Wind power safety situation awareness method and system for complex terrain hoisting operation

Abstract

The invention provides a wind power safety situation sensing method and system for complex terrain hoisting operation. The method comprises the steps that S1, wind speed and wind direction data collected by a plurality of monitoring nodes distributed in an operation area and real-time position data of a mobile operation vehicle are obtained; s2, on the basis of topographic data and the monitoring data, through wind field reconstruction processing, reconstructed wind field data covering the whole domain and including three-dimensional space wind field distribution and high-risk area information is generated; s3, performing dynamic space association and fusion on the reconstructed wind field data and the vehicle position to generate safety situation information; and judging an early warning condition based on the information and a preset warning rule, and sending early warning information to the vehicle in real time when the condition is met. According to the invention, the transformation from local monitoring to full-field dynamic sensing and from post-event alarm to pre-warning is realized, the problems of inaccurate wind field sensing and pre-warning lagging in complex terrains are solved, and the safety decision-making capability and active defense level of hoisting operation are remarkably improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of engineering safety monitoring and meteorological information, and particularly relates to a wind power safety situation awareness method and system for complex terrain hoisting operation. BACKGROUND

[0002] Landfills are usually located in valleys or low-lying areas, and the terrain conditions lead to complex and variable wind field environment, which is prone to vortex, gust and other non-steady wind flow. In the operation site such as fly ash solidification body landfill, various devices and personnel such as hoisting, vehicle transportation and personnel command are involved in cross operation, and the operation risk is highly concentrated. Especially in the hoisting link, in order to ensure the smooth hoisting of ton bags and other materials, the instantaneous wind power and change trend must be accurately monitored, so as to effectively avoid risks and ensure operation safety. However, the current wind power monitoring technology applied in such site has obvious shortcomings, which is difficult to meet the safety management needs in complex environment, and the main problems are as follows: 1. Single function, lack of comprehensive analysis ability: most of the existing wind power monitoring devices have limited functions, such as only providing instantaneous wind speed or wind direction measurement data. For example, the Chinese patent application with publication number CN221726063U discloses a wind power determinator, which lacks the ability of deep analysis and comprehensive judgment on the wind power change trend, especially for the complex wind field characteristics caused by the terrain such as valley (such as sudden increase of gust, rapid switching of wind direction, etc.), and cannot fully reflect the actual wind environment risk of the operation surface.

[0003] 2. Weak early warning ability, mainly passive response: the current technology mainly stays at the level of passive display of monitoring data in "process", such as intuitively displaying the current wind power level through the on-site display screen. Although this method has a certain prompting effect, it cannot actively predict the wind power change trend in the short term, and cannot establish an effective early warning linkage mechanism with key operation equipment such as crane, so as to prevent risks in advance.

[0004] 3. Insufficient scene adaptability, measurement deviation: general wind power measuring instruments are not optimized or corrected for wind field mode in special terrain such as valley. The installation position and measurement principle may cause significant deviation between the obtained data and the actual wind load condition of the operation equipment such as crane boom, reducing the pertinence and reliability of the monitoring data. Although the Chinese patent application with publication number CN110077972A discloses a crane and its wind resistance processing method and system, the method associates wind load with crane working condition, but its core still depends on the real-time feedback of crane sensors, which is essentially a "after" or "in-process" compensation adjustment strategy, and does not solve the core problem of predicting future wind field changes in advance to guide "in-advance" active risk avoidance.

[0005] 4. Lack of deployment flexibility and limited visibility: Most existing on-site wind monitoring devices are fixed in place, with relatively fixed and conspicuous locations. When hoisting personnel or equipment move or change direction, it may be impossible to continuously and conveniently observe the monitoring information, resulting in the interruption of critical wind condition information transmission. The monitoring device cannot play an effective safety warning role at all times during dynamic operations.

[0006] In summary, existing wind monitoring technologies are insufficient to effectively meet the safety production management needs of landfills in complex terrain and high-risk, cross-operation scenarios, which require precise wind field perception, trend prediction, proactive early warning, and flexible deployment. Summary of the Invention

[0007] The technical problem to be solved by this invention is: In view of the technical problems existing in the prior art, this invention provides a wind safety situation perception method and system for hoisting operations in complex terrain, aiming to realize the transformation from local monitoring to dynamic perception of the whole field, and from post-event alarm to pre-event warning, solving the problems of inaccurate wind field perception and delayed warning in complex terrain, and significantly improving the safety decision-making ability and active defense level of hoisting operations.

[0008] To solve the above-mentioned technical problems, the technical solution proposed by this invention is as follows: A wind-driven safety situation awareness method for hoisting operations in complex terrain includes the following steps: Step S1: Obtain wind speed and direction data collected by multiple monitoring nodes distributed throughout the work area, as well as real-time location data of mobile work vehicles within the work area. Step S2: Based on the terrain data of the work area and the wind speed and direction data collected by the multiple monitoring nodes, wind field reconstruction processing is performed to generate reconstructed wind field data covering the work area, which includes three-dimensional spatial wind field distribution information and high-risk wind field area information. Step S3: Perform dynamic spatial correlation and fusion processing on the reconstructed wind field data and the real-time location data of the mobile operation vehicle to generate safety situation information for real-time safety decision-making; make judgments based on the safety situation information and preset warning rules, and when the warning conditions are met, generate and send warning information to the mobile operation vehicle in real time.

[0009] As a further improvement to the method of the present invention: in step S2, the wind field reconstruction process includes: The Kriging interpolation algorithm is used to spatially interpolate the wind speed and wind direction data collected by the multiple monitoring nodes to obtain the initial three-dimensional wind field of the digital elevation model covering the working area. The initial three-dimensional wind field is matched and queried with a pre-built benchmark wind database to output a reconstructed three-dimensional spatial wind field distribution; the benchmark wind database contains three-dimensional benchmark wind field data obtained by high-precision computational fluid dynamics simulation based on the digital elevation model.

[0010] As a further improvement to the method of the present invention: the matching query processing uses the initial three-dimensional wind field as the query vector to retrieve the closest benchmark wind field data in the benchmark wind database, and generates the reconstructed three-dimensional spatial wind field distribution based on the retrieval results.

[0011] As a further improvement to the method of the present invention: in step S3, generating security situation information for real-time security decision-making includes: On the visual map interface of the work area, the three-dimensional spatial wind field distribution is visualized and rendered in the form of a dynamic flow field. The identified high-risk wind field areas are marked in a graphical manner that distinguishes them from safe areas; the visual attributes of the graphical markings of the high-risk wind field areas are dynamically adjusted according to the current threat level of the mobile operation vehicle based on the high-risk areas. The real-time location of mobile work vehicles is displayed as dynamic icons overlaid on the same visual map interface.

[0012] As a further improvement to the method of the present invention: in step S3, the warning rule includes: Distance warning rule: When the horizontal distance between the mobile work vehicle and the boundary of the high-risk wind field area is determined to be less than or equal to a first preset distance threshold, an early warning is triggered; Wind speed and direction composite warning rule: Based on the position of the mobile operation vehicle relative to the wind field and the current wind speed, a warning is triggered when the vehicle is determined to be downwind and the wind speed is greater than or equal to the first wind speed threshold, or when the vehicle is determined to be upwind and the wind speed is greater than or equal to the second wind speed threshold; the first wind speed threshold is greater than the second wind speed threshold.

[0013] As a further improvement to the method of the present invention: the triggering of the early warning includes: sending an early warning signal to the mobile work vehicle to trigger its audible and visual alarm device; for early warnings triggered by the wind speed and wind direction composite warning rule, the early warning signal is configured to drive the audible and visual alarm device to generate an alarm prompt that is different from the early warning triggered by the distance warning rule.

[0014] As a further improvement to the method of the present invention: In step S1, the monitoring node collects wind speed data through a mechanical centrifugal force grading triggering device. The mechanical centrifugal force grading triggering device includes a rotating shaft driven by a wind cup and metal balls with increasing weight arranged circumferentially along the rotating shaft. Each metal ball is fixed by an elastic constraint and corresponds to an independent circuit contact. When the wind speed reaches the preset level, the centrifugal force generated by the rotation overcomes the elastic constraint force of the corresponding metal ball, causing it to shift radially and connect the corresponding circuit, thereby outputting a binary coded signal that uniquely corresponds to the current wind speed level.

[0015] This invention also includes a wind-powered safety situation awareness system for hoisting operations in complex terrain, used to implement the above method, comprising: The data acquisition and transmission module is a wind sensor network consisting of multiple monitoring nodes distributed in the work area, used to collect wind speed and wind direction data at the location. The vehicle positioning unit is used to acquire real-time location data of mobile work vehicles within the work area; The data processing and wind field reconstruction module includes a central processing unit for receiving the wind speed, wind direction data, real-time location data, and terrain data of the work area; based on the terrain data and wind speed and wind direction data from multiple monitoring points, it generates reconstructed wind field data covering the work area and containing three-dimensional spatial wind field distribution information and high-risk wind field area information through a wind field reconstruction algorithm. The safety situation fusion and early warning module includes: a situation fusion unit for dynamically spatially associating and fusing reconstructed wind field data with real-time location data of mobile operation vehicles to generate safety situation information; an early warning judgment unit for judging based on safety situation information and preset warning rules, and generating early warning instructions when early warning conditions are met; and an early warning execution and interaction module for receiving early warning instructions and executing early warning responses via an on-board terminal installed on the mobile operation vehicle.

[0016] The present invention also provides a computer-readable storage medium storing a computer program / instructions programmed or configured to execute the wind safety situational awareness method for hoisting operations in complex terrain via a processor.

[0017] The present invention also provides a computer program product, including a computer program / instruction, which is programmed or configured to execute the wind safety situational awareness method for hoisting operations in complex terrain via a processor.

[0018] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. This invention acquires data from multiple distributed monitoring nodes within the operational area and reconstructs the wind field based on terrain data. This transforms sparse, discrete single-point wind condition observation data into a continuous three-dimensional spatial wind field distribution map covering the entire operational area. This completely changes the limitation of existing technologies that can only provide instantaneous wind speed and direction at individual points. It enables a holistic and structured analysis and understanding of non-uniform and unsteady wind fields (such as eddies and acceleration zones) caused by terrain disturbances, thereby solving the core cognitive problem of operators being unable to see or understand the overall wind field.

[0019] 2. This invention dynamically spatially correlates and fuses the reconstructed full-field wind field data with the real-time location data of mobile operating vehicles, and performs early warning judgments based on the safety situation information generated from this. This marks an upgrade of the early warning logic from "static alarms" that rely on a single, fixed-point wind speed threshold to "dynamic correlation early warnings" that simultaneously consider the dynamic wind field structure and the real-time location relationship of mobile vehicles. The system can proactively determine the relative situation between vehicles and high-risk wind field areas, thereby achieving early risk prediction and targeted intervention, and has made significant progress in the initiative, accuracy, and timeliness of early warnings.

[0020] 3. This invention constructs a complete information processing and decision support chain, from multi-source data acquisition to overall situation reconstruction and fusion-based early warning. The final early warning information delivered to the work vehicles is generated based on safety situation information that integrates the overall wind farm situation and the precise location of the vehicles. It is a highly contextualized safety decision-making basis that can be directly used to guide operations. This fundamentally changes the traditional disconnect between monitoring information, vehicle location, and command instructions, upgrading the backend "information display" to the frontend "situation-driven decision-making," significantly improving the efficiency and reliability of safety risk response in complex and dynamic operating environments. Attached Figure Description

[0021] Figure 1 This is a flowchart of a wind safety situation awareness method for hoisting operations in complex terrain, as described in an embodiment of the present invention.

[0022] Figure 2 This is a schematic diagram of the structural principle of the wind force measuring device (i.e., the mechanical graded trigger wind speed sensor) in an embodiment of the present invention.

[0023] Figure 3 This is a schematic diagram illustrating the structural principle of the wind direction measuring device (i.e., potentiometer-type wind direction sensor) in an embodiment of the present invention.

[0024] Figure 4 This is a schematic diagram of the arrangement of monitoring nodes in a typical valley-type landfill operation area according to an embodiment of the present invention.

[0025] Figure 5This is a schematic diagram of the security situation generated and displayed on the vehicle terminal in an embodiment of the present invention. Detailed Implementation

[0026] 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 a part of the embodiments of the present invention, and not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0027] like Figure 1 As shown in the figure, this embodiment provides a wind safety situation awareness method for hoisting operations in complex terrain, including the following steps: Step S1: Obtain wind speed and direction data collected by multiple monitoring nodes distributed throughout the work area, as well as real-time location data of mobile work vehicles within the work area.

[0028] In this embodiment, the monitoring node collects wind speed data through a mechanical centrifugal force grading triggering device. The mechanical centrifugal force grading triggering device includes a rotating shaft driven by a wind cup and metal balls with increasing weight arranged circumferentially along the rotating shaft. Each metal ball is fixed by an elastic constraint and corresponds to an independent circuit contact. When the wind speed reaches the preset level, the centrifugal force generated by the rotation overcomes the elastic constraint force of the corresponding metal ball, causing it to shift radially and connect the corresponding circuit, thereby outputting a binary coded signal that uniquely corresponds to the current wind speed level.

[0029] like Figure 2 As shown, in a specific application embodiment, a network consisting of multiple fixed monitoring nodes is deployed in the work area. Specifically, one monitoring node is set at each of the four high points in the four cardinal directions (east, south, west, and north) approximately 50 meters outside the landfill area, and above the rest area in the center of the landfill. Each node is equipped with a wind speed measuring device, a wind direction measuring device, and a positioning module for real-time collection and uploading of wind speed, wind direction, and timestamp data. The wind speed measuring device employs a mechanical graded triggering principle, and its interior contains six metal balls of progressively increasing weight, each corresponding to a specific wind speed level; for example... Figure 3 As shown, when the incoming wind speed reaches the corresponding level, the generated kinetic energy will drive the corresponding metal ball to move and connect an independent circuit, thereby outputting a graded electrical signal representing the current wind speed level. Figure 4As shown, the wind direction measuring device employs a potentiometer-type sensing principle. The rotation of the wind vane causes its sliding pointer to move on a ring-shaped resistive element. The changing resistance value is obtained through a measuring circuit, and the real-time wind direction angle is calculated based on a pre-calibrated resistance-angle relationship curve. The spatial coordinates of each node are determined by total station measurement and entered into the system as positioning data. Simultaneously, the system acquires the GPS positioning information of the hoisting cranes in the work area in real time through an IoT interface, thereby synchronously aggregating static node monitoring data and dynamic vehicle location information to the central processing unit.

[0030] Step S2: Based on the terrain data of the work area and the wind speed and direction data collected by multiple monitoring nodes, wind field reconstruction processing is performed to generate reconstructed wind field data covering the work area, which includes three-dimensional spatial wind field distribution information and high-risk wind field area information.

[0031] In this embodiment, the wind field reconstruction process includes: The Kriging interpolation algorithm was used to spatially interpolate the wind speed and direction data collected by multiple monitoring nodes to obtain the initial three-dimensional wind field of the digital elevation model covering the working area. The initial three-dimensional wind field is matched and queried with a pre-built benchmark wind database to output a reconstructed three-dimensional spatial wind field distribution; the benchmark wind database contains three-dimensional benchmark wind field data obtained by high-precision computational fluid dynamics simulation based on the digital elevation model.

[0032] In this embodiment, the matching query processing uses the initial three-dimensional wind field as the query vector to retrieve the closest benchmark wind field data in the benchmark wind database, and generates the reconstructed three-dimensional spatial wind field distribution based on the retrieval results.

[0033] This embodiment adopts an "offline pre-calculation - online intelligent matching" architecture: First, during the system deployment phase, using the digital elevation model (DEM) of the work area as the sole physical boundary condition, a high-resolution three-dimensional benchmark wind field covering various typical wind direction and speed combinations is pre-calculated through high-precision computational fluid dynamics (CFD) simulation, and a benchmark wind database is constructed. During online real-time operation, the system uses the preliminary three-dimensional wind field generated by Kriging interpolation of the field monitoring data as the query condition, and performs rapid intelligent matching and comparison with the benchmark wind database; through efficient retrieval and similarity analysis, the three-dimensional wind field that best matches the current situation is obtained directly from the database or after light interpolation correction; using the DEM as the unified computing domain, the time-consuming CFD solution process is transformed into a millisecond-level database query operation, thereby achieving near real-time wind field reconstruction with a second-level response while ensuring physical rationality.

[0034] In a more specific application embodiment, the multi-node data collected in step S1 is uploaded to the central processing unit. The central processing unit has a pre-set digital elevation model (DEM) of the work area as the basic terrain data. The DEM is a three-dimensional digital map composed of numerous data points containing horizontal coordinates (x, y) and elevation (z), capable of accurately reconstructing the terrain undulations of the site. Based on this DEM and real-time acquired wind speed and direction data, the central processing unit performs wind field reconstruction. The reconstruction process first employs the Kriging interpolation algorithm. Kriging is a statistical method based on spatial autocorrelation—that is, the closer things are, the more similar they are—and by quantifying the changes in this correlation, it provides an optimal, unbiased estimate for unknown points. ,in The value of a known point. This is the weight assigned to each known point. The unbiasedness of the Kriging method is reflected in the fact that the sum of all weights is 1. This ensures that the estimated value is free from systematic bias, and that optimality is reflected in the estimated value. Compared with the true value Find the optimal set of weights that minimizes the variance of the difference and satisfies the above conditions. This method can interpolate wind speed and direction data from discrete monitoring points to generate a continuous initial wind field covering the operational area.

[0035] Subsequently, based on this initial wind field and DEM terrain boundary, a pre-built lightweight computational fluid dynamics (CFD) model was invoked to solve the flow field. Computational fluid dynamics (CFD) primarily describes fluid motion based on the laws of mass and momentum conservation. The lightweight CFD model reasonably simplifies the complete CFD, with mass conservation manifested as a continuity equation. The conservation of momentum is embodied in the Navier-Stokes equations. .in, The density of air varies with time and space in high-speed wind fields. V represents the velocity vector, usually expressed as V = (u, v, w). • Represents the divergence operator, used to measure the fluid flux flowing out of an infinitesimally small volume. p represents the pressure gradient force, which is the driving force that drives wind to flow from a high-pressure area to a low-pressure area. μ 2 V represents viscous force, which is the shear stress that hinders fluid movement due to the viscosity of air. By solving these equations, the model can simulate the disturbance effect of terrain on airflow, thereby reconstructing a detailed three-dimensional spatial wind field distribution in the operational area and automatically identifying high-risk areas such as vortex zones (where air rotation is significant) and wind speed acceleration zones.

[0036] In practice, the nodes continuously collect data and send it to the central processing server. The server uses the as-built measurement data to generate a DEM as a static background and can dynamically update it according to the actual work surface elevation (e.g., backfilled to 110 meters). A processing framework built with Python is used, and Kriging interpolation is implemented with the help of libraries such as SciPy. Then, lightweight CFD simulation is run using OpenFOAM software to finally complete the reconstruction of the three-dimensional dynamic wind field and the identification of risk areas.

[0037] Step S3: Perform dynamic spatial correlation and fusion processing on the reconstructed wind field data and the real-time location data of the mobile operation vehicle to generate safety situation information for real-time safety decision-making; make judgments based on the safety situation information and preset warning rules, and when the warning conditions are met, generate and send warning information to the mobile operation vehicle in real time.

[0038] like Figure 5 As shown, in this embodiment, the security situation information for real-time security decision-making is generated by rendering it on a visual map interface of the work area. Specifically, this includes: On the visual map interface of the work area, the three-dimensional spatial wind field distribution is visualized and rendered in the form of dynamic flow field. High-risk wind field areas are identified and marked in a graphical manner that distinguishes them from safe areas; the visual attributes of the graphical markings of high-risk wind field areas are dynamically adjusted according to the current threat level of mobile operation vehicles in the high-risk areas. The real-time location of mobile work vehicles is displayed as dynamic icons overlaid on the same visual map interface.

[0039] In this embodiment, the warning rules include: Distance warning rule: When the horizontal distance between the mobile operation vehicle and the boundary of the high-risk wind field area is determined to be less than or equal to the first preset distance threshold, an early warning is triggered; Wind speed and direction composite warning rule: Based on the position of the mobile operation vehicle relative to the wind field and the current wind speed, a warning is triggered when the vehicle is determined to be downwind and the wind speed is greater than or equal to the first wind speed threshold, or when the vehicle is determined to be upwind and the wind speed is greater than or equal to the second wind speed threshold; the first wind speed threshold is greater than the second wind speed threshold.

[0040] In this embodiment, triggering the warning includes: sending a warning signal to the mobile work vehicle to trigger its audible and visual alarm device; for warnings triggered by the combined warning rules of wind speed and wind direction, the warning signal is configured to drive the audible and visual alarm device to generate an alarm prompt that is different from the warning triggered by the distance warning rule.

[0041] The following example illustrates the security situation awareness, early warning triggering, and response process: During a hoisting operation at a landfill in a valley, the central processing unit merges the reconstructed 3D wind field (containing an identified vortex zone) with the crane's real-time position onto an electronic map base map. The resulting safety situation map is then pushed in real-time to the crane operator's HMI interface via a 4G network. On the interface, the wind field is displayed as dynamic streamlines, the vortex zone is marked by a semi-transparent red polygon, and the crane's position is displayed in real-time as a triangle icon. As the crane approaches the vortex zone, the threat level calculated by the system increases, and the red polygon dynamically deepens in color from light red to warning red.

[0042] The system's preset warning rules include a first preset distance threshold of 50 meters, a first wind speed threshold (downwind) of level 6, and a second wind speed threshold (upwind) of level 5. When the system detects that the crane is located downwind of the eddy zone, with a horizontal distance of 45 meters and a current wind speed of level 4, this condition meets the distance warning rule (45 meters ≤ 50 meters) but does not meet the combined wind speed and direction rule (level 4 < level 6). The central processing unit immediately generates a warning command and sends it to the crane.

[0043] After receiving the command, the crane's onboard terminal triggers its audible and visual alarm device to emit a continuous buzzing sound (this is a standard alarm prompt triggered by distance warning). At the same time, the eddy current zone marker on the HMI interface begins to flash brightly and displays the text "West eddy current zone, distance 45 meters".

[0044] Upon hearing the alarm and checking the interface, the operator clearly saw on the situation map that they (triangle icon) were downwind of the eddy zone (red polygon). Based on this comprehensive safety situation information, the operator proactively decided to move the crane approximately 25 meters eastward to a safer area, away from the source of risk, thus effectively preventing the accident.

[0045] This scenario demonstrates that through visualization, operators can intuitively grasp the overall risks; through tiered and composite warning rules, the system can achieve accurate and differentiated risk assessments; and through differentiated early warning responses, it can effectively guide operators to pay attention to risks and take correct actions.

[0046] This embodiment addresses hoisting operations in complex terrains such as valley-type landfills by constructing a specialized intelligent wind safety situational awareness system. This system, through a system-level integrated solution that deeply integrates "hard sensing" and "soft computing," achieves a fully intelligent closed-loop process, from real-time perception of multi-dimensional data on-site to dynamic risk warning and decision support. Specifically, this invention comprises a complete technical solution consisting of a mechanical wind sensor network deployed at the work site, a data acquisition and processing unit responsible for aggregating multi-source data, a central processing server with a built-in dedicated wind field reconstruction model, a positioning module providing real-time location information for the work vehicle, and a distributed intelligent early warning terminal deployed in the driver's cab of the work vehicle. These components are organically linked through a communication network, forming a complete system integrating perception, computation, decision-making, and response, creating a holistic solution for proactive warning and defense against wind-induced risks in complex operating environments.

[0047] Building upon this foundation, this invention employs a dynamic fusion-based visualization situation generation method. It dynamically correlates and fuses a three-dimensional dynamic wind field, reconstructed in real-time from terrain and discrete point data, with the real-time location of mobile work vehicles under a unified spatiotemporal reference. This generates a graphical interface that intuitively and comprehensively reflects the safety situation, solving the fundamental problem of operators being unable to "see" or accurately assess intangible risks. Simultaneously, the invention's dedicated wind speed sensing device mechanically converts wind speed into a digital graded signal through a centrifugal force graded triggering mechanism, combining high reliability in harsh environments with ease of signal processing.

[0048] Compared with existing technologies, this invention brings significant benefits: First, it achieves perception fusion, combining the reliability of mechanical devices with the accuracy of electronic calibration to ensure the quality of basic data. Second, it achieves situational transparency by fusing multi-dimensional information such as terrain, wind field, and vehicle location into a real-time dynamic electronic map, making global risks readily apparent. Third, it achieves information penetration and front-end empowerment by synchronously pushing global situational information, traditionally concentrated at the back end, to front-line terminals such as the crane operator's cab in real time, empowering operators to make rapid and autonomous safety decisions based on panoramic information, improving the overall safety and responsiveness of the operating system. Fourth, it demonstrates strong scenario specificity; its wind field model and early warning rules are optimized for the specific risks of "valley terrain" and "lifting operations," solving the problem of poor adaptability of general equipment. Fifth, it showcases the creativity of technology aggregation by deeply integrating cross-domain mechanical sensing, computational fluid dynamics, the Internet of Things, and visualization technologies in a non-obvious way, generating a synergistic effect of "1+1>2" and forming a complete intelligent perception and decision support system.

[0049] It should be noted that the scope of protection of this invention is not limited to the specific technical details described in the preferred embodiments above. Within the scope of the core concept of this invention—namely, "reconstructing wind fields through multi-node data fusion with terrain and dynamically associating them with vehicle locations to achieve visualized early warning"—those skilled in the art can conceive of various alternative solutions. For example, in the data acquisition stage, wind speed measurement can also employ a cup anemometer or an ultrasonic anemometer, and wind direction measurement can employ photoelectric or magnetically encoded sensors; in the model building stage, terrain data can also be derived from satellite remote sensing or lidar scanning; at the algorithm level, spatial interpolation can also employ other mature algorithms such as the inverse distance weighting method and the spline function method. The specific devices (such as centrifugal metal ball graded triggering devices), data sources (such as engineering survey DEMs), and algorithms (such as Kriging interpolation methods) used in the preferred embodiments of this invention are preferred choices based on their comprehensive advantages in terms of reliability, availability, economy, and accuracy in the target application scenarios, and these alternative solutions all fall within the scope of protection of this invention.

[0050] This embodiment also provides a wind safety situation awareness system for hoisting operations in complex terrain, used to implement the above method, including: The data acquisition and transmission module is a wind sensor network consisting of multiple monitoring nodes distributed in the work area, used to collect wind speed and wind direction data at the location. The vehicle positioning unit is used to acquire real-time location data of mobile work vehicles within the work area; The data processing and wind field reconstruction module includes a central processing unit for receiving wind speed, wind direction data, real-time location data, and terrain data of the work area; based on the terrain data and wind speed and wind direction data from multiple monitoring points, it generates reconstructed wind field data covering the work area, containing three-dimensional spatial wind field distribution information and high-risk wind field area information through a wind field reconstruction algorithm. The safety situation fusion and early warning module includes: a situation fusion unit for dynamically spatially associating and fusing reconstructed wind field data with real-time location data of mobile operation vehicles to generate safety situation information; an early warning judgment unit for judging based on safety situation information and preset warning rules, and generating early warning instructions when early warning conditions are met; and an early warning execution and interaction module for receiving early warning instructions and executing early warning responses via an on-board terminal installed on the mobile operation vehicle.

[0051] This embodiment also provides a computer-readable storage medium storing a computer program / instruction that is programmed or configured to be used by a processor for a wind-powered safety situational awareness method for hoisting operations in complex terrain.

[0052] This embodiment also provides a computer program product, including a computer program / instruction that is programmed or configured to execute a wind safety situational awareness method for hoisting operations in complex terrain via a processor.

[0053] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the invention. Therefore, any simple modifications, equivalent changes, and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention should fall within the protection scope of the present invention.

Claims

1. A method for wind-powered safety situational awareness in hoisting operations in complex terrain, characterized in that, Includes the following steps: Step S1: Obtain wind speed and direction data collected by multiple monitoring nodes distributed throughout the work area, as well as real-time location data of mobile work vehicles within the work area. Step S2: Based on the terrain data of the work area and the wind speed and direction data collected by the multiple monitoring nodes, wind field reconstruction processing is performed to generate reconstructed wind field data covering the work area, which includes three-dimensional spatial wind field distribution information and high-risk wind field area information. Step S3: Perform dynamic spatial correlation and fusion processing on the reconstructed wind field data and the real-time location data of the mobile operation vehicle to generate safety situation information for real-time safety decision-making; Based on the security situation information and preset warning rules, a warning message is generated and sent to the mobile work vehicle in real time when the warning conditions are met.

2. The wind-powered safety situation awareness method for hoisting operations in complex terrain according to claim 1, characterized in that, In step S2, the wind field reconstruction process includes: The Kriging interpolation algorithm is used to spatially interpolate the wind speed and wind direction data collected by the multiple monitoring nodes to obtain the initial three-dimensional wind field of the digital elevation model covering the working area. The initial three-dimensional wind field is matched and queried with a pre-built benchmark wind database to output a reconstructed three-dimensional spatial wind field distribution; the benchmark wind database contains three-dimensional benchmark wind field data obtained by high-precision computational fluid dynamics simulation based on the digital elevation model.

3. The wind-powered safety situation awareness method for hoisting operations in complex terrain according to claim 2, characterized in that, The matching query process uses the initial three-dimensional wind field as the query vector to retrieve the closest benchmark wind field data from the benchmark wind database, and generates the reconstructed three-dimensional spatial wind field distribution based on the retrieval results.

4. The wind-powered safety situation awareness method for hoisting operations in complex terrain according to claim 1, characterized in that, In step S3, generating security situation information for real-time security decision-making includes: On the visual map interface of the work area, the three-dimensional spatial wind field distribution is visualized and rendered in the form of a dynamic flow field. The identified high-risk wind field areas are marked in a graphical manner that distinguishes them from safe areas; the visual attributes of the graphical markings of the high-risk wind field areas are dynamically adjusted according to the current threat level of the mobile operation vehicle based on the high-risk areas. The real-time location of mobile work vehicles is displayed as dynamic icons overlaid on the same visual map interface.

5. The wind-powered safety situation awareness method for hoisting operations in complex terrain according to claim 1, characterized in that, In step S3, the warning rules include: Distance warning rule: When the horizontal distance between the mobile work vehicle and the boundary of the high-risk wind field area is determined to be less than or equal to a first preset distance threshold, an early warning is triggered; Wind speed and direction composite warning rule: Based on the position of the mobile operation vehicle relative to the wind field and the current wind speed, a warning is triggered when the vehicle is determined to be downwind and the wind speed is greater than or equal to the first wind speed threshold, or when the vehicle is determined to be upwind and the wind speed is greater than or equal to the second wind speed threshold; the first wind speed threshold is greater than the second wind speed threshold.

6. The wind-powered safety situation awareness method for hoisting operations in complex terrain according to claim 5, characterized in that, The triggering of the early warning includes: sending an early warning signal to the mobile work vehicle to trigger its audible and visual alarm device; for early warnings triggered by the combined wind speed and wind direction warning rules, the early warning signal is configured to drive the audible and visual alarm device to generate an alarm prompt that is different from the early warning triggered by the distance warning rules.

7. The wind-powered safety situation awareness method for hoisting operations in complex terrain according to claim 1, characterized in that, In step S1, the monitoring node collects wind speed data through a mechanical centrifugal force grading triggering device. The mechanical centrifugal force grading triggering device includes a rotating shaft driven by a wind cup and metal balls with increasing weight arranged circumferentially along the rotating shaft. Each metal ball is fixed by an elastic constraint and corresponds to an independent circuit contact. When the wind speed reaches the preset level, the centrifugal force generated by the rotation overcomes the elastic constraint force of the corresponding metal ball, causing it to shift radially and connect the corresponding circuit, thereby outputting a binary coded signal that uniquely corresponds to the current wind speed level.

8. A wind-powered safety situational awareness system for hoisting operations in complex terrain, characterized in that, To implement the method according to any one of claims 1 to 7, comprising: The data acquisition and transmission module is a wind sensor network consisting of multiple monitoring nodes distributed in the work area, used to collect wind speed and wind direction data at the location. The vehicle positioning unit is used to acquire real-time location data of mobile work vehicles within the work area; The data processing and wind field reconstruction module includes a central processing unit for receiving the wind speed, wind direction data, real-time location data, and terrain data of the work area; based on the terrain data and wind speed and wind direction data from multiple monitoring points, it generates reconstructed wind field data covering the work area and containing three-dimensional spatial wind field distribution information and high-risk wind field area information through a wind field reconstruction algorithm. The safety situation fusion and early warning module includes: a situation fusion unit for dynamically spatially associating and fusing reconstructed wind field data with real-time location data of mobile operation vehicles to generate safety situation information; an early warning judgment unit for judging based on safety situation information and preset warning rules, and generating early warning instructions when early warning conditions are met; and an early warning execution and interaction module for receiving early warning instructions and executing early warning responses via an on-board terminal installed on the mobile operation vehicle.

9. A computer-readable storage medium storing a computer program / instructions, characterized in that, The computer program / instructions are programmed or configured to execute, via a processor, the wind safety situational awareness method for hoisting operations in complex terrain as described in any one of claims 1 to 7.

10. A computer program product comprising a computer program / instructions, characterized in that, The computer program / instructions are programmed or configured to execute, via a processor, the wind safety situational awareness method for hoisting operations in complex terrain as described in any one of claims 1 to 7.

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