Dynamic vibration cooperative compensation method and device for sensor with space optimization arrangement

Abstract

The invention provides a dynamic vibration cooperative compensation method and device for sensors in space optimization arrangement, and relates to the technical field of intelligent operation and maintenance of wind power generation equipment. The method comprises the following steps: calculating a global coverage rate corresponding to each sensor in a sensor monitoring domain according to the number of target grids covered by each sensor and the total number of the grids; the sensor with the minimum deployment number and the maximum coverage gain is selected as a target, all global coverage rates are updated and iteratively calculated, space optimization arrangement is carried out on all the sensors, and a target sensor is obtained; and performing compensation control on the data acquired by each target sensor. The device executes the method. According to the method and the device provided by the embodiment of the invention, a solid technical foundation can be provided for intelligent operation and maintenance of the wind turbine generator.

Description

Technical Field

[0001] This invention relates to the field of intelligent operation and maintenance technology for wind power generation equipment, specifically to a method and device for dynamic vibration collaborative compensation of sensors with optimized spatial arrangement. Background Technology

[0002] As the global energy structure accelerates its transition to a low-carbon model, the proportion of new energy power generation, represented by wind power, continues to rise, placing higher demands on the accuracy and reliability of internal thermal condition monitoring of generating units. Infrared thermal imaging technology, with its advantages of non-contact and full-field temperature measurement, has become a key means of assessing the condition of core components such as gearbox bearings and generator windings, providing accurate thermal monitoring data for predictive maintenance based on digital twins.

[0003] Existing installation schemes mostly employ fixed sensor networks for localized temperature acquisition, using big data platforms to collect temperature data and provide fault warnings. However, these schemes have significant shortcomings in practical applications: First, the traditional uniform distribution strategy fails to fully consider the thermal distribution characteristics of the nacelle's three-dimensional space, resulting in insufficient detection resolution in high-temperature areas and a risk of missing abnormal temperature rises in critical components. Second, the broadband mechanical vibrations generated during wind turbine operation cause periodic oscillations and high-frequency micro-displacements in the sensor mounting base, leading to thermal imaging shifts and blurring, thus affecting temperature measurement accuracy. Third, the superposition of electromagnetic interference and thermal noise inside the nacelle affects the continuity of monitoring.

[0004] Current technological improvements mainly involve increasing sensor deployment density or introducing local compensation devices. However, while these methods can improve data acquisition accuracy to some extent, they also lead to a surge in the complexity of sensor network wiring and fail to fundamentally solve the problems of vibration and environmental interference. Summary of the Invention

[0005] To address the problems in the prior art, embodiments of the present invention provide a method and apparatus for dynamic vibration collaborative compensation of sensors with optimized spatial arrangement, which can at least partially solve the problems existing in the prior art.

[0006] On one hand, this invention proposes a dynamic vibration collaborative compensation method for sensors with optimized spatial arrangement, comprising:

[0007] Within the sensor monitoring domain, the overall coverage rate corresponding to each sensor is calculated based on the number of target grids covered by each sensor and the total number of grids.

[0008] With the goal of minimizing the number of sensors deployed and selecting the sensors with the greatest coverage gain, the overall coverage rate of all sensors is updated and iterated to achieve spatial optimization of the arrangement of all sensors and obtain the target sensor.

[0009] Temperature-based error compensation is performed on the data collected by each target sensor. Attitude calculation is then performed on the data collected by each target sensor after error compensation. Finally, compensation control is applied to the data collected by each target sensor after attitude calculation.

[0010] Prior to the step of calculating the overall coverage rate within the sensor monitoring domain based on the number of target grids covered by each sensor and the total number of grids, the dynamic vibration collaborative compensation method for spatially optimized sensor arrangement further includes:

[0011] The coverage radius of each infrared sensor is determined, and the spherical space with the installation location of each infrared sensor as the center and the coverage radius of each infrared sensor as the radius is defined as the sensor monitoring area corresponding to each infrared sensor.

[0012] The method for coordinated dynamic vibration compensation of spatially optimized sensors, following the step of determining the sensor monitoring domain corresponding to each infrared sensor, further includes:

[0013] Iterate through each infrared sensor and calculate the distance between the center of each grid and the installation position of the corresponding infrared sensor.

[0014] Grids with a coverage radius less than or equal to that of the corresponding infrared sensor are defined as the target grids covered by the corresponding sensor.

[0015] The step of performing temperature-based error compensation on the data collected by each target sensor includes:

[0016] Zero-bias correction is performed on the amplitude and direction data of the vibration acceleration of the wind turbine nacelle to obtain accelerometer correction data; zero-bias correction is performed on the sensor attitude angle change data to obtain gyroscope correction data;

[0017] The zero bias value used for zero bias correction is determined based on a pre-obtained temperature-zero bias relationship curve.

[0018] The step of performing attitude calculation on the data collected by each target sensor after error compensation includes:

[0019] The attitude of the target sensor is iteratively updated based on the sampling time interval and the gyroscope calibration data, using a quaternion algorithm.

[0020] A rotation matrix is ​​generated based on the updated target sensor attitude, and the vibration acceleration in the global coordinate system is calculated based on the rotation matrix and the accelerometer calibration data.

[0021] Subtracting the gravitational acceleration from the vibration acceleration in the global coordinate system yields the optimized vibration acceleration in the global coordinate system after removing the gravitational component.

[0022] The compensation control for the data collected by each target sensor after attitude calculation includes:

[0023] The optimized vibration acceleration is subjected to a Fourier transform, and the vibration displacement is calculated by a quadratic integral; the vibration displacement includes horizontal vibration displacement and vertical vibration displacement.

[0024] Based on the vertical vibration displacement and the vertical distance from the corresponding target sensor to the target monitoring plane, the pitch angle that the gimbal needs to compensate for is calculated; based on the horizontal vibration displacement and the vertical distance from the corresponding target sensor to the target monitoring plane, the yaw angle that the gimbal needs to compensate for is calculated.

[0025] The pitch angle and yaw angle are used as input deviations of the PID controller to calculate the control quantity, which is then converted into a stepper motor pulse signal to drive the gimbal to complete the angle correction within a specified time.

[0026] On one hand, the present invention proposes a dynamic vibration collaborative compensation device for sensors with optimized spatial arrangement, comprising:

[0027] The calculation unit is used to calculate the overall coverage rate corresponding to each sensor within the sensor monitoring domain, based on the number of target grids covered by each sensor and the total number of grids.

[0028] The deployment unit is used to update and iteratively calculate the overall coverage rate with the goal of minimizing the number of sensors deployed and selecting the sensor with the greatest coverage gain, thereby achieving spatial optimization of the deployment of all sensors and obtaining the target sensor.

[0029] The compensation unit is used to perform temperature-based error compensation on the data collected by each target sensor, perform attitude calculation on the data collected by each target sensor after error compensation, and perform compensation control on the data collected by each target sensor after attitude calculation.

[0030] In another aspect, embodiments of the present invention provide a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the following method:

[0031] Within the sensor monitoring domain, the overall coverage rate corresponding to each sensor is calculated based on the number of target grids covered by each sensor and the total number of grids.

[0032] With the goal of minimizing the number of sensors deployed and selecting the sensors with the greatest coverage gain, the overall coverage rate of all sensors is updated and iterated to achieve spatial optimization of the arrangement of all sensors and obtain the target sensor.

[0033] Temperature-based error compensation is performed on the data collected by each target sensor. Attitude calculation is then performed on the data collected by each target sensor after error compensation. Finally, compensation control is applied to the data collected by each target sensor after attitude calculation.

[0034] This invention provides a computer-readable storage medium, comprising:

[0035] The computer-readable storage medium stores a computer program that, when executed by a processor, implements the following method:

[0036] Within the sensor monitoring domain, the overall coverage rate corresponding to each sensor is calculated based on the number of target grids covered by each sensor and the total number of grids.

[0037] With the goal of minimizing the number of sensors deployed and selecting the sensors with the greatest coverage gain, the overall coverage rate of all sensors is updated and iterated to achieve spatial optimization of the arrangement of all sensors and obtain the target sensor.

[0038] Temperature-based error compensation is performed on the data collected by each target sensor. Attitude calculation is then performed on the data collected by each target sensor after error compensation. Finally, compensation control is applied to the data collected by each target sensor after attitude calculation.

[0039] This invention also provides a computer program product, which includes a computer program that, when executed by a processor, implements the following method:

[0040] Within the sensor monitoring domain, the overall coverage rate corresponding to each sensor is calculated based on the number of target grids covered by each sensor and the total number of grids.

[0041] With the goal of minimizing the number of sensors deployed and selecting the sensors with the greatest coverage gain, the overall coverage rate of all sensors is updated and iterated to achieve spatial optimization of the arrangement of all sensors and obtain the target sensor.

[0042] Temperature-based error compensation is performed on the data collected by each target sensor. Attitude calculation is then performed on the data collected by each target sensor after error compensation. Finally, compensation control is applied to the data collected by each target sensor after attitude calculation.

[0043] The present invention provides a method and apparatus for dynamic vibration collaborative compensation of sensors with spatially optimized arrangement. Within the sensor monitoring domain, the overall coverage rate corresponding to each sensor is calculated based on the number of target grids covered by each sensor and the total number of grids. The method iteratively updates and calculates the overall coverage rate of all sensors, targeting the sensor with the fewest deployments and the largest coverage gain, thereby achieving spatially optimized arrangement of all sensors to obtain the target sensors. Temperature-based error compensation is performed on the data collected by each target sensor. Attitude calculation is then performed on the error-compensated data collected by each target sensor. Compensation control is then applied to the attitude-calculated data collected by each target sensor. This enables refined thermal field reconstruction of key components, enhanced anti-interference capabilities, and improved long-term operational stability, thus providing a solid technical foundation for intelligent operation and maintenance of wind turbine units. Attached Figure Description

[0044] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. In the drawings:

[0045] Figure 1 This is a schematic flowchart of a dynamic vibration collaborative compensation method for sensors with spatially optimized arrangement provided in an embodiment of the present invention.

[0046] Figure 2 This is a three-dimensional coordinate system diagram of the cabin interior provided in an embodiment of the present invention.

[0047] Figure 3 This is a diagram of a three-dimensional mesh layout scheme provided in an embodiment of the present invention.

[0048] Figure 4 This is a diagram of the multi-band cross-validation architecture provided in an embodiment of the present invention.

[0049] Figure 5 This is a schematic diagram of the inertial measurement unit structure provided in an embodiment of the present invention.

[0050] Figure 6 This is a diagram of the dynamic vibration collaborative compensation mechanism provided in an embodiment of the present invention.

[0051] Figure 7 This is a schematic diagram of the structure of a dynamic vibration collaborative compensation device for sensors with spatially optimized arrangement provided in an embodiment of the present invention.

[0052] Figure 8 This is a schematic diagram of the physical structure of a computer device provided in an embodiment of the present invention. Detailed Implementation

[0053] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings. Here, the illustrative embodiments and descriptions of the present invention are used to explain the present invention, but are not intended to limit the present invention. It should be noted that, unless otherwise specified, the embodiments and features in the embodiments of this application can be arbitrarily combined with each other.

[0054] Figure 1 This is a flowchart illustrating a dynamic vibration collaborative compensation method for spatially optimized sensor arrangement according to an embodiment of the present invention, as shown below. Figure 1 As shown, the dynamic vibration collaborative compensation method for spatially optimized sensor arrangement provided in this embodiment of the invention includes:

[0055] Step S1: Within the sensor monitoring domain, calculate the overall coverage rate corresponding to each sensor based on the number of target grids covered by each sensor and the total number of grids.

[0056] Step S2: With the goal of minimizing the number of sensors deployed and selecting the sensor with the greatest coverage gain, update and iterate to calculate the coverage of all regions, thereby optimizing the spatial arrangement of all sensors and obtaining the target sensor.

[0057] Step S3: Perform temperature-based error compensation on the data collected by each target sensor, perform attitude calculation on the data collected by each target sensor after error compensation, and perform compensation control on the data collected by each target sensor after attitude calculation.

[0058] In step S1 above, the device calculates the overall coverage rate corresponding to each sensor within the sensor monitoring domain based on the number of target grids covered by each sensor and the total number of grids. The device can be a computer device executing this method. The acquisition, storage, use, and processing of data in this application's technical solution all comply with relevant regulations. Figure 2 As shown, a three-dimensional XYZ coordinate system is constructed inside the engine room, where a represents the main shaft, b represents the gearbox, and c represents the generator.

[0059] Before the step of calculating the overall coverage rate within the sensor monitoring domain based on the number of target grids covered by each sensor and the total number of grids, the dynamic vibration collaborative compensation method for spatially optimized sensor arrangement further includes:

[0060] To determine the coverage radius of each infrared sensor, the spherical space centered at the installation location of each sensor and with a coverage radius equal to that of each sensor is defined as the sensor monitoring area corresponding to each sensor. The coverage radius R of the i-th infrared sensor can be calculated using the following formula.i :

[0061]

[0062] Where θ is the field of view of the sensor, and D is the vertical distance from the sensor to the target monitoring plane. Specifically, it can be the vertical distance from the optical center of the sensor to the target monitoring plane. The target monitoring plane can be understood as the plane on which the sensor will monitor the target.

[0063] In 3D spatial modeling, the monitoring domain of each sensor is defined as the area around the installation location of the infrared sensor (x). i ,y i ,z i ( ) is the center of the sphere and the coverage radius R i For a sphere of radius , the mathematical expression is:

[0064]

[0065] Although the actual sensor field of view is conical, using a spherical model as a conservative estimate can avoid the risk of missed detections due to geometric simplification, and is especially suitable for the redundancy design requirements inside complex mechanical structures.

[0066] After determining the sensor monitoring domain corresponding to each infrared sensor, the dynamic vibration collaborative compensation method for spatially optimized sensor arrangement further includes:

[0067] Iterate through each infrared sensor and calculate the distance between the center of each grid and the installation position of the corresponding infrared sensor.

[0068] Grids with a coverage radius less than or equal to that of the corresponding infrared sensor are defined as the target grids covered by the corresponding sensor. To quantify the overall system coverage, the three-dimensional space of the cabin is discretized into a cubic grid with a side length of 0.2 meters, and the center coordinates of each grid are (x... g ,y g ,z g Subsequently, the distance d between each sensor and the grid center is calculated according to the following formula. g :

[0069]

[0070] If d g ≤R i If a grid cell is covered, it is marked as covered. The overall coverage rate is calculated by determining the proportion of covered grid cells to the total number of grid cells.

[0071] In step S2 above, the device aims to minimize the number of sensors deployed while selecting sensors with the highest coverage gain. Iteratively calculating the overall coverage rate optimizes the spatial arrangement of all sensors to obtain the target sensors. The sensor layout optimization employs a greedy algorithm, iteratively selecting the sensor node with the highest coverage gain to minimize the number of sensors deployed. The three-dimensional network deployment scheme of this invention is as follows: Figure 3 As shown.

[0072] The dynamic vibration collaborative compensation method for the spatially optimized sensor arrangement also includes:

[0073] The cabin is divided into high-temperature, medium-temperature, and low-temperature zones;

[0074] A master sensor with a first-band numerical range is deployed in the high-temperature region, and slave sensors with a second-band numerical range are deployed in the medium-temperature region and the low-temperature region; the values ​​in the second-band numerical range are higher than the values ​​in the first-band numerical range.

[0075] A dual-band sensor is deployed at the boundary between the high-temperature zone and the medium-temperature zone; the fluctuation value range of the dual-band sensor includes the first band value range and the second band value range. The first band value range can be selected as 3-5 μm. The second band value range can be selected as 8-14 μm.

[0076] like Figure 4 As shown, based on the three-dimensional coordinate system inside the engine room and using historical operating data and a thermal simulation model, the engine room is divided into a high-temperature zone (including gearbox bearings and generator windings), a medium-temperature zone (including the hydraulic system and pitch motor), and a low-temperature zone (including the control cabinet and cable connectors). Among the target sensor nodes selected by the greedy algorithm, primary sensors with a wavelength of 3-5μm are prioritized for deployment in the high-temperature zone. Among the remaining nodes, slave sensors with a wavelength of 8-14μm are deployed in nodes that can cover the largest medium and low-temperature zones. At the boundary between the high-temperature and medium-temperature zones (such as the gearbox-generator connection), dual-band sensors are deployed regardless of the greedy algorithm's priority. It should be noted that the generator spans both the high-temperature and medium-temperature zones, while the generator connection is in the medium-temperature zone; therefore, the difference between the gearbox and generator connection can be selected as the boundary between the high-temperature and medium-temperature zones.

[0077] By rationally allocating sensors of different frequency bands, comprehensive and efficient coverage of the inside of the wind turbine can be achieved.

[0078] Further concealed, interference-resistant cabling design can be implemented:

[0079] Based on the 3D model of the cabin, available concealed passages were identified, and pre-drilled holes were made in the internal cavities of the support beams and equipment bases. Modular metal square tubes were pre-installed along the main beams and cabin walls, with cable tray spacing ≥20cm to avoid electromagnetic crosstalk. The cable shielding design adopted a double-layer structure of copper wire braiding (coverage >95%, thickness 0.1mm) and aluminum foil wrapping (overlap rate >30%, thickness 0.05mm) to suppress high-frequency (>1kHz) and low-frequency (<1kHz) interference, respectively. All shielding layers were connected to the main grounding busbar of the cabin at a single point (grounding resistance ≤0.1Ω) and isolated in sections through insulating joints to eliminate ground loop interference.

[0080] In step S3 above, the device performs temperature-based error compensation on the data collected by each target sensor, performs attitude calculation on the error-compensated data collected by each target sensor, and performs compensation control on the attitude-calculated data collected by each target sensor. For example... Figure 5 As shown, data acquisition can be achieved using a multi-sensor fusion architecture based on an inertial measurement unit (IMU). The multi-sensor fusion architecture includes a three-axis MEMS accelerometer, a three-axis MEMS gyroscope, a temperature compensation module, and a data fusion processor. The three-axis MEMS accelerometer and the three-axis MEMS gyroscope are respectively connected to the temperature compensation module, and the temperature compensation module is connected to the data fusion processor.

[0081] The accelerometer has a range of ±16g and a bandwidth of 0-500Hz, used to capture the amplitude and direction of vibration acceleration in the wind turbine nacelle; the gyroscope has a range of ±2000° / s and a bandwidth of 0-400Hz, used to detect changes in sensor attitude angle in real time. To eliminate the influence of temperature drift, the temperature compensation module incorporates a digital temperature sensor (accuracy ±0.5℃) to dynamically correct output deviations of MEMS devices, and uses a data fusion processor (optional low-power MCU) to achieve synchronous acquisition of data from multiple sensors. The IMU hardware nodes are deployed in vibration-sensitive areas such as the gearbox base and generator bearing housing, using a rigid mounting method to shorten the vibration transmission path.

[0082] like Figure 6 As shown, temperature-based error compensation, attitude calculation, and compensation control can be collectively referred to as a dynamic vibration collaborative compensation mechanism.

[0083] The step of performing temperature-based error compensation on the data collected by each target sensor includes:

[0084] Zero-bias correction is performed on the amplitude and direction data of the vibration acceleration of the wind turbine nacelle to obtain accelerometer correction data; zero-bias correction is performed on the sensor attitude angle change data to obtain gyroscope correction data;

[0085] The zero bias value used for zero bias correction is determined based on a pre-obtained temperature-zero bias relationship curve.

[0086] During the data acquisition phase, the IMU achieves cross-device synchronization with the infrared sensor and motorized gimbal via hardware trigger signals. The accelerometer outputs raw triaxial data a. x a y and a z (Unit: g) The gyroscope outputs the three-axis angular velocity ω x ω y and ω z (Unit: ° / s). During dynamic operation, the raw data is first subjected to zero-bias correction. Under static conditions, the zero-bias values ​​of the accelerometer and gyroscope are calculated as a. a and ω g The calibrated data is obtained by subtracting the measured value in real time, as shown in the following formula:

[0087] a corrected =a raw -a a

[0088] ω corrected =ω raw -ω g

[0089] Among them, a corrected For accelerometer calibration data, ω corrected For gyroscope calibration data, a raw This refers to the amplitude and direction data of the vibration acceleration of the wind turbine nacelle, i.e., the raw data output by the accelerometer; ω raw This refers to the sensor's attitude angle change data, i.e., the raw data output by the gyroscope.

[0090] The temperature-zero bias curve reflects the trend of the zero bias value as it changes with temperature. Knowing the current temperature, we can map the corresponding value 'a' to the temperature using the temperature-zero bias curve. a and ω g This eliminates errors caused by fluctuations in ambient temperature.

[0091] The process of calculating the attitude of each target sensor's acquired data after error compensation includes:

[0092] The attitude of the target sensor is iteratively updated based on the sampling time interval and the gyroscope calibration data, using a quaternion algorithm.

[0093] A rotation matrix is ​​generated based on the updated target sensor attitude, and the vibration acceleration in the global coordinate system is calculated based on the rotation matrix and the accelerometer calibration data.

[0094] Subtracting the gravitational acceleration from the vibration acceleration in the global coordinate system yields the optimized vibration acceleration in the global coordinate system after removing the gravitational component.

[0095] During the attitude calculation phase, the sensor attitude is iteratively updated based on a quaternion algorithm. In the wind turbine vibration compensation scenario, the purpose of attitude calculation is to accurately sense the sensor's own angle changes, thereby adjusting the gimbal angle in the opposite direction to counteract the field-of-view shift caused by vibration. The target sensor's attitude is iteratively updated according to the following formula:

[0096]

[0097] In the formula, q k The quaternion at the current moment (describing the current attitude); Δt is the sampling time interval, with a 100Hz update frequency corresponding to 0.01 seconds; This represents quaternion multiplication.

[0098] Transform the quaternion q into a 3×3 rotation matrix R(q), transform the acceleration vector in the sensor coordinate system to the global coordinate system (the fixed coordinate system of the cabin), and separate the vibration acceleration and gravity components, as shown in the following equation:

[0099] a global =R(q)·a corrected

[0100] a vibration =a global -[0,0,g]

[0101] Among them, a global Let a be the vibration acceleration in the global coordinate system. vibration This is the optimized vibration acceleration in the global coordinate system after removing the gravitational component, where g is the gravitational acceleration.

[0102] The compensation control for the data collected by each target sensor after attitude calculation includes:

[0103] The optimized vibration acceleration is subjected to a Fourier transform, and the vibration displacement is calculated by a quadratic integral; the vibration displacement includes horizontal vibration displacement and vertical vibration displacement.

[0104] Based on the vertical vibration displacement and the vertical distance from the corresponding target sensor to the target monitoring plane, the pitch angle that the gimbal needs to compensate for is calculated; based on the horizontal vibration displacement and the vertical distance from the corresponding target sensor to the target monitoring plane, the yaw angle that the gimbal needs to compensate for is calculated.

[0105] The pitch angle and yaw angle are used as input deviations of the PID controller to calculate the control quantity, which is then converted into a stepper motor pulse signal to drive the gimbal to complete the angle correction within a specified time.

[0106] During the compensation control phase, for a vibrationA 256-point FFT transformation is performed, followed by quadratic integration to calculate the vibration displacement d, as shown in the following equation:

[0107] d=∫∫a vibration dt 2

[0108] Based on the distance D from the sensor to the target, the gimbal pitch angle and yaw angle are calculated as follows:

[0109]

[0110] Where Δθ and Δφ are the pitch and yaw angles that the gimbal needs to compensate for, respectively; d x and d y These are the horizontal vibration displacement and the vertical vibration displacement, respectively.

[0111] The angular offsets Δθ and Δφ are used as the input deviation e(t) of the PID controller, as shown in the following equation:

[0112]

[0113] This is a standard PID controller; the relevant parameters will not be described in detail here.

[0114] The control quantity u(t) is converted into a stepper motor pulse signal to drive the gimbal to complete the angle correction within a specified time.

[0115] The dynamic vibration collaborative compensation method for spatially optimized sensor arrangement provided in this invention mainly solves the technical problem through the following technical solutions:

[0116] 1. Construct an XYZ three-dimensional coordinate system inside the cabin, solve for the effective coverage radius and monitoring domain of a single infrared sensor, discretize the three-dimensional space of the cabin, calculate the full coverage rate, and use a greedy algorithm to iteratively select the candidate node with the largest coverage gain to minimize the number of deployments.

[0117] 2. Based on the thermal radiation characteristics of components in different temperature zones, the monitoring area is divided into high-temperature zone, medium-temperature zone and low-temperature zone. 3-5μm band sensors are deployed in the high-temperature zone, 8-14μm band sensors are configured in the normal temperature zone, and dual-band overlapping monitoring nodes are set at the boundary between the high-temperature zone and the normal temperature zone.

[0118] 3. The power supply and communication lines of the sensors are embedded inside the square tube of the cabin structure, and double-layer metal braided shielding is used to protect against electromagnetic interference.

[0119] 4. Inertial measurement units (IMUs) are integrated in vibration-sensitive areas such as the gearbox base. By acquiring three-dimensional vibration data in real time, the electric pan-tilt unit is driven to perform PID closed-loop control, thereby realizing dynamic compensation and adjustment of the sensor's field of view.

[0120] The dynamic vibration collaborative compensation method for sensors with optimized spatial arrangement provided in this invention has the following beneficial technical effects:

[0121] 1. This invention overcomes the limitations of traditional two-dimensional uniform distribution strategies by deploying a master-slave sensor array, eliminates monitoring blind spots caused by environmental noise or obstruction of a single sensor, ensures full coverage of the internal space of the wind turbine, improves the accuracy of hot spot detection of key components, and provides high-confidence temperature field data for intelligent operation and maintenance systems.

[0122] 2. The concealed anti-interference wiring design proposed in this invention achieves high reliability deployment of sensor cables inside wind turbines through structural integration, multi-layer shielding and path optimization, reduces maintenance risks caused by exposed cables, and meets the long-term reliable operation requirements of wind turbines in harsh environments.

[0123] 3. This invention achieves full-degree-of-freedom compensation for the pitch and yaw angles of the sensor through coordinate system transformation and kinematic model calculation, eliminates the composite interference caused by multi-dimensional vibration coupling, actively cancels the field of view shift caused by vibration, significantly improves the stability of the thermal imaging sensor, and effectively solves the problems of image blurring and data distortion of wind turbines in high vibration scenarios.

[0124] The dynamic vibration collaborative compensation method for spatially optimized sensor arrangement provided in this invention calculates the overall coverage rate corresponding to each sensor within the sensor monitoring domain based on the number of target grids covered by each sensor and the total number of grids. Iteratively calculating the overall coverage rate of all sensors with the minimum number of deployed sensors and the maximum coverage gain is then performed to optimize the spatial arrangement of all sensors and obtain the target sensors. Temperature-based error compensation is applied to the data collected by each target sensor. Attitude calculation is then performed on the error-compensated data collected by each target sensor. Compensation control is then applied to the attitude-calculated data collected by each target sensor. This method enables refined thermal field reconstruction of key components, enhanced anti-interference capabilities, and improved long-term operational stability, thus providing a solid technical foundation for intelligent operation and maintenance of wind turbine units.

[0125] Furthermore, prior to the step of calculating the overall coverage rate within the sensor monitoring domain based on the number of target grids covered by each sensor and the total number of grids, the dynamic vibration collaborative compensation method for spatially optimized sensor arrangement further includes:

[0126] The coverage radius of each infrared sensor is determined by defining a spherical space centered at the installation location of each infrared sensor and with the coverage radius of each sensor as its radius. This space is then defined as the sensor monitoring area corresponding to each infrared sensor. This can be referred to the above embodiment for further explanation and will not be repeated here.

[0127] Furthermore, after determining the sensor monitoring domain corresponding to each infrared sensor, the dynamic vibration collaborative compensation method for the spatially optimized sensor arrangement further includes:

[0128] For each infrared sensor, calculate the distance between the center of each grid and the installation position of the corresponding infrared sensor; refer to the above embodiment for explanation, and will not be repeated here.

[0129] The grids whose coverage radius is less than or equal to that of the corresponding infrared sensor are defined as the target grids covered by the corresponding sensor. This can be referred to the above embodiments for further explanation, and will not be repeated here.

[0130] Furthermore, the step of performing temperature-based error compensation on the data collected by each target sensor includes:

[0131] Zero-bias correction is performed on the amplitude and direction data of the vibration acceleration of the wind turbine nacelle to obtain accelerometer correction data; zero-bias correction is performed on the sensor attitude angle change data to obtain gyroscope correction data; the above embodiments can be referred to for explanation, and will not be repeated here.

[0132] The zero-bias value used for zero-bias correction is determined based on a pre-obtained temperature-zero-bias relationship curve. This can be referred to the above embodiments for further explanation and will not be repeated here.

[0133] Furthermore, the attitude calculation of the acquired data from each target sensor after error compensation includes:

[0134] The attitude of the target sensor is iteratively updated based on the sampling time interval and the gyroscope calibration data using a quaternion algorithm; this can be referred to the above embodiments for explanation, and will not be repeated here.

[0135] A rotation matrix is ​​generated based on the updated attitude of the target sensor. The vibration acceleration in the global coordinate system is calculated based on the rotation matrix and the accelerometer correction data. This can be referred to the above embodiment for explanation, and will not be repeated here.

[0136] Subtracting the gravitational acceleration from the vibration acceleration in the global coordinate system yields the optimized vibration acceleration in the global coordinate system after removing the gravitational component. This can be referred to the above embodiments for further explanation and will not be repeated here.

[0137] Furthermore, the compensation control for the data acquired by each target sensor after attitude calculation includes:

[0138] The optimized vibration acceleration is subjected to a Fourier transform, and the vibration displacement is calculated by a quadratic integral; the vibration displacement includes horizontal vibration displacement and vertical vibration displacement; the above embodiments can be referred to for explanation, and will not be repeated here.

[0139] The pitch angle that the gimbal needs to compensate for is calculated based on the vertical vibration displacement and the vertical distance from the corresponding target sensor to the target monitoring plane; the yaw angle that the gimbal needs to compensate for is calculated based on the horizontal vibration displacement and the vertical distance from the corresponding target sensor to the target monitoring plane; these can be referred to the above embodiments for explanation, and will not be repeated here.

[0140] The pitch angle and yaw angle are used as input deviations for the PID controller to calculate the control quantity, which is then converted into a stepper motor pulse signal to drive the gimbal to complete the angle correction within a specified time. This can be referred to the above embodiment for further explanation and will not be repeated here.

[0141] Figure 7 This is a schematic diagram of the structure of a dynamic vibration collaborative compensation device for sensors with optimized spatial arrangement according to an embodiment of the present invention, as shown below. Figure 7 As shown, the dynamic vibration collaborative compensation device for spatially optimized sensor arrangement provided in this embodiment of the invention includes a calculation unit 701, an arrangement unit 702, and a compensation unit 703, wherein:

[0142] The calculation unit 701 is used to calculate the overall coverage rate corresponding to each sensor within the sensor monitoring domain based on the number of target grids covered by each sensor and the total number of grids. The layout unit 702 is used to update and iteratively calculate the overall coverage rate of all sensors with the minimum number of sensor deployments and the maximum coverage gain as the target, thereby achieving spatial optimization of the layout of all sensors and obtaining the target sensors. The compensation unit 703 is used to perform temperature-based error compensation on the data collected by each target sensor, perform attitude calculation on the data collected by each target sensor after error compensation, and perform compensation control on the data collected by each target sensor after attitude calculation.

[0143] Specifically, the calculation unit 701 in the device is used to calculate the overall coverage rate corresponding to each sensor within the sensor monitoring domain based on the number of target grids covered by each sensor and the total number of grids; the arrangement unit 702 is used to update and iteratively calculate all overall coverage rates with the goal of selecting the sensor with the fewest sensor deployments and the largest coverage gain, thereby achieving spatial optimization of the arrangement of all sensors to obtain the target sensor; the compensation unit 703 is used to perform temperature-based error compensation on the data collected by each target sensor, perform attitude calculation on the data collected by each target sensor after error compensation, and perform compensation control on the data collected by each target sensor after attitude calculation.

[0144] The dynamic vibration collaborative compensation device for spatially optimized sensor arrangement provided in this invention calculates the overall coverage rate corresponding to each sensor within the sensor monitoring domain based on the number of target grids covered by each sensor and the total number of grids. It then iteratively calculates the overall coverage rate of all sensors, targeting the sensor with the fewest deployments and the highest coverage gain, thereby achieving spatially optimized arrangement of all sensors to obtain the target sensors. Temperature-based error compensation is performed on the data collected by each target sensor, and attitude calculation is performed on the error-compensated data. Compensation control is then applied to the attitude-calculated data, enabling refined thermal field reconstruction of key components, enhanced anti-interference capabilities, and improved long-term operational stability, thus providing a solid technical foundation for intelligent operation and maintenance of wind turbine units.

[0145] Furthermore, prior to the step of calculating the overall coverage rate within the sensor monitoring domain based on the number of target grids covered by each sensor and the total number of grids, the dynamic vibration collaborative compensation device for the spatially optimized sensor arrangement is also used for:

[0146] The coverage radius of each infrared sensor is determined, and the spherical space with the installation location of each infrared sensor as the center and the coverage radius of each infrared sensor as the radius is defined as the sensor monitoring area corresponding to each infrared sensor.

[0147] Furthermore, after determining the sensor monitoring domain corresponding to each infrared sensor, the spatially optimized sensor dynamic vibration collaborative compensation device is also used for:

[0148] Iterate through each infrared sensor and calculate the distance between the center of each grid and the installation position of the corresponding infrared sensor.

[0149] Grids with a coverage radius less than or equal to that of the corresponding infrared sensor are defined as the target grids covered by the corresponding sensor.

[0150] Furthermore, the compensation unit 703 is specifically used for:

[0151] Zero-bias correction is performed on the amplitude and direction data of the vibration acceleration of the wind turbine nacelle to obtain accelerometer correction data; zero-bias correction is performed on the sensor attitude angle change data to obtain gyroscope correction data;

[0152] The zero bias value used for zero bias correction is determined based on a pre-obtained temperature-zero bias relationship curve.

[0153] Furthermore, the compensation unit 703 is specifically used for:

[0154] The attitude of the target sensor is iteratively updated based on the sampling time interval and the gyroscope calibration data, using a quaternion algorithm.

[0155] A rotation matrix is ​​generated based on the updated target sensor attitude, and the vibration acceleration in the global coordinate system is calculated based on the rotation matrix and the accelerometer calibration data.

[0156] Subtracting the gravitational acceleration from the vibration acceleration in the global coordinate system yields the optimized vibration acceleration in the global coordinate system after removing the gravitational component.

[0157] Furthermore, the compensation unit 703 is specifically used for:

[0158] The optimized vibration acceleration is subjected to a Fourier transform, and the vibration displacement is calculated by a quadratic integral; the vibration displacement includes horizontal vibration displacement and vertical vibration displacement.

[0159] Based on the vertical vibration displacement and the vertical distance from the corresponding target sensor to the target monitoring plane, the pitch angle that the gimbal needs to compensate for is calculated; based on the horizontal vibration displacement and the vertical distance from the corresponding target sensor to the target monitoring plane, the yaw angle that the gimbal needs to compensate for is calculated.

[0160] The pitch angle and yaw angle are used as input deviations of the PID controller to calculate the control quantity, which is then converted into a stepper motor pulse signal to drive the gimbal to complete the angle correction within a specified time.

[0161] The embodiments of the present invention provide a dynamic vibration collaborative compensation device for sensors with optimized spatial arrangement, which can be used to execute the processing flow of the above-described method embodiments. Its functions will not be repeated here, but can be referred to the detailed description of the above-described method embodiments.

[0162] Figure 8 This is a schematic diagram of the physical structure of a computer device provided in an embodiment of the present invention, such as... Figure 8 As shown, the computer device includes: a memory 801, a processor 802, and a computer program stored in the memory 801 and executable on the processor 802. When the processor 802 executes the computer program, it implements the following method:

[0163] Within the sensor monitoring domain, the overall coverage rate corresponding to each sensor is calculated based on the number of target grids covered by each sensor and the total number of grids.

[0164] With the goal of minimizing the number of sensors deployed and selecting the sensors with the greatest coverage gain, the overall coverage rate of all sensors is updated and iterated to achieve spatial optimization of the arrangement of all sensors and obtain the target sensor.

[0165] Temperature-based error compensation is performed on the data collected by each target sensor. Attitude calculation is then performed on the data collected by each target sensor after error compensation. Finally, compensation control is applied to the data collected by each target sensor after attitude calculation.

[0166] This embodiment discloses a computer program product, which includes a computer program that, when executed by a processor, implements the following method:

[0167] Within the sensor monitoring domain, the overall coverage rate corresponding to each sensor is calculated based on the number of target grids covered by each sensor and the total number of grids.

[0168] With the goal of minimizing the number of sensors deployed and selecting the sensors with the greatest coverage gain, the overall coverage rate of all sensors is updated and iterated to achieve spatial optimization of the arrangement of all sensors and obtain the target sensor.

[0169] Temperature-based error compensation is performed on the data collected by each target sensor. Attitude calculation is then performed on the data collected by each target sensor after error compensation. Finally, compensation control is applied to the data collected by each target sensor after attitude calculation.

[0170] This embodiment provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the following method:

[0171] Within the sensor monitoring domain, the overall coverage rate corresponding to each sensor is calculated based on the number of target grids covered by each sensor and the total number of grids.

[0172] With the goal of minimizing the number of sensors deployed and selecting the sensors with the greatest coverage gain, the overall coverage rate of all sensors is updated and iterated to achieve spatial optimization of the arrangement of all sensors and obtain the target sensor.

[0173] Temperature-based error compensation is performed on the data collected by each target sensor. Attitude calculation is then performed on the data collected by each target sensor after error compensation. Finally, compensation control is applied to the data collected by each target sensor after attitude calculation.

[0174] Compared with existing technologies, the dynamic vibration collaborative compensation method for spatially optimized sensor arrangement provided in this invention calculates the overall coverage rate corresponding to each sensor within the sensor monitoring domain based on the number of target grids covered by each sensor and the total number of grids. It then iteratively updates and calculates the overall coverage rate of all sensors, targeting the sensor with the fewest deployments and the largest coverage gain, thereby achieving spatial optimization of all sensors and obtaining the target sensors. Temperature-based error compensation is performed on the data collected by each target sensor, and attitude calculation is performed on the error-compensated data. Compensation control is then applied to the attitude-calculated data, enabling refined thermal field reconstruction of key components, enhanced anti-interference capabilities, and improved long-term operational stability, thus providing a solid technical foundation for intelligent operation and maintenance of wind turbine units.

[0175] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0176] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0177] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0178] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0179] In the description of this specification, the references to terms such as "an embodiment," "a specific embodiment," "some embodiments," "for example," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0180] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for dynamic vibration collaborative compensation of sensors with optimized spatial arrangement, characterized in that, include: Within the sensor monitoring domain, the overall coverage rate corresponding to each sensor is calculated based on the number of target grids covered by each sensor and the total number of grids. With the goal of minimizing the number of sensors deployed and selecting the sensors with the greatest coverage gain, the overall coverage rate of all sensors is updated and iterated to achieve spatial optimization of the arrangement of all sensors and obtain the target sensor. Temperature-based error compensation is performed on the data collected by each target sensor. Attitude calculation is then performed on the data collected by each target sensor after error compensation. Finally, compensation control is applied to the data collected by each target sensor after attitude calculation.

2. The dynamic vibration collaborative compensation method for sensors with optimized spatial arrangement according to claim 1, characterized in that, Before the step of calculating the overall coverage rate within the sensor monitoring domain based on the number of target grids covered by each sensor and the total number of grids, the dynamic vibration collaborative compensation method for spatially optimized sensor arrangement further includes: The coverage radius of each infrared sensor is determined, and the spherical space with the installation location of each infrared sensor as the center and the coverage radius of each infrared sensor as the radius is defined as the sensor monitoring area corresponding to each infrared sensor.

3. The dynamic vibration collaborative compensation method for sensors with optimized spatial arrangement according to claim 2, characterized in that, After determining the sensor monitoring domain corresponding to each infrared sensor, the dynamic vibration collaborative compensation method for spatially optimized sensor arrangement further includes: Iterate through each infrared sensor and calculate the distance between the center of each grid and the installation position of the corresponding infrared sensor. Grids with a coverage radius less than or equal to that of the corresponding infrared sensor are defined as the target grids covered by the corresponding sensor.

4. The dynamic vibration collaborative compensation method for sensors with optimized spatial arrangement according to claim 1, characterized in that, The step of performing temperature-based error compensation on the data collected by each target sensor includes: Zero-bias correction is performed on the amplitude and direction data of the vibration acceleration of the wind turbine nacelle to obtain accelerometer correction data; zero-bias correction is performed on the sensor attitude angle change data to obtain gyroscope correction data; The zero bias value used for zero bias correction is determined based on a pre-obtained temperature-zero bias relationship curve.

5. The dynamic vibration collaborative compensation method for sensors with optimized spatial arrangement according to claim 4, characterized in that, The process of calculating the attitude of each target sensor's acquired data after error compensation includes: The attitude of the target sensor is iteratively updated based on the sampling time interval and the gyroscope calibration data, using a quaternion algorithm. A rotation matrix is ​​generated based on the updated target sensor attitude, and the vibration acceleration in the global coordinate system is calculated based on the rotation matrix and the accelerometer calibration data. Subtracting the gravitational acceleration from the vibration acceleration in the global coordinate system yields the optimized vibration acceleration in the global coordinate system after removing the gravitational component.

6. The dynamic vibration collaborative compensation method for sensors with optimized spatial arrangement according to claim 5, characterized in that, The compensation control for the data collected by each target sensor after attitude calculation includes: The optimized vibration acceleration is subjected to a Fourier transform, and the vibration displacement is calculated by a quadratic integral; the vibration displacement includes horizontal vibration displacement and vertical vibration displacement. Based on the vertical vibration displacement and the vertical distance from the corresponding target sensor to the target monitoring plane, the pitch angle that the gimbal needs to compensate for is calculated; based on the horizontal vibration displacement and the vertical distance from the corresponding target sensor to the target monitoring plane, the yaw angle that the gimbal needs to compensate for is calculated. The pitch angle and yaw angle are used as input deviations of the PID controller to calculate the control quantity, which is then converted into a stepper motor pulse signal to drive the gimbal to complete the angle correction within a specified time.

7. A dynamic vibration collaborative compensation device for sensors with optimized spatial arrangement, characterized in that, include: The calculation unit is used to calculate the overall coverage rate corresponding to each sensor within the sensor monitoring domain, based on the number of target grids covered by each sensor and the total number of grids. The deployment unit is used to update and iteratively calculate the overall coverage rate with the goal of minimizing the number of sensors deployed and selecting the sensor with the greatest coverage gain, thereby achieving spatial optimization of the deployment of all sensors and obtaining the target sensor. The compensation unit is used to perform temperature-based error compensation on the data collected by each target sensor, perform attitude calculation on the data collected by each target sensor after error compensation, and perform compensation control on the data collected by each target sensor after attitude calculation.

8. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method of any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method of any one of claims 1 to 6.

10. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the method of any one of claims 1 to 6.

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