A Big Data-Based Early Warning System for Excavator Safety Operation

Abstract

This invention belongs to the technical field of predicting the safe operation of construction machinery. It proposes a big data-based early warning system for excavator safety operation, comprising: a 3D excavator model creation module for creating 3D models of the excavator and its components; a 3D working environment model creation module for creating 3D models of the excavator's working environment; a climate condition simulation module for conducting climate condition simulation experiments of the working environment to obtain the operating status of the excavator and its components under different climate conditions; a model import and alignment module for synchronously importing and aligning the excavator 3D model and the working environment 3D model to an AR 3D model; a real-time data integration module; and an early warning threshold setting module for constructing an early warning model for excavator safety operation and setting early warning thresholds and rules. This invention solves the problem of the difficulty in comprehensively analyzing the impact of changes in climate parameters such as temperature, humidity, and wind speed on the operating status of excavators.

Description

Technical Field

[0001] This invention belongs to the technical field of predicting the safe operation of construction machinery, and relates to an early warning system for the safe operation of excavators based on big data. Background Technology

[0002] With the accelerated pace of modernization, excavators, as key equipment in engineering construction, are increasingly valued for their operational safety. This safety is crucial not only for project progress and quality but also, more importantly, for the personal safety of construction workers. In actual operation, excavators face complex and variable working environments and weather conditions, which can pose potential threats to their safe operation. For example, environmental factors such as terrain undulations, landform features, and obstacle distribution, as well as climatic conditions such as temperature, humidity, and wind speed, all pose potential threats to their safe operation and may affect their work efficiency and safety.

[0003] Climate conditions are a crucial factor affecting the safe operation of excavators. Changes in climate parameters such as temperature, humidity, and wind speed can significantly impact the operating status of excavators. High temperatures can cause excavator engines to overheat and hydraulic systems to fail, while excessive humidity can affect the electrical systems and insulation performance of components. Furthermore, severe weather conditions such as strong winds and heavy rain can increase the difficulty and safety risks of operating excavators.

[0004] Based on the aforementioned problems, existing methods for monitoring the safe operation of excavators are no longer sufficient to meet the growing demands for construction safety. There is an urgent need for a safety operation early warning system that can comprehensively consider the excavator, its working environment, and climatic conditions. This system needs to be able to accurately create a three-dimensional model of the excavator and its working environment, acquire and analyze the excavator's operating status, working environment data, and climatic condition data in real time, and comprehensively analyze the impact of changes in temperature, humidity, and wind speed climatic parameters on the excavator's operating status. This will allow for the timely detection of potential safety hazards and the implementation of corresponding early warning measures to ensure the safe operation of the excavator. Summary of the Invention

[0005] To address the problem of the difficulty in comprehensively analyzing the impact of changes in climate parameters such as temperature, humidity, and wind speed on the operating status of excavators, this invention provides an excavator safety operation early warning system based on big data.

[0006] A big data-based early warning system for the safe operation of excavators includes: a 3D model building module for excavators, a 3D model building module for the working environment, a climate condition simulation module, a model import and alignment module, a real-time data integration module, and an early warning threshold setting module.

[0007] The excavator 3D model creation module is used to create 3D models of the excavator and its components, and to obtain the operating status of the excavator and its components.

[0008] The working environment 3D model building module is used to create a 3D model of the excavator's working environment and obtain real-time data on the terrain and landforms within the excavator's working environment.

[0009] The climate condition simulation module is used for climate condition simulation experiments of the working environment to obtain the operating status of the excavator and its components under different climate conditions.

[0010] The model import and alignment module is used to synchronously import and align the excavator 3D model and the working environment 3D model to the AR 3D model.

[0011] The real-time data integration module is used for cleaning, integrating, and standardizing the collected data.

[0012] The warning threshold setting module is used to construct an early warning model for the safe operation of excavators and to set warning thresholds and warning rules.

[0013] Preferably, the system further includes: a graphical display and interaction optimization module;

[0014] The graphical display and interactive optimization module is used to display the excavator safety operation warning signals in the AR 3D model to the operator and manager, and specifically includes: a graphical display unit and an interactive optimization unit;

[0015] The graphical display unit distinguishes different types of obstacles by setting different colors or icons, and uses different colors to distinguish the excavator and its components, and displays the warning information graphically on the three-dimensional model of the working environment.

[0016] The interactive optimization unit allows for adjusting the transparency of the AR 3D model, provides multiple viewpoint switching functions, and offers visual, auditory, and tactile feedback.

[0017] Preferably, the excavator 3D model building module includes:

[0018] High-precision scanning technologies, including 3D laser scanning and structured light scanning, are used to scan the excavator and its various components.

[0019] Import the scanned data into a 3D modeling tool to build a 3D model of the excavator;

[0020] Real-time data of key components of the excavator is collected and transmitted to the real-time data integration and dynamic tagging module.

[0021] Preferably, the working environment 3D model building module includes:

[0022] A three-dimensional model of the excavator's working environment was constructed using geographic information systems and remote sensing technology.

[0023] Different types of obstacles are assigned different colors or icons;

[0024] Elevation data of terrain and landforms are collected, and the elevation data is transmitted to the real-time data integration and dynamic labeling module.

[0025] Preferably, the climate condition simulation module includes:

[0026] By utilizing meteorological forecasting services and geographic information system technology, we can efficiently integrate and collect climate condition data to obtain key climate parameters for the working environment.

[0027] The key climate parameters of the working environment are imported into the three-dimensional model of the working environment to simulate the climate conditions of the working environment.

[0028] Preferably, the model import and alignment module includes:

[0029] Import the 3D model of the excavator and the 3D model of the working environment into a 3D engine or software platform;

[0030] Align with the ground or with a reference point to ensure the excavator 3D model and the working environment 3D model are correctly positioned and scaled in virtual space;

[0031] Accurate colliders are added to the 3D model of the excavator and the 3D model of the working environment, so that the collision detection logic is highly matched with the actual shape of the model;

[0032] The geometry and mesh optimization of AR 3D models create a virtual environment that is both realistic and highly interactive.

[0033] Preferably, the early warning threshold setting module incorporates the degree of aging of the excavator and its components, as well as humidity, into the temperature early warning threshold formula:

[0034] T warn =T max -ΔT-(A×Y)-(H×C H )

[0035] Among them, T warn It is the temperature warning threshold; T max ΔT is the highest temperature at which the excavator can safely operate under standard conditions; ΔT is the safety margin; A represents the coefficient of the excavator's aging on its temperature tolerance; Y is the number of years of use or maintenance records of the excavator; H is the coefficient of the effect of humidity on the excavator's heat dissipation effect; C H This is the current humidity value.

[0036] Preferably, the warning threshold setting module includes terrain and wind direction in the wind speed warning threshold formula:

[0037] V warn =V safe ×k-(T E ×ΔV E )-(D×ΔV D )

[0038] Among them, V warn It is the wind speed warning threshold; V safe It is the maximum wind speed at which an excavator can operate safely under standard conditions; k is a safety factor; T E It is the coefficient of the effect of terrain obstruction on wind speed; ΔV E It is the reduction in wind speed caused by terrain obstruction; D is the angle between the wind direction and the excavator's working direction; ΔV D It is the quantity by which changes in wind direction affect wind speed stability.

[0039] Preferably, the early warning threshold setting module includes a comprehensive early warning formula that takes into account multiple environmental factors:

[0040] w warn =w T ×f T (T)+w V ×f V (V)+w H ×f H (H)+w E ×f E (E)+C TV ×f TV (T,V)+C TH ×f TH (T,H)

[0041] Among them, w warn Indicates the comprehensive early warning value; w T w V w H w E These are the weighting coefficients for temperature, wind speed, humidity, and terrain, respectively; f T (T), f V (V), f H (H), f E (E) are nonlinear functions of temperature, wind speed, humidity, and topography, respectively;

[0042] T, V, H, and E are the current values ​​of temperature, wind speed, humidity, and terrain, respectively; C TV C TH These are the interaction coefficients between temperature and wind speed, and between temperature and humidity; f TV (T,V), fTH (T,H) are the interaction functions between temperature and wind speed, and temperature and humidity, respectively.

[0043] Preferably, the graphical display and interaction optimization module includes: displaying the warning information to operators and managers through an AR 3D model via multiple channels including wearable devices and mobile apps.

[0044] In summary, the present invention has the following beneficial technical effects:

[0045] 1. This invention constructs a highly detailed three-dimensional model of the excavator and its working environment, encompassing not only key operating parameters such as engine temperature, hydraulic system pressure, and travel speed, but also taking into account changes in the working environment, such as soil hardness, terrain slope, obstacle location, and climate conditions. Through real-time data integration and early warning threshold setting, the system can quickly identify any anomalies or potential safety hazards. This real-time monitoring and early warning mechanism greatly improves the operational safety of the excavator and reduces the probability of accidents.

[0046] 2. Utilizing advanced AR (Augmented Reality) technology, this invention synchronously imports and aligns the excavator's 3D model and the working environment's 3D model into a brand-new AR 3D model. This technology provides operators with an intuitive and accurate visual reference, enabling them to clearly see the excavator's specific position, posture, and working range within the working environment. This intuitiveness not only improves operator efficiency but also reduces operational difficulty and the risk of misoperation.

[0047] 3. This invention combines big data analytics and machine learning algorithms to deeply mine and analyze the collected data. By processing and analyzing the excavator's operational data, the system can identify potential fault modes and abnormal behaviors of the excavator and take early warning measures. This early warning system based on big data analytics and machine learning algorithms not only improves the intelligence level of early warnings but also enhances their accuracy. Attached Figure Description

[0048] Figure 1 This is a publicly available framework diagram of a big data-based early warning system for the safe operation of excavators. Detailed Implementation

[0049] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0050] The following is in conjunction with the appendix Figure 1 A preferred description of the present invention is provided below.

[0051] See appendix Figure 1 As shown, the present invention proposes a big data-based excavator safety operation early warning system, which can achieve accurate modeling and safety early warning of excavators and their components, operating environment, and climate conditions. Utilizing a brand-new AR 3D model, it provides operators with intuitive and accurate visual references and safety early warning information, thereby improving the safety operation level of excavators.

[0052] This excavator safety operation early warning system based on big data includes: an excavator 3D model creation module, a working environment 3D model creation module, a climate condition simulation module, a model import and alignment module, a real-time data integration module, an early warning threshold setting module, and a graphical display and interactive optimization module.

[0053] The climate condition simulation module is connected to the three-dimensional model of the working environment;

[0054] The excavator 3D model creation module and the working environment 3D model creation module are respectively connected to the model import and alignment module;

[0055] The model import and alignment module is connected to the real-time data integration module; the real-time data integration module is connected to the early warning threshold setting module; and the early warning threshold setting module is connected to the graphical display and interaction optimization module.

[0056] The excavator 3D model building module is used to create 3D digital models of the excavator and its components, and to obtain the operating status of the excavator and its components.

[0057] Specifically, high-precision scanning technologies such as 3D laser scanning and structured light scanning are used to perform comprehensive and high-precision scanning of the excavator and its various components. These technologies can capture the minute details and complex structures of the excavator and its components, ensuring that the excavator and its components are completely recorded.

[0058] Import the scanned data into professional 3D modeling tools, such as AutoCAD or SolidWorks, to accurately model each part of the excavator and ensure that the 3D model is highly consistent with the actual excavator.

[0059] A sensor network, including temperature sensors, pressure sensors, and speed sensors, is constructed to collect real-time data (e.g., temperature, humidity) of the excavator and its components, including the engine compartment, hydraulic system, and transmission system. The real-time data is then transmitted to the real-time data integration and dynamic labeling module, and the real-time data is presented intuitively through visualization methods such as sectional views and exploded views.

[0060] The working environment 3D model building module is used to create a 3D digital model of the excavator's working environment and obtain real-time data on the terrain and landforms within the excavator's operating area.

[0061] Specifically, using GIS (Geographic Information System) and remote sensing technology, precise terrain and landform modeling is carried out for the excavator's operating area, including the rolling hills, meandering rivers, crisscrossing roads, and other complex details of the natural and man-made environment.

[0062] Elevation data is acquired using GIS (Geographic Information System) and remote sensing technology, then processed to generate a 3D terrain model. This model realistically reproduces the terrain undulations and landform features of the work site, providing operators with an intuitive visual reference.

[0063] The 3D terrain model marks various obstacles in the excavator's working area, such as trees, utility poles, and buildings, distinguishing them by different colors or icons. Combined with the dynamic monitoring capabilities of remote sensing technology, the model updates real-time terrain and landform data to ensure its accuracy and timeliness.

[0064] The elevation data of the terrain and landforms collected in real time are transmitted to the real-time data integration and dynamic labeling module.

[0065] The climate condition simulation module is used for climate condition simulation experiments of the working environment to obtain the operating status of the excavator and its components under different climate conditions.

[0066] Specifically, by leveraging current advanced technologies, including professional forecasting services from meteorological observatories and Geographic Information System (GIS) technology, climate condition data can be efficiently integrated and collected in real time; key climate parameters for the work site, including temperature, humidity, and wind speed, can be obtained through weather forecasting systems, providing a data foundation for the early warning information release and feedback module.

[0067] To visually represent the climate conditions of the work environment, climate data is imported into a 3D model of the work environment to dynamically reflect changes in climate elements such as temperature, humidity, and wind speed, simulating the climate conditions of the work environment and helping operators understand the climate conditions of the work environment.

[0068] Based on current advanced technologies, including professional forecasting services from meteorological stations and Geographic Information System (GIS) technology, climate conditions are updated in real time, and the three-dimensional model of the working environment can dynamically adjust the simulation results of climate conditions.

[0069] The model import and alignment module is used to synchronously import and align the excavator 3D model and the working environment 3D model to a brand new AR 3D model.

[0070] The excavator 3D model and the working environment 3D model are synchronously imported and aligned to the new AR 3D model, including the following steps:

[0071] S1. Model import process: Ensure that the selected 3D engine or software platform is compatible with and can handle the original formats of the two models, and import the excavator 3D model and the working environment 3D model into the 3D engine or software platform.

[0072] If there are incompatibilities in the original format of the model, it is necessary to use a professional format conversion tool for preprocessing to ensure that the model can be imported successfully.

[0073] S2. Model alignment operation: Use the alignment tools provided by the 3D engine or software, such as: align to the ground, align to a reference point, etc., to ensure that the position and scale of the excavator 3D model and the working environment 3D model are correct in virtual space.

[0074] Further fine-tuning allows for manual adjustment of the model's position, rotation angle, and scaling ratio, enabling seamless integration between models through precise operations and ensuring the realism and immersion of the virtual environment.

[0075] S3, Collision Detection and Performance Optimization

[0076] 1. Add collision detection to the excavator 3D model and the working environment 3D model to add accurate colliders (including but not limited to cuboids, spheres and polygon meshes) to ensure that the collision detection logic is highly matched with the actual shape of the model, thereby improving detection accuracy and avoiding abnormal interactions between virtual objects;

[0077] 2. Optimize collision detection by improving the model's geometry and mesh, such as simplifying unnecessary details and merging similar vertices to reduce computational burden and improve rendering efficiency; and adjust the sensitivity parameters of collision detection appropriately to avoid false positives or false negatives caused by excessive sensitivity.

[0078] S4. Construct a brand new AR 3D model

[0079] After completing all the above steps, import the excavator 3D model and the working environment 3D model simultaneously and align them precisely to the new AR 3D model to form a virtual environment that is both realistic and interactive.

[0080] The real-time data integration module is used to clean, integrate, and standardize the collected data, and to perform in-depth mining and analysis using big data analysis and machine learning algorithms.

[0081] Specifically, the real-time data of the excavator and its key components (e.g., temperature, humidity), the elevation data of the terrain and landforms, and the climate condition data collected need to be cleaned, integrated, and standardized.

[0082] By applying big data analytics and machine learning algorithms, the integrated data is deeply mined and analyzed to identify potential failure modes and abnormal behaviors of excavators.

[0083] The warning threshold setting module is used to construct an early warning model for the safe operation of excavators and set reasonable warning thresholds and rules.

[0084] Based on historical and real-time data, an early warning model for excavator safe operation is constructed, and reasonable early warning thresholds and rules are set, as shown in the following formula:

[0085] 1. Temperature warning threshold formula (considering the aging of the excavator and its components, as well as the influence of humidity)

[0086] Excavators and their components age over time, reducing their tolerance to high temperatures. Humidity also affects the heat dissipation of the excavator and its components. Therefore, the degree of equipment aging (expressed as years of use or maintenance records) and humidity are incorporated into the temperature warning threshold formula:

[0087] T warn =T max -ΔT-(A×Y)-(H×C H )

[0088] Among them, T warn It is the temperature warning threshold; T max It is the highest temperature at which the excavator can operate safely under standard conditions; ΔT is the safety margin; A represents the coefficient of the excavator's aging effect on its temperature tolerance (which can be determined through experiments or data analysis);

[0089] Y represents the excavator's years of use or maintenance records (expressed in a quantitative way); H is the coefficient of humidity's influence on the excavator's heat dissipation (determined through experiments or data analysis); C H This is the current humidity value (expressed as a percentage).

[0090] For example, considering the impact of equipment aging on temperature tolerance and the effect of humidity on heat dissipation, we set the following temperature warning threshold formula:

[0091] Twarn = 80℃ - 10℃ - (0.5℃ / year × Y) - (0.02 × C) H (×80℃)

[0092] Assume T warn This is the temperature warning threshold; 80℃ is the highest temperature at which the excavator can safely operate under standard conditions; 10℃ is the safety margin; 0.5℃ / year represents the coefficient of the excavator's aging effect on temperature tolerance (assuming a decrease of 0.5℃ per year); Y represents the number of years the excavator has been in use; 0.02 represents the coefficient of humidity effect on the excavator's heat dissipation effect (assuming that for every 1% increase in humidity, the heat dissipation effect decreases by 0.02 times); C H This is the current humidity value (expressed as a percentage).

[0093] 2. Wind speed warning threshold formula (considering the influence of terrain and wind direction)

[0094] Wind speed warnings are not only related to wind speed magnitude but are also affected by terrain and wind direction. In complex terrain, wind speed may decrease due to terrain obstruction, and changes in wind direction may affect the stability of excavators. Terrain and wind direction can be incorporated into the wind speed warning threshold formula:

[0095] V warn =V safe ×k-(T E ×ΔV E )-(D×ΔV D )

[0096] Among them, V warn It is the wind speed warning threshold; V safe It is the maximum wind speed at which an excavator can operate safely under standard conditions; k is a safety factor; T E It is the coefficient of the effect of terrain obstruction on wind speed (which can be determined through terrain analysis or experiments);

[0097] ΔV E ΔV is the reduction in wind speed caused by terrain obstruction; D is the angle (in degrees) between the wind direction and the excavator's working direction; ΔV D It is the quantity that affects wind speed stability by changes in wind direction (which can be determined through experiments or data analysis, and is usually related to the angle and the wind speed).

[0098] For example, taking into account the impact of terrain obstruction and changes in wind direction on wind speed, we set the following formula for wind speed warning threshold:

[0099] V warn = 20m / s × 0.8 - (0.1m / s / degree × θ) E ×V actual )-(0.05m / s / degree×V actual )

[0100] Assume V warn θ is the wind speed warning threshold; 20 m / s is the maximum wind speed at which an excavator can safely operate under standard conditions; 0.8 is a safety factor (assuming the actual safe wind speed is 80% of the maximum wind speed); 0.1 m / s / degree is the coefficient for the influence of terrain obstruction on wind speed (for every 1 degree increase in terrain obstruction, the wind speed decreases by 0.1 m / s); E It is the angle of terrain obstruction (in degrees); V actual 1 is the current actual wind speed; 0.05 m / s / degree is the coefficient of the influence of wind direction change on wind speed stability (assuming that for every 1 degree increase in the angle between the wind direction and the working direction, the wind speed stability decreases by 0.05 m / s); D is the angle between the wind direction and the excavator's working direction (in degrees).

[0101] For example, assuming the current equipment has been in use for 5 years, the humidity is 80%, the actual wind speed is 15 m / s, the terrain obstruction angle is 30 degrees, and the angle between the wind direction and the working direction is 45 degrees, substitute these values ​​into the temperature warning threshold formula and the wind speed warning threshold formula:

[0102] Temperature warning threshold: T warn = 80℃ - 10℃ - (0.5℃ / year × 5 years) - (0.02 × 80% × 80℃) = 66℃

[0103] Wind speed warning threshold: V warn = 20m / s × 0.8 - (0.1m / s / degree × 30° × 15m / s) - (0.05m / s / degree × 15m / s × 45°) = 8.25m / s

[0104] Therefore, the calculated temperature warning threshold for the excavator is 66℃, and the wind speed warning threshold for the working environment is 8.25m / s. If the actual temperature of the excavator exceeds 66℃ or the actual wind speed in the environment exceeds 8.25m / s, the warning system will automatically generate a warning message.

[0105] 3. Comprehensive early warning formula (considering the nonlinear relationships and interactions of multiple factors)

[0106] To comprehensively consider the impact of various environmental factors (such as temperature, wind speed, humidity, terrain, and wind direction) on excavator operation safety, a comprehensive early warning formula is established. This formula considers the nonlinear relationships and interactions between various factors and satisfies the following equation:

[0107] w warn =w T ×f T (T)+w V ×f V (V)+w H ×fH (H)+w E ×f E (E)+C TV ×f TV (T,V)+C TH ×f TH (T,H)

[0108] Among them, w warn Indicates the comprehensive early warning value; w T w V w H w E These are the weighting coefficients for temperature, wind speed, humidity, and terrain, respectively; f T (T), f V (V), f H (H), f E (E) are nonlinear functions of temperature, wind speed, humidity, and topography, respectively;

[0109] T, V, H, and E are the current values ​​of temperature, wind speed, humidity, and terrain, respectively; C TV C TH These are the interaction coefficients between temperature and wind speed, and between temperature and humidity; f TV (T,V), f TH (T,H) are the interaction functions between temperature and wind speed, and temperature and humidity, respectively.

[0110] For example, an excavator operates in a mountainous area where the working environment is complex and changeable. To assess the safety of the working environment, we established the following comprehensive early warning formula, setting the weight coefficients, nonlinear functions, and interaction coefficients for each factor, satisfying the following formula:

[0111] w T =0.3, w V =0.25, w H =0.2, w E =0.25 (weighting coefficient);

[0112] (Temperature nonlinear function, assuming the maximum safe temperature is 50℃);

[0113] (Wind speed nonlinear function, assuming the maximum safe wind speed is 20m / s, and considering the square effect of wind speed);

[0114] (Humidity nonlinear function, assuming the optimal humidity is 30% and the maximum safe humidity is 100% and linear interpolation);

[0115] (The terrain is a nonlinear function. It is assumed that the impact of the terrain blocking angle E on safety is an S-shaped curve, with a maximum blocking angle of 90 degrees, but it is simplified to 45 degrees as the center point here.)

[0116] G TV =0.05, C TH =0.03 (interaction coefficient);

[0117] (The interaction function between temperature and wind speed, assuming that their influence is linear);

[0118] (Temperature and humidity interaction function, assuming that the combined effect of high temperature and high humidity is greater, but only begins to be considered when humidity exceeds 50%).

[0119] For example, suppose the current environmental factors are: temperature T = 40℃, wind speed V = 15m / s, humidity H = 60%, and terrain obstruction angle E = 30°; substitute these values ​​into the comprehensive early warning formula:

[0120] w warn =0.3×0.8+0.25×0.5625+0.2×0.4286+0.25×0.6225+0.05×0.6+0.03×0.02=0.6525

[0121] Therefore, assuming the preset comprehensive warning threshold is 0.7, the calculated comprehensive warning value of the excavator is 0.6525, which is lower than the threshold. Therefore, the warning system will not generate a warning message. This indicates that the current working environment is relatively safe and work can continue.

[0122] If the value of one or more environmental factors changes, causing the overall warning value to exceed the preset threshold, the warning system will automatically generate a warning message to remind operators to pay attention to work safety and take corresponding measures to reduce risks.

[0123] The graphical display and interactive optimization module is used to present the excavator safety operation warning signals in the new AR 3D model to operators and managers.

[0124] Specifically, it includes:

[0125] 1. Graphical display unit

[0126] In the 3D model of the work environment, obstacles such as trees, utility poles, and buildings are identified and marked in the work area through image processing technology. Different types of obstacles are distinguished by different colors or icons, and warning information is displayed in a graphical way in the 3D model of the work environment, such as danger areas marked with red borders and avoidance paths indicated by arrows.

[0127] In the 3D model of the excavator, different colors are used to distinguish the excavator and its various parts. Based on real-time data and early warning rules, potential danger areas are dynamically marked in the new AR 3D model to improve the readability of the model.

[0128] Through wearable devices, mobile apps, and other channels, early warning information is pushed to operators and managers in real time using a brand-new AR 3D model.

[0129] 2. Interaction Optimization Unit

[0130] A1. Allows operators to adjust the transparency of the 3D model so that the external environment is not obscured when observing the internal structure, achieving a visual effect that considers both the internal and external aspects.

[0131] A2. Provides multiple perspective switching functions, such as first-person perspective and third-person perspective, so that the operator can observe the excavator's operating status and working environment from different angles. Whether it is the immersive first-person perspective or the overall third-person perspective, the operator can easily switch between them to gain a more comprehensive understanding of the situation on site.

[0132] A3. During the interaction, visual, auditory, and tactile feedback is provided, such as a successful operation prompt sound and a change in the model's color, so that the operator can confirm the operation result. These feedback methods together constitute a multi-dimensional interactive experience.

[0133] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A big data-based early warning system for the safe operation of excavators, characterized in that, include: The module includes: excavator 3D model creation module, working environment 3D model creation module, climate condition simulation module, model import and alignment module, real-time data integration module, and early warning threshold setting module. The excavator 3D model creation module is used to create 3D models of the excavator and its components, and to obtain the operating status of the excavator and its components. The working environment 3D model building module is used to create a 3D model of the excavator's working environment and obtain real-time data on the terrain and landforms within the excavator's working environment. The climate condition simulation module is used for climate condition simulation experiments of the working environment to obtain the operating status of the excavator and its components under different climate conditions. The model import and alignment module is used to synchronously import and align the excavator 3D model and the working environment 3D model to the AR 3D model. The real-time data integration module is used for cleaning, integrating, and standardizing the collected data. The warning threshold setting module is used to construct an early warning model for the safe operation of excavators and to set warning thresholds and warning rules. The warning threshold setting module incorporates the degree of aging of the excavator and its components, as well as humidity, into the temperature warning threshold formula: ； in, It is the temperature warning threshold; It is the highest temperature at which an excavator can operate safely under standard conditions; It is a safety margin; A coefficient representing the effect of excavator aging on temperature tolerance; It refers to the excavator's years of use or maintenance records; It is the coefficient that reflects the effect of humidity on the excavator's heat dissipation effect; This is the current humidity value; The warning threshold setting module includes terrain and wind direction in the wind speed warning threshold formula: ； in, It is the wind speed warning threshold; This is the maximum wind speed at which an excavator can operate safely under standard conditions; It is a safety factor; It is the coefficient of the effect of terrain obstruction on wind speed; This is the reduction in wind speed caused by terrain obstruction; It is the angle between the wind direction and the excavator's operating direction; It is the quantity that affects wind speed stability due to changes in wind direction; The warning threshold setting module includes a comprehensive warning formula that takes into account multiple environmental factors. ； in, This indicates the overall early warning value; These are the weighting coefficients for temperature, wind speed, humidity, and terrain, respectively. These are nonlinear functions of temperature, wind speed, humidity, and terrain, respectively. , , , These are the current values ​​for temperature, wind speed, humidity, and terrain, respectively. , These are the interaction coefficients between temperature and wind speed, and between temperature and humidity, respectively. , These are the interaction functions between temperature and wind speed, and temperature and humidity, respectively.

2. The excavator safety operation early warning system based on big data according to claim 1, characterized in that, The system also includes: a graphical display and interaction optimization module; The graphical display and interactive optimization module is used to display the excavator safety operation warning signals in the AR 3D model to the operator and manager, and specifically includes: a graphical display unit and an interactive optimization unit; The graphical display unit distinguishes different types of obstacles by setting different colors or icons, and uses different colors to distinguish the excavator and its components, and displays the warning information graphically on the three-dimensional model of the working environment. The interactive optimization unit allows for adjusting the transparency of the AR 3D model, provides multiple viewpoint switching functions, and offers visual, auditory, and tactile feedback.

3. The excavator safety operation early warning system based on big data according to claim 1, characterized in that, The excavator 3D model building module includes: High-precision scanning technologies, including 3D laser scanning and structured light scanning, are used to scan the excavator and its various components. Import the scanned data into a 3D modeling tool to build a 3D model of the excavator; Real-time data of key components of the excavator is collected and transmitted to the real-time data integration and dynamic tagging module.

4. The excavator safety operation early warning system based on big data according to claim 3, characterized in that, The working environment 3D model creation module includes: A three-dimensional model of the excavator's working environment was constructed using geographic information systems and remote sensing technology. Different types of obstacles are assigned different colors or icons; Elevation data of terrain and landforms are collected, and the elevation data is transmitted to the real-time data integration and dynamic labeling module.

5. The excavator safety operation early warning system based on big data according to claim 4, characterized in that, The climate condition simulation module includes: By utilizing meteorological forecasting services and geographic information system technology, we can efficiently integrate and collect climate condition data to obtain key climate parameters for the working environment. The key climate parameters of the working environment are imported into the three-dimensional model of the working environment to simulate the climate conditions of the working environment.

6. The excavator safety operation early warning system based on big data according to claim 5, characterized in that, The model import and alignment module includes: Import the 3D model of the excavator and the 3D model of the working environment into a 3D engine or software platform; Align with the ground or with a reference point to ensure the excavator 3D model and the working environment 3D model are correctly positioned and scaled in virtual space; Accurate colliders are added to the 3D model of the excavator and the 3D model of the working environment, so that the collision detection logic is highly matched with the actual shape of the model; The geometry and mesh optimization of AR 3D models create a virtual environment that is both realistic and highly interactive.

7. The excavator safety operation early warning system based on big data according to claim 2, characterized in that, The graphical display and interactive optimization module includes: displaying warning information to operators and managers through AR 3D models via multiple channels including wearable devices and mobile apps.

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