Linkage Early Warning Device and Method for Wind Power High-Altitude Operation Support Platforms

Abstract

This application relates to a linkage early warning device and method for a wind power aerial work platform. This application is applicable to the field of new energy wind power technology. The technical problem to be solved by this application is: to provide a linkage early warning device and method for a wind power aerial work platform. The technical solution adopted in this application includes: multiple weighing sensors, respectively located at each force support point of the platform, for acquiring pressure detection information of the corresponding support point; an edge computing unit, located in the hoisting operation area, communicating with the multiple weighing sensors, capable of calculating the total load information of the platform based on the acquired pressure detection information of each support point; an early warning component, located on the platform, capable of issuing an alarm upon receiving an early warning message; and a controller, communicating with both the edge computing unit and the early warning component, capable of acquiring the total load information and comparing the total load information with an internal preset threshold, and issuing an early warning message to the early warning component if the total load information does not match.

Description

Technical Field

[0001] This invention relates to the field of new energy wind power technology, and in particular to a linkage early warning device and method for a load-bearing platform for high-altitude wind power operations. Background Technology

[0002] In high-altitude wind power construction, load-bearing platforms are used to support hoisting equipment, tools, and personnel. Their safe operation depends on accurate control of the total load. Traditionally, load verification has relied mainly on manual weighing using portable weighing equipment or experience-based estimation, which has significant drawbacks: (1) Inefficient, the operation needs to be interrupted for 5 to 10 minutes of manual measurement before each hoisting, which seriously affects the construction progress; (2) Insufficient accuracy. Manual operation is easily affected by perspective, reading error or environmental interference, making it difficult to accurately reflect the actual load, especially in off-center load or dynamic hoisting scenarios where the risk is higher. (3) The lack of a real-time early warning mechanism means that even if overload occurs, it cannot be detected in time, which can easily lead to platform instability, tilting, or even serious safety accidents such as sling breakage. Summary of the Invention

[0003] The technical problem to be solved by the present invention is to provide a linkage early warning device and method for a wind power high-altitude operation load-bearing platform, in view of the above-mentioned problems.

[0004] The technical solution adopted in this invention is: a linkage early warning device for a wind power high-altitude operation load-bearing platform, comprising: Multiple load cells are installed at each load-bearing support point of the load-bearing platform to obtain pressure detection information at the corresponding support point. The edge computing unit, located in the hoisting operation area, communicates with multiple weighing sensors and can calculate the total load information of the load-bearing platform based on the pressure detection information of each support point. The early warning component, located on the load-bearing platform, can issue an alarm when it receives a warning message; The controller communicates with the edge computing unit and the early warning component. It can obtain the total load information and compare the total load information with the internal preset threshold. If the total load information does not meet the threshold, it will send an early warning message to the early warning component.

[0005] Using the above-mentioned technical means, weighing sensors are arranged at each force support point of the load-bearing platform. Multiple weighing sensors can automatically collect pressure detection information at the support points. The edge computing unit processes the multiple pressure detection information in real time. The controller compares the threshold and triggers the alarm of the early warning component to achieve linkage early warning. The whole process does not require manual intervention.

[0006] In some embodiments, the controller has a preset first-level warning threshold and a second-level warning threshold. If the total load information is higher than the first-level warning threshold but lower than the second-level warning threshold, the controller sends a first warning message to the warning component. If the total load information is higher than the second-level warning threshold, the controller sends a second warning message to the warning component.

[0007] In some embodiments, the warning component includes a warning light and a buzzer, which are installed on the railing of the load-bearing platform. When the first warning information is received, the warning light flashes yellow, and when the second warning information is received, the warning light flashes red and the buzzer sounds.

[0008] In some embodiments, the load-bearing platform is cylindrical, and four weighing sensors are symmetrically arranged in a cross shape along the bottom periphery of the load-bearing platform. Four warning lights and buzzers are arranged in a circumferential distribution on the railing of the load-bearing platform.

[0009] In some embodiments, the weighing sensor is a resistance strain gauge weighing sensor with a sampling frequency ≥10Hz and a measurement accuracy of ±0.5%FS.

[0010] In some embodiments, the plurality of the weighing sensors transmit the pressure detection information to the edge computing unit via RS485 or CAN bus.

[0011] Another technical solution adopted in this invention is: A coordinated early warning method includes the following steps: S1. Continuously collect pressure detection information F_i (i=1,2,...,n) at each force support point of the load-bearing platform through multiple weighing sensors; S2. The edge computing unit receives pressure detection information and performs noise reduction and smoothing processing through a built-in digital filtering algorithm. S3. The edge computing unit calculates the total load of the platform F_total=∑F_i (i=1,2,...,n) based on the processed pressure detection information of each support point, and analyzes the horizontal attitude of the platform and calculates the real-time tilt angle θ. S4. If the horizontal attitude of the load-bearing platform is horizontal, the controller uses the internally preset first-level warning rated threshold T1 and second-level warning rated threshold T2 as the graded warning thresholds; if the horizontal attitude of the load-bearing platform is tilted, the controller dynamically updates T1 and T2 based on the real-time tilt angle θ and the internally preset relationship table to obtain the first-level warning update threshold T1' and the second-level warning update threshold T2'. S5. Based on the horizontal posture of the load-bearing platform, compare the total load F_total of the platform with the corresponding graded early warning threshold, and issue graded linkage early warnings based on the comparison results.

[0012] In some embodiments, the horizontal attitude of the analysis platform and the real-time tilt angle θ are calculated, including calculating the center-of-gravity coordinates of the platform load according to the pressure detection information Fi of each support point and its preset coordinate position on the load-bearing platform, and comprehensively judging the tilt degree of the platform and estimating the real-time tilt angle θ through the deviation result between the pressure of each support point and the theoretical average pressure and the offset between the center-of-gravity coordinates and the geometric center of the platform.

[0013] In some embodiments, based on the real-time tilt angle θ and the internal preset relationship table, T1 and T2 are dynamically updated to obtain T1' and T2', including: T1' = T1 * k(θ), T2' = T2 * k(θ), where k(θ) is a reduction coefficient less than 1, and the larger θ is, the smaller k(θ) is.

[0014] In some embodiments, the hierarchical linkage warning is performed according to the comparison result, including: If F_total ≤ T1', there is no warning; If T1' < F_total ≤ T2', the controller sends a first warning message to the warning component, driving the warning component to issue a corresponding first-level alarm; If F_total > T2', the controller sends a second warning message to the warning component, driving the warning component to issue a corresponding second-level alarm.

[0015] The beneficial effects of the present invention are: 1. By automatically collecting the loads of each support point using multiple weighing sensors and calculating the total load in real time using the edge computing unit, continuous automatic monitoring without manual intervention can be achieved, and load verification can be completed during the hoisting process, significantly improving the operation efficiency. At the same time, the use of multi-point distributed measurement can reflect the real load distribution, avoiding single-point estimation or off-center load misjudgment. The cooperation between the sensor and the edge computing can improve the objectivity and accuracy of the measurement, reducing the risk of structural instability or sling fracture caused by misjudgment. By comparing the total load with the preset threshold through the controller, when the limit is exceeded, the warning component is linked to issue an alarm, realizing the pre-warning of the overload risk and avoiding major high-altitude safety accidents such as platform tilt, structural overload, and sling fracture.

[0016] 2. By analyzing the platform load and attitude in real time using the edge computing unit and dynamically adjusting the warning threshold based on the attitude, the problem of inaccurate warning of the traditional fixed threshold method when the platform is tilted is solved, significantly improving the reliability and safety of the warning device.

[0017] 3. By constructing a three-dimensional early warning and monitoring network, a three-level linkage of "local sound and light alarm + remote central monitoring + mobile terminal instant push" has been realized, breaking the data silos of high-altitude operations and enabling ground safety officers and managers to grasp the status of the high-altitude platform in real time, which facilitates remote guidance and emergency response. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of the linkage early warning device in this application.

[0019] Figure 2 This is a schematic diagram of the linkage early warning method in this application.

[0020] Explanation of reference numerals in the attached figures: 1. Load-bearing platform; 2. Main crane hook; 3. Main crane sling; 4. Weighing sensor; 5. Buzzer; 6. Warning light;

[0021] This specification includes references to "one embodiment" or "implementation". The use of the phrase "in one embodiment" or "in an embodiment" does not necessarily refer to the same embodiment. Specific features, structures, or characteristics may be combined in any suitable manner consistent with this disclosure.

[0022] The term "comprising" is open-ended. As used in the appended claims, it does not exclude additional structures or steps.

[0023] "First," "second," etc. As used in this article, these terms serve as labels for the nouns preceding them and do not imply any type of ordering (e.g., spatial, temporal, logical, etc.).

[0024] The term "based on," as used herein, describes one or more factors that influence the determination. This term does not exclude additional factors influencing the determination. That is, the determination may be based solely on these factors or at least partially on them. Consider the phrase "A is determined based on B." In this case, B is the factor influencing the determination of A, and such phrases do not exclude the possibility that the determination of A may also be based on C. In other instances, A may be determined solely on B. Detailed Implementation

[0025] To enable those skilled in the art to better understand the present invention, the technical solution of the present invention will be further described below with reference to specific embodiments.

[0026] Example 1: Combination Figure 1As shown, this embodiment is a linkage early warning device for a wind power high-altitude operation support platform, including multiple weighing sensors 4, an edge computing unit, an early warning component, and a controller. The multiple weighing sensors 4 are distributed at each load-bearing support point of the support platform 1 to acquire pressure detection information at the corresponding support point. An edge computing unit is provided within the hoisting operation area, and the edge computing unit is communicatively connected to the multiple weighing sensors 4. The edge computing unit can acquire pressure detection information at each support point and calculate the total load information of the support platform 1 based on the pressure detection information. An early warning component is provided on the support platform 1, and the early warning component can issue an alarm when it receives an early warning message. Both the edge computing unit and the early warning component are communicatively connected to the controller. The controller can acquire the total load information and compare the total load information with an internal preset threshold. If the total load information does not meet the threshold, an early warning message is issued to the early warning component.

[0027] In some implementations, the edge computing unit uses an industrial-grade embedded computer, installed in a protective enclosure within the construction site. The edge computing unit communicates with all the load cells 4 to receive and process real-time pressure data from each support point. The edge computing unit incorporates a built-in filtering algorithm capable of real-time noise reduction and smoothing of the pressure detection information, and its built-in algorithm program is responsible for performing data filtering, load calculation, and platform attitude analysis.

[0028] Due to interference from wind vibration, hoisting sway, and mechanical impact in the high-altitude environment of wind power plants, the original sensor signals are prone to noise. By employing filtering algorithms, high-frequency jitter can be effectively suppressed, resulting in stable and reliable load values ​​and reducing the risk of false alarms or missed alarms. The smoothed data more accurately reflects the actual load trend, making threshold judgments more reliable.

[0029] In some implementations, the controller has preset primary and secondary warning thresholds. If the total load information is higher than the primary warning threshold but lower than the secondary warning threshold, the controller sends a first warning message to the warning component; if the total load information is higher than the secondary warning threshold, the controller sends a second warning message to the warning component. In this embodiment, the preset thresholds can be dynamically adjusted according to the platform structure materials and construction stage. Specifically, in this embodiment, the controller uses a programmable logic controller (PLC) or a dedicated microcontroller. The controller communicates with the edge computing unit and the warning component. The controller has preset static warning thresholds. For example, the primary warning rated threshold T1 is 80% of the rated load, and the secondary warning rated threshold T2 is 95% of the rated load, and a tilt-bearing capacity reduction coefficient relationship table is stored. For example: when the tilt angle θ < 2°, the reduction coefficient k = 1.0; when 2° ≤ θ < 5°, k = 0.9; when θ ≥ 5°, k = 0.7. This table is based on platform structural mechanics analysis and experimental data. By using the table showing the relationship between the primary warning threshold T1, the secondary warning threshold T2, and the tilt-bearing capacity reduction coefficient, and combining T1' = T1 * k(θ) and T2' = T2 * k(θ), T1 and T2 can be dynamically updated to obtain the primary warning update threshold T1' and the secondary warning update threshold T2'. Here, k(θ) is a reduction coefficient less than 1, and the larger θ is, the smaller k(θ) is.

[0030] Furthermore, the early warning components include a warning light 6 and a buzzer 5, which are installed on the railing of the load-bearing platform 1. The warning light 6 is a waterproof, high-brightness LED warning light, and the buzzer 5 is a high-decibel buzzer. The warning light 6 and buzzer 5 are arranged symmetrically around the platform railing to ensure that there are no blind spots in the visual and auditory perception of the on-site audible and visual alarms. When the first warning information is received, the warning light 6 flashes yellow; when the second warning information is received, the warning light 6 flashes red, and the buzzer 5 sounds. Specifically, taking the hoisting operation of a wind turbine tower as an example, the rated load of the load-bearing platform 1 is 1 ton, and the first-level warning threshold is set at 0.8 tons, and the second-level warning threshold is set at 0.9 tons. When the weight of the hoisted object gradually increases to 0.8 tons, the first warning information is triggered, and the warning light 6 at the hoisting operation site flashes yellow. When the weight reaches 0.9 tons, the second warning information is triggered, and the warning light 6 at the hoisting operation site flashes red at a frequency of 3Hz, and the buzzer 5 sounds.

[0031] The first-level warning indicates that the load is approaching its limit, guiding operators to work cautiously. The second-level warning forcibly alerts the danger of overloading and can require immediate cessation of operations.

[0032] In some implementation schemes, the load-bearing platform 1 in this embodiment is a circular steel structure aerial work platform with a diameter of approximately 3 meters. This platform is suspended from the top of the tower by six main hoisting slings 3 via main hoisting hooks 2, and is used to support personnel and equipment components during high-altitude operations such as generator maintenance. Four load cells 4 are symmetrically arranged in a cross shape along the bottom perimeter of the load-bearing platform 1. Four warning lights 6 and a buzzer 5 are arranged in a ring on the railing of the load-bearing platform 1. Specifically, in this embodiment, the load cells 4 are high-precision load cells, and the four load cells 4 are labeled S1, S2, S3, and S4 respectively. The ring-shaped distribution of the warning lights 6 ensures that operators in any position on the platform can see the lights, reflecting the scientific placement and comprehensive measurement.

[0033] In some implementations, the load cell 4 is a high-precision resistance strain gauge load cell with a sampling frequency ≥10Hz and a measurement accuracy of ±0.5%FS. These four sensors are fixedly mounted on four main load-bearing points between the platform base plate and the underlying load-bearing beam using high-strength bolts, and these four points are symmetrically distributed in a cross shape. This arrangement ensures that the sensors can directly and accurately measure the pressure transmitted from the platform frame.

[0034] In some implementations, multiple load cells 4 transmit pressure detection information to the edge computing unit via RS485 or CAN bus. In this embodiment, four sensors convert the acquired analog pressure signals into digital signals via RS485 bus and transmit them out. The cross-shaped symmetrical arrangement forms a stable measurement plane, and its data can not only be used to sum the total weight, but more importantly, by comparing the numerical differences at the four points, the tilt state of the platform and the position of the load center of gravity can be effectively calculated.

[0035] In some implementation schemes, the edge computing unit is connected to mobile terminal devices, including the safety officer's mobile phone. A remote monitoring center is also deployed at the ground or construction project command center. The edge computing unit, controller, and remote monitoring center are all connected via a 4G / 5G industrial IoT gateway, uploading data in real time, such as total platform load, tilt angle, and warning status. The server stores, analyzes, and centrally displays this data. When a high-level alarm is triggered, the server immediately sends an alarm notification to the relevant safety officer's mobile phone via SMS gateway and APP push service.

[0036] By coordinating mobile terminals, remote monitoring centers, and 4G / 5G industrial IoT gateways, two-way data interaction between field devices and remote terminals is achieved. On the one hand, data such as total platform load, tilt angle, and early warning status are uploaded in real time for remote monitoring. On the other hand, high-level alarms are pushed via SMS / APP, achieving dual early warning from both the field and remote locations, allowing safety officers and project command centers to grasp the danger as soon as possible and improve emergency response efficiency.

[0037] The implementation principle of the linkage early warning device for the wind power high-altitude operation load-bearing platform in the embodiment is as follows: By continuously and automatically collecting data through the weighing sensor 4, and processing and analyzing it in real time by the edge computing unit and controller, the weighing measurement can be performed without manual interruption of the operation, completely eliminating the time-consuming manual measurement of the past and realizing the simultaneous performance of load detection and hoisting operations, which greatly improves the construction progress.

[0038] By constructing a complete early warning system that includes real-time detection, dynamic threshold judgment, hierarchical linkage early warning, and remote synchronous reminders, load data collection, processing, and threshold comparison are all performed in real time. Furthermore, the early warning threshold can be dynamically adjusted according to the platform's tilt status. Once an early warning is triggered, on-site audible and visual alarms respond immediately, while the remote monitoring center and safety officer's mobile terminal simultaneously receive the alarm information. This fundamentally avoids the problem of not being able to detect overload in a timely manner and prevents safety accidents such as platform instability and sling breakage.

[0039] Example 2: Combination Figure 2 As shown, this embodiment is a linkage early warning method applied to the linkage early warning device described in Embodiment 1, including the following steps: S1. Continuously collect pressure detection information F_i (i=1,2,...,n) at each force support point of the load-bearing platform 1 through multiple weighing sensors 4; S2. The edge computing unit receives pressure detection information and performs noise reduction and smoothing processing through a built-in digital filtering algorithm. S3. The edge computing unit calculates the total load of the platform F_total=∑F_i (i=1,2,...,n) based on the processed pressure detection information of each support point, and analyzes the horizontal attitude of the platform and calculates the real-time tilt angle θ. S4. If the horizontal posture of the load-bearing platform 1 is horizontal, the controller uses the internally preset first-level warning rated threshold T1 and second-level warning rated threshold T2 as the graded warning thresholds; if the horizontal posture of the load-bearing platform 1 is tilted, the controller dynamically updates T1 and T2 based on the real-time tilt angle θ and the internally preset relationship table to obtain the first-level warning update threshold T1' and the second-level warning update threshold T2'. S5. Based on the horizontal posture of the load-bearing platform 1, compare the total load F_total of the platform with the corresponding graded early warning threshold, and perform graded linkage early warning based on the comparison result.

[0040] In some implementation schemes, data acquisition is performed in step S1. Specifically, multiple weighing sensors 4 fixedly installed at the force support points are used to synchronously and continuously acquire the real-time pressure simulation signals of each support point at a sampling frequency of not less than 20 Hz, and the converted digital pressure data is sent to the edge computing unit via RS485 bus.

[0041] In some implementations, data processing is performed in step S2. After receiving the data, the edge computing unit calls its built-in filtering algorithm to process the raw pressure data in real time. Specifically, a first-order low-pass filter is used to filter out high-frequency noise caused by wind vibration and mechanical vibration, and then a moving average filter is used to smooth the data to obtain stable and reliable pressure values ​​for each support point.

[0042] High-frequency noise caused by wind and mechanical vibration is filtered out by a first-order low-pass filter to avoid false load signals. The data is smoothed by a moving average filter to output a stable load value that truly reflects the load trend. The use of dual filtering effectively reduces the risk of false alarms / missed alarms in the system and makes threshold judgment more reliable.

[0043] In some implementations, step S3 involves load attitude analysis, which analyzes the horizontal attitude of the platform and calculates the real-time tilt angle θ. This includes calculating the center-of-gravity coordinates of the platform load based on the pressure detection information F_i at each support point and its preset coordinate position on the load-bearing platform 1. The degree of platform tilt and the real-time tilt angle θ are then comprehensively determined by the deviation between the pressure at each support point and the theoretical average pressure, along with the offset of the center-of-gravity coordinates from the platform's geometric center. Specifically, based on the processed F_i, the edge computing unit performs the core calculations: ① Calculate the total load: F_total = ΣF_i (i=1 to 4); ② Analyze the platform attitude: calculate the position of the load's center of gravity relative to the platform's geometric center based on the preset cross-symmetric coordinates of each sensor. By analyzing the differences between the four F_i values ​​and the center-of-gravity offset, a comprehensive judgment is made regarding whether the platform is tilted, and the real-time tilt angle θ is estimated.

[0044] The total load is calculated using ∑F_i to achieve foundation load detection. Combined with preset sensor coordinates, the real-time tilt angle θ is calculated based on numerical differences and center of gravity offset, enabling accurate judgment of the platform's attitude. This combined load and attitude analysis overcomes the limitations of traditional methods that only detect the total load, making it suitable for the actual working conditions of dynamic high-altitude hoisting in wind power projects.

[0045] In some embodiments, dynamic threshold decision-making is implemented in step S4. Based on the real-time tilt angle θ and the internal preset relationship table, T1 and T2 are dynamically updated to obtain T1' and T2', including: T1' = T1 * k(θ), T2' = T2 * k(θ), where k(θ) is a reduction coefficient less than 1, and the larger θ is, the smaller k(θ) is. Specifically, the controller receives F_total and θ, and according to the preset "tilt angle - reduction coefficient k(θ)" relationship table, for example: when θ < 2°, k = 1.0; when 2° ≤ θ < 5°, k = 0.9, the static warning thresholds T1 and T2 are dynamically adjusted to obtain the current effective thresholds: T1' = T1 * k(θ), T2' = T2 * k(θ).

[0046] The reduction coefficient is formulated based on structural mechanics analysis and experimental data, which conforms to the principles of engineering mechanics and ensures the scientific nature of the dynamic threshold. The larger the tilt angle, the smaller the reduction coefficient, so that the warning threshold adapts to the actual bearing capacity after the platform tilts, reducing the safety hazard that the platform tilts but is judged not to be overloaded according to the horizontal threshold, realizing the dynamic intelligent matching of the threshold, and making the warning more in line with the actual working conditions.

[0047] In some embodiments, step S5 implements hierarchical linkage warning. The hierarchical linkage warning is carried out according to the comparison result. Taking the update of the threshold as an example, it includes: If F_total ≤ T1', there is no warning; If T1' < F_total ≤ T2', the controller sends the first warning information to the warning component to drive the warning component to issue the corresponding first-level alarm; If F_total > T2', the controller sends the second warning information to the warning component to drive the warning component to issue the corresponding second-level alarm.

[0048] Specifically, if F_total ≤ T1', the system operates normally; If T1' < F_total ≤ T2', a first-level warning is triggered and the yellow light flashes; If F_total > T2', a second-level warning is triggered, the red light flashes, the buzzer sounds five long beeps, and the alarm information is synchronously pushed to the remote monitoring center and the safety officer's mobile terminal APP through the Internet of Things gateway.

[0049] The first-level warning is a reminder warning, which reminds the operator that the load limit is approaching, guides careful operation, and reserves space for operation adjustment; the second-level warning is a forced warning, which directly warns of the overload danger and requires the operation to be stopped immediately, realizing risk gradient control and avoiding the abruptness or lag of the warning with a single threshold.

[0050] The implementation principle of an embodiment of the linkage warning method is: High-precision resistance strain gauge load cells 4 are symmetrically arranged at the force support points of the load-bearing platform 1. The pressure simulation signals of each support point are synchronously and continuously collected at a sampling frequency of ≥10Hz. The analog signals are converted into digital signals through RS485 / CAN bus and then transmitted to the edge computing unit to provide raw data for subsequent analysis.

[0051] After receiving the raw pressure data, the edge computing unit uses a built-in first-order low-pass and moving average filtering algorithm to denoise and smooth the raw signal containing high-frequency noise, filtering out environmental interference such as wind vibration, hoisting sway, and mechanical impact at high altitudes of wind power plants, and outputting stable and reliable pressure values ​​for each support point, thus eliminating the impact of false data on subsequent analysis.

[0052] Based on the processed pressure value, the edge computing unit performs two core calculations: ① Calculates the real-time total load of the platform using the total load formula F_total=∑F_i (i=1,2,...,n); ② Combines the preset coordinate positions of each sensor with the differences in sensor values ​​and the offset of the center of gravity to comprehensively calculate the real-time tilt angle θ of the platform and the position of the load center of gravity, realizing dual analysis of load and attitude, and transmits the calculation results F_total and the real-time tilt angle θ to the controller.

[0053] After receiving the total load and tilt angle data, the controller makes dynamic threshold decisions: ① If the platform is level or nearly level (θ≈0°), the preset first / second level rated warning thresholds (T1, T2) are directly used; ② If the platform is tilted, the corresponding k(θ) is matched according to the preset "tilt angle-reduction coefficient relationship table", and updated to the real-time effective warning thresholds through the formulas T1'=T1×k(θ) and T2'=T2×k(θ); then the real-time total load F_total of the platform is compared with the effective thresholds to determine the risk level.

[0054] Based on the threshold comparison results, the controller sends corresponding warning commands to the on-site warning components. At the same time, it uploads the data / alarms to the remote monitoring center and the safety officer's mobile terminal through the industrial IoT gateway, realizing hierarchical linkage warning between the on-site and remote locations.

[0055] Example 3: This embodiment is an engineering application example of the linkage early warning method in Embodiment 2.

[0056] To enable those skilled in the art to more clearly understand the technical solution, dynamic early warning logic, and significant advancements compared to static threshold methods of the present invention, a specific workflow example is provided below. It should be particularly noted that the specific load values ​​(e.g., 0.7 tons, 0.15 tons), tilt angle (3°), and thresholds (0.8t, 0.95t) used in this example are artificially set based on well-known engineering knowledge, typical platform rated parameters, and reasonable off-center load mechanical models. The aim is to clearly and completely demonstrate the entire process of the present invention's method (data acquisition → filtering → attitude and load analysis → dynamic threshold decision → multi-level linkage early warning). The core value of this example lies in illustrating how the described method steps work together to achieve intelligent early warning. The specific values ​​do not constitute any limitation on the scope of protection of the present invention, nor are they a record of specific experimental data.

[0057] Workflow diagram: The platform, with a load of 0.7 tons, is in a horizontal position (θ≈0°). At this point, the effective thresholds T1'=0.8t and T2'=0.95t, with no warning. Workers hoist a 0.15-ton piece of equipment to one side of the platform, causing a slight tilt. The edge computing unit calculates the total load F_total=0.85 tons and the tilt angle θ≈3°. The controller, based on θ=3°, looks up k=0.9, and adjusts the dynamic thresholds to T1'=0.72t and T2'=0.855t.

[0058] Since F_total=0.85t>T2'=0.855t, the controller immediately triggered a level-two overload alarm. On-site: Warning light 6 flashed red, buzzer 5 sounded, notifying platform operators to immediately stop loading and adjust load distribution. Simultaneously, the alarm information was sent to the ground monitoring center via the IoT gateway, a pop-up alarm appeared on the large screen, and a push notification was simultaneously sent to the safety supervisor's mobile app: "#2 wind turbine high-altitude platform, level-two overload alarm! Current load 0.85 tons, platform tilt 3°, please take immediate action!"

[0059] The above are all preferred embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Therefore, all equivalent changes made in accordance with the structure, shape and principle of the present invention should be covered within the scope of protection of the present invention.

Claims

1. A linkage early warning device for a wind power high-altitude work platform, characterized in that, include: Multiple load cells (4) are installed at each load-bearing support point of the load-bearing platform (1) to obtain pressure detection information at the corresponding support point; The edge computing unit is located in the hoisting operation area and is connected to multiple weighing sensors (4). It can calculate the total load information of the load-bearing platform (1) based on the pressure detection information of each support point. The early warning component, located on the load-bearing platform (1), is capable of issuing an alarm when it receives an early warning message; The controller communicates with the edge computing unit and the early warning component. It can obtain the total load information and compare the total load information with the internal preset threshold. If the total load information does not meet the threshold, it will send an early warning message to the early warning component.

2. The linkage early warning device for a wind power high-altitude work support platform according to claim 1, characterized in that: The controller has a preset first-level warning threshold and a second-level warning threshold. If the total load information is higher than the first-level warning threshold but lower than the second-level warning threshold, the controller sends a first warning message to the warning component. If the total load information is higher than the second-level warning threshold, the controller sends a second warning message to the warning component.

3. The linkage early warning device for a wind power high-altitude work support platform according to claim 2, characterized in that: The warning component includes a warning light (6) and a buzzer (5). The warning light (6) and the buzzer (5) are installed on the railing of the load-bearing platform (1). When the first warning information is received, the warning light (6) flashes yellow. When the second warning information is received, the warning light (6) flashes red and the buzzer (5) sounds.

4. A linkage early warning device for a wind power high-altitude work platform according to claim 3, characterized in that: The load-bearing platform (1) is cylindrical, and four weighing sensors (4) are symmetrically arranged in a cross shape on the bottom of the periphery of the load-bearing platform (1). Four warning lights (6) and buzzers (5) are arranged in a ring on the railing of the load-bearing platform (1).

5. A linkage early warning device for a wind power high-altitude work support platform according to claim 1, characterized in that: The weighing sensor (4) is a resistance strain gauge weighing sensor (4), with a sampling frequency ≥10Hz and a measurement accuracy of ±0.5%FS.

6. A linkage early warning device for a wind power high-altitude work support platform according to claim 1, characterized in that: Multiple weighing sensors (4) transmit the pressure detection information to the edge computing unit via RS485 or CAN bus.

7. A linkage early warning method, applied to the linkage early warning device according to any one of claims 1 to 6, characterized in that, Includes the following steps: S1. Continuously collect pressure detection information F_i (i=1,2,...,n) of each force support point of the load-bearing platform (1) through multiple weighing sensors (4); S2. The edge computing unit receives pressure detection information and performs noise reduction and smoothing processing through a built-in digital filtering algorithm. S3. The edge computing unit calculates the total load of the platform F_total=∑F_i(i=1,2,...,n) based on the processed pressure detection information of each support point, and analyzes the horizontal attitude of the platform and calculates the real-time tilt angle θ. S4. If the horizontal posture of the load-bearing platform (1) is horizontal, the controller uses the internally preset first-level warning rated threshold T1 and second-level warning rated threshold T2 as the graded warning thresholds. If the horizontal attitude of the load-bearing platform (1) is tilted, the controller dynamically updates T1 and T2 based on the real-time tilt angle θ and the internal preset relationship table to obtain the first-level early warning update threshold T1' and the second-level early warning update threshold T2'. S5. Based on the horizontal attitude of the load-bearing platform (1), compare the total load F_total of the platform with the corresponding graded early warning threshold, and perform graded linkage early warning based on the comparison result.

8. The linkage early warning method according to claim 7, characterized in that: The analysis platform's horizontal attitude and calculation of the real-time tilt angle θ include calculating the center of gravity coordinates of the platform load based on the pressure detection information F_i of each support point and its preset coordinate position on the load-bearing platform (1), and comprehensively judging the tilt degree of the platform and estimating the real-time tilt angle θ by the deviation results of the pressure of each support point from the theoretical average pressure and the offset of the center of gravity coordinates from the geometric center of the platform.

9. The linkage early warning method according to claim 7, characterized in that: The method of dynamically updating T1 and T2 based on the real-time tilt angle θ and the internal preset relationship table to obtain T1' and T2' includes: T1' = T1 * k(θ), T2' = T2 * k(θ), where k(θ) is a reduction coefficient less than 1, and the larger θ is, the smaller k(θ) is.

10. A linkage early warning method according to claim 7, characterized in that: The tiered and coordinated early warning system based on the comparison results includes: If F_total ≤ T1', then there is no warning; If T1' < F_total ≤ T2', the controller sends the first warning information to the warning component, driving the warning component to issue the corresponding first-level alarm; If F_total > T2', the controller sends a second warning message to the warning component, driving the warning component to issue the corresponding secondary alarm.

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