An infrared thermography non-destructive testing method for a wind turbine blade

Abstract

The present application relates to a kind of infrared thermography nondestructive testing methods of wind turbine blade, comprising the following steps: 1), unmanned aerial vehicle takes off, flies to the position to be detected, and is adsorbed in the region to be measured;2), central control processing system activates infrared thermal imager, makes the temperature of blade to be measured zone gradually increase, and real-time acquisition of the infrared image of the region to be measured, record the temperature distribution of blade in the process of temperature rise;3), central control processing system processes infrared image, identifies abnormal area in temperature distribution, and extracts key features from infrared image;4), use the extracted features to detect anomaly, compare the features under normal state, identify the internal defects or abnormalities of blade;5), after completing the detection of the region, go to the next region to be measured, and repeat the operation of 2) to 4).The present application realizes high-precision detection to internal small defects of blade by unmanned aerial vehicle combined with infrared thermography technology, improves the accuracy and efficiency of detection.

Description

Technical field

[0001] The present invention relates to an infrared thermal imaging nondestructive testing method, in particular to an infrared thermal imaging nondestructive testing method for wind turbine blades, which can accurately detect wind turbine blades and belongs to the technical field of nondestructive testing. [Background Technology]

[0002] With the increasing depletion of fossil energy, finding clean, practical, and renewable energy sources has become an urgent issue. Wind energy has attracted considerable attention for its renewable, widespread, and pollution-free nature. Its primary utilization method is to convert wind energy into electricity through wind turbines. Wind energy is one of the most technologically mature and widely marketed renewable energy sources. During the energy transition, the quality and safety of wind turbines are crucial. As key components of wind turbines, wind blades are subject to complex stress conditions during their long-term service life, including bending loads, inertial forces, and torsional loads. Furthermore, they are inevitably affected by various adverse weather conditions, such as strong winds, salt spray, thunderstorms, sandstorms, rain, and snow, which can lead to varying degrees of defects and damage to wind blades.

[0003] Traditional nondestructive testing methods for wind turbine blades primarily include visual inspection and conventional testing equipment (such as ultrasonic testing and vibration testing). These methods suffer from the following issues: 1) Conventional testing equipment typically requires direct contact with the blade surface, potentially damaging the blade, especially when detecting small defects; 2) Traditional methods are often limited by the testing environment and equipment maintenance, making comprehensive and efficient internal inspection of blades impossible; 3) Visual inspection requires manual labor, resulting in low efficiency, while conventional testing equipment may require downtime for inspection, impacting wind turbine operation time.

[0004] Therefore, in order to solve the above problems, it is necessary to provide an innovative infrared thermal imaging non-destructive testing method for wind turbine blades to overcome the above defects in the prior art. [Summary of the invention]

[0005] To solve the above problems, the purpose of the present invention is to provide an infrared thermal imaging non-destructive testing method for wind turbine blades, which adopts an adsorption-type drone and an infrared thermal imaging device, combined with advanced algorithms, to efficiently realize damage detection of wind turbine blades.

[0006] To achieve the above-mentioned object, the technical solution adopted by the present invention is as follows: a method for nondestructive testing of wind turbine blades by infrared thermal imaging, which adopts an adsorption-type drone infrared thermal imaging device, which includes a drone, a central control and processing system, an infrared thermal imager, a telescopic connecting rod device and an adsorption device;

[0007] The detection method comprises the following steps:

[0008] 1) The drone takes off, flies to the position of the blade to be tested, and is attached to the area to be tested by the adsorption device;

[0009] 2) The central control processing system activates the infrared thermal imager to generate a moderate heat source, gradually increasing the temperature of the blade test area. It also collects infrared images of the test area in real time and records the temperature distribution of the blade during the heating process.

[0010] 3) The central control processing system processes the infrared image, identifies abnormal areas in the temperature distribution, and extracts key features from the infrared image;

[0011] 4) Using the extracted features to perform anomaly detection, comparing the features under normal conditions, identifying internal defects or anomalies in the blade, and generating a detailed inspection report;

[0012] 5) After completing the inspection of the area, use the roller of the adsorption device to move to the next area to be tested and repeat the operations from 2) to 4).

[0013] The infrared thermal imaging nondestructive testing method for wind turbine blades of the present invention is further as follows: the infrared thermal imager is connected to the central control processing system via a telescopic connecting rod device, and a universal knob is installed inside the telescopic connecting rod device, so that the infrared thermal imager can perform a full-angle detection of the area to be tested; the infrared thermal imager includes an infrared imaging camera and a flash lamp.

[0014] The infrared thermal imaging nondestructive testing method for wind turbine blades of the present invention further comprises: the step 1) specifically comprises:

[0015] 1-1), the drone arrives above the area to be tested and slowly descends until the retractable suction cup of the adsorption device accurately fits the area to be tested;

[0016] 1-2), the exhaust valve on the retractable suction cup of the adsorption device starts to start, and the air in the surface of the test area is discharged, so that it is firmly adsorbed. After the air is exhausted, the exhaust valve is closed;

[0017] 1-3), after the inspection of the area is completed, the propeller of the drone begins to reverse until the lift of the propeller is equal to the adsorption force of the adsorption device. The roller of the adsorption device starts and moves the device to the next inspection area for inspection.

[0018] The infrared thermal imaging nondestructive testing method for wind turbine blades of the present invention further comprises: in step 2), the infrared thermal imaging image acquisition method is as follows:

[0019] 2-1), turn on the infrared thermal imager;

[0020] 2-2), the infrared thermal imager starts to record thermal images at a fixed frame rate, and after a delay, saves the thermal images formed when the halogen flash lamp is excited;

[0021] 2-3), the collected infrared thermal images are processed.

[0022] The infrared thermal imaging nondestructive testing method for wind turbine blades of the present invention further comprises: in step 3), the temperature abnormality area is determined by temperature gradient calculation, and the method is as follows:

[0023] 3-1), assuming that the surface temperature field of the wind turbine blade can be described by a two-dimensional temperature distribution function T(x, y, t), where x and y are the coordinates on the blade surface and t is time;

[0024] 3-2), set the active heat source to heat the blade, generating an additional heat source, represented by Q(x,y,t);

[0025] 3-3), the heat conduction equation is used to describe the evolution of the temperature field:

[0026]

[0027] Where: ρ is the density of the blade, c is the specific heat capacity of the blade, k is the thermal conductivity of the blade, is the divergence operator;

[0028] 3-4), the infrared thermal imaging device senses the infrared radiation of the blade to be tested and obtains the temperature distribution image T of the test area 内部 (x, y, t); by processing the infrared image, denoising, and calibrating the temperature, the processed internal temperature distribution image T is obtained 处理后 (x,y,t);

[0029] 3-5), calculate the temperature gradient, which represents the rate of change of the temperature field:

[0030]

[0031] in, represents the temperature gradient;

[0032] 3-6) Using the location and intensity information of the thermal gradient source, identify the abnormal temperature area caused by the active heat source:

[0033]

[0034] Where P(x,y,t) represents the abnormal area.

[0035] The infrared thermal imaging nondestructive testing method for wind turbine blades of the present invention further comprises: in step 4), the blade abnormality determination method is specifically as follows:

[0036] 4-1), using the dynamic baseline model, according to the operating status and environment of the wind turbine:

[0037] Dynamic baseline model i,j =f(T 历史,i,j , other operating parameters)

[0038] Where T 历史,i,j Represents the value of the observed data, here it represents the value of the wind turbine operation;

[0039] 4-2) Set up an adaptive adjustment mechanism to dynamically adjust the anomaly index threshold based on historical data and anomaly detection results:

[0040] Abnormal index threshold 动态 =g(historical anomaly index, other factors)

[0041] 4-3) Smoothing the anomaly index in space and time to eliminate possible noise and sudden changes:

[0042]

[0043] Among them, M i,j is the abnormality index, N i,j is the original anomaly index;

[0044] 4-4) Use dynamic thresholds, that is, dynamically adjust the thresholds according to different operating states and environmental conditions, and use statistical methods to set the thresholds:

[0045]

[0046] Among them, E represents the dynamic threshold, p represents the mean, k represents the multiple, and s represents the standard deviation;

[0047] 4-5) Set the dynamic threshold and determine whether there is an internal anomaly by comparing the anomaly index and the dynamic threshold:

[0048]

[0049] Among them, W(x,y,t) represents the detection result.

[0050] The infrared thermal imaging nondestructive testing method for wind turbine blades of the present invention may also be as follows: the adsorption device includes a suction cup and a roller, and the adsorption of the suction cup and the movement of the roller are both instructed by a central control processing system.

[0051] Compared with the prior art, the present invention has the following beneficial effects:

[0052] 1. The infrared thermal imaging nondestructive testing method for wind turbine blades of the present invention uses a drone to fly to the area to be tested, adsorb on the surface, and then generate a heat source through infrared rays. Combined with infrared thermal imaging technology, it can achieve high-precision detection of tiny defects inside the blades, improve the accuracy and efficiency of detection, and at the same time achieve a comprehensive assessment of the overall condition of the blades.

[0053] 2. The infrared thermal imaging non-destructive testing method for wind turbine blades of the present invention does not require direct contact with the wind turbine blades, thereby avoiding damage or impact on the object being tested during testing.

[0054] 3. The infrared thermal imaging nondestructive testing method for wind turbine blades of the present invention can provide real-time thermal images, allowing users to immediately observe the thermal distribution of the object being tested.

[0055] 4. The infrared thermal imaging nondestructive testing method for wind turbine blades of the present invention provides a roller on the adsorption device, so that the device can move in a plane while adsorbing. This optimizes the traditional testing method of continuous takeoff and landing and then adsorption, greatly improving the efficiency while reducing the loss of the device itself.

Brief Description of the Drawings

[0056] Figure 1 It is a structural schematic diagram of the adsorption-type UAV infrared thermal imaging device of the present invention.

[0057] Figure 2 yes Figure 1 The effect of infrared thermal imager inspecting leaves.

[0058] Figure 3 yes Figure 1 Schematic diagram of the structure of the adsorption device.

[0059] Figure 4 yes Figure 1 The effect diagram of the adsorption device and blade adsorption. [Specific implementation method]

[0060] Please refer to the instruction manual Figure 1 To the attached Figure 4 As shown in the figure, it is an adsorption type UAV infrared thermal imaging device of the present invention, which consists of a UAV 1, a central control processing system 2, an infrared thermal imager 3, a telescopic connecting rod device 4 and an adsorption device 5.

[0061] The drone 1 is a drone of the prior art, and the central control processing system 2, the infrared thermal imager 3, the telescopic connecting rod device 4 and the adsorption device 5 are respectively installed on the drone 1.

[0062] The infrared thermal imager 3 is connected to the central control and processing system 2 via a telescopic connecting rod device 4 and is controlled by the central control and processing system 2. In other words, all detection information obtained by the infrared thermal imager 3 is transmitted to the central control and processing system 2, processed, and then transmitted to the ground by the central control and processing system 2.

[0063] The infrared thermal imager 3 includes an infrared imaging camera 10 and a flash lamp 9. A universal knob is installed inside the telescopic connecting rod device 4, so that the infrared thermal imager 3 can detect the area to be measured 11 without blind spots.

[0064] Because infrared thermal imaging is very sensitive to changes in surface temperature, this high sensitivity enables the device to detect tiny temperature differences and can penetrate some materials to detect the temperature distribution beneath the surface, thereby discovering deep-seated problems or defects. Infrared thermal imaging is also effective in low-light conditions or in adverse weather conditions. Compared with visible light, infrared radiation is less dependent on lighting conditions, so it can be reliably detected at night or in adverse weather conditions. No special preparation is required for the object being measured, such as surface covering or marking, which reduces the complexity of the operation and is especially suitable for equipment with large or complex structures. Infrared thermal imaging provides an overall thermal image, not just local information, which helps to fully understand the thermal performance of the object being measured and is also conducive to predicting potential problems.

[0065] The adsorption device 5 is provided with a roller 8, so that the device can move in a plane while adsorbing, which optimizes the traditional detection process that requires the drone to take off and land continuously before adsorbing, greatly improving the efficiency while reducing the loss of the device itself.

[0066] The infrared thermal imaging nondestructive testing method for wind turbine blades using the above-mentioned adsorption-type drone infrared thermal imaging device comprises the following steps:

[0067] Step 1) The drone 1 takes off and flies to the position of the blade to be inspected, and then is adsorbed on the area to be inspected 11 by the adsorption device 5. The specific process includes the following:

[0068] 1-1), the drone 1 arrives above the test area 11 and slowly descends until the retractable suction cup 7 of the adsorption device 5 is precisely in contact with the test area.

[0069] 1-2), the exhaust valve 6 on the retractable suction cup 7 of the adsorption device 5 starts to start, and the air in the surface of the test area 11 is discharged, so that it is firmly adsorbed. After the air is exhausted, the exhaust valve 6 is closed.

[0070] 1-3), after the detection of the area, the propeller of the unmanned aerial vehicle 1 starts to reverse until the lift of the propeller and the adsorption force of the adsorption device 5 are the same, and the roller 8 of the adsorption device 5 starts to move to the next detection area for detection.

[0071] Step 2), the central control processing system 2 activates the infrared thermal imager 3 to generate a moderate heat source to gradually increase the temperature of the blade to be detected area 11, and real-time collects the infrared image of the area to be detected, and records the temperature distribution of the blade during the temperature rising process.

[0072] Specifically, the infrared thermal imaging image collection method is as follows:

[0073] 2-1), turn on the infrared thermal imager 3.

[0074] 2-2), the infrared thermal imager 3 starts to record thermal imaging at a certain fixed frame frequency, and after a delay, the thermal imaging formed when the halogen flash lamp 9 is excited is saved.

[0075] 2-3), the collected infrared thermal imaging is processed.

[0076] Step 3), the central control processing system processes the infrared image, identifies the abnormal area in the temperature distribution, and extracts the key features from the infrared image.

[0077] In this step, the temperature abnormal area is determined by temperature gradient calculation, and the method is as follows:

[0078] 3-1), it is assumed that the surface temperature field of the wind turbine blade can be described by a two-dimensional temperature distribution function T(x, y, t), wherein x and y are coordinates on the surface of the blade, and t is time.

[0079] 3-2), set the active heat source to heat the blade to generate an additional heat source, which is represented by Q(x, y, t). This heat source can be periodic and adjusted by the control system.

[0080] 3-3), the heat conduction equation is used to describe the evolution of the temperature field:

[0081]

[0082] Where: p is the density of the blade, c is the specific heat capacity of the blade, k is the thermal conductivity of the blade, is the divergence operator.

[0083] 3-4), the infrared thermal imaging device obtains the temperature distribution image T 内部 (x, y, t) of the area to be detected by sensing the infrared radiation of the blade to be detected area; by processing the infrared image, denoising and calibrating the temperature, the processed internal temperature distribution image T处理后 (x,y,t).

[0084] 3-5), calculate the temperature gradient, which represents the rate of change of the temperature field:

[0085]

[0086] in, represents the temperature gradient; represents the temperature gradient in the horizontal direction, Represents the temperature gradient in the vertical direction.

[0087] 3-6) Using the location and intensity information of the thermal gradient source, identify the abnormal temperature area caused by the active heat source:

[0088]

[0089] Where P(x,y,t) represents the abnormal area.

[0090] Step 4) Use the extracted features to perform anomaly detection, compare the features under normal conditions, identify internal defects or anomalies in the blade, and generate a detailed inspection report.

[0091] Specifically, the blade abnormality determination method is:

[0092] 4-1), using the dynamic baseline model, according to the operating status and environment of the wind turbine:

[0093] Dynamic baseline model i,j =f(T 历史,i,j , other operating parameters)

[0094] Among them, T 历史,i,j Represents the value of the observed data, here it represents the value of the wind turbine operation.

[0095] A note of clarification: A dynamic baseline model refers to a detection system in which the parameters or state of the baseline model can be dynamically adjusted based on real-time data from the system's operation. Baseline models are typically used to describe the state or performance level of a system during normal operation. The introduction of a dynamic baseline model allows the model to adaptively update over time, due to environmental changes, or other external factors. Consider a temperature monitoring system used to monitor the temperature of mechanical equipment. While a traditional baseline model might be the average temperature of the equipment during normal operation, a dynamic baseline model can adjust the baseline based on real-time data.

[0096] 4-2) Set up an adaptive adjustment mechanism to dynamically adjust the anomaly index threshold based on historical data and anomaly detection results:

[0097] Abnormal index threshold 动态=g(historical anomaly index, other factors).

[0098] The outlier index threshold refers to an adaptive adjustment mechanism that dynamically adjusts the anomaly index threshold based on historical data and anomaly detection results. It automatically learns the system's operating status by monitoring system performance and maintenance records. Therefore, both the dynamic baseline model and the anomaly index threshold are set in different environments based on objective conditions, aiming to improve the algorithm's adaptability and robustness, enabling it to better adapt to different working environments and actual operating conditions.

[0099] 4-3) Smoothing the anomaly index in space and time to eliminate possible noise and sudden changes:

[0100]

[0101] Among them, M i,j is the abnormality index, N i,j is the original anomaly index.

[0102] 4-4) Use dynamic thresholds, that is, dynamically adjust the thresholds according to different operating states and environmental conditions, and use statistical methods to set the thresholds:

[0103]

[0104] Where E represents the dynamic threshold, p represents the mean, k represents the multiple, and s represents the standard deviation.

[0105] 4-5) Set the dynamic threshold and determine whether there is an internal anomaly by comparing the anomaly index and the dynamic threshold:

[0106]

[0107] Among them, W(x,y,t) represents the detection result.

[0108] Step 5), after completing the inspection of the area, the adsorption device 5 moves to the next area to be inspected 11 through the roller 8 provided therewith, and repeats the operations from 2) to 4).

[0109] The above specific implementation methods are only preferred embodiments of this creation and are not intended to limit this creation. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of this creation should be included in the scope of protection of this creation.

Claims

1. A nondestructive testing method for wind turbine blades using infrared thermal imaging, characterized by: It uses an adsorption-type UAV infrared thermal imaging device, which includes a UAV, a central control and processing system, an infrared thermal imager, a telescopic connecting rod device and an adsorption device; The detection method comprises the following steps: 1) The drone takes off, flies to the blade's inspection location, and then attaches to the inspection area through an adsorption device; 2) The central control processing system activates the infrared thermal imager to generate a moderate heat source, gradually increasing the temperature of the blade's test area. It also collects infrared images of the test area in real time and records the temperature distribution of the blade during the heating process. 3) The central control processing system processes the infrared image, identifies abnormal areas in the temperature distribution, and extracts key features from the infrared image; 4) Use the extracted features to perform anomaly detection, compare the features under normal conditions, identify internal defects or anomalies in the blade, and generate a detailed inspection report; The specific method for determining blade abnormality is as follows: 4-1), using the dynamic baseline model, according to the operating status and environment of the wind turbine: in Represents the value of the observed data, here it represents the value of the wind turbine operation; 4-2) Set up an adaptive adjustment mechanism to dynamically adjust the anomaly index threshold based on historical data and anomaly detection results: 4-3) Smoothing the anomaly index in space and time to eliminate possible noise and sudden changes: in, is the abnormality index, is the original anomaly index; 4-4) Use dynamic thresholds, that is, dynamically adjust the thresholds according to different operating states and environmental conditions, and use statistical methods to set the thresholds: Among them, E represents the dynamic threshold, p represents the mean, k represents the multiple, and s represents the standard deviation; 4-5) Set the dynamic threshold and determine whether there is an internal anomaly by comparing the anomaly index and the dynamic threshold: in, Indicates test results 5) After completing the inspection of the area, use the roller on the adsorption device to move to the next area to be tested and repeat operations 2) to 4).

2. The infrared thermal imaging nondestructive testing method for wind turbine blades according to claim 1, characterized in that: The infrared thermal imager is connected to the central control processing system through a telescopic connecting rod device. A universal knob is installed inside the telescopic connecting rod device, so that the infrared thermal imager can perform blind spot detection on the area to be tested. The infrared thermal imager includes an infrared imaging camera and a flash lamp.

3. The infrared thermal imaging nondestructive testing method for wind turbine blades according to claim 1, characterized in that: The step 1) is specifically as follows: 1-1) The drone arrives above the area to be tested and slowly descends until the retractable suction cup of the adsorption device accurately fits the area to be tested; 1-2) The exhaust valve on the retractable suction cup of the adsorption device starts to operate, exhausting the air on the surface of the test area so that it can be firmly adsorbed. After all the air is exhausted, the exhaust valve closes. 1-3) After the inspection of the area is completed, the propeller of the drone begins to reverse until the lift of the propeller is equal to the adsorption force of the adsorption device. The roller of the adsorption device starts and moves the device to the next inspection area for inspection.

4. The infrared thermal imaging nondestructive testing method for wind turbine blades according to claim 1, characterized in that: In step 2), the infrared thermal imaging image acquisition method is as follows: 2-1) Turn on the infrared thermal imager; 2-2), the infrared thermal imager starts to record thermal images at a fixed frame rate, and after a delay, saves the thermal images formed when the halogen flash lamp is excited; 2-3) Process the acquired infrared thermal images.

5. The infrared thermal imaging nondestructive testing method for wind turbine blades according to claim 1, characterized in that: In step 3), the temperature abnormality area is determined by temperature gradient calculation, and the method is as follows: 3-1), assuming that the surface temperature field of the wind turbine blade can be represented by a two-dimensional temperature distribution function Description, where and are the coordinates on the blade surface, It’s time; 3-2), set the active heat source to heat the blades, generate an additional heat source, and use express; 3-3), the heat conduction equation is used to describe the evolution of the temperature field: in: is the density of the blade, c is the specific heat capacity of the blade, k is the thermal conductivity of the blade, is the divergence operator; 3-4), the infrared thermal imaging device senses the infrared radiation of the blade to be tested and obtains the temperature distribution image of the tested area ;By processing the infrared image, removing noise and calibrating the temperature, the processed internal temperature distribution image is obtained ; 3-5), calculate the temperature gradient, which represents the rate of change of the temperature field: in, represents the temperature gradient; 3-6) Using the location and intensity information of the thermal gradient source, identify the abnormal temperature area caused by the active heat source: in, Indicates abnormal area.

6. The infrared thermal imaging nondestructive testing method for wind turbine blades according to claim 1, characterized in that: The adsorption device includes a suction cup and a roller, and the adsorption of the suction cup and the movement of the roller are both instructed by a central control processing system.

Images