Blade recognition method and system based on high-energy laser clearance radar

Abstract

The present invention provides a blade identification method based on a high-energy laser clearance radar. The method first obtains raw signal data from a single beam of the high-energy laser clearance radar, preprocesses the acquired raw signal from the single beam, and then, based on the preprocessed signal data and taking the blade's trajectory as a prerequisite, searches for suspected blade tip moments according to different blade periods N. Based on the suspected blade tip moments, the method searches for blade signals in positive and negative directions to determine the true blade tip moments. It then calculates and outputs all blade ranging values and appearance times within the current blade cycle. Finally, it updates different blade periods N based on the blade appearance times. This method reduces the interference of foggy environments on blade detection by the laser clearance radar. Taking the blade's trajectory as a prerequisite, it reduces the false alarm rate of the laser clearance radar in complex weather conditions, improves the reliability of the laser clearance radar's ranging data, and provides a stable and effective data source for the wind turbine master control's clearance warning and protection mechanism.

Description

Technical Field

[0001] The present invention relates to the field of laser radar object recognition and measurement technology, and in particular to a blade recognition method and system based on a high-energy laser clearance radar. Background Art

[0002] A high-energy laser clearance radar is a laser ranging radar that monitors blade tip clearance distance in real time and has fog-penetrating capabilities. When blade clearance approaches the specified minimum clearance value, the wind turbine control system can immediately take protective measures, such as deceleration and blade retraction. Compared to conventional laser clearance radars, which output the distance to the target object, high-energy laser clearance radars output a digital signal accumulated from continuous laser pulses. This data is represented by signal peaks from multiple targets, including dust, fog, water droplets, blade signals, and ground signals. Blade signals can easily be confused with fog signals. To distinguish blade signals from these target objects, feature extraction is required. Dedicated data processing methods are then used to extract the blade signals, and finally, the blade signals are converted into specific distance values. Currently, no effective solution has been proposed to address the difficulty of distinguishing blade signals from fog signals in high-energy laser radars. Summary of the Invention

[0003] In order to solve the problems of the prior art, the present invention provides a blade identification method and system based on a high-energy laser clearance radar, which can quickly, efficiently and accurately identify blade signals, reduce the interference of foggy environments on laser clearance radar blade detection to a certain extent, greatly reduce the false alarm rate of blades in complex environments, improve the reliability of laser clearance radar blade ranging data, and provide a stable and effective data source for the clearance warning protection mechanism of the wind turbine master control.

[0004] To this end, the specific technical solutions adopted in the present invention are as follows:

[0005] According to one aspect of the present invention, a blade recognition method based on a high-energy laser clearance radar is provided, the recognition method comprising the following steps:

[0006] S1. Obtaining the raw signal data of a single beam of a high-energy laser clearance radar;

[0007] S2. Preprocess the original signal of the acquired single light beam to obtain the ranging value and signal strength within the blade range and the ground range of the current frame signal respectively;

[0008] S3. Establish a lookup table of different blade periods N and the same blade period n according to the impeller speed, and initialize the different blade periods N and the same blade period n;

[0009] S4. Based on the pre-processed signal data and taking the blade's trajectory as the premise, according to different blade periods N, find the moment when the blade signal appears and the ground signal disappears, that is, the suspected blade tip moment;

[0010] S5. Search for blade signals in the positive and negative directions according to the suspected blade tip moment, calculate and output all blade distance values and occurrence times in the current blade cycle;

[0011] S6. Update the different leaf periods N according to the leaf appearance time.

[0012] Furthermore, the obtained raw signal data of the high-energy laser clearance radar represents the signal intensity at different distances along the direction of a single light beam.

[0013] Furthermore, the preprocessing process of the original signal of the acquired single light beam includes the following steps:

[0014] S21, setting the size of the sliding window to 11, selecting the minimum value of the signal in the sliding window as the baseline, subtracting the signal value of the baseline from the acquired original signal to obtain the signal after removing the baseline;

[0015] S22. Set the peak search range of the ground signal and the blade signal respectively, and obtain the ranging value and signal strength corresponding to the maximum value of the signal peak respectively, that is, the ranging value Dist_blade and signal strength DN_blade within the blade range of the current frame signal, and the ranging value Dist_ground and signal strength DN_ground within the ground range of the current frame signal.

[0016] Furthermore, the estimating of the blade cycle comprises the following steps:

[0017] S31. Establish a lookup table for the period N of different blades and the period n of the same blade based on parameters such as blade length, blade tip linear velocity, blade tip width, and laser radar data output frequency;

[0018] S32. Initialize the fan to run at full power, convert the period of different blades to 2s, and convert it into a frame count of N. Search the lookup table for the same blade period n corresponding to the different blade period N.

[0019] Furthermore, the step of searching for the suspected blade tip moment includes the following steps:

[0020] S41, determine the current frame f according to different leaf cycles N and the same leaf cycle n cnt The maximum depth of searching for leaves in the negative and positive directions is 2n+1;

[0021] S42, respectively calculate the blade signal strength DN_blade at the distance measurement value Dist_blade corresponding to the negative direction and positive direction signals and the current framefront DN_blade back ;

[0022] S43. Based on the idea of threshold classification, find the moment when the signal strength DN_blade in the blade range of the current frame is larger and the signal strength DN_ground in the ground range is smaller, which is the suspected blade tip moment.

[0023] Furthermore, the calculation and output of the blade distance value includes the following steps:

[0024] S51. For all frame signals within the same blade cycle N, find the frame with the largest difference between the blade signal intensity DN_blade and the ground signal intensity DN_ground in the same frame as the true blade tip moment;

[0025] S52: directly use the signal of the next blade cycle as the suspected blade tip moment, and continue the judgment of the next blade cycle;

[0026] S53. For the actual blade tip moment, search for consecutive frames with smaller differences in the same blade distance value Dist_blade in the negative and positive directions, save and output the blade distance value and the occurrence time.

[0027] Furthermore, the updating of the different blade periods N is obtained by subtracting the appearance moments of the blades in the two preceding and following periods.

[0028] According to another aspect of the present invention, a blade identification system based on a high-energy laser clearance radar is also provided. The blade identification system includes an original signal acquisition module, a signal preprocessing module, a blade period estimation and update module, a blade tip moment query module, and a blade ranging value output module.

[0029] Wherein, the original signal acquisition module is used to obtain the original signal value of the high-energy laser clearance radar;

[0030] The signal preprocessing module is used to extract the ranging value and signal strength within the blade range and the ranging value and signal strength within the ground range from the acquired original high-energy laser clearance radar signal;

[0031] The estimation and updating module is used to establish a lookup table of different blade periods N and the same blade period n, and to update the different blade periods N and the same blade period n according to the blade appearance time output in real time;

[0032] The blade tip query time module is used to determine all possible blade signal ranging values and corresponding blade signal occurrence times in the current blade cycle;

[0033] The blade distance value output module saves and outputs the blade distance value at the current moment according to the moment when the blade signal appears.

[0034] The present invention also provides a device for a blade identification method based on a high-energy laser clearance radar, which includes at least a processor and a memory, wherein the memory stores computer-executable instructions, and the processor executes the computer-executable instructions stored in the memory, so that the blade identification system based on the high-energy laser clearance radar executes the above-mentioned blade identification method based on the high-energy laser clearance radar.

[0035] The present invention also provides a computer-readable storage medium storing a computer program or instruction. When the computer program or instruction is executed, the above-mentioned blade identification method based on high-energy laser clearance radar is implemented.

[0036] The beneficial effects of the present invention are:

[0037] 1) The present invention starts from the actual signal data measured by the high-energy laser clearance radar and adopts a blade identification method based on tracing the running trajectory of the blade. It can quickly, efficiently and accurately identify the blade signal, and can reduce the interference of the foggy environment on the blade detection of the laser clearance radar to a certain extent. It greatly reduces the false alarm rate of the blades of the clearance radar in complex environments, improves the reliability of the blade ranging data of the laser clearance radar, and provides a stable and effective data source for the clearance early warning protection mechanism of the wind turbine master control.

[0038] 2) The present invention utilizes the fog-penetrating capability of a high-energy laser clearance radar. Based on the periodic characteristics of the blades, the fog signal can be distinguished from the blade signal. Different blade cycles and the same blade cycle are updated in real time according to the different moments of appearance of the blade signals. The blade signals can be detected continuously and stably, thus achieving stable output of blade ranging values at high fan speeds. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0040] Figure 1 This is a flow chart of a blade recognition method based on a high-energy laser clearance radar according to an embodiment of the present invention;

[0041] Figure 2 1 is a schematic diagram of the principle of a blade recognition method based on a high-energy laser clearance radar according to an embodiment of the present invention;

[0042] Figure 3 3. Graphs showing results before and after raw signal preprocessing of a blade recognition method based on a high-energy laser clearance radar according to an embodiment of the present invention;

[0043] Figure 4 3. It is a schematic diagram of blade tip moment characteristics of a blade recognition method based on a high-energy laser clearance radar according to an embodiment of the present invention. DETAILED DESCRIPTION

[0044] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0045] According to an embodiment of the present invention, a blade identification method and system based on a high-energy laser clearance radar are provided.

[0046] The present invention will now be further described with reference to the accompanying drawings and specific embodiments. Figure 1 and Figure 2 As shown, according to one embodiment of the present invention, a blade recognition method based on a high-energy laser clearance radar is provided, and the method includes the following steps:

[0047] S1. Obtaining the raw signal data of a single beam of a high-energy laser clearance radar;

[0048] Figure 3 The figure is a result diagram before and after the original signal preprocessing of a blade recognition method based on a high-energy laser clearance radar according to an embodiment of the present invention. Specifically, the high-energy laser clearance radar obtains the target signal distribution at different distances with a frequency of 100Hz, such as Figure 3 As shown in (a), the horizontal axis represents the distance, and the vertical axis represents the signal strength of the target measured by the high-energy laser clearance radar. Along different distance directions, from near to far, the peak signals are the end face signal, fog signal, blade signal, and ground signal. The distance corresponding to the end face signal peak is 1000 cm, so the actual height of the tower is 12000 cm-1000 cm=11000 cm, and the actual length of the blade is 9000 cm-1000 cm=8000 cm. It can be seen from the figure that due to the unique fog penetration capability of the high-energy laser clearance radar, when the fog signal intensity behind the end face signal is relatively large, the high-energy laser clearance radar can still detect the blade signal and the ground signal.

[0049] S2. preprocessing the target signal of the acquired single light beam;

[0050] Specifically, the target signal of a single light beam is preprocessed to obtain the ranging value and signal strength within the blade range and the ground range of the current frame signal. The preprocessing process includes:

[0051] S21. According to the target signal distribution of the current frame, the size of the sliding window is set to 11. The minimum value of the target signal in the sliding window is used as the baseline of the target signal. The target signal in the sliding window of the current frame minus the baseline in the sliding window of the current frame is obtained to obtain the signal in the sliding window after removing the baseline. The window is moved sequentially to obtain the signal of the current frame after removing the baseline. Figure 3 As shown in (b), it can be seen from the figure that the signal after removing the baseline can completely distinguish the signals of different targets from the noise;

[0052] S22. Based on the signal after removing the baseline of the current frame, based on the idea of threshold classification, first set the minimum detection distance and maximum detection distance of the blade signal, and find the peak with the largest signal strength within the minimum detection distance and maximum detection distance of the blade. If the signal strength of the signal peak is greater than the threshold, the threshold can be set to 300 here, and the ranging distance and signal strength corresponding to the peak are used as the ranging value Dist_blade and signal strength DN_blade of the blade signal respectively; then set the minimum detection distance and maximum detection distance of the ground signal, and find the peak with the largest signal strength within the minimum detection distance and maximum detection distance of the ground. If the signal strength of the peak is greater than the threshold, the threshold can be set to 300 here, and the ranging distance and signal strength corresponding to the signal peak are used as the ranging value Dist_ground and signal strength DN_ground of the ground signal respectively.

[0053] S3, estimate the blade cycle;

[0054] Specifically, a lookup table of different blade periods N and the same blade period n is established according to the impeller speed, and the different blade periods N and the same blade period n are initialized. The processing process includes:

[0055] S31. Input blade length Blade_length, blade tip linear velocity v, and blade tip width L. The time interval between different blades is T, in seconds, and the transit time of the same blade is t, in milliseconds, which can be expressed as:

[0056]

[0057]

[0058] S32. Based on the radar data output frequency of high-energy laser clearance being 100 Hz, i.e., the time interval is 10 ms, the time interval T of different blades and the transit time t of the same blade are converted into the period N (frame) of different blades and the period n (frame) of the same blade, and a lookup table of the correlation between the two is established, as shown in the following table:

[0059]

[0060] S33, the wind turbine is initialized to run at full power, the period of different blades is 2s, which is converted into a frame count of N=200 frames, and the same blade period n=2 frames corresponding to the different blade period N are searched according to the lookup table.

[0061] S4, looking for the suspected tip moment;

[0062] Specifically, based on the preprocessed signal data and taking the blade's trajectory as the premise, we search for the moment when the blade signal appears and the ground signal disappears according to different blade periods N, i.e., the suspected blade tip moment. The processing process includes:

[0063] S41, determine the frame count f of the current frame according to different leaf periods N and the same leaf period n cnt The maximum depth of searching for leaves in the negative and positive directions is 2n+1, that is, the frame count corresponding to the negative direction is f cnt -(2n+1), the frame count corresponding to the positive direction is f cnt +(2n+1);

[0064] S42, according to the blade signal strength DN_blade and the distance value Dist_blade of the current frame, respectively calculate the blade signal strength DN_blade at the distance value Dist_blade corresponding to the current frame in the negative direction and the positive direction front DN_blade back ;

[0065] S43, based on the idea of threshold classification, if the blade signal strength DN_blade of the current frame is greater than DN_blade front and greater than DN_blade back , and the blade signal strength DN_blade is less than half of DN_ground, then the current frame is a suspected blade tip moment, otherwise, continue to judge the next frame.

[0066] S5. Calculate and output all blade distance values and occurrence times within the current blade cycle. The processing includes:

[0067] S51, for the frame count and the current frame count f cntFor all frame signals within a period N, find the frame with the largest difference between the blade signal intensity DN_blade and the ground signal intensity DN_ground in the same frame, and take it as the true blade tip moment, such as Figure 4 As shown in the figure, it can be seen that the blade signal strength within the range of 50m-100m is much greater than the ground signal strength within the range of 100m-150m at the same moment. The blade signal appears periodically and appears in the range of frame count 0-N, N-2*N, and 2*N-3*N.

[0068] S52, the frame count and the current frame count f cnt All frame signals with a difference greater than one cycle N are directly used as the suspected tip moment of the next blade cycle N-2*N, and the judgment of the next blade cycle is continued;

[0069] S53. For the real blade tip moment, search in the negative and positive directions with a maximum depth of 2n+1. If the blade distance value of the queried continuous frame is slightly different from the blade distance value Dist_blade at the blade tip moment and is within the ranging range of ±2m, save and output the blade distance value and the occurrence time corresponding to the continuous frame.

[0070] S6. Update different blade cycles N;

[0071] Specifically, the new different leaf period N is obtained by subtracting the leaf appearance times in the two previous and next periods.

[0072] According to another embodiment of the present invention, a blade identification system based on a high-energy laser clearance radar is provided. The blade identification system of the high-energy laser clearance radar includes an original signal acquisition module, a signal preprocessing module, a blade period estimation and update module, a blade tip moment query module, and a blade ranging value output module.

[0073] The original signal acquisition module is used to obtain the original signal value of the high-energy laser clearance radar;

[0074] The signal preprocessing module is used to extract the ranging value and signal strength within the blade range and the ranging value and signal strength within the ground range from the acquired original high-energy laser clearance radar signal;

[0075] The estimation and updating module is used to establish a lookup table of different blade periods N and the same blade period n, and to update the different blade periods N and the same blade period n according to the blade appearance time output in real time;

[0076] The blade tip query time module is used to determine all possible blade signal ranging values and corresponding blade signal occurrence times in the current blade cycle;

[0077] The blade distance value output module saves and outputs the blade distance value at the current moment according to the moment when the blade signal appears.

[0078] To sum up, with the help of the above-mentioned technical scheme of the present invention, starting from the actual signal data measured by the high-energy laser clearance radar, the blade identification method adopted is based on tracing the running trajectory of the blade, which can quickly, efficiently and accurately identify the blade signal, and can reduce the interference of the foggy environment on the blade detection of the laser clearance radar to a certain extent, greatly reduce the false alarm rate of the blades of the clearance radar in a complex environment, improve the reliability of the blade ranging data of the laser clearance radar, and provide a stable and effective data source for the clearance warning protection mechanism of the wind turbine master control.

[0079] In addition, the present invention utilizes the fog-penetrating capability of a high-energy laser clearance radar. According to the periodic characteristics of the blades, it can distinguish the fog signal from the blade signal. Different blade cycles and the same blade cycle are updated in real time according to the different times when the blade signals appear. The blade signals can be detected continuously and stably, thereby achieving stable output of blade ranging values at high fan speeds.

[0080] The above specific embodiments are used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to examples, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

[0081] The present invention also provides a device for a blade identification method based on a high-energy laser clearance radar, which includes at least a processor and a memory, wherein the memory stores computer-executable instructions, and the processor executes the computer-executable instructions stored in the memory, so that the blade identification system based on the high-energy laser clearance radar executes the above-mentioned blade identification method based on the high-energy laser clearance radar.

[0082] The present invention also provides a computer-readable storage medium storing a computer program or instruction. When the computer program or instruction is executed, the above-mentioned blade identification method based on high-energy laser clearance radar is implemented.

[0083] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device embodiment, the above is only a preferred embodiment of the present invention. Since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment. The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited to this. Any technical personnel familiar with this technical field is within the technical scope disclosed by the present invention. For ordinary technical personnel in this technical field, changes or replacements that can be easily thought of should be covered within the protection scope of the present invention without departing from the principle of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A blade recognition method based on high-energy laser clearance radar, characterized in that: The following steps are involved: S1. Obtaining the raw signal data of a single beam of a high-energy laser clearance radar; S2. Preprocess the original signal of the acquired single light beam to obtain the ranging value and signal strength within the blade range and the ground range of the current frame signal respectively; S3, real-time estimation of different blade periods N and the same blade period n, establishing a lookup table of different blade periods N and the same blade period n, and initializing the different blade periods N and the same blade period n; the real-time estimation of different blade periods N and the same blade period n specifically includes the following steps: S31. Establish a lookup table of the correspondence between the period N of different blades and the period n of the same blade based on parameters such as blade length, blade tip linear velocity, blade tip width, and laser radar data output frequency; S32, initialize the fan to operate at full power, convert the period of different blades to 2s, convert it to frame count N, and search the same blade period n corresponding to the different blade period N according to the lookup table; S4. Based on the pre-processed signal data and taking the blade's trajectory as a premise, according to different blade periods N, searching for the moment when the blade signal appears and the ground signal disappears, i.e., the suspected blade tip moment; the process of searching for the suspected blade tip moment specifically includes the following steps: S41, determine the current frame f according to different leaf cycles N and the same leaf cycle n cnt The maximum depth of searching for leaves in the negative and positive directions is 2n+1; S42, respectively calculate the blade signal strength DN_blade at the distance measurement value Dist_blade corresponding to the negative direction and positive direction signals and the current frame front DN_blade back ; S43, based on the idea of threshold classification, find the moment when the signal strength DN_blade within the blade range of the current frame is larger and the signal strength DN_ground within the ground range is smaller, which is the suspected blade tip moment; S5. Search for blade signals in the positive and negative directions according to the suspected blade tip moment, calculate and output all blade distance values and occurrence times in the current blade cycle; S6. Update the different leaf periods N according to the leaf appearance time.

2. The blade recognition method based on high-energy laser clearance radar according to claim 1 is characterized in that: The high-energy laser clearance radar signal obtained in step S1 is a single-beam signal.

3. The blade recognition method based on high-energy laser clearance radar according to claim 1 is characterized in that: The preprocessing process of the obtained original signal of the single light beam in step S2 includes the following steps: S21, setting the size of the sliding window to 11, selecting the minimum value of the signal in the sliding window as the baseline, subtracting the signal value of the baseline from the acquired original signal to obtain the signal after removing the baseline; S22. Set the peak search range of the ground signal and the blade signal respectively, and obtain the ranging value and signal strength corresponding to the maximum value of the signal peak respectively, that is, the ranging value Dist_blade and signal strength DN_blade within the blade range of the current frame signal, and the ranging value Dist_ground and signal strength DN_ground within the ground range of the current frame signal.

4. The blade identification method based on high-energy laser clearance radar according to claim 1 is characterized in that: The process of calculating and outputting all blade distance measurement values and occurrence times in the current blade cycle in step S5 specifically includes the following steps: S51. For all frame signals within the same blade cycle N, find the frame with the largest difference between the blade signal intensity DN_blade and the ground signal intensity DN_ground in the same frame as the true blade tip moment; S52: directly use the signal of the next blade cycle as the suspected blade tip moment, and continue the judgment of the next blade cycle; S53. For the actual blade tip moment, search for consecutive frames with smaller differences in the same blade distance measurement value Dist_blade in the negative and positive directions, save and output the blade distance measurement value and the occurrence time.

5. The blade identification method based on high-energy laser clearance radar according to claim 1 is characterized in that: In the updating process of the blade period N in step S6, different blade periods N are updated in real time according to the appearance moments of the blades in the two preceding and following periods.

6. A blade identification system based on a high-energy laser clearance radar, used to implement the steps of the high-energy laser clearance radar blade identification method according to any one of claims 1 to 5, characterized in that: It includes original signal acquisition module, signal preprocessing module, blade cycle estimation and update module, blade tip moment query module, and blade distance value output module; The original signal acquisition module is used to obtain the original signal value of the high-energy laser clearance radar; The signal preprocessing module is used to extract the ranging value and signal strength within the blade range and the ranging value and signal strength within the ground range from the acquired original high-energy laser clearance radar signal; The estimation and updating module is used to establish a lookup table of different blade periods N and the same blade period n, and to update the different blade periods N and the same blade period n according to the blade appearance time output in real time; The blade tip query time module is used to determine all possible blade signal ranging values and corresponding blade signal occurrence times in the current blade cycle; The blade distance value output module saves and outputs the blade distance value at the current moment according to the moment when the blade signal appears.

7. A device for blade identification method based on high-energy laser clearance radar, characterized by: It includes at least a processor and a memory, the memory stores computer-executable instructions, and the processor executes the computer-executable instructions stored in the memory, so that the blade recognition system based on the high-energy laser clearance radar executes the blade recognition method based on the high-energy laser clearance radar as described in claim 1.

8. A computer-readable storage medium, characterized in that A computer program or instruction is stored, and when the computer program or instruction is executed, the blade identification method based on high-energy laser clearance radar described in claim 1 is implemented.

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