should be understood that the above summary and the following detailed description of the invention are exemplary and explanatory, and are intended to provide further explanation of the invention as claimed. Attached Figure Description

[0043] Figure 1 This is a flowchart illustrating one embodiment of the present invention.

[0044] Figure 2 This is a schematic diagram of the harmful gas concentration obtained by the array of harmful gas sensors.

[0045] Figure 3 According to Figure 2 The rough distribution map of harmful gas concentrations was obtained from the data calculation.

[0046] Figure 4 According to Figure 3 The rough edge of the calculated harmful gas.

[0047] Figure 5 According to Figure 4 The calculated precise edge of the harmful gas.

[0048] Figure 6 According to Figure 5 The calculated precise distribution map of harmful gas concentrations.

[0049] Figure 7 According to Figure 6 A schematic diagram of the calculated area where harmful gases accumulate. Detailed Implementation

[0050] To facilitate understanding by those skilled in the art, the present invention will now be described in further detail with reference to the embodiments:

[0051] refer to Figure 1 A method for detecting the distribution of harmful gases in battery disassembly, based on a harmful gas detection system, includes an inspection robot and several harmful gas sensors. The harmful gas sensors are arranged in an array around the corresponding disassembly equipment. The harmful gas sensors are placed on the ground. The inspection robot is used to walk around the disassembly equipment and detect harmful gases.

[0052] In this embodiment, the hazardous gas sensors can be arranged in a rectangular array, with the center of the array located at the center point of the dismantling equipment and positioned on the ground. When hazardous gases leak due to electrolyte evaporation, some of these gases, being denser than air, will gradually sink and slowly diffuse, thus being detected by the hazardous gas sensors on the ground. However, the hazardous gas sensors have a certain detection delay, which is addressed by the method provided in this embodiment. An inspection robot, also equipped with hazardous gas sensors, can perform inspections around the dismantling equipment.

[0053] The detection method includes the following steps:

[0054] S1, after any of the harmful gas sensors detects a harmful gas, the concentrations of the harmful gas detected by multiple harmful gas sensors are obtained, a rough distribution map of the harmful gas concentration is generated, and the rough edges of the harmful gas concentration in the rough distribution map of the harmful gas concentration are extracted;

[0055] In this embodiment, when any of the hazardous gas sensors detects a hazardous gas, it indicates that the hazardous gas has leaked from the dismantling equipment, and hazardous gas distribution detection is required. Since the multiple hazardous gas sensors are deployed in fixed positions and their spacing forms an array, the hazardous gas concentration in the area corresponding to each sensor can be obtained, such as... Figure 2 As shown in the figure. Then, after obtaining the concentration of harmful gases corresponding to each sensor, a rough distribution map of the harmful gas concentration can be obtained by generating the corresponding concentration distribution map, such as... Figure 3 As shown, due to the gaps between the harmful gas sensors in the array, the rough distribution map of the harmful gas concentration generated at this time is coarse and cannot accurately reflect the distribution of harmful gases.

[0056] Further, in step S1, the concentrations of harmful gases detected by multiple harmful gas sensors are spatially interpolated and smoothed to generate a rough distribution map of harmful gas concentrations.

[0057] like Figure 2 As shown, based on the data collected by the sensors, a distribution map of hazardous substance concentrations at different locations within the area can be constructed. These data points can be smoothed using interpolation algorithms, such as Kriging interpolation and inverse distance weighting, to generate a continuous concentration distribution map. Through spatial interpolation and dynamic path adjustment, the hazardous gas concentration distribution of the point matrix can be converted into a coarse distribution map.

[0058] Then, based on the preset concentration contour lines, a rough outline of the harmful gas is established, such as... Figure 4 The blue line shown represents the rough edge of the harmful gas.

[0059] S2, control the inspection robot to perform inspections along the rough edge of the harmful gas as the original inspection path. During the inspection process, predict the flow speed and diffusion direction of the harmful gas based on the rough distribution map of the harmful gas concentration, and dynamically adjust the original inspection path to obtain the precise edge of the harmful gas.

[0060] In this step, a rough distribution map of the harmful gas concentration is obtained by deploying multiple harmful gas sensors. At this time, the inspection robot inspects the rough edge of the harmful gas to obtain a definite edge of the harmful gas distribution. At the same time, during the inspection process, the harmful gas may further diffuse or flow in a certain direction. Therefore, it is necessary to continuously and in real time adjust the rough edge of the harmful gas so that the inspection robot can reach the vicinity of the edge of the harmful gas more quickly, thereby obtaining the edge of the harmful gas distribution and avoiding the inspection robot blindly scanning along a fixed route, which would waste a lot of time.

[0061] Furthermore, the flow velocity of the harmful gas is obtained using the following formula:

[0062] Where v is the flow velocity, dC is the change in the concentration of harmful gas, dt is the unit time, and Δx is the distance between adjacent harmful gas sensors;

[0063] The diffusion direction of harmful gases is obtained through the following steps: acquiring the concentration gradient obtained from the harmful gas sensor, constructing the gradient vector field of the gas flow, and taking the direction with the largest concentration gradient as the diffusion direction of the harmful gas.

[0064] In this step, the gas flow rate can be estimated by analyzing the changes in concentration at different time points, using the rate of change of harmful gases. The flow velocity of the harmful gas can be obtained by relating the distance Δx between the sensor and the adjacent harmful gas sensor.

[0065] Furthermore, harmful gases typically flow from areas of high concentration to areas of low concentration. By comparing data from multiple sensors, the direction of gas flow can be determined. For example, if a sensor shows a high concentration while neighboring sensors show a lower concentration, it can be inferred that the gas is flowing from a high-concentration region to a low-concentration region. By measuring the concentration gradient at various locations, a gradient vector field of the gas flow can be constructed. The direction of gas flow is the direction of the maximum concentration gradient.

[0066] Further, in step S2, based on the rough distribution map of harmful gas concentration, the flow velocity and diffusion direction of the harmful gas are predicted, and the actual harmful gas concentration obtained by the inspection robot, the original inspection path is dynamically adjusted. The precise edge of the harmful gas is obtained through the inspection robot, including:

[0067] S2.1, The harmful gas is coarsely discretized to obtain the original inspection path target point set of the inspection robot;

[0068] S2.2 Calculate the time point when the inspection robot reaches the next original path target point, predict the flow speed, diffusion direction and coordinates of the next original path target point based on the rough distribution map of the harmful gas concentration, and calculate the estimated offset position of the harmful gas at the next original path target point.

[0069] S2.3, control the inspection robot to reach the estimated offset position, obtain the actual concentration of harmful gas near the estimated offset position through the inspection robot, and take the coordinate of the sudden change in the concentration of harmful gas near the estimated offset position as the actual offset position.

[0070] S2.4, the coordinates of the subsequent original path target point and the offset of the actual offset position are weighted and added together to obtain the adjusted coordinates of the subsequent original path target point;

[0071] S2.5, repeat steps S2.2 to S2.4 until the inspection robot completes a closed path, connect the coordinates of all actual offset positions and perform smooth calculation to obtain the precise edge of the harmful gas.

[0072] In this step, for example, Figure 4 The blue edges shown are discretized to obtain, for example, the coordinates of 100 target points that the inspection robot needs to traverse. The rough edges represent the approximate extent of the gas leak area, but these edges are usually continuous. Therefore, they need to be transformed into discrete target points through a certain meshing or sampling method. These target points represent the rough edges of the hazardous gas distribution. Then, since the inspection robot takes different times to reach each target point, the hazardous gas may further flow or disperse. Therefore, after predicting the flow velocity and diffusion direction of the hazardous gas using the rough hazardous gas concentration distribution map, the approximate location of the hazardous gas distribution area after changes can be predicted based on the time required for the inspection robot to reach the target point, thus obtaining the estimated offset location.

[0073] Next, the inspection robot is guided to the estimated offset position. At this point, the robot begins detection in the vicinity of this estimated offset position, for example, by performing an S-shaped path detection. This allows for real-time measurement and correction of the estimated position. Hazardous gas sensors on the robot measure the gas concentration near the offset position in real time. When the gas concentration changes abruptly, i.e., a sharp change, the point of change is usually a marker of the leak source or gas boundary. By comparing the estimated offset position with the actual measured concentration data, the robot can calculate the accurate actual offset position. This process ensures that the robot can more accurately track the edge of the gas leak area.

[0074] Finally, the coordinates of subsequent target points are further corrected using the actual offset positions. For example, if the offset between the estimated and actual offset positions of the previous point is A, then the offsets of subsequent points will generally be around A. During dynamic path adjustment, the robot continuously corrects its path to adapt to real-time changes in gas concentration. Combining and weighting the coordinates of the original target points with the actual offset positions makes the path more consistent with the actual gas diffusion situation. By weighting the offsets, the relationship between the actual offset and the original path target points can be balanced. The weights are usually gradually reduced over time to avoid excessively frequent path adjustments, which would decrease inspection efficiency. Simultaneously, the robot adjusts its travel route based on the weighted target points to ensure inspection along the precise edges of the gas leak area. This process helps improve the detection accuracy of gas leaks and avoids omissions.

[0075] The process of executing steps S2.2 through S2.4 repeatedly completes a full iteration. The robot continuously adjusts its path based on real-time data until the entire area is inspected. Each time, the path is corrected based on new data, gradually approaching the precise edge of the hazardous gas. Finally, all actual offset positions are smoothly connected to obtain a smooth, accurate, and continuous precise edge of the hazardous gas.

[0076] Furthermore, the weighted sum of the coordinates of the subsequent original path target point and the offset of the actual offset position is achieved using the following formula:

[0077] ,

[0078] in This indicates the coordinates of the target point on the subsequent original path after adjustment. Indicates the coordinates of the target point on the subsequent original path. This represents the offset amount at the actual offset position. Indicates weight, It is a positive number less than 1, and It gradually decreases over time.

[0079] In this step, the offset distance and direction can be obtained by comparing the estimated offset position with the actual offset position. Combining the offset distance and direction yields the offset amount. Weights are set in this formula. The goal is that, during the initial inspection phase, the time it reaches the target point is close to the time when the harmful gas is roughly generated at the edge in step S1, and the changes in gas dispersion and flow are also small. Therefore, during the initial inspection phase, the actual offset of the position is relatively small. The weight is relatively small at this time. The larger displacement allows the inspection robot to be controlled to approach the original path target point more closely, thus reducing the impact of offset on the robot's path. However, in the later stages of the inspection robot's operation, the changes in gas dispersion and flow are significant, resulting in a substantial shift in the actual offset position. The weight is relatively large at this time. The smaller size allows the inspection robot to be controlled to move closer to the coordinates of the target point after the original path is offset, thereby dynamically adjusting the target point corresponding to the robot's walking path and balancing the relationship between the actual offset of harmful gas diffusion and the target point of the original path.

[0080] The precise edge of the harmful gas obtained in step S2 can be as follows: Figure 5 As shown.

[0081] S3, optimize the rough distribution map of harmful gas concentration by the precise edge of the harmful gas to obtain the precise distribution map of harmful gas concentration;

[0082] By optimizing the coarse distribution map, the location of the gas leak edge can be captured more accurately. This precise edge identification helps to understand the accurate distribution of hazardous gases, avoid potential omissions, and improve the accuracy of the detection system. At the same time, the accurate concentration distribution map can more accurately simulate the formation of hazardous gas accumulation areas, helping to identify potential danger zones after a gas leak, provide early warnings, and take preventive measures.

[0083] Furthermore, by optimizing the rough distribution map of harmful gas concentration using the precise edge of the harmful gas, a precise distribution map of harmful gas concentration is obtained, including:

[0084] The concentrations of harmful gases detected by multiple harmful gas sensors are interpolated using radial basis functions with the precise edge of the harmful gas as a constraint condition to obtain a precise distribution map of the harmful gas concentration.

[0085] In this step, radial basis function (RBF) is a commonly used method for data interpolation and surface fitting. Its core idea is to use a distance-based function to smoothly interpolate the entire region based on existing discrete data points, such as concentration data detected by a hazardous gas sensor. During the interpolation process, precise edges of the hazardous gas concentration act as constraints. Since the edges of gas leaks represent areas of drastic gas concentration changes, using these precise edges ensures that the interpolation calculations obtain more accurate results in areas with large gas concentration variations. By using these edges as constraints, the interpolation results can better reflect the actual situation of gas diffusion. Through RBF interpolation, all areas not covered by the sensor can be filled, generating a concentration distribution map of the entire region. Due to the constraints of the precise edges, changes in gas concentration will be accurately processed and displayed near these edges. The final result is as follows: Figure 6 The diagram shows the precise distribution of harmful gas concentrations.

[0086] S4. Calculate the formation area of ​​the harmful gas pool based on the accurate distribution map of the harmful gas concentration, the flow velocity of the harmful gas, and the diffusion direction of the harmful gas.

[0087] Furthermore, based on the precise distribution map of the harmful gas concentration, the flow velocity of the harmful gas, and the diffusion direction, the formation area of ​​the harmful gas pool is calculated to include:

[0088] S4.1, Extract the streamlines and isoconcentration lines of the harmful gases from the accurate distribution map of harmful gas concentration;

[0089] S4.2, by using the streamlines and isoconcentration lines of the harmful gas, combined with the flow velocity and diffusion direction of the harmful gas, and the surrounding environment of the dismantling equipment, a hydrodynamic model of the harmful gas is performed, and the formation area of ​​the harmful gas pool is calculated through the hydrodynamic model of the harmful gas.

[0090] Furthermore, S4.2 includes:

[0091] S4.2.1, Establish a three-dimensional geometric model that includes the dismantling equipment, the surrounding environment, and obstacles;

[0092] S4.2.2, Obtain the air velocity, temperature and humidity around the dismantling equipment, as well as the physical properties of harmful gases;

[0093] S4.2.3, import the three-dimensional geometric model, the air velocity, temperature and humidity around the dismantling equipment, the physical properties of the harmful gases, and the accurate distribution map of the concentration of the harmful gases into the fluid dynamics system to establish a fluid dynamics model of the harmful gases;

[0094] S4.2.4, The formation area of ​​the harmful gas pool is obtained by calculating the area where harmful gas accumulates due to the presence of obstacles or the reduction of external wind speed through the harmful gas hydrodynamic model.

[0095] In this step, the data from the original hazardous gas sensors guides the inspection robot's path. After the robot's inspection, a precise edge of the hazardous gas distribution is obtained. Further optimization of the rough hazardous gas concentration distribution map yields a precise hazardous gas concentration distribution map, which can be used to analyze gas flow patterns after electrolyte leakage. Fluid dynamics models (such as CFD simulations) are used to predict the gas flow path and diffusion direction within the dismantling area. Airflow in different areas may be affected by dismantling equipment, ventilation conditions, temperature, and airflow; the robot can adjust its inspection path in real time based on this flow information.

[0096] Specifically, firstly, 3D modeling software is used to create geometric models of the dismantling equipment and its surrounding environment. These models need to accurately reflect the dismantling area, equipment location, walls, passageways, windows, and other physical elements that may affect gas flow. Then, environmental monitoring equipment, such as airflow meters and temperature and humidity sensors, is installed to acquire real-time data on air velocity, temperature, and humidity in the dismantling area. Next, the 3D geometric models, air velocity, temperature and humidity data, gas physical properties, and gas concentration distribution maps are input into fluid dynamics simulation software. By setting appropriate boundary and initial conditions, the location of the gas leakage source, gas type, and concentration are defined, and the gas diffusion process is simulated. The gas flow path within the dismantling area is calculated, simulating how the gas diffuses due to the influence of equipment and obstacles. Diffusion equations are used to simulate the gas diffusion process, considering the influence of environmental factors such as air velocity, temperature, and humidity on gas flow. Finally, the accumulation area of ​​harmful gases can be deduced, such as... Figure 7 As shown.

[0097] Furthermore, a hazardous gas distribution detection system suitable for battery disassembly is provided, which implements the aforementioned hazardous gas distribution detection method suitable for battery disassembly during operation.

[0098] 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-ROM, optical storage, etc.) containing computer-usable program code.

[0099] 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.

[0100] 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.

[0101] 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 the preferred embodiments as well as all changes and modifications falling within the scope of the invention.

[0102] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms should not be construed as necessarily referring to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

Claims

1. A method for detecting the distribution of harmful gases during battery disassembly, characterized in that: The system is based on a hazardous gas detection system, including an inspection robot and several hazardous gas sensors. The hazardous gas sensors are arranged in an array around a corresponding dismantling device. The hazardous gas sensors are placed on the ground. The inspection robot is used to walk around the dismantling device and detect hazardous gases. The detection method includes the following steps: S1, after any of the harmful gas sensors detects a harmful gas, the concentrations of the harmful gas detected by multiple harmful gas sensors are obtained, a rough distribution map of the harmful gas concentration is generated, and the rough edges of the harmful gas concentration in the rough distribution map of the harmful gas concentration are extracted; S2, control the inspection robot to perform inspections along the rough edge of the hazardous gas as the original inspection path. During the inspection process, predict the flow velocity and diffusion direction of the hazardous gas based on the rough distribution map of the hazardous gas concentration, and dynamically adjust the original inspection path according to the actual hazardous gas concentration obtained by the inspection robot. The precise edge of the hazardous gas obtained by the inspection robot includes: S2.1, The harmful gas is coarsely discretized to obtain the original inspection path target point set of the inspection robot; S2.2 Calculate the time point when the inspection robot reaches the next original path target point, predict the flow speed, diffusion direction and coordinates of the next original path target point based on the rough distribution map of the harmful gas concentration, and calculate the estimated offset position of the harmful gas at the next original path target point. S2.3, control the inspection robot to reach the estimated offset position, obtain the actual concentration of harmful gas near the estimated offset position through the inspection robot, and take the coordinate of the sudden change in the concentration of harmful gas near the estimated offset position as the actual offset position. S2.4, the coordinates of the subsequent original path target point and the offset of the actual offset position are weighted and added together to obtain the adjusted coordinates of the subsequent original path target point; The weighted sum of the coordinates of the subsequent original path target point and the offset of the actual offset position is achieved using the following formula: ， in This indicates the coordinates of the target point on the subsequent original path after adjustment. Indicates the coordinates of the target point on the subsequent original path. This represents the offset amount of the actual offset position. Indicates weight, It is a positive number less than 1, and Gradually decreases over time; S2.5, repeat S2.2~S2.4 until the inspection robot completes a closed path, connect the coordinates of all actual offset positions and perform smooth calculation to obtain the precise edge of the harmful gas. S3, optimize the rough distribution map of harmful gas concentration by the precise edge of the harmful gas to obtain the precise distribution map of harmful gas concentration; S4. Calculate the formation area of ​​the harmful gas pool based on the accurate distribution map of the harmful gas concentration, the flow velocity of the harmful gas, and the diffusion direction of the harmful gas.

2. The method for detecting the distribution of harmful gases during battery disassembly according to claim 1, characterized in that: In step S1, the concentrations of harmful gases detected by multiple harmful gas sensors are spatially interpolated and smoothed to generate a rough distribution map of harmful gas concentrations.

3. The method for detecting the distribution of harmful gases during battery disassembly according to claim 1, characterized in that: The flow velocity of harmful gases is obtained using the following formula: Where v is the flow velocity, dC is the change in the concentration of harmful gas, dt is the unit time, and Δx is the distance between adjacent harmful gas sensors; The diffusion direction of harmful gases is obtained through the following steps: acquiring the concentration gradient obtained from the harmful gas sensor, constructing the gradient vector field of the gas flow, and taking the direction with the largest concentration gradient as the diffusion direction of the harmful gas.

4. The method for detecting the distribution of harmful gases during battery disassembly according to claim 1, characterized in that: By optimizing the rough distribution map of harmful gas concentration using the precise edge of the harmful gas, a precise distribution map of harmful gas concentration is obtained, including: The concentrations of harmful gases detected by multiple harmful gas sensors are interpolated using radial basis functions with the precise edge of the harmful gas as a constraint condition to obtain a precise distribution map of the harmful gas concentration.

5. The method for detecting the distribution of harmful gases during battery disassembly according to claim 1, characterized in that: Based on the precise distribution map of the harmful gas concentration, the flow velocity of the harmful gas, and the diffusion direction, the formation area of ​​the harmful gas pool is calculated to include: S4.1, Extract the streamlines and isoconcentration lines of the harmful gases from the accurate distribution map of the harmful gas concentration; S4.2, by using the streamlines and isoconcentration lines of the harmful gas, combined with the flow velocity and diffusion direction of the harmful gas, and the surrounding environment of the dismantling equipment, a hydrodynamic model of the harmful gas is performed, and the formation area of ​​the harmful gas pool is calculated through the hydrodynamic model of the harmful gas.

6. The method for detecting the distribution of harmful gases during battery disassembly according to claim 5, characterized in that: S4.2 includes: S4.2.1, Establish a three-dimensional geometric model that includes the dismantling equipment, the surrounding environment, and obstacles; S4.2.2, Obtain the air velocity, temperature and humidity around the dismantling equipment, as well as the physical properties of harmful gases; S4.2.3, import the three-dimensional geometric model, the air velocity, temperature and humidity around the dismantling equipment, the physical properties of the harmful gases, and the accurate distribution map of the concentration of the harmful gases into the fluid dynamics system to establish a fluid dynamics model of the harmful gases; S4.2.4, The formation area of ​​the harmful gas pool is obtained by calculating the area where harmful gas accumulates due to the presence of obstacles or the reduction of external wind speed through the harmful gas hydrodynamic model.

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