Active safety control method and device for engineering machinery based on multi-parameter analysis

Abstract

The invention relates to the technical field of engineering machinery, and discloses an engineering machinery active safety control method and device based on multi-parameter analysis, and the method comprises the steps: collecting the multi-modal data of an environment where the engineering machinery is located based on a multi-modal data collection device, and constructing a dynamic model of the engineering machinery and the environment according to the multi-modal data, analyzing the multi-modal data through a dynamic model to obtain an environment data analysis result and an equipment data analysis result, determining an operation risk level of the engineering machinery according to the environment data analysis result and the equipment data analysis result, and determining an optimal working path of the engineering machinery according to the multi-modal data. And generating a safety control strategy according to the operation risk level and the optimal working path. Therefore, by implementing the method, the evaluation accuracy of the operation risk can be improved, the probability of misoperation of operators is reduced, the operation accuracy and reliability of the engineering machinery are enhanced, and the operation efficiency, the operation stability and the operation safety of the engineering machinery are further improved.

Description

Technical Field

[0001] The present invention relates to the technical field of engineering machinery, and in particular to an active safety control method and device for engineering machinery based on multi-parameter analysis. Background Art

[0002] In the field of construction machinery, with the development of intelligent and automated technologies, the safety and efficiency of excavators and other equipment operating in complex terrain are gaining increasing attention. Currently, excavator operations on complex terrain such as slopes still rely primarily on the driver's experience and manual operation. This manual operation method is easily influenced by subjective factors, poses safety risks, lacks the ability to perceive environmental factors, cannot effectively respond to emergencies, and has low control accuracy, resulting in low operating efficiency and safety.

[0003] Currently, existing technologies typically rely on single-sensor monitoring or simple early warning systems combined with driver experience to improve operational safety. However, this approach only monitors a single parameter and fails to comprehensively consider the multi-dimensional factors of the operating environment. This leads to inaccurate operational risk assessments and ineffective operational safety assurance. Therefore, it is particularly important to develop a technical solution that can improve the accuracy of operational risk assessments and, in turn, enhance operational safety. Summary of the Invention

[0004] The present invention provides a method and device for active safety control of engineering machinery based on multi-parameter analysis, which can help improve the accuracy of operation risk assessment and thus improve operation safety.

[0005] In order to solve the above technical problems, the first aspect of the present invention discloses an active safety control method for engineering machinery based on multi-parameter analysis, the method comprising: Collecting multimodal data of the environment in which the construction machinery is located based on a preset multimodal data acquisition device, and constructing a dynamic model of the construction machinery and the environment based on the multimodal data, wherein the multimodal data includes environmental data and equipment data; Analyzing the multimodal data using the dynamic model to obtain an environmental data analysis result and an equipment data analysis result, and determining an operation risk level of the engineering machinery based on the environmental data analysis result and the equipment data analysis result using the dynamic model; determining an optimal working path of the engineering machinery according to the multimodal data; A safety control strategy for the engineering machinery is generated according to the operation risk level and the optimal working path, and the operation of the engineering machinery is controlled according to the safety control strategy.

[0006] As an optional embodiment, in the first aspect of the present invention, the environmental data includes slope data, type data, and flatness data of the working area of ​​the engineering machinery, the equipment data includes load data and center of gravity offset data of the engineering machinery, the environmental data analysis results include environmental data indicators corresponding to each type of environmental data and a comprehensive probability of disaster occurrence in the working area, and the equipment data analysis results include an overturning moment indicator; The multimodal data is analyzed by the dynamic model to obtain environmental data analysis results and equipment data analysis results, including: Analyzing the environmental data to obtain environmental data indicators corresponding to each type of environmental data, the environmental data indicators including an inclination angle indicator corresponding to the slope data, a friction coefficient indicator corresponding to the type data, and a flatness indicator corresponding to the flatness data; Obtaining meteorological data for an operating area of ​​the engineering machinery within a preset time period, determining a probability of occurrence of at least one natural disaster in the operating area based on an environmental data indicator corresponding to each type of environmental data, and determining a comprehensive probability of occurrence of the disaster in the operating area based on the meteorological data and the probability of occurrence of each type of natural disaster; The overturning moment index of the construction machinery is calculated according to the equipment data and the inclination angle index of the working area.

[0007] As an optional embodiment, in the first aspect of the present invention, determining the operation risk level of the engineering machinery according to the environmental data analysis results and the equipment data analysis results using the dynamic model includes: Obtaining a parameter weight set corresponding to the engineering machinery, the parameter weight set including a first weight corresponding to the tilt angle index, a second weight corresponding to the friction coefficient index, a third weight corresponding to the flatness index, a fourth weight corresponding to the comprehensive probability of disaster occurrence, and a fifth weight corresponding to the overturning moment index; Calculating the operation risk of the engineering machinery according to the parameter weight set, the environmental data index corresponding to each type of environmental data, the comprehensive probability of disaster occurrence, the overturning moment index, and a preset operation risk calculation formula, and determining the operation risk level of the engineering machinery according to the operation risk; The operational risk calculation formula includes:

[0008] in, represents the first weight, represents the tilt angle index, represents the second weight, represents the friction coefficient index, represents the third weight, represents the flatness index, represents the fourth weight, P represents the comprehensive probability of the disaster, represents the fifth weight, and M represents the overturning moment index.

[0009] As an optional implementation manner, in the first aspect of the present invention, determining the optimal working path of the engineering machinery according to the multimodal data includes: Constructing a grid map of the working area of ​​the engineering machinery based on the multimodal data, the grid map including a plurality of grids and grid parameters of each grid, the grid parameters of each grid including at least slope data, friction coefficient, and obstacle marker corresponding to the grid; determining at least one working path corresponding to the engineering machinery according to the gridded map; Obtaining a parameter coefficient corresponding to each of the grid parameters, and calculating a path cost of each of the working paths based on the grid parameters of each of the grids and the parameter coefficient corresponding to each of the grid parameters; According to the path cost of each working path, an optimal working path of the engineering machine is selected from each working path.

[0010] As an optional implementation manner, in the first aspect of the present invention, generating the safety control strategy of the engineering machinery according to the operation risk level and the optimal working path includes: determining whether the operation risk level is greater than a preset first risk level threshold, and generating a risk reminder strategy for the construction machinery when the operation risk level is greater than the first risk level threshold; determining whether the operation risk level is greater than a preset second risk level threshold, and when the operation risk level is greater than the second risk level threshold, determining at least one risky position in the optimal working path, wherein the second risk level threshold is greater than the first risk level threshold; For each risk position, calculating the maximum operating speed and center of gravity adjustment angle of the engineering machinery at the risk position according to the inclination angle index, the friction coefficient index, and the load data corresponding to the risk position; An operation control strategy for the engineering machinery is generated based on the maximum operating speed and the center of gravity adjustment angle corresponding to each risk position, and a safety control strategy for the engineering machinery is generated based on the risk reminder strategy and / or the operation control strategy.

[0011] As an optional embodiment, in the first aspect of the present invention, the method further comprises: Predicting projection information of the engineering machine when operating in the optimal working path, and determining a safety boundary of the engineering machine in the optimal working path based on the projection information and slope data of the working area of ​​the engineering machine; In the process of controlling the operation of the engineering machinery according to the safety control strategy, real-time data of a current position of the engineering machinery in the optimal working path is determined, and the safety margin is adjusted according to the real-time data to obtain a target safety margin, wherein the real-time data includes wind speed change data and / or load change data; A recommended operating range of the engineering machinery is determined according to the target safety margin, and the target safety margin and the recommended operating range are visually displayed.

[0012] As an optional embodiment, in the first aspect of the present invention, calculating the overturning moment index of the construction machinery based on the equipment data and the inclination angle index of the working area includes: Calculating the overturning moment of the engineering machinery according to the load data of the engineering machinery, the center of gravity offset data, the slope inclination angle index of the working area, and a preset overturning moment calculation formula; Acquiring a maximum overturning moment of the engineering machinery, and normalizing the overturning moment of the engineering machinery according to the maximum overturning moment to obtain an overturning moment index of the engineering machinery; The overturning moment calculation formula includes:

[0013] Wherein, W represents the load data, Indicates the center of gravity offset data.

[0014] A second aspect of the present invention discloses an active safety control device for engineering machinery based on multi-parameter analysis, the device comprising: An acquisition module is configured to acquire multimodal data of the environment in which the construction machinery is located based on a preset multimodal data acquisition device, and to construct a dynamic model of the construction machinery and the environment based on the multimodal data, wherein the multimodal data includes environmental data and equipment data; an analysis module, configured to analyze the multimodal data using the dynamic model to obtain an environmental data analysis result and an equipment data analysis result, and determine an operation risk level of the engineering machinery based on the environmental data analysis result and the equipment data analysis result using the dynamic model; a first determining module, configured to determine an optimal working path of the engineering machine according to the multimodal data; A generation module is used to generate a safety control strategy for the engineering machinery according to the operation risk level and the optimal working path, and control the operation of the engineering machinery according to the safety control strategy.

[0015] As an optional embodiment, in the second aspect of the present invention, the environmental data includes slope data, type data, and flatness data of the working area of ​​the engineering machinery, the equipment data includes load data and center of gravity offset data of the engineering machinery, the environmental data analysis results include environmental data indicators corresponding to each type of environmental data and a comprehensive probability of disaster occurrence in the working area, and the equipment data analysis results include an overturning moment indicator; The analysis module analyzes the multimodal data using the dynamic model to obtain the environmental data analysis results and the device data analysis results in a manner that specifically includes: Analyzing the environmental data to obtain environmental data indicators corresponding to each type of environmental data, the environmental data indicators including an inclination angle indicator corresponding to the slope data, a friction coefficient indicator corresponding to the type data, and a flatness indicator corresponding to the flatness data; Obtaining meteorological data for an operating area of ​​the engineering machinery within a preset time period, determining a probability of occurrence of at least one natural disaster in the operating area based on an environmental data indicator corresponding to each type of environmental data, and determining a comprehensive probability of occurrence of the disaster in the operating area based on the meteorological data and the probability of occurrence of each type of natural disaster; The overturning moment index of the construction machinery is calculated according to the equipment data and the inclination angle index of the working area.

[0016] As an optional embodiment, in the second aspect of the present invention, the analysis module determines the operation risk level of the engineering machinery according to the environmental data analysis results and the equipment data analysis results through the dynamic model, specifically including: Obtaining a parameter weight set corresponding to the engineering machinery, the parameter weight set including a first weight corresponding to the tilt angle index, a second weight corresponding to the friction coefficient index, a third weight corresponding to the flatness index, a fourth weight corresponding to the comprehensive probability of disaster occurrence, and a fifth weight corresponding to the overturning moment index; Calculating the operation risk of the engineering machinery according to the parameter weight set, the environmental data index corresponding to each type of environmental data, the comprehensive probability of disaster occurrence, the overturning moment index, and a preset operation risk calculation formula, and determining the operation risk level of the engineering machinery according to the operation risk; The operational risk calculation formula includes:

[0017] in, represents the first weight, represents the tilt angle index, represents the second weight, represents the friction coefficient index, represents the third weight, represents the flatness index, represents the fourth weight, P represents the comprehensive probability of the disaster, represents the fifth weight, and M represents the overturning moment index.

[0018] As an optional implementation, in the second aspect of the present invention, the manner in which the first determination module determines the optimal working path of the engineering machinery according to the multimodal data specifically includes: Constructing a grid map of the working area of ​​the engineering machinery based on the multimodal data, the grid map including a plurality of grids and grid parameters of each grid, the grid parameters of each grid including at least slope data, friction coefficient, and obstacle marker corresponding to the grid; determining at least one working path corresponding to the engineering machinery according to the gridded map; Obtaining a parameter coefficient corresponding to each of the grid parameters, and calculating a path cost of each of the working paths based on the grid parameters of each of the grids and the parameter coefficient corresponding to each of the grid parameters; According to the path cost of each working path, an optimal working path of the engineering machine is selected from each working path.

[0019] As an optional implementation, in the second aspect of the present invention, the generation module generates the safety control strategy for the engineering machinery according to the operation risk level and the optimal working path, specifically including: determining whether the operation risk level is greater than a preset first risk level threshold, and generating a risk reminder strategy for the construction machinery when the operation risk level is greater than the first risk level threshold; determining whether the operation risk level is greater than a preset second risk level threshold, and when the operation risk level is greater than the second risk level threshold, determining at least one risky position in the optimal working path, wherein the second risk level threshold is greater than the first risk level threshold; For each risk position, calculating the maximum operating speed and center of gravity adjustment angle of the engineering machinery at the risk position according to the inclination angle index, the friction coefficient index, and the load data corresponding to the risk position; An operation control strategy for the engineering machinery is generated based on the maximum operating speed and the center of gravity adjustment angle corresponding to each risk position, and a safety control strategy for the engineering machinery is generated based on the risk reminder strategy and / or the operation control strategy.

[0020] As an optional embodiment, in the second aspect of the present invention, the device further includes: a prediction module, configured to predict projection information of the engineering machine when operating in the optimal working path, and determine a safety margin of the engineering machine in the optimal working path based on the projection information and slope data of the working area of ​​the engineering machine; a second determining module, configured to determine real-time data of a current position of the engineering machinery in the optimal working path while the generating module controls the operation of the engineering machinery according to the safety control strategy, and adjust the safety margin according to the real-time data to obtain a target safety margin, wherein the real-time data includes wind speed change data and / or load change data; The second determination module is further configured to determine a recommended operating range of the engineering machinery according to the target safety boundary, and to visually display the target safety boundary and the recommended operating range.

[0021] As an optional embodiment, in the second aspect of the present invention, the analysis module calculates the overturning moment index of the engineering machinery based on the equipment data and the inclination angle index of the working area in a manner that specifically includes: Calculating the overturning moment of the engineering machinery according to the load data of the engineering machinery, the center of gravity offset data, the slope inclination angle index of the working area, and a preset overturning moment calculation formula; Acquiring a maximum overturning moment of the engineering machinery, and normalizing the overturning moment of the engineering machinery according to the maximum overturning moment to obtain an overturning moment index of the engineering machinery; The overturning moment calculation formula includes:

[0022] Wherein, W represents the load data, Indicates the center of gravity offset data.

[0023] A third aspect of the present invention discloses another active safety control device for engineering machinery based on multi-parameter analysis, the device comprising: a memory storing executable program code; a processor coupled to the memory; The processor calls the executable program code stored in the memory to execute part or all of the steps in the active safety control method for engineering machinery based on multi-parameter analysis as described in any one of the first aspects of the present invention.

[0024] The fourth aspect of the present invention discloses a computer storage medium, which stores computer instructions. When the computer instructions are called, they are used to execute some or all of the steps in the active safety control method of engineering machinery based on multi-parameter analysis described in any one of the first aspects of the present invention.

[0025] Compared with the prior art, the present invention has the following beneficial effects: In an embodiment of the present invention, multimodal data of the environment in which the construction machinery is located is collected based on a preset multimodal data acquisition device, and a dynamic model of the construction machinery and the environment is constructed based on the multimodal data. The multimodal data is analyzed by the dynamic model to obtain environmental data analysis results and equipment data analysis results. The dynamic model is used to determine the operation risk level of the construction machinery based on the environmental data analysis results and the equipment data analysis results. The optimal working path of the construction machinery is determined based on the multimodal data. A safety control strategy for the construction machinery is generated based on the operation risk level and the optimal working path, and the operation of the construction machinery is controlled according to the safety control strategy. It can be seen that the implementation of the present invention can improve the accuracy and reliability of the assessment of operation risk, reduce the probability of operator error in operating the construction machinery, enhance the accuracy and reliability of the operation of the construction machinery, and thereby improve the operation efficiency, operation stability, and operation safety of the construction machinery. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0027] Figure 1 This is a flow chart of an active safety control method for engineering machinery based on multi-parameter analysis disclosed in an embodiment of the present invention; Figure 2 This is a flow chart of another method for active safety control of engineering machinery based on multi-parameter analysis disclosed in an embodiment of the present invention; Figure 3 This is a schematic structural diagram of an active safety control device for engineering machinery based on multi-parameter analysis disclosed in an embodiment of the present invention; Figure 4 1 is a schematic structural diagram of another active safety control device for engineering machinery based on multi-parameter analysis disclosed in an embodiment of the present invention; Figure 5 This is a structural diagram of another active safety control device for engineering machinery based on multi-parameter analysis disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0028] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0029] The terms "first," "second," and so on, in the description and claims of the present invention and the accompanying drawings are used to distinguish between different items, not to describe a specific order. Furthermore, the terms "including," "having," and any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, apparatus, product, or end comprising a series of steps or elements is not limited to the listed steps or elements but may optionally include steps or elements not listed therein, or may optionally include other steps or elements inherent to such process, method, product, or end.

[0030] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present invention. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute a separate or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0031] The present invention discloses a method and device for active safety control of construction machinery based on multi-parameter analysis. These methods can improve the accuracy and reliability of operational risk assessments, reduce the probability of operator errors in operating construction machinery, enhance the accuracy and reliability of construction machinery operations, and thereby improve the operational efficiency, stability, and safety of construction machinery. These methods are described in detail below.

[0032] Example 1 See also Figure 1 , Figure 1 This is a flow chart of an active safety control method for engineering machinery based on multi-parameter analysis disclosed in an embodiment of the present invention. Figure 1The described method for active safety control of engineering machinery based on multi-parameter analysis can be applied to engineering machinery, and the engineering machinery may include an active safety control device for engineering machinery based on multi-parameter analysis, wherein the active safety control device for engineering machinery based on multi-parameter analysis may include an intelligent device for controlling the engineering machinery, and the intelligent device may include any one of a data acquisition device, an intelligent server, or an intelligent platform, and the intelligent server may include a local server or a cloud server, which is not limited in the embodiment of the present invention. Figure 1 As shown, the active safety control method for engineering machinery based on multi-parameter analysis may include the following operations: 101. Collect multimodal data of the environment in which the construction machinery is located based on the preset multimodal data acquisition equipment, and construct a dynamic model of the construction machinery and the environment based on the multimodal data.

[0033] In an embodiment of the present invention, optionally, the preset multimodal data acquisition device can be a device integrated on the engineering machinery, or a device independently installed in the working area of ​​the engineering machinery. Specifically, the multimodal data acquisition device can include one or more combinations of inertial measurement units (IMUs), lidars, ultrasonic sensors, global navigation satellite systems (GNSSs), angle sensors, weight sensors, infrared sensors, cameras, etc. The multimodal data can include environmental data and equipment data, which is not limited by the present invention.

[0034] 102. Analyze multimodal data through dynamic models to obtain environmental data analysis results and equipment data analysis results, and determine the operation risk level of construction machinery based on the environmental data analysis results and equipment data analysis results through dynamic models.

[0035] In an embodiment of the present invention, optionally, multimodal data can be analyzed through a dynamic model to obtain environmental data analysis results and equipment data analysis results, wherein the environmental data analysis results can reflect the various factors that affect the operational safety of the engineering machinery in the environment in which the engineering machinery is located, and the equipment data analysis results can reflect the safety influencing factors of the engineering machinery itself. The dynamic model can be used to determine the operational risk level of the engineering machinery based on the environmental data analysis results and the equipment data analysis results. The higher the risk level, the lower the operational safety of the engineering machinery, which is not limited by the present invention.

[0036] 103. Determine the optimal working path of construction machinery based on multimodal data.

[0037] In an embodiment of the present invention, optionally, a high-precision map of the working area of ​​the engineering machinery can be constructed based on multimodal data, and then the optimal working path of the engineering machinery can be determined in the high-precision map. The optimal working path has the highest safety while ensuring the operating requirements of the engineering machinery, and the present invention does not limit this.

[0038] 104. Generate a safety control strategy for construction machinery based on the operation risk level and the optimal working path, and control the operation of the construction machinery according to the safety control strategy.

[0039] In an embodiment of the present invention, optionally, the safety control strategy of the engineering machinery may include a risk reminder strategy and / or an operation control strategy. The risk reminder strategy is used to alert the operator of the engineering machinery to related risks, and the operation control strategy is used to control the operation of the engineering machinery, or to assist the operator of the engineering machinery in manipulating the engineering machinery. The present invention does not limit this.

[0040] It can be seen that implementation Figure 1 The described active safety control method for engineering machinery based on multi-parameter analysis can collect multi-modal data of the environment in which the engineering machinery is located based on a preset multi-modal data acquisition device, and construct a dynamic model of the engineering machinery and the environment based on the multi-modal data. The multi-modal data is analyzed through the dynamic model to obtain environmental data analysis results and equipment data analysis results. The dynamic model is used to determine the operation risk level of the engineering machinery based on the environmental data analysis results and the equipment data analysis results, which can improve the accuracy and reliability of the operation risk assessment, determine the optimal working path of the engineering machinery based on the multi-modal data, generate a safety control strategy for the engineering machinery based on the operation risk level and the optimal working path, and control the operation of the engineering machinery based on the safety control strategy, which can reduce the probability of errors in the operation of the engineering machinery by the operator, enhance the operation accuracy and reliability of the engineering machinery, and thereby improve the operation efficiency, operation stability and operation safety of the engineering machinery.

[0041] In an optional embodiment, determining the optimal working path of the engineering machine based on the multimodal data may include the following operations: Constructing a grid map of the working area of ​​the engineering machinery based on the multimodal data, the grid map including a plurality of grids and grid parameters of each grid, the grid parameters of each grid including at least slope data, friction coefficient, and obstacle markers corresponding to the grid; determining at least one working path corresponding to the construction machinery according to the grid map; Obtaining parameter coefficients corresponding to each grid parameter, and calculating the path cost of each working path based on the grid parameters of each grid and the parameter coefficients corresponding to each grid parameter; According to the path cost of each working path, the optimal working path of the construction machinery is selected in each working path.

[0042] In this optional embodiment, optionally, a grid map of the working area of ​​the engineering machinery can be constructed based on the multimodal data. Specifically, a grid map of the working area of ​​the engineering machinery can be constructed based on the terrain 3D point cloud data detected by the lidar, the global coordinate data detected by the GNSS, the posture data of the engineering machinery detected by the IMU, and the obstacle identification data detected by the camera. The grid map includes multiple grids and grid parameters of each grid. The grid parameters of each grid include at least slope data, friction coefficient and obstacle mark corresponding to the grid, wherein the obstacle mark may include fixed obstacle mark and / or temporary obstacle mark. Temporary obstacles may include fallen rocks, unrelated personnel, etc. The grid map may be updated at preset time intervals, and temporary obstacles in the map may be marked as red restricted areas. The preset time may include 200ms, which is not limited in this embodiment.

[0043] In this optional embodiment, at least one working path corresponding to the engineering machinery may be optionally determined based on the grid map, a parameter coefficient corresponding to each grid parameter may be obtained, and a path cost of each working path may be calculated based on the grid parameters of each grid and the parameter coefficient corresponding to each grid parameter. The parameter coefficients may include a first parameter coefficient corresponding to the slope data, a second parameter coefficient corresponding to the friction coefficient, and a third parameter coefficient corresponding to the obstacle marker. The calculation formula of the path cost includes:

[0044] in, represents the first parameter coefficient, represents the second parameter coefficient, Represents the third parameter coefficient, which is not limited in this embodiment.

[0045] In this optional embodiment, optionally, the optimal working path of the engineering machinery can be screened in each working path based on the path cost of each working path. Specifically, the working path with the smallest path cost can be screened as the optimal working path of the engineering machinery, which is not limited in this embodiment.

[0046] It can be seen that the implementation of this optional embodiment can construct a grid map of the working area of ​​the engineering machinery based on multimodal data, determine at least one working path corresponding to the engineering machinery based on the grid map, obtain the parameter coefficient corresponding to each grid parameter, and calculate the path cost of each working path based on the grid parameters of each grid and the parameter coefficient corresponding to each grid parameter. According to the path cost of each working path, the optimal working path of the engineering machinery is screened in each working path. The optimal working path of the engineering machinery can be determined by constructing a grid map and calculating the path cost, thereby improving the accuracy of determining the optimal working path, and at the same time improving the safety and operability of the determined optimal working path.

[0047] Example 2 See also Figure 2 , Figure 2 This is a flow chart of an active safety control method for engineering machinery based on multi-parameter analysis disclosed in an embodiment of the present invention. Figure 2 The described method for active safety control of engineering machinery based on multi-parameter analysis can be applied to engineering machinery, and the engineering machinery may include an active safety control device for engineering machinery based on multi-parameter analysis, wherein the active safety control device for engineering machinery based on multi-parameter analysis may include an intelligent device for controlling the engineering machinery, and the intelligent device may include any one of a data acquisition device, an intelligent server, or an intelligent platform, and the intelligent server may include a local server or a cloud server, which is not limited in the embodiment of the present invention. Figure 2 As shown, the active safety control method for engineering machinery based on multi-parameter analysis may include the following operations: 201. Multimodal data of the environment in which the construction machinery is located is collected based on a preset multimodal data acquisition device, and a dynamic model of the construction machinery and the environment is constructed based on the multimodal data.

[0048] 202. Analyze the environmental data to obtain environmental data indicators corresponding to each type of environmental data.

[0049] In an embodiment of the present invention, the environmental data may optionally include slope data, type data, and flatness data of the working area of ​​the engineering machinery. The environmental data may be analyzed to obtain environmental data indicators corresponding to each type of environmental data. The environmental data analysis results may include the environmental data indicators corresponding to each type of environmental data and the comprehensive probability of disaster occurrence in the working area. Specifically: The slope data can be analyzed to obtain the inclination angle index corresponding to the slope data; The type data can be analyzed to obtain a friction coefficient index corresponding to the type data, wherein the type data can represent the road type data of the engineering machinery operation area, or the type data of the engineering machinery operation object. The type data may include soil type, gravel type, concrete type, etc. The road surface texture data can be collected by lidar and / or camera, and the road surface type data can be identified by combining a machine learning algorithm. Then, the friction coefficient corresponding to the type data is determined based on the correspondence between the type data and the friction coefficient pre-stored in the database. The friction coefficient is then updated based on real-time meteorological data to obtain a friction coefficient index. The flatness data can be analyzed to obtain a flatness index corresponding to the flatness data. Specifically, the standard deviation value of the road surface flatness data in the construction machinery operation area can be calculated based on the inertial measurement unit acceleration data combined with the lidar point cloud analysis as the flatness index corresponding to the flatness data. When the flatness index is greater than a preset flatness threshold, a flatness warning can be triggered. The flatness threshold can be user-defined or determined based on historical data and / or standard operating parameters of construction machinery, for example, 5 cm.

[0050] 203. Obtain meteorological data for the operation area of ​​the construction machinery within a preset time period, determine the probability of occurrence of at least one natural disaster in the operation area based on the environmental data indicators corresponding to each type of environmental data, and determine the comprehensive probability of occurrence of disasters in the operation area based on the meteorological data and the probability of occurrence of each natural disaster.

[0051] In an embodiment of the present invention, optionally, meteorological data of the operating area of ​​the construction machinery within a preset time period can be obtained. The preset time period may include the time period before the current moment when the construction machinery performs construction work (the previous day), and may also include the time period after the current moment (the next day). That is, the meteorological data may include historical meteorological data within the day before the current moment when the construction machinery performs construction work, and may also include predicted meteorological data within the day after the current moment. The present invention does not limit this.

[0052] In an embodiment of the present invention, optionally, the probability of occurrence of at least one natural disaster in the operating area can be determined based on the environmental data indicators corresponding to each type of environmental data. Specifically, the slope cracks and / or loose stones in the operating area can be analyzed and determined based on the environmental data indicators corresponding to the environmental data based on visual sensors, etc., and then the probability of occurrence of natural disasters such as landslides, collapses, mudslides, ground collapse / subsidence in the operating area can be determined. Then, based on the meteorological data and the probability of occurrence of each natural disaster, the comprehensive probability of occurrence of disasters in the operating area can be determined. Specifically, based on the meteorological data, the rainfall, air temperature and humidity and other data in the operating area can be determined, and then the probability of occurrence of at least one natural disaster in the operating area can be updated. The updated probability of occurrence of each natural disaster can be comprehensively calculated to obtain the comprehensive probability of occurrence of disasters in the operating area. The present invention does not limit this.

[0053] 204. Calculate the overturning moment index of the construction machinery based on the equipment data and the inclination angle index of the working area.

[0054] In an embodiment of the present invention, optionally, the equipment data may include the load data and center of gravity offset data of the engineering machinery, and the equipment data analysis results may include an overturning moment index. Specifically, the load data, center of gravity offset data and inclination angle index of the working area of ​​the engineering machinery can be comprehensively calculated to obtain the overturning moment index of the engineering machinery.

[0055] 205. Determine the operational risk level of construction machinery through dynamic models based on the environmental data analysis results and equipment data analysis results.

[0056] 206. Determine the optimal working path of construction machinery based on multimodal data.

[0057] 207. Generate a safety control strategy for construction machinery based on the operation risk level and the optimal working path, and control the operation of the construction machinery according to the safety control strategy.

[0058] In the embodiment of the present invention, for other descriptions of step 201 and steps 205 to 207, please refer to the detailed description of steps 101 to 104 in the first embodiment of the present invention, which will not be repeated in this embodiment of the present invention.

[0059] It can be seen that implementation Figure 2 The described active safety control method for construction machinery based on multi-parameter analysis can collect multimodal data of the construction machinery's environment using a preset multimodal data acquisition device, construct a dynamic model of the construction machinery and its environment based on the multimodal data, analyze the environmental data to obtain environmental data indicators corresponding to each type of environmental data, obtain meteorological data for the construction machinery's operating area within a preset time period, and then determine the comprehensive probability of disasters occurring in the operating area. Based on the equipment data and the tilt angle indicator of the operating area, the overturning moment indicator of the construction machinery is calculated, thereby improving the accuracy and reliability of the environmental data analysis results and the equipment data analysis results of the construction machinery. The dynamic model is used to determine the operation risk level of the construction machinery based on the environmental data analysis results and the equipment data analysis results, thereby improving the accuracy and reliability of the operation risk assessment. The optimal operation path of the construction machinery is determined based on the multimodal data. Based on the operation risk level and the optimal operation path, a safety control strategy for the construction machinery is generated, and the operation of the construction machinery is controlled according to the safety control strategy. This reduces the probability of operator error in operating the construction machinery, enhances the accuracy and reliability of the operation of the construction machinery, and thereby improves the operation efficiency, stability, and safety of the construction machinery.

[0060] In an optional embodiment, determining the operation risk level of the construction machinery based on the environmental data analysis results and the equipment data analysis results through the dynamic model may include the following operations: Obtaining a parameter weight set corresponding to the engineering machinery, the parameter weight set including a first weight corresponding to the tilt angle index, a second weight corresponding to the friction coefficient index, a third weight corresponding to the flatness index, a fourth weight corresponding to the comprehensive probability of disaster occurrence, and a fifth weight corresponding to the overturning moment index; Calculate the operation risk of construction machinery based on the parameter weight set, the environmental data indicators corresponding to each type of environmental data, the comprehensive probability of disaster occurrence, the overturning moment indicator, and the preset operation risk calculation formula, and determine the operation risk level of the construction machinery based on the operation risk; The operational risk calculation formula includes:

[0061] in, represents the first weight, Indicates the tilt angle indicator, represents the second weight, Indicates the friction coefficient index, represents the third weight, Indicates the flatness index, represents the fourth weight, P represents the comprehensive probability of disaster occurrence, represents the fifth weight, and M represents the overturning moment index.

[0062] In this optional embodiment, the parameter weight set corresponding to the engineering machinery may be pre-written into the controller firmware during system initialization. Optionally, the user may modify and adjust the parameter weight set as needed, wherein the parameter weight set may include a first weight corresponding to the tilt angle index, a second weight corresponding to the friction coefficient index, a third weight corresponding to the flatness index, a fourth weight corresponding to the comprehensive probability of disaster occurrence, and a fifth weight corresponding to the overturning moment index. In the operation risk calculation formula, represents the first weight, Indicates the tilt angle indicator, represents the second weight, Indicates the friction coefficient index, represents the third weight, Indicates the flatness index, represents the fourth weight, P represents the comprehensive probability of disaster occurrence, represents the fifth weight, M represents the overturning moment index, and the sum of all weights is equal to 1, that is:

[0063] For example, , , , , , this embodiment does not limit it.

[0064] It can be seen that the implementation of this optional embodiment can obtain the parameter weight set corresponding to the construction machinery, calculate the operation risk of the construction machinery according to the parameter weight set, the environmental data indicators corresponding to each type of environmental data, the comprehensive probability of disaster occurrence, the overturning moment indicator and the preset operation risk calculation formula, and determine the operation risk level of the construction machinery according to the operation risk, thereby improving the accuracy of calculating the operation risk, and then improving the accuracy of determining the operation risk level of the construction machinery, thereby improving the operation safety of the construction machinery.

[0065] In another optional embodiment, generating a safety control strategy for engineering machinery based on the operation risk level and the optimal working path may include the following operations: Determine whether the operation risk level is greater than a preset first risk level threshold, and generate a risk reminder strategy for construction machinery when the operation risk level is greater than the first risk level threshold; determining whether the operation risk level is greater than a preset second risk level threshold, and when the operation risk level is greater than the second risk level threshold, determining at least one risk position in the optimal working path, where the second risk level threshold is greater than the first risk level threshold; For each risk location, calculate the maximum operating speed and center of gravity adjustment angle of the construction machinery at the risk location based on the tilt angle index, friction coefficient index, and load data corresponding to the risk location; An operation control strategy for the construction machinery is generated based on the maximum operating speed and center of gravity adjustment angle corresponding to each risk position, and a safety control strategy for the construction machinery is generated based on the risk reminder strategy and / or the operation control strategy.

[0066] In this optional embodiment, it is optional to determine whether the operation risk level is greater than a preset first risk level threshold value, and the preset first risk level threshold value may include 0.5. When the operation risk level is greater than the first risk level threshold value, a risk reminder strategy for construction machinery is generated. The risk reminder strategy is used to remind users to be alert to risks in a preset reminder method. The preset reminder method may include one or more combinations of sound reminders, light reminders, icon reminders, etc., which are not limited in this embodiment.

[0067] In this optional embodiment, optionally, after the operation risk level is greater than the first risk level threshold, it is possible to continue to determine whether the operation risk level is greater than a preset second risk level threshold. The preset second risk level threshold may include 0.7. When the operation risk level is greater than the second risk level threshold, at least one risk position in the optimal working path may be determined, wherein the risk position may be determined based on environmental data indicators. For example, when the inclination angle index of a certain position in the optimal working path is greater than a preset inclination angle threshold (for example, 15°), the position is determined to be a risk position. When the friction coefficient index of a certain position in the optimal working path is less than the preset friction coefficient threshold, the position is determined to be a risk position. When the flatness index of a certain position in the optimal working path is greater than a preset flatness threshold (for example, 5cm), the position is determined to be a risk position. The second risk level threshold is greater than the first risk level threshold. This is not limited in this embodiment.

[0068] In this optional embodiment, optionally, for each risk position, the maximum operating speed and center of gravity adjustment angle of the engineering machinery at the risk position may be calculated based on the tilt angle index, friction coefficient index, and load data corresponding to the risk position, wherein the calculation formula of the maximum operating speed includes:

[0069] The calculation formula for the center of gravity adjustment angle includes:

[0070] in, Indicates the maximum operating speed of the construction machinery at the nth risk position, Indicates the center of gravity adjustment angle of the construction machinery at the nth risk position, represents the friction coefficient index of the nth risk position, represents the tilt angle index of the nth risk position, and W represents the load data of the construction machinery at the nth risk position; Among them, the center of gravity adjustment angle can be used to adjust the overall center of the construction machinery. When the construction machinery includes excavators, cranes, aerial work platforms and other equipment with load-bearing extension arms such as buckets and hooks, the center of gravity adjustment angle can be used to adjust the angles of load-bearing extension arms such as buckets and hooks to balance the center of gravity of the construction machinery; the operation control strategy of the construction machinery can be generated according to the maximum operating speed and center of gravity adjustment angle corresponding to each risk position, and the safety control strategy of the construction machinery can be generated according to the risk reminder strategy and / or operation control strategy. This is not limited in this embodiment.

[0071] It can be seen that the implementation of this optional embodiment can determine whether the operation risk level is greater than the preset first risk level threshold. When the operation risk level is greater than the first risk level threshold, a risk reminder strategy for the engineering machinery is generated, and whether the operation risk level is greater than the preset second risk level threshold is determined. When the operation risk level is greater than the second risk level threshold, at least one risk position in the optimal working path is determined, and the second risk level threshold is greater than the first risk level threshold. For each risk position, according to the inclination angle index, friction coefficient index and load data corresponding to the risk position, the maximum operating speed and center of gravity adjustment angle of the engineering machinery at the risk position are calculated. According to the maximum operating speed and center of gravity adjustment angle corresponding to each risk position, an operation control strategy for the engineering machinery is generated, and a safety control strategy for the engineering machinery is generated according to the risk reminder strategy and / or the operation control strategy. This can improve the accuracy of the generated safety control strategy, and control the operation of the engineering machinery according to the safety control strategy, which can reduce the probability of error in the operator's operation of the engineering machinery, enhance the operation accuracy and reliability of the engineering machinery, and thereby improve the operation efficiency, operation stability and operation safety of the engineering machinery.

[0072] In yet another optional embodiment, the engineering machinery active safety control method based on multi-parameter analysis may further include the following operations: Predicting the projection information of the construction machinery when operating in the optimal working path, and determining the safety boundary of the construction machinery in the optimal working path based on the projection information and the slope data of the working area of ​​the construction machinery; In the process of controlling the operation of the construction machinery according to the safety control strategy, real-time data of the current position of the construction machinery in the optimal working path is determined, and the safety margin is adjusted according to the real-time data to obtain a target safety margin, the real-time data including wind speed change data and / or load change data; Determine the recommended operating range of construction machinery based on the target safety boundary, and visualize the target safety boundary and recommended operating range.

[0073] In this optional embodiment, the projection information of the engineering machinery when operating in the optimal working path may optionally include the projection information of the tracks of the engineering machinery. Specifically, the track projection information will change dynamically as the posture of the engineering machinery changes. High-precision three-dimensional map data can be provided based on the laser radar to capture the specific position and shape of the tracks. The geographic coordinates of the engineering machinery are given by GNSS for auxiliary positioning. The IMU measures the data of the engineering machinery, including the pitch angle and the tilt angle, and then determines the track projection information of the engineering machinery. The safety boundary of the engineering machinery in the optimal working path can be determined based on the projection information and the slope data of the working area of ​​the engineering machinery. The calculation formula of the safety boundary includes:

[0074] In the process of controlling the operation of engineering machinery according to the safety control strategy, the real-time data of the current position of the engineering machinery in the optimal working path can be determined. The real-time data may include wind speed change data and / or load change data. The safety boundary can be adjusted according to the real-time data to obtain the target safety boundary. For example, when the wind speed is greater than 10m / s, the boundary shrinks by 15%. The recommended operating range of the engineering machinery can be determined based on the target safety boundary, and the target safety boundary and the recommended operating range can be visualized. Specifically, the target safety boundary and the recommended operating range can be marked with different colors, for example, the target safety boundary is marked with a red dotted line and the recommended operating range is marked with a green overlay. The target safety boundary and the recommended operating range can be visualized on the screen in the cockpit of the engineering machinery, or on the smart glasses worn by the driver that are wired or wirelessly connected to the engineering machinery. This is not limited in this embodiment.

[0075] It can be seen that the implementation of this optional embodiment can predict the projection information of the engineering machinery when it is operating in the optimal working path, and determine the safety boundary of the engineering machinery in the optimal working path based on the projection information and the slope data of the working area of ​​the engineering machinery. In the process of controlling the operation of the engineering machinery according to the safety control strategy, the real-time data of the current position of the engineering machinery in the optimal working path is determined, and the safety boundary is adjusted according to the real-time data to obtain the target safety boundary. The recommended operating range of the engineering machinery is determined according to the target safety boundary, and the target safety boundary and the recommended operating range are visualized. Based on the determined safety boundary and operating range, the operator can be guided to operate the engineering machinery, reduce the dependence on the operator's experience, reduce the possibility of operating errors, and improve the operating efficiency, operation stability and operation safety of the engineering machinery.

[0076] In yet another optional embodiment, calculating the overturning moment index of the construction machinery based on the equipment data and the tilt angle index of the working area may include the following operations: Calculate the overturning moment of the construction machinery based on the load data of the construction machinery, the center of gravity offset data, the slope inclination angle index of the working area, and the preset overturning moment calculation formula; Obtaining the maximum overturning moment of the construction machinery, and normalizing the overturning moment of the construction machinery according to the maximum overturning moment to obtain an overturning moment index of the construction machinery; The overturning moment calculation formula includes:

[0077] Where W represents the load data, Indicates the center of gravity offset data.

[0078] In this optional embodiment, the load data of the engineering machinery can be optionally determined by a pressure sensor, etc., and the center of gravity offset data of the engineering machinery can be measured by an IMU. The overturning moment of the engineering machinery can be calculated based on the load data of the engineering machinery, the center of gravity offset data, the slope inclination angle index of the working area, and a preset overturning moment calculation formula. Then, the overturning moment of the engineering machinery is normalized according to the maximum overturning moment to obtain the overturning moment index of the engineering machinery. The maximum overturning moment of the engineering machinery is determined by the physical limit of the engineering machinery. The overturning moment calculation formula of the engineering machinery includes:

[0079] The calculation formula for the overturning moment index of construction machinery includes:

[0080] Where W represents the load data, Indicates the center of gravity offset data. Indicates the maximum overturning moment.

[0081] In this optional embodiment, optionally, when the overturning moment index of the engineering machinery is greater than a preset overturning moment threshold, the risk level of the engineering machinery can be increased by one level, for example, from medium risk to high risk, and the overturning moment threshold can include 0.5, which is not limited in this embodiment.

[0082] It can be seen that the implementation of this optional embodiment can calculate the overturning moment of the engineering machinery based on the load data of the engineering machinery, the center of gravity offset data, the slope inclination angle index of the working area and the preset overturning moment calculation formula, obtain the maximum overturning moment of the engineering machinery, and normalize the overturning moment of the engineering machinery according to the maximum overturning moment to obtain the overturning moment index of the engineering machinery, which can improve the accuracy of determining the overturning moment index of the engineering machinery, and then improve the accuracy of determining the operation risk level of the engineering machinery, and improve the operational safety of the engineering machinery.

[0083] Example 3 See also Figure 3 , Figure 3 This is a schematic diagram of the structure of an active safety control device for engineering machinery based on multi-parameter analysis disclosed in an embodiment of the present invention. Figure 3 The described active safety control device for engineering machinery based on multi-parameter analysis can be applied to engineering machinery. The active safety control device for engineering machinery based on multi-parameter analysis can include an intelligent device for controlling the engineering machinery. The intelligent device can include any one of a data acquisition device, an intelligent server, or an intelligent platform. The intelligent server includes a local server or a cloud server, which is not limited in the embodiment of the present invention. Figure 3As shown, the active safety control device for engineering machinery based on multi-parameter analysis may include: The acquisition module 301 is used to collect multimodal data of the environment in which the construction machinery is located based on a preset multimodal data acquisition device, and to construct a dynamic model of the construction machinery and the environment based on the multimodal data, where the multimodal data includes environmental data and equipment data; An analysis module 302 is configured to analyze the multimodal data using a dynamic model to obtain environmental data analysis results and equipment data analysis results, and determine the operation risk level of the construction machinery based on the environmental data analysis results and the equipment data analysis results using the dynamic model; A first determination module 303 is configured to determine an optimal working path of the construction machinery based on the multimodal data; The generation module 304 is used to generate a safety control strategy for the construction machinery according to the operation risk level and the optimal working path, and control the operation of the construction machinery according to the safety control strategy.

[0084] It can be seen that implementation Figure 3 The described active safety control device for engineering machinery based on multi-parameter analysis can collect multi-modal data of the environment in which the engineering machinery is located based on a preset multi-modal data acquisition device, and construct a dynamic model of the engineering machinery and the environment based on the multi-modal data. The multi-modal data is analyzed through the dynamic model to obtain environmental data analysis results and equipment data analysis results. The dynamic model is used to determine the operation risk level of the engineering machinery based on the environmental data analysis results and the equipment data analysis results, which can improve the accuracy and reliability of the operation risk assessment, determine the optimal working path of the engineering machinery based on the multi-modal data, generate a safety control strategy for the engineering machinery based on the operation risk level and the optimal working path, and control the operation of the engineering machinery based on the safety control strategy, which can reduce the probability of errors in the operation of the engineering machinery by the operator, enhance the operation accuracy and reliability of the engineering machinery, and thereby improve the operation efficiency, operation stability and operation safety of the engineering machinery.

[0085] In an optional embodiment, if Figure 4 As shown, the environmental data includes the slope data, type data, and flatness data of the working area of ​​the engineering machinery; the equipment data includes the load data and center of gravity offset data of the engineering machinery; the environmental data analysis results include the environmental data indicators corresponding to each type of environmental data and the comprehensive probability of disaster occurrence in the working area; the equipment data analysis results include the overturning moment indicator; The analysis module 302 analyzes the multimodal data using a dynamic model to obtain the environmental data analysis results and the device data analysis results in the following specific ways: Analyze the environmental data to obtain environmental data indicators corresponding to each type of environmental data, including an inclination angle indicator corresponding to the slope data, a friction coefficient indicator corresponding to the type data, and a flatness indicator corresponding to the flatness data; Obtaining meteorological data for the operation area of ​​the construction machinery within a preset time period, determining the probability of occurrence of at least one natural disaster in the operation area based on environmental data indicators corresponding to each type of environmental data, and determining a comprehensive probability of occurrence of disasters in the operation area based on the meteorological data and the probability of occurrence of each natural disaster; Calculate the overturning moment index of the construction machinery based on the equipment data and the inclination angle index of the working area.

[0086] It can be seen that implementation Figure 4 The described active safety control device for construction machinery based on multi-parameter analysis can collect multimodal data of the construction machinery's environment using a preset multimodal data acquisition device, construct a dynamic model of the construction machinery and its environment based on the multimodal data, analyze the environmental data to obtain environmental data indicators corresponding to each type of environmental data, obtain meteorological data for the construction machinery's operating area within a preset time period, and thereby determine the comprehensive probability of disasters occurring in the operating area. Based on the equipment data and the tilt angle indicator of the operating area, the overturning moment indicator of the construction machinery is calculated, thereby improving the accuracy and reliability of the environmental data analysis results and the equipment data analysis results of the construction machinery. The dynamic model is used to determine the operation risk level of the construction machinery based on the environmental data analysis results and the equipment data analysis results, thereby improving the accuracy and reliability of the operation risk assessment. The optimal operating path of the construction machinery is determined based on the multimodal data. Based on the operation risk level and the optimal operating path, a safety control strategy for the construction machinery is generated, and the operation of the construction machinery is controlled according to the safety control strategy. This reduces the probability of operator error in operating the construction machinery, enhances the accuracy and reliability of the operation of the construction machinery, and thereby improves the operation efficiency, stability, and safety of the construction machinery.

[0087] In another optional embodiment, Figure 4 As shown, the analysis module 302 determines the operation risk level of the construction machinery based on the environmental data analysis results and the equipment data analysis results through the dynamic model. The specific method includes: Obtaining a parameter weight set corresponding to the engineering machinery, the parameter weight set including a first weight corresponding to the tilt angle index, a second weight corresponding to the friction coefficient index, a third weight corresponding to the flatness index, a fourth weight corresponding to the comprehensive probability of disaster occurrence, and a fifth weight corresponding to the overturning moment index; Calculate the operation risk of construction machinery based on the parameter weight set, the environmental data indicators corresponding to each type of environmental data, the comprehensive probability of disaster occurrence, the overturning moment indicator, and the preset operation risk calculation formula, and determine the operation risk level of the construction machinery based on the operation risk; The operational risk calculation formula includes:

[0088] in, represents the first weight, Indicates the tilt angle indicator, represents the second weight, Indicates the friction coefficient index, represents the third weight, Indicates the flatness index, represents the fourth weight, P represents the comprehensive probability of disaster occurrence, represents the fifth weight, and M represents the overturning moment index.

[0089] It can be seen that implementation Figure 4 The described active safety control device for engineering machinery based on multi-parameter analysis can obtain a parameter weight set corresponding to the engineering machinery, calculate the operation risk of the engineering machinery according to the parameter weight set, the environmental data indicators corresponding to each environmental data, the comprehensive probability of disaster occurrence, the overturning moment indicator and the preset operation risk calculation formula, and determine the operation risk level of the engineering machinery according to the operation risk, thereby improving the accuracy of calculating the operation risk, and further improving the accuracy of determining the operation risk level of the engineering machinery, thereby improving the operation safety of the engineering machinery.

[0090] In another optional embodiment, Figure 4 As shown, the specific manner in which the first determining module 303 determines the optimal working path of the engineering machinery according to the multimodal data includes: Constructing a grid map of the working area of ​​the engineering machinery based on the multimodal data, the grid map including a plurality of grids and grid parameters of each grid, the grid parameters of each grid including at least slope data, friction coefficient, and obstacle markers corresponding to the grid; determining at least one working path corresponding to the construction machinery according to the grid map; Obtaining parameter coefficients corresponding to each grid parameter, and calculating the path cost of each working path based on the grid parameters of each grid and the parameter coefficients corresponding to each grid parameter; According to the path cost of each working path, the optimal working path of the construction machinery is selected in each working path.

[0091] It can be seen that implementation Figure 4The described active safety control device for engineering machinery based on multi-parameter analysis can construct a grid map of the working area of ​​the engineering machinery according to multimodal data, determine at least one working path corresponding to the engineering machinery according to the grid map, obtain the parameter coefficient corresponding to each grid parameter, and calculate the path cost of each working path according to the grid parameters of each grid and the parameter coefficient corresponding to each grid parameter. According to the path cost of each working path, the optimal working path of the engineering machinery is screened in each working path. The optimal working path of the engineering machinery can be determined by constructing the grid map and calculating the path cost, thereby improving the accuracy of determining the optimal working path and improving the safety and operability of the determined optimal working path.

[0092] In another optional embodiment, Figure 4 As shown, the specific manner in which the generation module 304 generates the safety control strategy for the engineering machinery according to the operation risk level and the optimal working path includes: Determine whether the operation risk level is greater than a preset first risk level threshold, and generate a risk reminder strategy for construction machinery when the operation risk level is greater than the first risk level threshold; determining whether the operation risk level is greater than a preset second risk level threshold, and when the operation risk level is greater than the second risk level threshold, determining at least one risk position in the optimal working path, where the second risk level threshold is greater than the first risk level threshold; For each risk location, calculate the maximum operating speed and center of gravity adjustment angle of the construction machinery at the risk location based on the tilt angle index, friction coefficient index, and load data corresponding to the risk location; An operation control strategy for the construction machinery is generated based on the maximum operating speed and center of gravity adjustment angle corresponding to each risk position, and a safety control strategy for the construction machinery is generated based on the risk reminder strategy and / or the operation control strategy.

[0093] It can be seen that implementation Figure 4The described active safety control device for engineering machinery based on multi-parameter analysis can determine whether the operation risk level is greater than a preset first risk level threshold. When the operation risk level is greater than the first risk level threshold, a risk reminder strategy for the engineering machinery is generated, and whether the operation risk level is greater than a preset second risk level threshold is determined. When the operation risk level is greater than the second risk level threshold, at least one risk position in the optimal working path is determined, and the second risk level threshold is greater than the first risk level threshold. For each risk position, the maximum operating speed and center of gravity adjustment angle of the engineering machinery at the risk position are calculated based on the inclination angle index, friction coefficient index and load data corresponding to the risk position. Based on the maximum operating speed and center of gravity adjustment angle corresponding to each risk position, an operation control strategy for the engineering machinery is generated, and a safety control strategy for the engineering machinery is generated based on the risk reminder strategy and / or the operation control strategy. This can improve the accuracy of the generated safety control strategy, and control the operation of the engineering machinery based on the safety control strategy, which can reduce the probability of error in the operator's operation of the engineering machinery, enhance the operation accuracy and reliability of the engineering machinery, and thereby improve the operation efficiency, operation stability and operation safety of the engineering machinery.

[0094] In another optional embodiment, Figure 4 As shown, the engineering machinery active safety control device based on multi-parameter analysis may further include: Prediction module 305, used to predict the projection information of the construction machine when operating in the optimal working path, and determine the safety boundary of the construction machine in the optimal working path based on the projection information and the slope data of the working area of ​​the construction machine; A second determining module 306 is configured to determine real-time data of the current position of the construction machinery in the optimal working path during the process of the generating module 304 controlling the operation of the construction machinery according to the safety control strategy, and adjust the safety margin based on the real-time data to obtain a target safety margin, wherein the real-time data includes wind speed change data and / or load change data; The second determining module 306 is further configured to determine a recommended operating range of the engineering machinery according to the target safety margin, and to visually display the target safety margin and the recommended operating range.

[0095] It can be seen that implementation Figure 4The described active safety control device for engineering machinery based on multi-parameter analysis can predict the projection information of the engineering machinery when operating in the optimal working path, and determine the safety boundary of the engineering machinery in the optimal working path based on the projection information and the slope data of the working area of ​​the engineering machinery. In the process of controlling the operation of the engineering machinery according to the safety control strategy, the real-time data of the current position of the engineering machinery in the optimal working path is determined, and the safety boundary is adjusted according to the real-time data to obtain the target safety boundary. The recommended operating range of the engineering machinery is determined according to the target safety boundary, and the target safety boundary and the recommended operating range are visualized. Based on the determined safety boundary and operating range, the visual display can guide the operator to operate the engineering machinery, reduce the dependence on the operator's experience, reduce the possibility of operating errors, and improve the operating efficiency, operation stability and operation safety of the engineering machinery.

[0096] In another optional embodiment, Figure 4 As shown, the specific method for the analysis module 302 to calculate the overturning moment index of the construction machinery based on the equipment data and the tilt angle index of the working area includes: Calculate the overturning moment of the construction machinery based on the load data of the construction machinery, the center of gravity offset data, the slope inclination angle index of the working area, and the preset overturning moment calculation formula; Obtaining the maximum overturning moment of the construction machinery, and normalizing the overturning moment of the construction machinery according to the maximum overturning moment to obtain an overturning moment index of the construction machinery; The overturning moment calculation formula includes:

[0097] Where W represents the load data, Indicates the center of gravity offset data.

[0098] It can be seen that implementation Figure 4 The described active safety control device for engineering machinery based on multi-parameter analysis can calculate the overturning moment of the engineering machinery based on the load data of the engineering machinery, the center of gravity offset data, the slope inclination angle index of the working area and the preset overturning moment calculation formula, obtain the maximum overturning moment of the engineering machinery, and normalize the overturning moment of the engineering machinery according to the maximum overturning moment to obtain the overturning moment index of the engineering machinery. It can improve the accuracy of determining the overturning moment index of the engineering machinery, thereby improving the accuracy of determining the operation risk level of the engineering machinery and improving the operational safety of the engineering machinery.

[0099] Example 4 See also Figure 5 , Figure 5This is a schematic diagram of the structure of another active safety control device for engineering machinery based on multi-parameter analysis disclosed in an embodiment of the present invention. Figure 5 As shown, the active safety control device for engineering machinery based on multi-parameter analysis may include: A memory 401 storing executable program code; a processor 402 coupled to the memory 401; The processor 402 calls the executable program code stored in the memory 401 to execute the steps of the active safety control method for engineering machinery based on multi-parameter analysis described in the first embodiment of the present invention or the second embodiment of the present invention.

[0100] Example 5 An embodiment of the present invention discloses a computer storage medium, which stores computer instructions. When the computer instructions are called, they are used to execute some or all of the steps in any one of the active safety control methods for engineering machinery based on multi-parameter analysis disclosed in the first embodiment of the present invention.

[0101] Example 6 An embodiment of the present invention discloses a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to enable a computer to execute the steps of the active safety control method of engineering machinery based on multi-parameter analysis described in Example 1 or Example 2.

[0102] The device embodiments described above are merely illustrative, wherein the modules described as separate components may or may not be physically separate, and the components shown as modules may or may not be physical modules, i.e., they may be located in one place or distributed across multiple network modules. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Those skilled in the art can understand and implement the present invention without inventive effort.

[0103] Through the detailed description of the above embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, or of course, by means of hardware. Based on this understanding, the above technical solution, in essence, or the portion that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as a read-only memory (ROM), a random access memory (RAM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a one-time programmable read-only memory (OTPROM), an electronically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM), or other optical disk storage, magnetic disk storage, magnetic tape storage, or any other computer-readable medium capable of carrying or storing data.

[0104] Finally, it should be noted that the active safety control method and device for engineering machinery based on multi-parameter analysis disclosed in the embodiment of the present invention only discloses a preferred embodiment of the present invention, which is only used to illustrate the technical solution of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, ordinary technicians in this field should understand that it is still possible to modify the technical solutions recorded in the aforementioned embodiments, or to make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. An active safety control method for engineering machinery based on multi-parameter analysis, characterized in that: The method comprises: Collecting multimodal data of the environment in which the construction machinery is located based on a preset multimodal data acquisition device, and constructing a dynamic model of the construction machinery and the environment based on the multimodal data, wherein the multimodal data includes environmental data and equipment data; Analyzing the multimodal data using the dynamic model to obtain an environmental data analysis result and an equipment data analysis result, and determining an operation risk level of the engineering machinery based on the environmental data analysis result and the equipment data analysis result using the dynamic model; determining an optimal working path of the engineering machinery according to the multimodal data; A safety control strategy for the engineering machinery is generated according to the operation risk level and the optimal working path, and the operation of the engineering machinery is controlled according to the safety control strategy.

2. The active safety control method for engineering machinery based on multi-parameter analysis according to claim 1 is characterized in that: The environmental data includes slope data, type data, and flatness data of the working area of ​​the engineering machinery; the equipment data includes load data and center of gravity offset data of the engineering machinery; the environmental data analysis results include environmental data indicators corresponding to each type of environmental data and a comprehensive probability of disaster occurrence in the working area; and the equipment data analysis results include an overturning moment indicator; The multimodal data is analyzed by the dynamic model to obtain environmental data analysis results and equipment data analysis results, including: Analyzing the environmental data to obtain environmental data indicators corresponding to each type of environmental data, the environmental data indicators including an inclination angle indicator corresponding to the slope data, a friction coefficient indicator corresponding to the type data, and a flatness indicator corresponding to the flatness data; Obtaining meteorological data for an operating area of ​​the engineering machinery within a preset time period, determining a probability of occurrence of at least one natural disaster in the operating area based on an environmental data indicator corresponding to each type of environmental data, and determining a comprehensive probability of occurrence of the disaster in the operating area based on the meteorological data and the probability of occurrence of each type of natural disaster; The overturning moment index of the construction machinery is calculated according to the equipment data and the inclination angle index of the working area.

3. The active safety control method for engineering machinery based on multi-parameter analysis according to claim 2 is characterized in that: Determining the operation risk level of the engineering machinery according to the environmental data analysis result and the equipment data analysis result by the dynamic model includes: Obtaining a parameter weight set corresponding to the engineering machinery, the parameter weight set including a first weight corresponding to the tilt angle index, a second weight corresponding to the friction coefficient index, a third weight corresponding to the flatness index, a fourth weight corresponding to the comprehensive probability of disaster occurrence, and a fifth weight corresponding to the overturning moment index; Calculating the operation risk of the engineering machinery according to the parameter weight set, the environmental data index corresponding to each type of environmental data, the comprehensive probability of disaster occurrence, the overturning moment index, and a preset operation risk calculation formula, and determining the operation risk level of the engineering machinery according to the operation risk; The operational risk calculation formula includes: in, represents the first weight, represents the tilt angle index, represents the second weight, represents the friction coefficient index, represents the third weight, represents the flatness index, represents the fourth weight, P represents the comprehensive probability of the disaster, represents the fifth weight, and M represents the overturning moment index.

4. The active safety control method for construction machinery based on multi-parameter analysis according to any one of claims 1 to 3, characterized in that: Determining the optimal working path of the engineering machinery according to the multimodal data includes: Constructing a grid map of the working area of ​​the engineering machinery based on the multimodal data, the grid map including a plurality of grids and grid parameters of each grid, the grid parameters of each grid including at least slope data, friction coefficient, and obstacle marker corresponding to the grid; determining at least one working path corresponding to the engineering machinery according to the gridded map; Obtaining a parameter coefficient corresponding to each of the grid parameters, and calculating a path cost of each of the working paths based on the grid parameters of each of the grids and the parameter coefficient corresponding to each of the grid parameters; According to the path cost of each working path, an optimal working path of the engineering machine is selected from each working path.

5. The active safety control method for engineering machinery based on multi-parameter analysis according to claim 2 or 3, characterized in that: Generating a safety control strategy for the engineering machinery according to the operation risk level and the optimal working path includes: determining whether the operation risk level is greater than a preset first risk level threshold, and generating a risk reminder strategy for the construction machinery when the operation risk level is greater than the first risk level threshold; determining whether the operation risk level is greater than a preset second risk level threshold, and when the operation risk level is greater than the second risk level threshold, determining at least one risky position in the optimal working path, wherein the second risk level threshold is greater than the first risk level threshold; For each risk position, calculating the maximum operating speed and center of gravity adjustment angle of the engineering machinery at the risk position according to the inclination angle index, the friction coefficient index, and the load data corresponding to the risk position; An operation control strategy for the engineering machinery is generated based on the maximum operating speed and the center of gravity adjustment angle corresponding to each risk position, and a safety control strategy for the engineering machinery is generated based on the risk reminder strategy and / or the operation control strategy.

6. The active safety control method for engineering machinery based on multi-parameter analysis according to claim 2 or 3, characterized in that: The method further comprises: Predicting projection information of the engineering machine when operating in the optimal working path, and determining a safety boundary of the engineering machine in the optimal working path based on the projection information and slope data of the working area of ​​the engineering machine; In the process of controlling the operation of the engineering machinery according to the safety control strategy, real-time data of a current position of the engineering machinery in the optimal working path is determined, and the safety margin is adjusted according to the real-time data to obtain a target safety margin, wherein the real-time data includes wind speed change data and / or load change data; A recommended operating range of the engineering machinery is determined according to the target safety margin, and the target safety margin and the recommended operating range are visually displayed.

7. The active safety control method for engineering machinery based on multi-parameter analysis according to claim 2 or 3, characterized in that: Calculating the overturning moment index of the construction machinery according to the equipment data and the inclination angle index of the working area includes: Calculating the overturning moment of the engineering machinery according to the load data of the engineering machinery, the center of gravity offset data, the slope inclination angle index of the working area, and a preset overturning moment calculation formula; Acquiring a maximum overturning moment of the engineering machinery, and normalizing the overturning moment of the engineering machinery according to the maximum overturning moment to obtain an overturning moment index of the engineering machinery; The overturning moment calculation formula includes: Wherein, W represents the load data, Indicates the center of gravity offset data.

8. An active safety control device for engineering machinery based on multi-parameter analysis, characterized in that: The device comprises: An acquisition module is configured to acquire multimodal data of the environment in which the construction machinery is located based on a preset multimodal data acquisition device, and to construct a dynamic model of the construction machinery and the environment based on the multimodal data, wherein the multimodal data includes environmental data and equipment data; an analysis module, configured to analyze the multimodal data using the dynamic model to obtain an environmental data analysis result and an equipment data analysis result, and determine an operation risk level of the engineering machinery based on the environmental data analysis result and the equipment data analysis result using the dynamic model; a first determining module, configured to determine an optimal working path of the engineering machine according to the multimodal data; A generation module is used to generate a safety control strategy for the engineering machinery according to the operation risk level and the optimal working path, and control the operation of the engineering machinery according to the safety control strategy.

9. An active safety control device for engineering machinery based on multi-parameter analysis, characterized in that: The device comprises: a memory storing executable program code; a processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the active safety control method for engineering machinery based on multi-parameter analysis as described in any one of claims 1 to 7.

10. A computer storage medium, characterized in that The computer storage medium stores computer instructions, and when the computer instructions are called, they are used to execute the active safety control method for engineering machinery based on multi-parameter analysis as described in any one of claims 1 to 7.

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