CN119267120B - Wind driven generator blade running state monitoring method based on three-dimensional modeling - Google Patents
Wind driven generator blade running state monitoring method based on three-dimensional modeling Download PDFInfo
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Abstract
本发明提供了一种基于三维建模的风力发电机叶片运行状态监测方法，涉及风力发电机叶片运行状态监测技术领域，所述方法包括：获取地面激光雷达采集的无变形目标叶片处于第一预设位置的标准点云数据列表A，获取地面激光雷达采集的目标叶片处于第一预设位置的当前点云数据列表B，获取A中每一标准点云数据与B中每一当前点云数据的最小距离，以得到A对应的最小距离列表LA；若LA中大于预设距离L’的最小距离的数量NUM1小于预设的最小距离的数量阈值，则确定目标叶片无变形；否则，根据C和空中激光雷达采集的目标叶片处于第二预设位置的当前点云数据，确定目标叶片的变形区域；本发明能够实现对风力发电机叶片的整体变形监测。
The present invention provides a method for monitoring the operating status of a wind turbine blade based on three-dimensional modeling, and relates to the technical field of monitoring the operating status of a wind turbine blade. The method comprises: obtaining a standard point cloud data list A of a target blade without deformation collected by a ground laser radar at a first preset position, obtaining a current point cloud data list B of a target blade at the first preset position collected by the ground laser radar, obtaining the minimum distance between each standard point cloud data in A and each current point cloud data in B, so as to obtain a minimum distance list LA corresponding to A; if the number NUM 1 of the minimum distances greater than a preset distance L' in LA is less than a preset minimum distance number threshold, it is determined that the target blade has no deformation; otherwise, according to C and the current point cloud data of the target blade at a second preset position collected by an aerial laser radar, the deformation area of the target blade is determined; the present invention can realize the overall deformation monitoring of the wind turbine blade.
Description
Technical Field
The invention relates to the technical field of wind driven generator blade running state monitoring, in particular to a wind driven generator blade running state monitoring method based on three-dimensional modeling.
Background
In the field of wind power generation, the blades of a wind driven generator can possibly fail in the annual running process, currently, strain, displacement and vibration sensors are commonly arranged in the blades of the wind driven generator to detect the deformation and vibration of the blades in the running process of the wind driven generator, and when the blades are obviously deformed, alarm information is given. The method adopts the point type sensors, namely, the deformation value of the local part can be detected, the detection range is small relative to the huge blade, and the faults of the whole deformation of the blade can not be accurately detected, so that how to detect the faults when the whole deformation faults occur to the blade of the wind driven generator becomes the technical problem to be solved urgently.
Disclosure of Invention
Aiming at the technical problems, the invention adopts the following technical scheme:
according to a first aspect of the present application, there is provided a method for monitoring the operational state of a wind turbine blade based on three-dimensional modeling, the method comprising the steps of:
S100, acquiring a standard point cloud data list A= (A 1,A2,…,Ai,…,An) of a non-deformation target blade at a first preset position, wherein i=1, 2,.. N, wherein A i is point cloud data of an ith preset point on the target blade when the target blade is at the first preset position, and n is the number of preset points on the target blade;
S200, acquiring a current point cloud data list B= (B 1,B2,…,Bj,…,Bm) of a target blade acquired by the ground laser radar at a first preset position, wherein j=1, 2, & m, wherein B j is the j-th current point cloud data acquired by the ground laser radar when the target blade is at the first preset position, and m is the number of the current point cloud data acquired by the ground laser radar when the target blade is at the first preset position;
s300, obtaining the minimum distance between each standard point cloud data in A and each current point cloud data in B to obtain a minimum distance list LA= (LA 1,LA2,…,LAi,…,LAn) corresponding to A, wherein LA i is the minimum distance between A i and each current point cloud data in B;
s400, acquiring the number NUM 1 of the minimum distance larger than the preset distance L' in LA;
S500, if NUM 1 is less than NUM ', determining that the target blade is not deformed, otherwise, entering S600, wherein NUM' is a preset minimum distance quantity threshold;
S600, acquiring a standard point cloud data list C= (C 1,C2,…,Ci,…,Cn) of a non-deformed target blade at a second preset position, wherein C i is point cloud data of an ith preset point on the target blade when the target blade is at the second preset position, and the aerial laser radar is arranged at the top of a host of a wind driven generator;
S700, determining a deformation area of the target blade according to the C and the current point cloud data of the target blade at the second preset position, which are acquired by the aerial laser radar.
According to another aspect of the present application, there is also provided a non-transitory computer readable storage medium storing at least one instruction or at least one program, the at least one instruction or the at least one program being loaded and executed by a processor to implement the above method for monitoring an operation state of a wind turbine blade based on three-dimensional modeling.
According to another aspect of the present application, there is also provided an electronic device comprising a processor and the above-described non-transitory computer-readable storage medium.
The invention has at least the following beneficial effects:
the wind driven generator blade running state monitoring method based on three-dimensional modeling obtains a standard point cloud data list A of a target blade without deformation, which is collected by a ground laser radar, at a first preset position, obtains a current point cloud data list B of the target blade, which is collected by the ground laser radar, at the first preset position, obtains the minimum distance between each standard point cloud data in A and each current point cloud data in B to obtain a minimum distance list LA corresponding to A, determines that the target blade is not deformed if the number NUM 1 of the minimum distances, which is larger than a preset distance L', in LA is smaller than the number threshold of the preset minimum distances, and determines the deformation area of the target blade according to the current point cloud data of the target blade, which is collected by the C and the air laser radar, otherwise, realizes the integral deformation monitoring of the wind driven generator blade.
Furthermore, the ground laser radar and the air laser radar are arranged at the same time, the deformation of the target blade is monitored by using the point cloud data of the target blade obtained by the laser radars at different positions, and the probability that the laser radars with different space dimensions are moved at the same time is extremely small, so that the monitoring accuracy can be further improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flowchart of a method for monitoring the running state of a wind turbine blade based on three-dimensional modeling according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to fall within the scope of the invention.
It should be noted that, based on the present disclosure, one of ordinary skill in the art should appreciate that one aspect described herein may be implemented independently of any other aspect, and that two or more of these aspects may be combined in various ways. For example, an apparatus may be implemented and/or a method practiced using any number of the aspects set forth herein. In addition, such apparatus may be implemented and/or such methods practiced using other structure and/or functionality in addition to one or more of the aspects set forth herein.
A method for monitoring the operational state of a wind turbine blade based on three-dimensional modeling will be described with reference to a flowchart of the method for monitoring the operational state of a wind turbine blade based on three-dimensional modeling shown in fig. 1.
The wind driven generator blade running state monitoring method based on three-dimensional modeling can comprise the following steps:
S100, acquiring a standard point cloud data list A= (A 1,A2,…,Ai,…,An) of a deformation-free target blade at a first preset position, wherein i=1, 2, & gt, and n, wherein A i is point cloud data of an ith preset point on the target blade when the target blade is at the first preset position, n is the number of preset points on the target blade, the ground laser radar is arranged on the ground on the back side of the wind driven generator blade, the target blade is any blade in the wind driven generator blade, and A is obtained through a ground laser radar coordinate system.
In the embodiment, when the target blade is not deformed, the target blade can be placed at a first preset position, for example, the target blade is placed at a vertically downward position, point cloud data of the target blade when the target blade is located at the first preset position is obtained through a ground laser radar installed on the ground on the back side of the wind driven generator blade, and it is to be noted that when each point cloud data corresponding to the target blade is obtained, each point is marked according to a position relationship on the target blade, n points are marked altogether, and each point cloud data comprises coordinates of a point corresponding to each point cloud data in a ground laser radar coordinate system.
Further, since the wind speed may affect the deformation of the target blade, when the wind speed a is acquired, the corresponding wind speed at that time may be acquired first, and the standard point cloud data may be acquired at that wind speed, that is, different wind speeds correspond to different standard point cloud data lists.
S200, acquiring a current point cloud data list B= (B 1,B2,…,Bj,…,Bm) of a target blade acquired by the ground laser radar at a first preset position, wherein j=1, 2, & m, wherein B j is the j-th current point cloud data acquired by the ground laser radar when the target blade is at the first preset position, and m is the number of the current point cloud data acquired by the ground laser radar when the target blade is at the first preset position.
In this embodiment, the point cloud data of the target blade at the first preset position may be obtained in real time when the wind driven generator is running, and further the point cloud data of the target blade at the first preset position may be obtained.
S300, obtaining the minimum distance between each standard point cloud data in A and each current point cloud data in B to obtain a minimum distance list LA= (LA 1,LA2,…,LAi,…,LAn) corresponding to A, wherein LA i is the minimum distance between A i and each current point cloud data in B.
In this embodiment, for a i, the distance of each current point cloud data in a i and B may be calculated, and then the minimum distance in the distances is calculated, so as to obtain the minimum distance LA i corresponding to a i, and further obtain LA.
S400, the number NUM 1 of the minimum distance larger than the preset distance L' in the LA is obtained.
In this embodiment, the preset distance L' may be obtained through a large number of experiments, which will not be described herein.
S500, if NUM 1 is less than NUM ', determining that the target blade is not deformed, otherwise, entering S600, wherein NUM' is a preset minimum distance quantity threshold.
In this embodiment, if the target blade is not deformed, then, in an ideal case, the minimum distance in LA should be smaller than L ', and in consideration of the presence of error in monitoring, in a case where the target blade is not deformed, there may be a case where the individual minimum distance in LA is larger than L ', so NUM ' is set to improve the accuracy of monitoring.
S600, a standard point cloud data list C= (C 1,C2,…,Ci,…,Cn) of a non-deformation target blade at a second preset position, which is acquired by an aerial laser radar, is acquired, wherein C i is point cloud data of an ith preset point on the target blade when the target blade is at the second preset position, the aerial laser radar is installed at the top of a host computer of a wind driven generator, and C is acquired through an aerial laser radar coordinate system.
In the embodiment, an aerial laser radar is further arranged at the top of a host of the wind driven generator, when the target blade is not deformed, the target blade can be placed at a second preset position, for example, the target blade is placed at a vertical upward position, point cloud data of the target blade when the target blade is located at the second preset position is obtained through the aerial laser radar arranged at the top of the host of the wind driven generator, and therefore C is obtained.
Further, the ground laser radar and the air laser radar in the embodiment are 512-line laser radar, and can completely cover the target blade.
S700, determining a deformation area of the target blade according to the C and the current point cloud data of the target blade at the second preset position, which are acquired by the aerial laser radar.
In the embodiment, if NUM is greater than or equal to NUM', deformation of the target blade cannot be determined directly at this time, because the position of the ground laser radar may be moved due to some factors, for example, the ground laser radar is manually moved, so that coordinates of the ground laser radar are changed, the obtained point cloud data of the target blade is changed greatly under the condition that the target blade is not deformed, and in order to improve the accuracy of judgment, auxiliary judgment is needed to be performed by using the point cloud data of the target blade obtained by the aerial laser radar.
Further, step S700 may include the steps of:
S710, acquiring a current point cloud data list D= (D 1,D2,…,Dp,…,Dq) of the target blade acquired by the aerial laser radar at a second preset position, wherein p=1, 2, & q, D p is the p-th current point cloud data acquired by the laser radar in the time space of the target blade at the second preset position, and q is the number of the current point cloud data acquired by the laser radar in the time space of the target blade at the second preset position.
In this embodiment, when the target blade is at the second preset position, the point cloud data corresponding to the target blade may be obtained by the aerial lidar to obtain D, and it should be noted that the time for the aerial lidar to obtain the point cloud data of the target blade each time is different, so that the number of the correspondingly obtained point cloud data may also be different.
S720, obtaining the distance between each standard point cloud data in C and each current point cloud data in D to obtain a distance list set LC= (LC 1,LC2,…,LCi,…,LCn) corresponding to C, wherein LC i is a distance list corresponding to C i, and LC i=（LCi,1,LCi,2,…,LCi,p,…,LCi,q）;LCi,p is the distance between C i and D p.
S730, determining a minimum distance list ZC= (ZC 1,ZC2,…,ZCi,…,ZCn) corresponding to C according to LC, wherein ZC i is the minimum distance corresponding to C i, ZC i=MIN（LCi, and MIN () is a preset minimum function.
S740, traversing the ZC, if the ZC i > L', determining C i as the first target point cloud data to obtain a first target point cloud data list e= (E 1,E2,…,Er,…,Es), r=1, 2,..s, where E r is the determined r first target point cloud data, and S is the determined number of first target point cloud data.
S750, if S < NUM', determining that the ground laser radar position moves, otherwise, entering S760.
In this embodiment, if s < NUM', the point cloud data acquired by the air lidar indicates that the target blade is not deformed, so that it can be determined that the position of the ground lidar is moving or that the ground lidar is faulty.
S760, determining the deformation area of the target blade according to the minimum distance greater than the preset distance L' in E and LA.
In this embodiment, if s is greater than or equal to NUM', it means that the aerial lidar also monitors that the target blade may be deformed, however, the position of the aerial lidar may also be moved, and thus further determination is required.
Further, step S760 may include the steps of:
And S761, traversing LA, if LA i is larger than L', determining A i as second target point cloud data to obtain a second target point cloud data list F= (F 1,F2,…,Fu,…,Fv), wherein u = 1,2, & v, F u is the determined u second target point cloud data, and v is the number of the determined second target point cloud data.
In this embodiment, if LA i > L', it indicates that the point corresponding to a i on the target blade is abnormal, and therefore, it is determined as the second target point cloud data.
And S762, clustering the first target point cloud data in the E and the second target point cloud data in the F by using a preset clustering algorithm according to the position coordinates corresponding to each first target point cloud data in the E and the position coordinates corresponding to each second target point cloud data in the F so as to obtain a cluster list CE corresponding to the E and a cluster list CF corresponding to the F.
In this embodiment, after the first target point cloud data with the abnormality in the E and the second target point cloud data with the abnormality in the F are determined, the first target point cloud data and the second target point cloud data are both corresponding to coordinates, the first target point cloud data and the second target point cloud data may be clustered according to the corresponding coordinates, so that adjacent points are clustered into one cluster, and the preset clustering algorithm may be a DBSCAN clustering algorithm.
S763, obtaining a sub-region corresponding to the first target point cloud data in each cluster in the CE to obtain a sub-region list qe= (QE 1,QE2,…,QEa,…,QEb) corresponding to the CE, a=1, 2.
S764, obtaining a sub-region corresponding to the cloud data of the first target point in each cluster in the CF to obtain a sub-region list qf= (QF 1,QF2,…,QFc,…,QFd) corresponding to the CF, c=1, 2.
S765, if b=d=1 and the overlapping area of QE 1 and QF 1 is greater than the preset overlapping area threshold, determining QE 1 or QF 1 as the deformation area of the target blade.
In this embodiment, it can be understood that the deformation area of the target blade is unchanged whether the target blade is located at the first preset position or the second preset position, and if b=d=1 and the overlapping area of QE 1 and QF 1 is greater than the preset overlapping area threshold, it means that the deformation areas of the target blade monitored by the ground laser radar and the air laser radar are the same area, and therefore, QE 1 or QF 1 is determined as the deformation area of the target blade.
Further, after step S765, the method may further include the steps of:
s766, if b=d >1, and the overlapping area of each sub-region in the QE and one sub-region in the QF is greater than the preset overlapping area threshold, determining each sub-region in the QE or each sub-region in the QF as the deformation region of the target blade.
In this embodiment, if b=d >1, and the overlapping area of each sub-region in the QE and one sub-region in the QF is greater than the preset overlapping area threshold, it indicates that the ground lidar and the aerial lidar both monitor a plurality of deformation regions, and the deformation regions monitored by the ground lidar and the deformation regions monitored by the aerial lidar are in one-to-one correspondence, so each sub-region in the QE or each sub-region in the QF is determined as the deformation region of the target blade.
And S767, if b=d >1 and the maximum overlapping area of the QE and each sub-region in the QF is smaller than a preset overlapping area threshold value, determining that the ground laser radar or the air laser radar is moved.
In this embodiment, if b=d >1, and the maximum overlapping area of the QE and each sub-area in the QF is smaller than the preset overlapping area threshold, it indicates that the ground lidar and the aerial lidar both monitor multiple deformation areas, but the deformation areas monitored by the ground lidar and the deformation areas monitored by the aerial lidar cannot be in one-to-one correspondence, which may be that the ground lidar or the aerial lidar moves in position.
If b is not equal to d, then determining that the ground laser radar or air laser radar position is moving S768.
In this embodiment, if b is not equal to d, it indicates that the number of deformation areas monitored by the ground lidar is different from the number of deformation areas monitored by the air lidar, and the result is less likely to be consistent, so that it is determined that the ground lidar or the air lidar moves in position.
For the above-mentioned case, it is possible to check whether the positions of the ground laser radar and the air laser radar are moved and whether the operation state is normal by a manual mode.
Further, after step S700, the method may further include the steps of:
S800, if the target blade has a deformation area, establishing a three-dimensional model corresponding to the target blade by using B.
And S810, coloring and displaying the deformation area on the three-dimensional model.
In this embodiment, after determining the deformed area on the target blade, the three-dimensional model corresponding to the target blade may be built using the B obtained in the above step, and the deformed area may be colored and displayed on the three-dimensional model, so as to prompt the user of the specific position of the deformed area.
According to the wind driven generator blade running state monitoring method based on three-dimensional modeling, a standard point cloud data list A of a target blade without deformation, which is acquired by a ground laser radar, at a first preset position is acquired, a current point cloud data list B of the target blade, which is acquired by the ground laser radar, at the first preset position is acquired, the minimum distance between each standard point cloud data in the A and each current point cloud data in the B is acquired to obtain a minimum distance list LA corresponding to the A, if the number NUM 1 of the minimum distances, which is larger than the preset distance L', in the LA is smaller than the number threshold of the preset minimum distances, the target blade is determined to be free from deformation, otherwise, the deformation area of the target blade is determined according to the C and the current point cloud data, which are acquired by the air laser radar, of the target blade at a second preset position, and therefore the overall deformation monitoring of the wind driven generator blade is achieved.
Furthermore, the ground laser radar and the air laser radar are arranged at the same time, the deformation of the target blade is monitored by using the point cloud data of the target blade obtained by the laser radars at different positions, and the probability that the laser radars with different space dimensions are moved at the same time is extremely small, so that the monitoring accuracy can be further improved.
Furthermore, although the steps of the methods in the present disclosure are depicted in a particular order in the drawings, this does not require or imply that the steps must be performed in that particular order, or that all illustrated steps be performed, to achieve desirable results. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step to perform, and/or one step decomposed into multiple steps to perform, etc.
Embodiments of the present invention also provide a non-transitory computer readable storage medium that may be disposed in an electronic device to store at least one instruction or at least one program for implementing one of the methods embodiments, the at least one instruction or the at least one program being loaded and executed by the processor to implement the methods provided by the embodiments described above.
The program product may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium can be, for example, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of a readable storage medium include an electrical connection having one or more wires, a portable disk, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
The computer readable signal medium may include a data signal propagated in baseband or as part of a carrier wave with readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A readable signal medium may also be any readable medium that is not a readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Program code for carrying out operations of the present application may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device, partly on a remote computing device, or entirely on the remote computing device or server. In the case of remote computing devices, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., connected via the Internet using an Internet service provider).
Embodiments of the present invention also provide an electronic device comprising a processor and the aforementioned non-transitory computer-readable storage medium.
The electronic device is merely an example, and should not impose any limitations on the functionality and scope of use of embodiments of the present application.
The electronic device is in the form of a general purpose computing device. The components of the electronic device may include, but are not limited to, the at least one processor, the at least one memory, and a bus connecting the various system components, including the memory and the processor.
Wherein the memory stores program code that is executable by the processor to cause the processor to perform steps in various embodiments described herein.
The memory may include readable media in the form of volatile memory, such as Random Access Memory (RAM) and/or cache memory, and may further include Read Only Memory (ROM).
The memory may also include programs/utilities having a set (at least one) of program modules including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each or some combination of which may include an implementation of a network environment.
The bus may be one or more of several types of bus structures including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor, or a local bus using any of a variety of bus architectures.
The electronic device may also communicate with one or more external devices (e.g., keyboard, pointing device, bluetooth device, etc.), with one or more devices that enable a user to interact with the electronic device, and/or with any device (e.g., router, modem, etc.) that enables the electronic device to communicate with one or more other computing devices. Such communication may be through an input/output (I/O) interface. And, the electronic device may also communicate with one or more networks such as a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network, such as the Internet, through a network adapter. The network adapter communicates with other modules of the electronic device via a bus. It should be appreciated that although not shown, other hardware and/or software modules may be used in connection with the electronic device, including, but not limited to, microcode, device drivers, redundant processors, external disk drive arrays, RAID systems, tape drives, data backup storage systems, and the like.
From the above description of embodiments, those skilled in the art will readily appreciate that the example embodiments described herein may be implemented in software, or may be implemented in software in combination with the necessary hardware. Thus, the technical solution according to the embodiments of the present disclosure may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (may be a CD-ROM, a U-disk, a mobile hard disk, etc.) or on a network, including several instructions to cause a computing device (may be a personal computer, a server, a terminal device, or a network device, etc.) to perform the method according to the embodiments of the present disclosure.
Embodiments of the present invention also provide a computer program product comprising program code for causing an electronic device to carry out the steps of the method according to the various exemplary embodiments of the invention as described in the specification, when said program product is run on the electronic device.
While certain specific embodiments of the invention have been described in detail by way of example, it will be appreciated by those skilled in the art that the above examples are for illustration only and are not intended to limit the scope of the invention. Those skilled in the art will also appreciate that many modifications may be made to the embodiments without departing from the scope and spirit of the invention.
Claims (7)
1. The wind driven generator blade running state monitoring method based on three-dimensional modeling is characterized by comprising the following steps of:
S100, acquiring a standard point cloud data list A= (A 1,A2,…,Ai,…,An) of a non-deformation target blade at a first preset position, wherein i=1, 2,.. N, wherein A i is point cloud data of an ith preset point on the target blade when the target blade is at the first preset position, and n is the number of preset points on the target blade;
S200, acquiring a current point cloud data list B= (B 1,B2,…,Bj,…,Bm) of a target blade acquired by the ground laser radar at a first preset position, wherein j=1, 2, & m, wherein B j is the j-th current point cloud data acquired by the ground laser radar when the target blade is at the first preset position, and m is the number of the current point cloud data acquired by the ground laser radar when the target blade is at the first preset position;
s300, obtaining the minimum distance between each standard point cloud data in A and each current point cloud data in B to obtain a minimum distance list LA= (LA 1,LA2,…,LAi,…,LAn) corresponding to A, wherein LA i is the minimum distance between A i and each current point cloud data in B;
s400, acquiring the number NUM 1 of the minimum distance larger than the preset distance L' in LA;
S500, if NUM 1 is less than NUM ', determining that the target blade is not deformed, otherwise, entering S600, wherein NUM' is a preset minimum distance quantity threshold;
S600, acquiring a standard point cloud data list C= (C 1,C2,…,Ci,…,Cn) of a non-deformed target blade at a second preset position, wherein C i is point cloud data of an ith preset point on the target blade when the target blade is at the second preset position, and the aerial laser radar is arranged at the top of a host of a wind driven generator;
S700, determining a deformation area of the target blade according to the C and the current point cloud data of the target blade at the second preset position acquired by the aerial laser radar;
step S700 includes the steps of:
S710, acquiring a current point cloud data list D= (D 1,D2,…,Dp,…,Dq) of a target blade acquired by the aerial laser radar at a second preset position, wherein p=1, 2, & q, wherein D p is the p-th current point cloud data acquired by the laser radar in the time space of the target blade at the second preset position, and q is the number of the current point cloud data acquired by the laser radar in the time space of the target blade at the second preset position;
s720, obtaining the distance between each standard point cloud data in C and each current point cloud data in D to obtain a distance list set LC= (LC 1,LC2,…,LCi,…,LCn) corresponding to C, wherein LC i is a distance list corresponding to C i, and LC i=（LCi,1,LCi,2,…,LCi,p,…,LCi,q）;LCi,p is the distance between C i and D p;
S730, determining a minimum distance list ZC= (ZC 1,ZC2,…,ZCi,…,ZCn) corresponding to C according to LC, wherein ZC i is the minimum distance corresponding to C i, ZC i=MIN（LCi) and MIN () is a preset minimum function;
S740, traversing the ZC, if the ZC i > L', determining C i as first target point cloud data to obtain a first target point cloud data list e= (E 1,E2,…,Er,…,Es), r=1, 2,..s, wherein E r is the determined r first target point cloud data, and S is the determined number of first target point cloud data;
s750, if S < NUM', determining that the ground laser radar position moves, otherwise, entering S760;
S760, determining the deformation area of the target blade according to the minimum distance greater than the preset distance L' in E and LA.
2. The method for monitoring the operational state of a wind turbine blade based on three-dimensional modeling of claim 1, wherein step S760 comprises the steps of:
S761, traversing LA, if LA i > L', determining a i as second target point cloud data to obtain a second target point cloud data list f= (F 1,F2,…,Fu,…,Fv), u=1, 2,..v, wherein F u is the determined u-th second target point cloud data, and v is the determined number of second target point cloud data;
S762, clustering the first target point cloud data in the E and the second target point cloud data in the F respectively by using a preset clustering algorithm according to the position coordinates corresponding to each first target point cloud data in the E and the position coordinates corresponding to each second target point cloud data in the F so as to obtain a cluster list CE corresponding to the E and a cluster list CF corresponding to the F;
S763, obtaining a sub-region corresponding to the cloud data of the first target point in each cluster in the CE to obtain a sub-region list QE= (QE 1,QE2,…,QEa,…,QEb) corresponding to the CE, wherein a = 1,2,..b, QE a is the sub-region corresponding to the cloud data of the first target point in the a-th cluster in the CE, and b is the number of clusters in the CE;
S764, obtaining a sub-region corresponding to the cloud data of the first target point in each cluster in the CF to obtain a sub-region list qf= (QF 1,QF2,…,QFc,…,QFd), c=1, 2, d; QF c is a sub-region corresponding to cloud data of a second target point in a c-th cluster in the CF, and d is the number of clusters in the CF;
S765, if b=d=1 and the overlapping area of QE 1 and QF 1 is greater than the preset overlapping area threshold, determining QE 1 or QF 1 as the deformation area of the target blade.
3. The method for monitoring the operational state of a wind turbine blade based on three-dimensional modeling according to claim 2, further comprising the steps of, after step S765:
S766, if b=d >1, and the overlapping area of each sub-region in the QE and one sub-region in the QF is greater than the preset overlapping area threshold, determining each sub-region in the QE or each sub-region in the QF as a deformed region of the target blade;
s767, if b=d >1, and the maximum overlapping area of the QE and each sub-area in the QF is smaller than the preset overlapping area threshold, determining that the ground laser radar or the air laser radar moves;
if b is not equal to d, then determining that the ground laser radar or air laser radar position is moving S768.
4. The method for monitoring the running state of the wind driven generator blade based on the three-dimensional modeling according to claim 2, wherein the preset clustering algorithm comprises a DBSCAN clustering algorithm.
5. The method for monitoring the running state of the wind driven generator blade based on the three-dimensional modeling according to claim 1, wherein the ground laser radar and the air laser radar are 512-line laser radars.
6. The method for monitoring the running state of a wind turbine blade based on three-dimensional modeling according to claim 1, wherein a and C are related to the current wind speed.
7. The method for monitoring the operational state of a wind turbine blade based on three-dimensional modeling according to claim 1, wherein after step S700, the method further comprises the steps of:
s800, if a deformation area exists in the target blade, establishing a three-dimensional model corresponding to the target blade by using the B;
And S810, coloring and displaying the deformation area on the three-dimensional model.
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