Wind tower deformation monitoring method and device

Abstract

The present disclosure proposes a method and device for monitoring the deformation of a wind tower, which relates to the field of data processing technology. The method includes: receiving a reference coordinate system sent by a terminal and an attitude quaternion corresponding to a target sensor at a current monitoring moment; wherein the target sensor is arranged on the wind tower to be monitored; determining the target coordinates of a target sampling point in the current carrier coordinate system of the target sensor in the reference coordinate system according to the attitude quaternion corresponding to the target sensor at the current monitoring moment; determining the current deformation information of the target sensor at the current monitoring moment according to the target coordinates; and sending the current deformation information to the terminal so that the terminal displays the current deformation information. Thus, it is possible to timely and effectively obtain the current deformation information of the wind tower to be monitored based on the target sensor and the reference coordinate system arranged on the wind tower to be monitored, thereby avoiding the influence of artificial objective judgment and improving the accuracy of deformation monitoring of the wind tower.

Description

Technical Field

[0001] The present disclosure relates to the field of data processing technology, and in particular to a method and device for monitoring deformation of a wind tower. Background Art

[0002] The wind tower is a typical mast structure, such as Figure 1 As shown, the mast structure of the wind tower is a tall structure consisting of an upright slender pole and several layers of fiber ropes arranged obliquely along the height direction. The pole is the main load-bearing structure, and the fiber ropes pull the pole in three or four directions to ensure the self-support and stability of the pole.

[0003] Although the mast structure of the wind tower has been widely used due to its advantages such as economy and beauty, its damage rate is also high, which is determined by its characteristics. Its characteristics are high pole, relatively small cross section, small stiffness and poor stability. At the same time, the safety and reliability of the mast structure is poor. As long as a rope is loose, a rope node plate is broken or a chord is unstable, it is easy to cause the destruction of the entire structure. Due to the high flexibility of the mast structure, its stiffness and damping are small. Under the action of wind load, the pole body is prone to large vibration. Strong wind and ice-wrapped ropes are very likely to produce galloping phenomena, causing the ropes to vibrate violently, resulting in the instability of local rods and local areas of the mast structure, thereby causing the overall stability to be lost and collapsed. Quantitative monitoring, evaluation and analysis of the deformation degree of the wind tower, ensuring the safe and normal operation of wind measurement equipment and wind towers, and obtaining complete and effective wind tower observation data are of great significance for effective and reasonable wind energy resource assessment and ensuring the smooth implementation of wind farm development and construction plans. Summary of the invention

[0004] The present disclosure aims to solve one of the technical problems in the related art at least to some extent.

[0005] The present disclosure proposes a method and device for monitoring deformation of a wind tower, so as to timely and effectively obtain the current deformation information of the wind tower to be monitored based on a target sensor and a reference coordinate system set on the wind tower to be monitored, avoid the influence of artificial objective judgment, and improve the accuracy of deformation information.

[0006] The first aspect of the present disclosure provides a method for monitoring deformation of a wind tower, which is applied to a server. The method includes:

[0007] The reference coordinate system sent by the receiving terminal and the attitude quaternion corresponding to the target sensor at the current monitoring time; wherein the target sensor is set on the wind tower to be monitored;

[0008] Determine the target coordinates of the target sampling point in the current carrier coordinate system of the target sensor in the reference coordinate system according to the attitude quaternion corresponding to the target sensor at the current monitoring moment;

[0009] Determine, according to the target coordinates, current deformation information of the target sensor at the current monitoring moment; wherein the current deformation information includes at least one of current verticality, current tilt direction, and current distortion;

[0010] The current deformation information is sent to the terminal, so that the terminal displays the current deformation information.

[0011] A second aspect of the present disclosure provides a method for monitoring deformation of a wind tower, which is applied to a terminal. The method includes:

[0012] In response to the user's operation on the display page, a target sensor is determined from a plurality of candidate sensors, and a reference coordinate system is determined from a plurality of preset coordinate systems; wherein the target sensor is set on a wind tower to be monitored;

[0013] Sending the reference coordinate system and the attitude quaternion corresponding to the target sensor at the current monitoring time to the server, so that the server determines the target coordinates of the target sampling point in the current carrier coordinate system of the target sensor in the reference coordinate system according to the attitude quaternion corresponding to the target sensor at the current monitoring time, and determines the current deformation information of the target sensor at the current monitoring time according to the target coordinates, and sends the current deformation information to the terminal; wherein the current deformation information includes at least one of the current verticality, the current tilt direction, and the current distortion;

[0014] The current deformation information sent by the server is received, and the current deformation information is displayed.

[0015] A third aspect of the present disclosure provides a wind tower deformation monitoring device, which is applied to a service end. The device includes:

[0016] A receiving module, used for receiving the reference coordinate system sent by the terminal and the attitude quaternion corresponding to the target sensor at the current monitoring time; wherein the target sensor is arranged on the wind tower to be monitored;

[0017] A first determination module, configured to determine the target coordinates of the target sampling point in the current carrier coordinate system of the target sensor in the reference coordinate system according to the attitude quaternion corresponding to the target sensor at the current monitoring moment;

[0018] A second determination module is used to determine the current deformation information of the target sensor at the current monitoring time according to the target coordinates; wherein the current deformation information includes at least one of a current verticality, a current tilt direction, and a current distortion;

[0019] The first sending module is used to send the current deformation information to the terminal, so that the terminal displays the current deformation information.

[0020] A fourth aspect of the present disclosure provides a wind tower deformation monitoring device, which is applied to a terminal. The device includes:

[0021] A determination module, configured to determine a target sensor from a plurality of candidate sensors and determine a reference coordinate system from a plurality of preset coordinate systems in response to a user's operation on the display page; wherein the target sensor is arranged on a wind tower to be monitored;

[0022] A sending module, used for sending the reference coordinate system and the attitude quaternion corresponding to the target sensor at the current monitoring time to the server, so that the server determines the target coordinates of the target sampling point in the current carrier coordinate system of the target sensor in the reference coordinate system according to the attitude quaternion corresponding to the target sensor at the current monitoring time, and determines the current deformation information of the target sensor at the current monitoring time according to the target coordinates, and sends the current deformation information to the terminal; wherein the current deformation information includes at least one of the current verticality, the current tilt direction, and the current distortion;

[0023] The receiving module is used to receive the current deformation information sent by the server and display the current deformation information.

[0024] The fifth aspect embodiment of the present disclosure proposes an electronic device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the wind tower deformation monitoring method proposed in the first aspect embodiment of the present disclosure is implemented, or the wind tower deformation monitoring method proposed in the second aspect embodiment of the present disclosure is implemented.

[0025] The sixth aspect embodiment of the present disclosure proposes a non-temporary computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, it implements the wind tower deformation monitoring method proposed in the first aspect embodiment of the present disclosure, or implements the wind tower deformation monitoring method proposed in the second aspect embodiment of the present disclosure.

[0026] Additional aspects and advantages of the present disclosure will be given in part in the following description and in part will be obvious from the following description or learned through practice of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The above and / or additional aspects and advantages of the present disclosure will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0028] Figure 1A schematic diagram of the structure of a wind tower provided by the present disclosure;

[0029] Figure 2 A schematic diagram of the flow of a method for monitoring deformation of a wind tower provided in the first embodiment of the present disclosure;

[0030] Figure 3 A schematic diagram of the flow of a method for monitoring deformation of a wind tower provided in the second embodiment of the present disclosure;

[0031] Figure 4 A schematic diagram of a polar coordinate system provided by the present disclosure;

[0032] Figure 5 A schematic diagram of the first tilted frequency distribution corresponding to each quadrant pair provided in the present disclosure;

[0033] Figure 6 A schematic diagram of the first verticality mean distribution corresponding to each quadrant pair provided in the present disclosure;

[0034] Figure 7 A schematic diagram of the flow of a method for monitoring deformation of a wind tower provided in Embodiment 3 of the present disclosure;

[0035] Figure 8 A schematic diagram of the flow of a method for monitoring deformation of a wind tower provided in the fourth embodiment of the present disclosure;

[0036] Fig. 9 A schematic diagram of the flow of a method for monitoring deformation of a wind tower provided in Embodiment 5 of the present disclosure;

[0037] Fig.10 A schematic diagram of the flow of a method for monitoring deformation of a wind tower provided in Embodiment 6 of the present disclosure;

[0038] Fig.11 A schematic diagram of a display page provided for the present disclosure;

[0039] Fig.12 A schematic diagram of a display page provided for the present disclosure;

[0040] Fig.13 A schematic diagram of a display page provided for the present disclosure;

[0041] Fig.14 A schematic diagram of the structure of a wind tower deformation monitoring device provided in Embodiment 7 of the present disclosure;

[0042] Fig.15 This is a structural schematic diagram of the wind tower deformation monitoring device provided in Example 8 of the present disclosure. DETAILED DESCRIPTION

[0043] Embodiments of the present disclosure are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present disclosure, and should not be construed as limiting the present disclosure.

[0044] The present disclosure provides a method and device for monitoring deformation of a wind tower.

[0045] The following describes the method and device for monitoring deformation of a wind tower according to an embodiment of the present disclosure with reference to the accompanying drawings.

[0046] Figure 2 This is a flow chart of the method for monitoring deformation of a wind tower provided in the first embodiment of the present disclosure.

[0047] The embodiment of the present disclosure takes the method for monitoring deformation of a wind tower configured in a device for monitoring deformation of a wind tower as an example. The device for monitoring deformation of a wind tower can be applied to any electronic device so that the electronic device can perform the function of monitoring deformation of a wind tower.

[0048] Among them, the electronic device can be any device with computing capabilities, such as a PC (Personal Computer), a mobile terminal, a server, etc. The mobile terminal can be, for example, a mobile phone, a tablet computer, a personal digital assistant, a wearable device, and other hardware devices with various operating systems, touch screens and / or display screens.

[0049] like Figure 2 As shown, the wind tower deformation monitoring method may include the following steps:

[0050] Step 201: receiving a reference coordinate system sent by a terminal and a posture quaternion corresponding to a target sensor at a current monitoring time.

[0051] The target sensor is arranged on the wind tower to be monitored, wherein the target sensor may be, for example, a gyroscope sensor.

[0052] Among them, the reference coordinate system (also called the reference coordinate system) can be, for example, a local coordinate system, a northeast celestial coordinate system (or a northeast celestial global coordinate system), a carrier coordinate system of a target sensor in a target state, and the like.

[0053] It should be noted that the target state may be, for example, a stationary state, or a state without significant shaking, or a state without wind or with light wind, and so on.

[0054] It should also be noted that in actual engineering installation, it is difficult to place the gyro sensor absolutely horizontally and strictly facing north. In order to reduce the engineering difficulty, it is necessary to use a custom reference coordinate system instead of the northeast sky coordinate system, that is, the attitude of the gyro in good conditions such as no wind and no deformation of the tower can be used as a reference, and the carrier coordinate system of the gyro sensor in this state will be determined as the reference coordinate system.

[0055] The reference coordinate system may be an O-XYZ rectangular coordinate system.

[0056] In the embodiment of the present disclosure, after the user determines the reference coordinate system, the terminal can send the reference coordinate system determined by the user to the server, and after the user determines the target sensor, the terminal can establish a communication connection with the target sensor to obtain the attitude quaternion corresponding to the target sensor at the current monitoring time, and can send the attitude quaternion corresponding to the target sensor at the current monitoring time to the server, so that the server can receive the reference coordinate system sent by the terminal and the attitude quaternion corresponding to the target sensor at the current monitoring time.

[0057] Step 202 : determining the target coordinates of the target sampling point in the current carrier coordinate system of the target sensor in the reference coordinate system according to the attitude quaternion corresponding to the target sensor at the current monitoring time.

[0058] Among them, the current carrier coordinate system can be an O-xyz rectangular coordinate system.

[0059] It is understandable that at the current monitoring moment, the target sensor has a corresponding posture. Therefore, the target sensor may have a corresponding carrier coordinate system at the current monitoring moment. In the present disclosure, the carrier coordinate system at the current moment is recorded as the current carrier coordinate system.

[0060] As a possible implementation method, the mapping relationship between the current carrier coordinate system and the reference coordinate system of the target sensor is determined according to the attitude quaternion corresponding to the target sensor at the current monitoring moment, and the target coordinates of the target sampling point in the current carrier coordinate system in the reference coordinate system can be determined according to the mapping relationship.

[0061] In the embodiment of the present disclosure, the mapping relationship between the current carrier coordinate system of the target sensor and the reference coordinate system may be determined according to the attitude quaternion corresponding to the target sensor at the current monitoring moment.

[0062] For example, assuming that the reference coordinate system is the northeast celestial coordinate system, the attitude quaternion corresponding to the target sensor at the current monitoring time is (q0, q1, q2, q3), the origin of the current carrier coordinate system tower is the same as the origin of the reference coordinate system g, and the rotation matrix from the current carrier coordinate system tower to the reference coordinate system g is For any sampling point ρ under the current carrier coordinate system tower s =(x,y,z) T , according to the rotation matrix from the current carrier coordinate system tower to the reference coordinate system g, determine the mapping relationship between the current carrier coordinate system tower and the reference coordinate system g, which can be expressed as:

[0063]

[0064] Among them, ρ r It refers to the coordinates of the sampling points in the current carrier coordinate system mapped to the reference coordinate system.

[0065] For another example, assuming that the reference coordinate system is the carrier coordinate system r of the target sensor in the target state, the attitude quaternion of the target sensor in the target state is (s0, s1, s2, s3), and the origins of the current carrier coordinate system tower, the reference coordinate system r and the northeast celestial coordinate system g corresponding to the target sensor at the current monitoring time are the same, the mapping relationship between the current carrier coordinate system tower of the target sensor and the reference coordinate system r can be determined by the following steps:

[0066] 1. According to the attitude quaternion (s0, s1, s2, s3) of the target sensor in the target state, determine the first rotation matrix between the carrier coordinate system r of the target sensor in the target state and the northeast celestial coordinate system g

[0067]

[0068] 2. According to the rotation matrix between the carrier coordinate system r and the northeast sky coordinate system g of the target sensor in the target state Determine the second rotation matrix from the northeast sky coordinate system g to the carrier coordinate system r of the target sensor in the target state

[0069]

[0070] 3. According to the attitude quaternion (q0, q1, q2, q3) of the target sensor at the current monitoring time, the third rotation matrix between the current carrier coordinate system tower of the target sensor and the northeast sky coordinate system g can be determined according to formula (2):

[0071] 4. For any sampling point ρ in the current carrier coordinate system tower of the target sensor s =(x,y,z) T , according to the second rotation matrix from the northeast sky coordinate system g to the carrier coordinate system r of the target sensor in the target state And the third rotation matrix between the current carrier coordinate system tower of the target sensor and the northeast sky coordinate system g Determine the mapping relationship between the current carrier coordinate system tower of the target sensor and the carrier coordinate system r of the target sensor in the target state. The mapping relationship can be expressed as:

[0072]

[0073] Among them, ρ r It refers to the coordinates of the sampling points in the current carrier coordinate system tower of the target sensor mapped to the carrier coordinate system r of the target sensor in the target state.

[0074] Thus, the mapping relationship between the current carrier coordinate system of the target sensor and the reference coordinate system can be effectively determined.

[0075] Therefore, in the present disclosure, the target coordinates of the target sampling point in the current carrier coordinate system in the reference coordinate system can be determined based on the mapping relationship.

[0076] The target sampling point may be pre-set, for example, a point with coordinates (0, 0, 1), or a point with coordinates (0, 1, 0), and so on.

[0077] For example, formulas (1) and (2) may be used to determine the target coordinates of the target sampling point in the current carrier coordinate system in the reference coordinate system.

[0078] Step 203: Determine the current deformation information of the target sensor at the current monitoring moment according to the target coordinates.

[0079] The current deformation information may include at least one of a current verticality, a current tilt direction, and a current distortion.

[0080] The current verticality is used to indicate the degree of inclination of the wind tower to be monitored at the current monitoring moment.

[0081] When the target sampling point is located on the z-axis of the current carrier coordinate system, the current tilt direction is determined based on the angle between the projection of the line between the target sampling point and the origin O on the XY plane in the reference coordinate system and the Y-axis.

[0082] When the target sampling point is located on the y-axis of the current carrier coordinate system, the current tilt direction is determined based on the angle between the projection of the line between the target sampling point and the origin O on the XY plane in the reference coordinate system and the Y-axis.

[0083] Still using the above example for illustration, assuming that the coordinates of the target sampling point in the current carrier coordinate system are (0, 0, 1), that is, the target sampling point is located on the z-axis of the current carrier coordinate system, then according to formula (1) and formula (2), the target coordinates (X1, Y1, Z1) of the target sampling point are determined as follows:

[0084]

[0085] The current verticality Δ of the wind tower to be monitored at the current monitoring time can be determined according to the following formula (7):

[0086]

[0087] It should be noted that the current verticality Δ has the same sign as X1;

[0088] According to the following formula (8) and formula (9), the current tilt direction θ of the wind tower to be monitored at the current monitoring time can be determined as:

[0089]

[0090] As another example, assuming that the coordinates of the target sampling point in the current carrier coordinate system are (0, 1, 0), that is, the target sampling point is located on the y-axis of the current carrier coordinate system, then according to formula (1) and formula (2), the target coordinates (X2, Y2, Z2) of the target sampling point are determined as follows:

[0091]

[0092] According to the following formulas (11) and (12), the current distortion φ of the wind tower to be monitored at the current monitoring time can be determined as:

[0093]

[0094] Step 204: Send the current deformation information to the terminal so that the terminal displays the current deformation information.

[0095] In the embodiment of the present disclosure, the current deformation information may be sent to the terminal so that the terminal displays the current deformation information.

[0096] In a possible implementation of the embodiment of the present disclosure, a plurality of third deformation information of the target sensor within a second set time period before the current monitoring moment is obtained; wherein the third deformation information may include a second verticality; the worst verticality is determined from the plurality of second verticalities and the current verticality; and the worst verticality is sent to the terminal so that the terminal displays the worst verticality.

[0097] The second set duration may be pre-set, such as 10 minutes, 5 minutes, etc., and the present disclosure does not impose any limitation on this.

[0098] It should be noted that the calculation method of the second verticality is similar to the calculation method of the current verticality, and this disclosure will not elaborate on this.

[0099] The worst verticality may be, for example, a minimum value among a plurality of second verticalities and the current verticality.

[0100] In a possible implementation of the embodiment of the present disclosure, the current deformation information of the wind tower to be monitored may be saved in the target database, thereby facilitating subsequent data calls.

[0101] The deformation monitoring method of a wind tower of the disclosed embodiment receives the reference coordinate system sent by the terminal, and the attitude quaternion corresponding to the target sensor at the current monitoring moment; wherein the target sensor is arranged on the wind tower to be monitored; according to the attitude quaternion corresponding to the target sensor at the current monitoring moment, the target coordinates of the target sampling point in the current carrier coordinate system of the target sensor in the reference coordinate system are determined; according to the target coordinates, the current deformation information of the target sensor at the current monitoring moment is determined; wherein the current deformation information includes at least one of the current verticality, the current tilt direction, and the current distortion; and the current deformation information is sent to the terminal so that the terminal displays the current deformation information. Thus, it is possible to timely and effectively obtain the current deformation information of the wind tower to be monitored based on the target sensor and the reference coordinate system arranged on the wind tower to be monitored, thereby avoiding the influence of artificial objective judgment and improving the accuracy of deformation information.

[0102] It is understandable that under the influence of wind force or engineering quality, the ropes of the wind tower to be monitored are unevenly stressed. Therefore, it is necessary to remind the user of the unevenly stressed ropes. Figure 3 , the above process is described in detail.

[0103] Figure 3 This is a flow chart of the method for monitoring deformation of a wind tower provided in the second embodiment of the present disclosure.

[0104] like Figure 3 As shown, based on the above embodiments of the present disclosure, the wind tower deformation monitoring method may further include the following steps:

[0105] Step 301: Acquire a plurality of first deformation information of a target sensor within a first set time period before a current monitoring moment.

[0106] The first deformation information may include a first verticality and a first tilt direction.

[0107] It should be noted that the calculation method of the first verticality is similar to the calculation method of the current verticality in step 203, and the present disclosure will not elaborate on this.

[0108] It should also be noted that the calculation method of the first tilt direction is similar to the calculation method of the current tilt direction in step 203, and the present disclosure will not elaborate on this.

[0109] In the embodiment of the present disclosure, the first set duration may be, for example, 24 hours, 15 days, 30 days, etc., and the present disclosure does not impose any limitation on this.

[0110] Step 302: Based on each first verticality, determine a plurality of target analysis samples from a plurality of first deformation information, and determine the quadrant in which the first tilt direction in each target analysis sample is located in the set coordinate system.

[0111] The coordinate system is set to be divided into an even number of quadrants.

[0112] The set coordinate system may be, for example, a polar coordinate system.

[0113] As an example, assume that the coordinate system is set to a polar coordinate system, where the polar coordinate system takes true north as 0 degrees and is divided into 16 quadrants clockwise. Assume that the quadrant division of the polar coordinate system is as follows: Figure 4 As shown, the starting angle and ending angle of each quadrant in the polar coordinate system are shown in Table 1:

[0114] Table 1 Starting angle and ending angle of each quadrant in the polar coordinate system

[0115]

[0116]

[0117] It should be noted that the above-mentioned examples of dividing the polar coordinate system are only exemplary. In practical applications, other division methods may be used to divide the polar coordinate system, and the present disclosure does not impose any limitation on this.

[0118] In the embodiment of the present disclosure, a plurality of target analysis samples may be determined from a plurality of first deformation information based on the first verticalities.

[0119] In order to determine multiple target analysis samples from multiple first deformation information, as a possible implementation method, first, the first verticalities can be arranged in ascending order to obtain a sorting sequence; secondly, the predicted number can be determined based on the total number of first deformation information and a set ratio; thirdly, the first verticality in the sorting sequence whose sequence number is less than or equal to the predicted number can be determined as the target verticality; finally, the first deformation information corresponding to the target verticality can be determined as the target analysis sample.

[0120] In the embodiment of the present disclosure, the set ratio may be pre-set, for example, it may be 90%, 93%, etc., and the present disclosure does not impose any limitation on this.

[0121] As an example, assuming that there are 100 pieces of first deformation information and the ratio is set to 90%, correspondingly, there are 100 first verticalities, and the first verticalities can be arranged in order from small to large to obtain a corresponding sorting sequence; based on the total number of first deformation information 100 and the set ratio 90%, the predicted number is determined to be 90 (=100*90%); the first verticality in the sorting sequence whose sequence number is less than or equal to the predicted number 90 is determined as the target verticality; finally, the first deformation information corresponding to the target verticality can be determined as the target analysis sample.

[0122] In this way, it is possible to effectively obtain target analysis samples from multiple first deformation information.

[0123] In the embodiment of the present disclosure, the quadrant in which the first tilt direction in each target analysis sample is located in the set coordinate system can also be determined. For example, assuming that the set coordinate system is a polar coordinate system, the polar coordinate system is divided into the following Figure 1 Among the 16 quadrants shown, the first tilt direction in the target analysis sample 1 is 33.5°. According to the division method in Table 1, it can be determined that the quadrant where the first tilt direction in the target analysis sample 1 is located in the set coordinate system is the second quadrant.

[0124] Step 303, for any quadrant in the set coordinate system, determine the first tilt frequency corresponding to the quadrant according to the number of first analysis samples in the quadrant; wherein the first analysis sample is a target analysis sample with a first tilt direction in the quadrant.

[0125] As an example, for any quadrant in the set coordinate system, the number of first analysis samples in the quadrant may be determined as the first tilt frequency corresponding to the quadrant.

[0126] For example, assuming that the target analysis samples include sample 1, sample 2, sample 3, sample 4, and sample 5, for the third quadrant in the set coordinate system, assuming that the first tilt directions of sample 1, sample 2, and sample 3 are all in the third quadrant, then it can be determined that sample 1, sample 2, and sample 3 are all the first analysis samples in the third quadrant, and the first tilt frequency corresponding to the third quadrant can be determined to be 3.

[0127] Step 304 : determining a first verticality mean value corresponding to the quadrant according to the first tilt frequency corresponding to the quadrant and the first verticality in each first analysis sample of the quadrant.

[0128] As an example, the ratio of the sum of the first verticalities in the first analysis samples of the quadrant to the first tilt frequency corresponding to the quadrant may be determined as the first verticality mean value corresponding to the quadrant.

[0129] Still using the above example for explanation, assuming that the first verticality in sample 1 of the third quadrant is Q1, the first verticality in sample 2 is Q2, and the first verticality in sample 3 is Q3, then the average first verticality corresponding to the third quadrant is (Q1+Q2+Q3) / 3.

[0130] Step 305 , for any quadrant pair in the set coordinate system, determine the symmetric value of the first tilt direction distribution corresponding to the quadrant pair according to the first tilt frequency corresponding to the first quadrant and the first tilt frequency corresponding to the second quadrant.

[0131] The first quadrant and the second quadrant are any two quadrants that have a matching relationship in a set coordinate system, and the quadrant pair includes the first quadrant and the second quadrant.

[0132] In the embodiment of the present disclosure, two quadrants that are symmetrical about the pole center in the set coordinate system may be determined as quadrants that have a matching relationship.

[0133] For example, suppose the coordinate system is set to Figure 4 In the polar coordinate system in , the 1st quadrant and the 9th quadrant have a matching relationship, so the 1st quadrant and the 9th quadrant can be determined as a quadrant pair, wherein the first quadrant is the 1st quadrant and the second quadrant is the 9th quadrant, or the first quadrant is the 9th quadrant and the second quadrant is the 1st quadrant.

[0134] The symmetric value of the first tilt direction distribution may be used to indicate the symmetry of the distribution of the first tilt direction in the corresponding quadrant pair.

[0135] As a possible implementation, when the coordinate system is divided into 2m (m is a positive integer greater than 0) quadrants, for the i-th quadrant pair in the set coordinate system, the following formula can be used to determine the symmetric value of the first tilt direction distribution corresponding to the i-th quadrant pair:

[0136]

[0137] Among them, the first quadrant in the i-th quadrant pair is the i-th quadrant in the set coordinate system, and the second quadrant in the i-th quadrant pair is the i±m-th quadrant in the set coordinate system. Characterizes the first tilt frequency corresponding to the first quadrant, or Characterizes the first tilt frequency corresponding to the second quadrant.

[0138] It should be noted that, when the value of the distribution symmetry of the first tilt direction corresponding to the quadrant pair is higher, the distribution symmetry of the first tilt direction in the corresponding quadrant pair is lower.

[0139] Step 306: Determine symmetrical values ​​of the first verticality distribution corresponding to the quadrant pair according to the first verticality mean value corresponding to the first quadrant and the first verticality mean value corresponding to the second quadrant.

[0140] The symmetric value of the first verticality distribution may be used to indicate the symmetry of the distribution of the first verticality in the corresponding quadrant pair.

[0141] As a possible implementation, when the coordinate system is divided into 2m (m is a positive integer greater than 0) quadrants, for the i-th quadrant pair in the set coordinate system, the following formula can be used to determine the first verticality distribution symmetry value S corresponding to the i-th quadrant pair: Δi :

[0142]

[0143] in, Characterizes the first verticality mean corresponding to the first quadrant, or Characterizes the first verticality mean corresponding to the second quadrant.

[0144] It should be noted that, when the symmetric value of the first verticality distribution corresponding to the quadrant pair is higher, the symmetry of the distribution of the first verticality in the corresponding quadrant pair is lower.

[0145] Step 307, based on the first tilt frequency and the first verticality mean corresponding to each quadrant, as well as the symmetric values ​​of the first tilt direction distribution and the symmetric values ​​of the first verticality distribution corresponding to the quadrant pair where each quadrant is located, determine the target quadrant from each quadrant, and send the target quadrant to the terminal so that the user can pay attention to the stress condition of the target fiber rope located in the target quadrant; wherein the target fiber rope is a fiber rope set on the wind tower to be monitored.

[0146] As an example, it is assumed that the first tilt frequencies corresponding to each quadrant are as shown in Table 2:

[0147] Table 2 The first tilt frequency distribution table corresponding to each quadrant

[0148]

[0149] Then the first tilt frequency distribution corresponding to each quadrant pair is as follows Figure 5 As shown, the first tilt direction corresponding to each quadrant pair is symmetrically distributed and has the following values ​​as shown in Table 3:

[0150] Table 3 Symmetrical distribution values ​​of the first tilt direction corresponding to each quadrant pair

[0151]

[0152]

[0153] Assume that the mean values ​​of the first verticality corresponding to each quadrant are as shown in Table 4:

[0154] Table 4 Distribution table of the first verticality mean values ​​corresponding to each quadrant

[0155]

[0156] Then the mean distribution of the first verticality corresponding to each quadrant pair is as follows: Figure 6 As shown, the first verticality distribution corresponding to each quadrant pair is symmetrically distributed as shown in Table 5:

[0157] Table 5 Symmetrical values ​​of the first verticality distribution corresponding to each quadrant pair

[0158] Quadrant Pair <![CDATA[S Δi (%)]]> Quadrant 1 pair (Quadrant 1 and Quadrant 9) 27.0 Quadrant 2 pair (Quadrant 2 and Quadrant 10) 2.7 Quadrant 3 Pair (Quadrant 3 and Quadrant 11) 48.5 4th Quadrant Pair (Quadrant 4 and Quadrant 12) 70.2 Quadrant 5 Pair (Quadrant 5 and Quadrant 13) 99.4 Quadrant 6 Pair (Quadrant 6 and Quadrant 14) 139.5 Quadrant 7 Pair (Quadrant 7 and Quadrant 15) 121.6 8th Quadrant Pair (8th and 16th Quadrant) 61.6

[0159] Based on the first tilt frequency corresponding to each quadrant and the symmetrical distribution value of the first tilt direction corresponding to the quadrant pair where each quadrant is located, it can be determined that the swing of the wind tower to be monitored at the height where the target sensor is located is concentrated in the first quadrant pair (i.e., the first and ninth quadrants). Although the symmetrical distribution values ​​of the first tilt direction of the second, third and fourth quadrant pairs of the wind tower to be monitored are higher, the symmetry of the tilt of the wind tower to be monitored to the second, third and fourth quadrant pairs is lower, but it is not obvious as a whole. It can be determined that the force on the wind tower to be monitored is uniform in the quadrant pairs other than the first quadrant pair, and the tower body of the wind tower to be monitored is relatively stable. Based on the mean value of the first verticality corresponding to each quadrant and the symmetrical distribution value of the first verticality corresponding to the quadrant pair where each quadrant is located, it can be determined that the wind tower to be monitored at the height where the target sensor is located has a larger tilt degree in the first quadrant pair, and the tilt degree on the west side is larger than that on the east side. In summary, the high-frequency and large-scale tilt of the wind tower to be monitored at the height where the target sensor is located occurs in the first quadrant pair, so the first quadrant pair can be determined as the target quadrant, that is, the first quadrant and the ninth quadrant are determined as the target quadrant, and the target quadrant is sent to the terminal so that the user can pay attention to the stress condition of the target fiber rope located in the target quadrant; wherein, the target fiber rope is a fiber rope set on the wind tower to be monitored.

[0160] The deformation monitoring method of a wind tower in an embodiment of the present disclosure obtains a plurality of first deformation information of a target sensor within a first set time period before a current monitoring moment; wherein the first deformation information includes a first verticality and a first tilt direction; based on each first verticality, a plurality of target analysis samples are determined from the plurality of first deformation information, and the quadrant in which the first tilt direction in each target analysis sample is located in the set coordinate system is determined; wherein the set coordinate system is divided into an even number of quadrants; for any quadrant in the set coordinate system, the first tilt frequency corresponding to the quadrant is determined according to the number of first analysis samples in the quadrant; wherein the first analysis sample is a target analysis sample with a tilt direction in the quadrant; according to the tilt frequency corresponding to the quadrant and the first verticality in each first analysis sample in the quadrant, the first verticality mean corresponding to the quadrant is determined; for any quadrant pair in the set coordinate system, the quadrant is determined according to the first tilt frequency corresponding to the first quadrant and the first tilt frequency corresponding to the second quadrant. The corresponding first tilt direction distribution is symmetrically valued; wherein, the first quadrant and the second quadrant are any two quadrants that have a matching relationship in the set coordinate system, the quadrant pair includes the first quadrant and the second quadrant, and the first tilt direction distribution symmetrically valued is used to indicate the distribution symmetry of the first tilt direction in the corresponding quadrant pair; according to the first verticality mean value corresponding to the first quadrant and the first verticality mean value corresponding to the second quadrant, the first verticality distribution symmetrical value corresponding to the quadrant pair is determined; wherein, the first verticality distribution symmetrical value is used to indicate the distribution symmetry of the first verticality in the corresponding quadrant pair; based on the first tilt frequency and the first verticality mean value corresponding to each quadrant, as well as the first tilt direction distribution symmetrical value and the first verticality distribution symmetrical value corresponding to the quadrant pair where each quadrant is located, the target quadrant is determined from each quadrant, and the target quadrant is sent to the terminal, so that the user can pay attention to the stress condition of the target fiber rope located in the target quadrant; wherein the target fiber rope is the fiber rope set on the wind tower to be monitored. Therefore, the target fiber rope with greater force in the wind tower to be monitored can be effectively determined, so that the user can pay attention to the target fiber rope, which is applicable.

[0161] In a possible implementation of the present disclosure, the collapse risk level of the wind tower to be monitored can be predicted based on the deformation information of the target sensor. Figure 6 The above process is described in detail.

[0162] Figure 7 This is a flow chart of the method for monitoring deformation of a wind tower provided in the third embodiment of the present disclosure.

[0163] like Figure 7 As shown, based on the above embodiments of the present disclosure, the wind tower deformation monitoring method may further include the following steps:

[0164] Step 701 : Acquire a plurality of second deformation information of a target sensor in any first monitoring period of a plurality of first monitoring periods before a current monitoring moment; wherein the second deformation information includes a first distortion.

[0165] It should be noted that the calculation method of the first verticality is similar to the calculation method of the current twisting degree in step 203, and the present disclosure will not elaborate on this.

[0166] In the embodiment of the present disclosure, the duration of the first monitoring cycle can be 5 minutes, 10 minutes, 20 minutes, etc., and the present disclosure does not impose any limitation on this.

[0167] In the embodiment of the present disclosure, there may be multiple first monitoring cycles before the current monitoring moment.

[0168] Therefore, in the present disclosure, a plurality of second deformation information of the target sensor in any first monitoring period of a plurality of first monitoring periods before the current monitoring moment is obtained.

[0169] As an example, multiple second deformation information of the target sensor in each first monitoring period may be stored in advance, so that in subsequent data applications, multiple second deformation information of the target sensor in any first monitoring period may be directly obtained from the stored information.

[0170] Step 702: Determine the distortion frequency of the target sensor according to each first distortion degree of the target sensor in a plurality of first monitoring cycles.

[0171] In the embodiment of the present disclosure, according to each first distortion degree of the target sensor in a plurality of first monitoring cycles, the distortion frequency corresponding to the target sensor may be determined by using the following formula:

[0172]

[0173] Among them, P φ represents the distortion frequency corresponding to the target sensor, n represents the total number of first distortions of the target sensor in multiple first monitoring cycles, φ m represents the mth first distortion degree of the target sensor in multiple first monitoring cycles, and COUNT(·) is a counting function.

[0174] Step 703, for the i-th first monitoring cycle among multiple first monitoring cycles, determine the standard deviation corresponding to the target sensor in the i-th first monitoring cycle based on multiple first distortions of the target sensor in the i-th first monitoring cycle; wherein i∈[1,r] and i is a positive integer, and r is the number of first monitoring cycles.

[0175] As an example, it is assumed that the first distortions of the target sensor in the i-th first monitoring cycle are φ1, φ2, ... φ k , where k is the number of first distortions in the i-th first monitoring cycle, the standard deviation of the target sensor in the i-th first monitoring cycle can be determined according to the following formula:

[0176]

[0177]

[0178] in, represents the standard deviation of the target sensor in the first monitoring cycle of i, represents the average value of each first distortion in the i-th first monitoring cycle.

[0179] Step 704 : determining the distortion influence degree corresponding to the target sensor in the i-th first monitoring period based on the distortion frequency corresponding to the target sensor and the standard deviation corresponding to the target sensor in the i-th first monitoring period.

[0180] In the embodiment of the present disclosure, based on the distortion frequency corresponding to the target sensor and the standard deviation corresponding to the target sensor in the i-th first monitoring period, the distortion influence degree corresponding to the target sensor in the i-th first monitoring period can be determined by the following formula:

[0181]

[0182] Among them, Q i It represents the distortion influence degree of the target sensor in the first monitoring cycle of i, represents the standard deviation of the target sensor in the first monitoring cycle of i, Represents the normalized value of each standard deviation, min(σ φ ) represents the minimum value of the standard deviation of the target sensor corresponding to each first monitoring period, max(σ φ ) represents the maximum value of the standard deviation of the target sensor corresponding to each first monitoring period.

[0183] Step 705 : determining the distortion influence level of the target sensor in the i-th first monitoring period based on the distortion influence level corresponding to the target sensor in the i-th first monitoring period.

[0184] Optionally, the distortion impact level may include distortion impact level one, distortion impact level two, and distortion impact level three.

[0185] As an example, in the case where the distortion impact level includes distortion impact level 1, distortion impact level 2, and distortion impact level 3, when the distortion impact level of the target sensor in the i-th first monitoring period is in the range of [0, 0.3), it can be determined that the distortion impact level of the target sensor in the i-th first monitoring period is distortion impact level 1; when the distortion impact level of the target sensor in the i-th first monitoring period is in the range of [0.3, 0.4), it can be determined that the distortion impact level of the target sensor in the i-th first monitoring period is distortion impact level 2; when the distortion impact level of the target sensor in the i-th first monitoring period is in the range of [0.4, 0.5], it can be determined that the distortion impact level of the target sensor in the i-th first monitoring period is distortion impact level 3. Therefore, the division of distortion impact levels is shown in Table 6:

[0186] Table 6 Classification of distortion impact levels

[0187] Distortion Impact Level Distortion Impact Level 1 Distortion Impact Level 2 Distortion Impact Level 3 Distortion influence value range [0,0.3) [0.3,0.4) [0.4,0.5]

[0188] It should be noted that the above classification of distortion influence levels is only exemplary. In practical applications, it can also be other levels, and this application does not impose any limitation on this.

[0189] Step 706: Determine a first prediction level of the wind tower to be monitored based on the distortion influence level corresponding to the target sensor in each first monitoring period.

[0190] The first prediction level is used to indicate the tower collapse risk level of the wind tower to be monitored.

[0191] As a possible implementation manner, the first prediction level of the wind tower to be monitored may be determined according to the following steps:

[0192] Step 7061: Determine the first number of first monitoring periods for each distortion impact level according to the type of distortion impact level corresponding to each first monitoring period.

[0193] As an example, assuming that the distortion impact levels include distortion impact level 1, distortion impact level 2, and distortion impact level 3, when the distortion impact level corresponding to the first monitoring period is distortion impact level 1, it is the first category, when the distortion impact level corresponding to the first monitoring period is distortion impact level 2, it is the second category, and when the distortion impact level corresponding to the first monitoring period is distortion impact level 3, it is the third category.

[0194] Therefore, in the present disclosure, the first number of first monitoring periods for each distortion impact level may be determined according to the type of distortion impact level corresponding to each first monitoring period.

[0195] As an example, assuming that the first monitoring period includes period 1, period 2, period 3, period 4, period 5, and period 6, and the distortion level corresponding to period 1 is distortion impact level 1, the distortion level corresponding to period 2 is distortion impact level 2, the distortion level corresponding to period 3 is distortion impact level 2, the distortion level corresponding to period 4 is distortion impact level 1, the distortion level corresponding to period 5 is distortion impact level 1, and the distortion level corresponding to period 6 is distortion impact level 3, then the first number of the first monitoring period with distortion level 1 is 3, the first number of the first monitoring period with distortion level 2 is 2, and the first number of the first monitoring period with distortion level 3 is 1.

[0196] Step 7062: Determine a first ratio corresponding to a corresponding type of distortion impact level according to the first number of first monitoring cycles of each distortion impact level and the total number of first monitoring cycles.

[0197] As a possible implementation manner, for any distortion impact level, the ratio of the first number of first monitoring cycles of the distortion impact level to the total number of first monitoring cycles can be determined as the first ratio corresponding to the distortion impact level.

[0198] Still using the above example for explanation, for a distortion impact level of distortion impact level one, the ratio of the first number 3 of the first monitoring period of distortion impact level one to the total number 6 of the first monitoring period can be determined as the first ratio corresponding to this distortion impact level (i.e., distortion impact level one), i.e., 1 / 2; for a distortion impact level of distortion impact level two, the ratio of the first number 2 of the first monitoring period of distortion impact level two to the total number 6 of the first monitoring period can be determined as the first ratio corresponding to this distortion impact level (i.e., distortion impact level two), i.e., 1 / 3; for a distortion impact level of distortion impact level three, the ratio of the first number 1 of the first monitoring period of distortion impact level three to the total number 6 of the first monitoring period can be determined as the first ratio corresponding to this distortion impact level (i.e., distortion impact level three), i.e., 1 / 6.

[0199] Step 7063: Determine a first prediction level based on first ratios corresponding to various distortion influence levels.

[0200] As a possible implementation method, when the distortion impact level includes distortion impact level one, distortion impact level two, and distortion impact level three, when the first ratio corresponding to distortion impact level three is not less than the first set threshold, the first prediction level can be determined to be extremely high risk; when the first ratio corresponding to distortion impact level two is not less than the second set threshold, and the first ratio corresponding to distortion impact level three is not less than the third set threshold, the first prediction level can be determined to be high risk; when the first ratio corresponding to distortion impact level two is not less than the fourth set threshold, and the first ratio corresponding to distortion impact level three is not less than the fifth set threshold, the first prediction level can be determined to be medium risk; when the first ratio corresponding to distortion impact level two is less than the sixth set threshold, and the first ratio corresponding to distortion impact level three is not less than the seventh set threshold, the first prediction level can be determined to be low risk; when the first ratio corresponding to distortion impact level one is greater than the eighth set threshold, and the first ratio corresponding to distortion impact level three is less than the ninth set threshold, the first prediction level can be determined to be safe.

[0201] It should be noted that the first set threshold, the second set threshold, the third set threshold, the fourth set threshold, the fifth set threshold, the sixth set threshold, the seventh set threshold, the eighth set threshold, and the ninth set threshold are all pre-set, and the present disclosure does not impose any restrictions on the values ​​of the above-mentioned set thresholds.

[0202] As an example, the determination of the first prediction level of the wind tower to be monitored is shown in Table 8:

[0203] Table 8 Determination of the first prediction level of the wind tower to be monitored

[0204]

[0205] It should be noted that the values ​​of the above-mentioned threshold values ​​are only exemplary and may be other values ​​in practical applications, and the present disclosure does not impose any limitation on this.

[0206] It should also be noted that the settings of the first set threshold, the second set threshold, the third set threshold, the fourth set threshold, the fifth set threshold, the sixth set threshold, the seventh set threshold, the eighth set threshold, and the ninth set threshold can be obtained based on a large number of experimental foundations.

[0207] Therefore, it is possible to effectively determine the first prediction level based on the first ratios corresponding to various distortion influence levels, that is, to effectively determine the tower collapse risk level of the wind tower to be monitored.

[0208] The deformation monitoring method of a wind tower of the disclosed embodiment can effectively predict the collapse risk level of the wind tower to be monitored, so that relevant staff can judge the engineering quality of the wind tower to be monitored according to the collapse risk level of the wind tower to be monitored and take corresponding wind protection measures.

[0209] It is understandable that a plurality of target sensors may be provided on the wind tower to be monitored. In a possible implementation of the present disclosure, when the coordinate system is divided into 2m quadrants and the number of target sensors is n, the risk of collapse of the wind tower to be monitored can be predicted based on the deformation information of the wind tower to be monitored at the n target sensors, wherein any target sensor is provided at a height corresponding to the wind tower to be monitored, and m and n are both natural numbers not equal to 0. Figure 7 The above process is described in detail.

[0210] Figure 8 This is a flow chart of the method for monitoring deformation of a wind tower provided in the fourth embodiment of the present disclosure.

[0211] like Figure 8 As shown, based on the above embodiments of the present disclosure, the wind tower deformation monitoring method may further include the following steps:

[0212] Step 801 : for any target sensor and any second monitoring period in a plurality of second monitoring periods before a current monitoring moment, obtain a plurality of third deformation information of the target sensor in the second monitoring period.

[0213] The third deformation information may include a second verticality and a second tilt direction.

[0214] It should be noted that the calculation method of the second verticality is similar to the calculation method of the current verticality in step 203, and the present disclosure will not elaborate on this.

[0215] It should also be noted that the calculation method of the second tilt direction is similar to the calculation method of the current tilt direction in step 203, and this disclosure will not elaborate on this.

[0216] In the embodiment of the present disclosure, the duration of the second monitoring cycle can be 5 minutes, 10 minutes, 20 minutes, etc., and the present disclosure does not impose any limitation on this.

[0217] It should be noted that the duration of the second monitoring cycle may be the same as or different from the duration of the first monitoring cycle in step 701, and this application does not impose any limitation on this.

[0218] In the embodiment of the present disclosure, there may be multiple second monitoring cycles before the current monitoring moment.

[0219] Therefore, in the present disclosure, for any target sensor and any second monitoring period in multiple second monitoring periods before the current monitoring moment, multiple third deformation information of the target sensor in the second monitoring period can be obtained.

[0220] For example, multiple third deformation information of each target sensor in each second monitoring period may be stored in advance, so that in subsequent data applications, multiple third deformation information of any target sensor in any second monitoring period may be directly obtained from the stored information.

[0221] Step 802: Determine, based on a plurality of third deformation information, that the target sensor has symmetrically distributed values ​​in a second tilt direction corresponding to a second monitoring period.

[0222] It should be noted that the method for calculating the symmetric value of the second tilt direction distribution corresponding to the second monitoring period of the target sensor is similar to the method for calculating the symmetric value of the first tilt direction distribution in the previous embodiment, and will not be described in detail here.

[0223] Step 803, for the i-th quadrant pair of the j-th target sensor, determine the first coefficient of variation of the i-th quadrant pair of the j-th target sensor according to the symmetrical distribution of values ​​of the second tilt direction corresponding to the j-th target sensor in each second monitoring period; wherein, i∈[1,m] and i is a positive integer, j∈[1,n] and j is a positive integer.

[0224] In the embodiment of the present disclosure, for the i-th quadrant pair of the j-th target sensor, the following formula can be used to determine the first coefficient of variation α of the i-th quadrant pair of the j-th target sensor: θji :

[0225]

[0226] Where i∈[1,m] and i is a positive integer, j∈[1,n] and j is a positive integer, k is the sequence number of the second monitoring period, S θjik Characterizes that the i-th quadrant of the j-th target sensor has a symmetrical distribution of values ​​in the second tilt direction corresponding to the k-th second monitoring period, min(S θji ) represents the minimum value of the symmetrical distribution of the second tilt direction corresponding to the i-th quadrant pair of the j-th target sensor in each second monitoring period, max(S θji ) represents the maximum value of the symmetrical distribution of the second tilt direction corresponding to the i-th quadrant pair of the j-th target sensor in each second monitoring period, is the normalized value corresponding to the i-th quadrant pair of the j-th target sensor in the k-th second monitoring period, and σ(·) is the standard deviation function.

[0227] Step 804 : determining a first variation level of the i-th quadrant pair of the j-th target sensor according to the first variation coefficient of the i-th quadrant pair of the j-th target sensor.

[0228] Optionally, the first variation level includes primary, secondary, and tertiary levels of the first variation.

[0229] As an example, in the case where the first variation level includes the first, second, and third levels of the first variation, when the value range of the first variation coefficient of the i-th quadrant pair of the j-th target sensor is [0, 0.3), the first variation level of the i-th quadrant pair of the j-th target sensor can be determined to be the first level of the first variation; when the value range of the first variation coefficient of the i-th quadrant pair of the j-th target sensor is [0.3, 0.4), the first variation level of the i-th quadrant pair of the j-th target sensor can be determined to be the second level of the first variation; when the value range of the first variation coefficient of the i-th quadrant pair of the j-th target sensor is [0.4, 0.5], the first variation level of the i-th quadrant pair of the j-th target sensor can be determined to be the third level of the first variation. Therefore, the division of the first variation level is shown in Table 9:

[0230] Table 9 Classification of the first variation level

[0231]

[0232] It should be noted that the above classification of the first variation level is only exemplary, and in practical applications, it can also be other, and this application does not limit this.

[0233] Step 805 , for the i-th quadrant pair, determine the highest level among the first variation levels of the i-th quadrant pair of each target sensor as the first reference level of the i-th quadrant pair; wherein i∈[1,m] and i is a positive integer.

[0234] As an example, assuming that for the third quadrant pair, the first variation level of the third quadrant pair of target sensor 1 is the first level of the first variation, the first variation level of the third quadrant pair of target sensor 2 is the second level of the first variation, the first variation level of the third quadrant pair of target sensor 3 is the second level of the first variation, the first variation level of the third quadrant pair of target sensor 4 is the first level of the first variation, and the first variation level of the third quadrant pair of target sensor 5 is the first level of the first variation, then the highest level among the above first variation levels is the second level of the first variation, and it can be determined that the first reference level of the third quadrant pair is the second level of the first variation.

[0235] Step 806: Determine the second prediction level of the wind tower to be monitored according to the first reference level of each quadrant pair.

[0236] The second prediction level may be used to indicate the tower collapse risk level of the wind tower to be monitored.

[0237] In the embodiment of the present disclosure, the second prediction level of the wind tower to be monitored may be determined according to the first reference level of each quadrant pair.

[0238] As a possible implementation manner, the second prediction level of the wind tower to be monitored may be determined according to the following steps:

[0239] Step 8061: Determine the second number of quadrant pairs of each first reference level according to the type of the first reference level of each quadrant pair.

[0240] As an example, assuming that the first reference level includes the first, second, and third levels of the first variation, then when the first reference level of the quadrant pair is the first level of the first variation, it is the first category, when the first reference level of the quadrant pair is the second level of the first variation, it is the first category, and when the first reference level of the quadrant pair is the third level of the first variation, it is the third category.

[0241] Therefore, in the present disclosure, the second number of quadrant pairs of each first reference level may be determined according to the type of the first reference level of each quadrant pair.

[0242] As an example, assume that the first reference level of each quadrant pair is as shown in Table 10:

[0243] Table 10 First reference level for each quadrant pair

[0244] Quadrant Pair First reference level Quadrant 1 pair (Quadrant 1 and Quadrant 9) First Variation Level Quadrant 2 pair (Quadrant 2 and Quadrant 10) Secondary to the first variation Quadrant 3 Pair (Quadrant 3 and Quadrant 11) The third level of the first variation 4th Quadrant Pair (Quadrant 4 and Quadrant 12) The third level of the first variation Quadrant 5 Pair (Quadrant 5 and Quadrant 13) Secondary to the first variation Quadrant 6 Pair (Quadrant 6 and Quadrant 14) First Variation Level Quadrant 7 Pair (Quadrant 7 and Quadrant 15) Secondary to the first variation 8th Quadrant Pair (8th and 16th Quadrant) The third level of the first variation

[0245] According to the type of the first reference level of each quadrant pair in Table 10, the second number of quadrant pairs for each first reference level can be determined, that is, the second number of quadrant pairs whose first reference level is the first level of the first variation is 2, the second number of quadrant pairs whose first reference level is the second level of the first variation is 3, and the second number of quadrant pairs whose first reference level is the third level of the first variation is 3.

[0246] Step 8062: Determine a second ratio corresponding to the first reference level of the corresponding type according to the second number of quadrant pairs of each first reference level and the total number of quadrant pairs.

[0247] As a possible implementation manner, for any first reference level, the ratio of the first number of quadrant pairs of the first reference level to the total number of quadrant pairs can be determined as the second ratio corresponding to the first reference level.

[0248] Still using the above example to illustrate, for the first level of the first variation, the ratio of the first quantity 2 of the quadrant pairs whose first reference level is the first level of the first variation to the total quantity 8 of the quadrant pairs can be determined as the second ratio corresponding to the first level of the first variation, that is, 1 / 4; for the second level of the first variation, the ratio of the first quantity 3 of the quadrant pairs whose first reference level is the second level of the first variation to the total quantity 8 of the quadrant pairs can be determined as the second ratio corresponding to the second level of the first variation, that is, 3 / 8; for the third level of the first variation, the ratio of the first quantity 3 of the quadrant pairs whose first reference level is the third level of the first variation to the total quantity 8 of the quadrant pairs can be determined as the second ratio corresponding to the third level of the first variation, that is, 3 / 8.

[0249] Step 8063: Determine a second prediction level according to second ratios corresponding to various first reference levels.

[0250] In the embodiment of the present disclosure, the second prediction level may be determined according to the second ratios corresponding to various first reference levels.

[0251] As a possible implementation, when the first reference level includes the first, second, and third levels of the first variation, when the second ratio corresponding to the third level of the first variation is not less than the tenth set threshold, the second prediction level can be determined to be extremely high risk; when the second ratio corresponding to the second level of the first variation is not less than the eleventh set threshold, and the second ratio corresponding to the third level of the first variation is not less than the twelfth set threshold, the second prediction level can be determined to be high risk; when the second ratio corresponding to the second level of the first variation is not less than the thirteenth set threshold, and the second ratio corresponding to the third level of the first variation is not less than the fourteenth set threshold, the second prediction level can be determined to be medium risk; when the second ratio corresponding to the second level of the first variation is less than the fifteenth set threshold, and the second ratio corresponding to the third level of the first variation is not less than the sixteenth set threshold, the second prediction level can be determined to be low risk; when the second ratio corresponding to the first level of the first variation is greater than the seventeenth set threshold, and the second ratio corresponding to the third level of the first variation is less than the eighteenth set threshold, the second prediction level can be determined to be a safe level.

[0252] Among them, it should be noted that the tenth set threshold, the eleventh set threshold, the twelfth set threshold, the thirteenth set threshold, the fourteenth set threshold, the fifteenth set threshold, the sixteenth set threshold, the seventeenth set threshold, and the eighteenth set threshold are all pre-set, and the present disclosure does not impose any restrictions on the values ​​of the above-mentioned set thresholds.

[0253] As an example, the second prediction level of the wind tower to be monitored is determined as shown in Table 11:

[0254] Table 11 Determination table of the second prediction level of the wind tower to be monitored

[0255]

[0256] It should be noted that the values ​​of the above-mentioned threshold values ​​are only exemplary and may be other values ​​in practical applications, and the present disclosure does not impose any limitation on this.

[0257] It should also be noted that the tenth set threshold, the eleventh set threshold, the twelfth set threshold, the thirteenth set threshold, the fourteenth set threshold, the fifteenth set threshold, the sixteenth set threshold, the seventeenth set threshold, and the eighteenth set threshold can be obtained based on a large number of experimental foundations.

[0258] Therefore, it is possible to effectively determine the second prediction level based on the second ratios corresponding to various first reference levels, that is, to effectively determine the tower collapse risk level of the wind tower to be monitored.

[0259] The deformation monitoring method for a wind tower according to the disclosed embodiment can effectively predict the collapse risk level of a wind tower to be monitored.

[0260] It should be noted that another method can be used to predict the collapse risk level of the wind tower to be monitored. The above process is described in detail below in conjunction with 9.

[0261] Fig. 9 This is a flow chart of the method for monitoring deformation of a wind tower provided in Embodiment 5 of the present disclosure.

[0262] like Fig. 9 As shown, based on the above embodiments of the present disclosure, the wind tower deformation monitoring method may further include the following steps:

[0263] Step 901 : for any target sensor and any second monitoring period, determine, based on a plurality of second deformation information, a symmetrical value of a second verticality distribution corresponding to the target sensor in the second monitoring period.

[0264] It should be noted that the method for calculating the second verticality distribution symmetric value corresponding to the second monitoring period of the target sensor is similar to the method for calculating the first verticality distribution symmetric value in the above embodiment, and will not be elaborated here.

[0265] Step 902, for the i-th quadrant pair of the j-th target sensor, determine the second coefficient of variation of the i-th quadrant pair of the j-th target sensor according to the symmetrical values ​​of the second verticality distribution corresponding to the j-th target sensor in each second monitoring period; wherein, i∈[1,m] and i is a positive integer, j∈[1,n] and j is a positive integer.

[0266] In the embodiment of the present disclosure, for the i-th quadrant pair of the j-th target sensor, the second coefficient of variation of the i-th quadrant pair of the j-th target sensor can be determined by the following formula:

[0267]

[0268] Where i∈[1,m] and i is a positive integer, j∈[1,n] and j is a positive integer, k is the sequence number of the second monitoring period, S Δjik Characterizes that the second verticality distribution corresponding to the i-th quadrant of the j-th target sensor in the k-th second monitoring period is symmetrical, min(S Δji ) represents the minimum value of the symmetrical values ​​of the second verticality distribution corresponding to the i-th quadrant pair of the j-th target sensor in each second monitoring period, max(S Δji ) represents the maximum value of the symmetrical values ​​of the second verticality distribution corresponding to the i-th quadrant pair of the j-th target sensor in each second monitoring period, is the normalized value corresponding to the i-th quadrant pair of the j-th target sensor in the k-th second monitoring period, and σ(·) is the standard deviation function.

[0269] Step 903: Determine a second variation level of the i-th quadrant pair of the j-th target sensor according to the second variation coefficient of the i-th quadrant pair of the j-th target sensor.

[0270] Optionally, the second variation level includes primary, secondary, and tertiary levels of the second variation.

[0271] As an example, when the second variation level includes the first, second, and third levels of the second variation, when the value range of the second variation coefficient of the i-th quadrant pair of the j-th target sensor is [0, 0.3), the second variation level of the i-th quadrant pair of the j-th target sensor can be determined to be the first level of the second variation; when the value range of the second variation coefficient of the i-th quadrant pair of the j-th target sensor is [0.3, 0.4), the second variation level of the i-th quadrant pair of the j-th target sensor can be determined to be the second level of the second variation; when the value range of the second variation coefficient of the i-th quadrant pair of the j-th target sensor is [0.4, 0.5], the second variation level of the i-th quadrant pair of the j-th target sensor can be determined to be the third level of the second variation. Therefore, the division of the second variation level is shown in Table 12:

[0272] Table 12 Classification of the second variation level

[0273]

[0274] It should be noted that the above classification of the second variation level is only exemplary. In practical applications, it can be other, and this application does not limit this.

[0275] Step 904 , for the i-th quadrant pair, determine the highest level among the second variation levels of the i-th quadrant pair of each target sensor as the second reference level of the i-th quadrant pair; wherein i∈[1,m] and i is a positive integer.

[0276] As an example, assuming that for the first quadrant pair, the second variation level of the first quadrant pair of target sensor 1 is the third level of the second variation, the second variation level of the first quadrant pair of target sensor 2 is the first level of the second variation, the second variation level of the first quadrant pair of target sensor 3 is the second level of the second variation, the second variation level of the first quadrant pair of target sensor 4 is the first level of the second variation, and the second variation level of the first quadrant pair of target sensor 5 is the first level of the second variation, then the highest level among the above second variation levels is the third level of the second variation, and it can be determined that the second reference level of the first quadrant pair is the third level of the second variation.

[0277] Step 905: Determine the third prediction level of the wind tower to be monitored according to the second reference level of each quadrant pair.

[0278] The third prediction level may be used to indicate the tower collapse risk level of the wind tower to be monitored.

[0279] In the embodiment of the present disclosure, the third prediction level of the wind tower to be monitored may be determined according to the second reference level of each quadrant pair.

[0280] As a possible implementation manner, the third prediction level of the wind tower to be monitored may be determined according to the following steps:

[0281] Step 9051: Determine the third number of quadrant pairs of each second reference level according to the type of the second reference level of each quadrant pair.

[0282] It should be noted that the method for determining the third number of quadrant pairs of each second reference level is similar to the method for determining the second number of quadrant pairs of each first reference level in step 7061, and will not be elaborated here.

[0283] Step 9052: Determine a third ratio corresponding to the second reference level of the corresponding type according to the third number of quadrant pairs of each type of second reference level and the total number of quadrant pairs.

[0284] As a possible implementation manner, for any second reference level, the ratio of the third number of quadrant pairs of the second reference level to the total number of quadrant pairs can be determined as the third ratio corresponding to the second reference level.

[0285] Still using the above example for explanation, for the first level of the second variation, the ratio of the third quantity 1 of the quadrant pairs whose second reference level is the first level of the second variation to the total quantity 8 of the quadrant pairs can be determined as the third proportion corresponding to the first level of the second variation, that is, 1 / 8; for the second level of the second variation, the ratio of the third quantity 3 of the quadrant pairs whose second reference level is the second level of the second variation to the total quantity 8 of the quadrant pairs can be determined as the third proportion corresponding to the second level of the second variation, that is, 3 / 8; for the third level of the second variation, the ratio of the third quantity 4 of the quadrant pairs whose second reference level is the third level of the second variation to the total quantity 8 of the quadrant pairs can be determined as the third proportion corresponding to the third level of the second variation, that is, 1 / 2 (i.e., 4 / 8).

[0286] Step 9053: Determine a third prediction level according to the second proportions corresponding to various second reference levels.

[0287] In the embodiment of the present disclosure, the third prediction level may be determined according to third ratios corresponding to various second reference levels.

[0288] As a possible implementation method, when the second reference level includes the first, second and third levels of the second variation, when the third ratio corresponding to the third level of the second variation is not less than the nineteenth set threshold, the third prediction level can be determined to be extremely high risk; when the third ratio corresponding to the second level of the second variation is not less than the twentieth set threshold, and the third ratio corresponding to the third level of the second variation is not less than the twenty-first set threshold, the third prediction level can be determined to be high risk; when the third ratio corresponding to the second level of the second variation is not less than the twenty-second set threshold, and the third ratio corresponding to the third level of the second variation is not less than the twenty-third set threshold, the third prediction level can be determined to be medium risk; when the third ratio corresponding to the second level of the second variation is less than the twenty-fourth set threshold, and the third ratio corresponding to the third level of the second variation is not less than the twenty-fifth set threshold, the third prediction level can be determined to be low risk; when the third ratio corresponding to the first level of the second variation is greater than the twenty-sixth set threshold, and the third ratio corresponding to the third level of the second variation is less than the twenty-seventh set threshold, the third prediction level can be determined to be a safe level.

[0289] It should be noted that the nineteenth set threshold, the twentieth set threshold, the twenty-first set threshold, the twenty-second set threshold, the twenty-third set threshold, the twenty-fourth set threshold, the twenty-fifth set threshold, the twenty-sixth set threshold, and the twenty-seventh set threshold are all pre-set, and the present disclosure does not impose any restrictions on the values ​​of the above-mentioned set thresholds.

[0290] As an example, the third prediction level of the wind tower to be monitored is determined as shown in Table 13:

[0291] Table 13 Determination of the second prediction level of the wind tower to be monitored

[0292]

[0293] It should be noted that the values ​​of the above-mentioned threshold values ​​are only exemplary and may be other values ​​in practical applications, and the present disclosure does not impose any limitation on this.

[0294] It should also be noted that the nineteenth set threshold, the twentieth set threshold, the twenty-first set threshold, the twenty-second set threshold, the twenty-third set threshold, the twenty-fourth set threshold, the twenty-fifth set threshold, the twenty-sixth set threshold, and the twenty-seventh set threshold can be obtained based on a large number of experimental foundations.

[0295] Therefore, it is possible to effectively determine the second prediction level based on the third ratios corresponding to various second reference levels, that is, effectively determine the tower collapse risk level of the wind tower to be monitored.

[0296] As a possible implementation method, when the tower collapse risk level of the wind tower to be monitored exists in the first prediction level, the second prediction level and the third prediction level, the first prediction level, the second prediction level and the third prediction level can be compared to determine the highest prediction level from the first prediction level, the second prediction level and the third prediction level, and the highest prediction level can be determined as the target tower collapse risk level of the wind tower to be monitored, and the target tower collapse risk level can be sent to the terminal so that the user can promptly adopt wind protection measures corresponding to the target tower collapse risk level.

[0297] It should be noted that the explanation of the first prediction level in step 706 and the explanation of the first prediction level in step 806 are also applicable to this embodiment and are not elaborated here.

[0298] The deformation monitoring method for a wind tower according to the disclosed embodiment can effectively predict the collapse risk level of a wind tower to be monitored.

[0299] The above is an explanation of the deformation monitoring method of a wind tower from the service end side. The following is an explanation of the deformation monitoring method of a wind tower from the terminal side.

[0300] Fig.10 This is a flow chart of the method for monitoring deformation of a wind tower provided in Embodiment 6 of the present disclosure.

[0301] like Fig.10 As shown, the wind tower deformation monitoring method may also include the following steps:

[0302] Step 1001 , in response to a user operation on a display page, a target sensor is determined from a plurality of candidate sensors, and a reference coordinate system is determined from a plurality of preset coordinate systems.

[0303] The target sensor may be arranged on a wind tower to be monitored.

[0304] Among them, the reference coordinate system is the O-XYZ rectangular coordinate system.

[0305] Among them, the candidate sensor may be a gyroscope sensor.

[0306] In the embodiment of the present disclosure, in response to the user's operation on the display page, a target sensor may be determined from a plurality of candidate sensors.

[0307] For example, Fig.11 As shown, the display page can display relevant information of multiple candidate sensors, so that the user can select a target sensor based on the relevant information of the multiple candidate sensors displayed on the display page.

[0308] It should be noted that when the candidate sensor provides at least one of multiple communication methods such as CAN (Controller Area Network) communication, MODBUS serial communication protocol, Bluetooth, etc., the corresponding communication method can be used to establish communication between the candidate sensor and the terminal. For example, when the gyroscope sensor uses Bluetooth communication, the Bluetooth communication method can be used to establish communication between the gyroscope sensor and the terminal, so that the gyroscope sensor can be searched through the terminal's device search, and the searched gyroscope sensor can be added to the device list.

[0309] In one possible embodiment of the present disclosure, Fig.12 As shown, the display page can also set at least one of a connection device component, a disconnection component, a deletion device component and a manual addition component; wherein the connection device component is used to establish communication between the terminal and the selected target sensor, the disconnection component is used to disconnect the communication between the terminal and the selected target sensor, the deletion device component is used to delete the target sensor related information from the display page, and the manual addition component is used to obtain manually input target sensor related information.

[0310] In an embodiment of the present disclosure, in response to a user's operation on a display page, a reference coordinate system may be determined from a plurality of preset coordinate systems.

[0311] For example, Fig.13 As shown, the display page can display multiple preset coordinate systems, so that in response to the user's selection operation, the reference coordinate system can be determined from the multiple preset coordinate systems.

[0312] Step 1002, sending the reference coordinate system and the attitude quaternion corresponding to the target sensor at the current monitoring time to the server, so that the server determines the target coordinates of the target sampling point in the current carrier coordinate system of the target sensor in the reference coordinate system according to the attitude quaternion corresponding to the target sensor at the current monitoring time, and determines the current deformation information of the target sensor at the current monitoring time according to the target coordinates, and sends the current deformation information to the terminal.

[0313] The current deformation information may include at least one of the current verticality, the current tilt direction, and the current distortion. It should be noted that the explanation of the current verticality, the current tilt direction, and the current distortion in step 203 is also applicable to this embodiment and will not be repeated here.

[0314] In the disclosed embodiment, after the user determines the target sensor, the terminal can establish a communication connection with the target sensor, thereby obtaining the attitude quaternion corresponding to the target sensor at the current monitoring time, and can send the attitude quaternion corresponding to the target sensor at the current monitoring time to the server. Similarly, after the user determines the reference coordinate system, the terminal can send the reference coordinate system to the server.

[0315] Thus, the server can receive the reference coordinate system sent by the terminal and the attitude quaternion corresponding to the target sensor at the current monitoring time.

[0316] Step 1003, receiving the current deformation information sent by the server, and displaying the current deformation information.

[0317] In the embodiment of the present disclosure, the terminal may receive the current deformation information sent by the server, and may display the current deformation information.

[0318] The method for monitoring deformation of a wind tower of the disclosed embodiment determines a target sensor from a plurality of candidate sensors and determines a reference coordinate system from a plurality of preset coordinate systems in response to an operation of a user on a display page; wherein the target sensor is arranged on the wind tower to be monitored; sends the reference coordinate system and the attitude quaternion corresponding to the target sensor at the current monitoring time to the server, so that the server determines the target coordinates of the target sampling point in the current carrier coordinate system of the target sensor in the reference coordinate system according to the attitude quaternion corresponding to the target sensor at the current monitoring time, and determines the current deformation information of the target sensor at the current monitoring time according to the target coordinates, and sends the current deformation information to the terminal; wherein the current deformation information includes at least one of the current verticality, the current tilt direction, and the current distortion, the current verticality is used to indicate the tilt degree of the wind tower to be monitored at the current monitoring time, and the current distortion is used to indicate the angle between the projection of the line between the target sampling point and the origin O on the XY plane and the Y axis at the current monitoring time; receives the current deformation information sent by the server, and displays the current deformation information. Therefore, it is possible to timely and effectively obtain the current deformation information of the wind tower to be monitored based on the target sensor and the reference coordinate system flexibly determined by the user.

[0319] With the above Figures 2 to 9 Corresponding to the wind tower deformation monitoring method provided in the embodiment, the present disclosure also provides a wind tower deformation monitoring device. Figures 2 to 9 The wind tower deformation monitoring method provided in the embodiment corresponds to the wind tower deformation monitoring method, so the implementation of the wind tower deformation monitoring method is also applicable to the wind tower deformation monitoring device provided in the embodiment of the present disclosure, and will not be described in detail in the embodiment of the present disclosure.

[0320] Fig.14 This is a structural schematic diagram of a wind tower deformation monitoring device provided in Embodiment 7 of the present disclosure.

[0321] like Fig.14 As shown, the wind tower deformation monitoring device 1400 may include: a receiving module 1401 , a first determining module 1402 , a second determining module 1403 and a first sending module 1404 .

[0322] The receiving module 1401 is used to receive the reference coordinate system sent by the terminal and the attitude quaternion corresponding to the target sensor at the current monitoring time; wherein the target sensor is set on the wind tower to be monitored.

[0323] The first determination module 1402 is used to determine the target coordinates of the target sampling point in the current carrier coordinate system of the target sensor in the reference coordinate system according to the attitude quaternion corresponding to the target sensor at the current monitoring moment.

[0324] The second determination module 1403 is used to determine the current deformation information of the target sensor at the current monitoring moment according to the target coordinates; wherein the current deformation information includes at least one of the current verticality, the current tilt direction, and the current distortion.

[0325] The first sending module 1404 is configured to send the current deformation information to the terminal so that the terminal displays the current deformation information.

[0326] In a possible implementation of the embodiment of the present disclosure, the wind tower deformation monitoring device 1400 may further include:

[0327] The first acquisition module is used to acquire a plurality of first deformation information of the target sensor within a first set time period before the current monitoring moment; wherein the first deformation information includes a first verticality and a first tilt direction.

[0328] A third determination module is used to determine a plurality of target analysis samples from the plurality of first deformation information based on the first verticalities, and determine the quadrant in which the first tilt direction in each target analysis sample is located in a set coordinate system; wherein the set coordinate system is divided into an even number of quadrants;

[0329] The fourth determination module is used to determine the first tilt frequency corresponding to any quadrant in the set coordinate system according to the number of first analysis samples in the quadrant; wherein the first analysis sample is a target analysis sample with a first tilt direction in the quadrant.

[0330] The fifth determination module is used to determine a first verticality mean value corresponding to the quadrant according to the first tilt frequency corresponding to the quadrant and the first verticality in each first analysis sample of the quadrant.

[0331] The sixth determination module is used to determine, for any quadrant pair in the set coordinate system, the symmetric value of the first tilt direction distribution corresponding to the quadrant pair according to the first tilt frequency corresponding to the first quadrant and the first tilt frequency corresponding to the second quadrant; wherein the first quadrant and the second quadrant are any two quadrants that have a matching relationship in the set coordinate system, the quadrant pair includes the first quadrant and the second quadrant, and the symmetric value of the first tilt direction distribution is used to indicate the distribution symmetry of the first tilt direction in the corresponding quadrant pair.

[0332] The seventh determination module is used to determine the symmetric value of the first verticality distribution corresponding to the quadrant pair according to the first verticality mean value corresponding to the first quadrant and the first verticality mean value corresponding to the second quadrant; wherein the symmetric value of the first verticality distribution is used to indicate the distribution symmetry of the first verticality in the corresponding quadrant pair.

[0333] A processing module is used to determine a target quadrant from each quadrant based on the first tilt frequency and the first verticality mean value corresponding to each quadrant, as well as the symmetrical distribution values ​​of the first tilt direction and the symmetrical distribution values ​​of the first verticality corresponding to the quadrant pair where each quadrant is located, and send the target quadrant to the terminal so that the user can pay attention to the stress condition of the target fiber rope located in the target quadrant; wherein the target fiber rope is a fiber rope set on the wind tower to be monitored.

[0334] In a possible implementation of the embodiment of the present disclosure, the wind tower deformation monitoring device 1400 may further include:

[0335] The second acquisition module is used to acquire a plurality of second deformation information of the target sensor in any first monitoring period of a plurality of first monitoring periods before a current monitoring moment; wherein the second deformation information includes a first distortion.

[0336] The eighth determination module is used to determine the distortion frequency corresponding to the target sensor according to each first distortion degree of the target sensor in a plurality of first monitoring cycles by using the following formula:

[0337] Among them, φ m -φ m-1 ≠0, m=2, 3…n

[0338] Among them, P φ represents the distortion frequency corresponding to the target sensor, n represents the total number of first distortions of the target sensor in multiple first monitoring cycles, φ m represents the mth first distortion degree of the target sensor in multiple first monitoring cycles, and COUNT(·) is a counting function.

[0339] The ninth determination module is used to determine the standard deviation corresponding to the target sensor in the i-th first monitoring cycle among multiple first monitoring cycles based on multiple first distortions of the target sensor in the i-th first monitoring cycle; wherein i∈[1,r] and i is a positive integer, and r is the number of first monitoring cycles.

[0340] The tenth determination module is used to determine the distortion influence degree corresponding to the target sensor in the i-th first monitoring period by using the following formula based on the distortion frequency corresponding to the target sensor and the standard deviation corresponding to the target sensor in the i-th first monitoring period:

[0341]

[0342] Among them, Q i It represents the distortion influence degree of the target sensor in the first monitoring cycle of i, represents the standard deviation of the target sensor in the first monitoring cycle of i, Represents the normalized value of each standard deviation, min(σ φ ) represents the minimum value of the standard deviation of the target sensor corresponding to each first monitoring period, max(σ φ ) represents the maximum value of the standard deviation of the target sensor corresponding to each first monitoring period.

[0343] The eleventh determining module is used to determine the distortion influence level of the target sensor in the i-th first monitoring period based on the distortion influence corresponding to the target sensor in the i-th first monitoring period.

[0344] The twelfth determination module is used to determine the first prediction level of the wind tower to be monitored based on the distortion influence level corresponding to the target sensor in each first monitoring period; wherein the first prediction level is used to indicate the tower collapse risk level of the wind tower to be monitored.

[0345] In a possible implementation of the embodiments of the present disclosure, the twelfth determination module is used to: determine the first number of first monitoring periods for each distortion impact level according to the type of distortion impact level corresponding to each first monitoring period; determine the first ratio corresponding to the corresponding type of distortion impact level according to the first number of first monitoring periods for each distortion impact level and the total number of first monitoring periods; and determine the first prediction level based on the first ratios corresponding to various distortion impact levels.

[0346] In a possible implementation of the embodiment of the present disclosure, the distortion impact level includes distortion impact level one, distortion impact level two, and distortion impact level three; the twelfth determination module is used to: in response to the first ratio corresponding to the distortion impact level three being not less than the first set threshold, determine that the first prediction level is extremely high risk; in response to the first ratio corresponding to the distortion impact level two being not less than the second set threshold, and the first ratio corresponding to the distortion impact level three being not less than the third set threshold, determine that the first prediction level is high risk; in response to the first ratio corresponding to the distortion impact level two being not less than the fourth set threshold, and the first ratio corresponding to the distortion impact level three being not less than the fifth set threshold, determine that the first prediction level is medium risk; in response to the first ratio corresponding to the distortion impact level two being less than the sixth set threshold, and the first ratio corresponding to the distortion impact level three being not less than the seventh set threshold, determine that the first prediction level is low risk; in response to the first ratio corresponding to the distortion impact level one being greater than the eighth set threshold, and the first ratio corresponding to the distortion impact level three being less than the ninth set threshold, determine that the first prediction level is safe level.

[0347] In a possible implementation of the embodiment of the present disclosure, the coordinate system is divided into 2m quadrants, the number of target sensors is n, wherein any target sensor is set at a height corresponding to the wind tower to be monitored, and m and n are both natural numbers not equal to 0; the wind tower deformation monitoring device 1400 may further include:

[0348] The third acquisition module is used to acquire multiple third deformation information of the target sensor in the second monitoring period for any target sensor and any second monitoring period before the current monitoring moment; wherein the third deformation information includes the second verticality and the second tilt direction.

[0349] A thirteenth determination module is used to determine, based on the plurality of third deformation information, that the target sensor is symmetrically distributed in the second tilt direction corresponding to the second monitoring period.

[0350] The fourteenth determination module is used to determine the first variation coefficient α of the i-th quadrant pair of the j-th target sensor by using the following formula: θji :

[0351]

[0352] Where i∈[1,m] and i is a positive integer, j∈[1,n] and j is a positive integer, k is the sequence number of the first monitoring cycle, S θjik Characterizes that the i-th quadrant of the j-th target sensor has a symmetrical distribution of values ​​in the second tilt direction corresponding to the k-th second monitoring period, min(S θji ) represents the minimum value of the symmetrical distribution of the second tilt direction corresponding to the i-th quadrant pair of the j-th target sensor in each second monitoring period, max(S θji ) represents the maximum value of the symmetrical distribution of the second tilt direction corresponding to the i-th quadrant pair of the j-th target sensor in each second monitoring period, is the normalized value corresponding to the i-th quadrant pair of the j-th target sensor in the k-th second monitoring period, and σ(·) is the standard deviation function.

[0353] The fifteenth determination module is used to determine a first variation level of the i-th quadrant pair of the j-th target sensor according to a first variation coefficient of the i-th quadrant pair of the j-th target sensor.

[0354] The sixteenth determination module is used to determine, for the i-th quadrant pair, the highest level among the first variation levels of the i-th quadrant pair of each target sensor as the first reference level of the i-th quadrant pair.

[0355] The seventeenth determination module is used to determine the second prediction level of the wind tower to be monitored according to the first reference level of each quadrant pair; wherein the second prediction level is used to indicate the tower collapse risk level of the wind tower to be monitored.

[0356] In a possible implementation of the embodiment of the present disclosure, the wind tower deformation monitoring device 1400 may further include:

[0357] An eighteenth determination module is used to determine, for any target sensor and any second monitoring period, a symmetrical value of the second verticality distribution corresponding to the target sensor in the second monitoring period according to multiple third deformation information.

[0358] The nineteenth determination module is used to determine the second coefficient of variation of the i-th quadrant pair of the j-th target sensor using the following formula:

[0359]

[0360] Where i∈[1,m] and i is a positive integer, j∈[1,n] and j is a positive integer, k is the sequence number of the second monitoring period, S Δjik Characterizes that the second verticality distribution corresponding to the i-th quadrant of the j-th target sensor in the k-th second monitoring period is symmetrical, min(S Δji ) represents the minimum value of the symmetrical values ​​of the second verticality distribution corresponding to the i-th quadrant pair of the j-th target sensor in each second monitoring period, max(S Δji ) represents the maximum value of the symmetrical values ​​of the second verticality distribution corresponding to the i-th quadrant pair of the j-th target sensor in each second monitoring period, is the normalized value corresponding to the i-th quadrant pair of the j-th target sensor in the k-th second monitoring period, and σ(·) is the standard deviation function.

[0361] The twentieth determination module is used to determine the second variation level of the i-th quadrant pair of the j-th target sensor according to the second variation coefficient of the i-th quadrant pair of the j-th target sensor.

[0362] The twenty-first determination module is used to determine, for the i-th quadrant pair, the highest level among the second variation levels of the i-th quadrant pair of each target sensor as the second reference level of the i-th quadrant pair.

[0363] The twenty-second determination module is used to determine the third prediction level of the wind tower to be monitored according to the second reference level of each quadrant pair; wherein the third prediction level is used to indicate the tower collapse risk level of the wind tower to be monitored.

[0364] The deformation monitoring device for a wind tower of the disclosed embodiment receives the reference coordinate system sent by the terminal, and the attitude quaternion corresponding to the target sensor at the current monitoring moment; wherein the target sensor is arranged on the wind tower to be monitored; according to the attitude quaternion corresponding to the target sensor at the current monitoring moment, the target coordinates of the target sampling point in the current carrier coordinate system of the target sensor in the reference coordinate system are determined; according to the target coordinates, the current deformation information of the target sensor at the current monitoring moment is determined; wherein the current deformation information includes at least one of the current verticality, the current tilt direction, and the current distortion; and the current deformation information is sent to the terminal so that the terminal displays the current deformation information. Thus, it is possible to timely and effectively obtain the current deformation information of the wind tower to be monitored based on the target sensor and the reference coordinate system arranged on the wind tower to be monitored, thereby avoiding the influence of artificial objective judgment and improving the accuracy of deformation information.

[0365] With the above Fig.10 Corresponding to the wind tower deformation monitoring method provided in the embodiment, the present disclosure also provides a wind tower deformation monitoring device. Fig.10 The wind tower deformation monitoring method provided in the embodiment corresponds to the wind tower deformation monitoring method, so the implementation of the wind tower deformation monitoring method is also applicable to the wind tower deformation monitoring device provided in the embodiment of the present disclosure, and will not be described in detail in the embodiment of the present disclosure.

[0366] Fig.15 This is a structural schematic diagram of the wind tower deformation monitoring device provided in Example 8 of the present disclosure.

[0367] like Fig.15 As shown, the wind tower deformation monitoring device 1500 may include: a determination module 1501 , a sending module 1502 and a receiving module 1503 .

[0368] The determination module 1501 is used to determine a target sensor from a plurality of candidate sensors and a reference coordinate system from a plurality of preset coordinate systems in response to a user's operation on the display page; wherein the target sensor is arranged on a wind tower to be monitored.

[0369] The sending module 1502 is used to send the reference coordinate system and the attitude quaternion corresponding to the target sensor at the current monitoring time to the server, so that the server determines the target coordinates of the target sampling point in the current carrier coordinate system of the target sensor in the reference coordinate system according to the attitude quaternion corresponding to the target sensor at the current monitoring time, and determines the current deformation information of the target sensor at the current monitoring time according to the target coordinates, and sends the current deformation information to the terminal; wherein the current deformation information includes at least one of the current verticality, the current tilt direction, and the current distortion.

[0370] The receiving module 1503 is used to receive the current deformation information sent by the server and display the current deformation information.

[0371] The method for monitoring deformation of a wind tower of the disclosed embodiment determines a target sensor from a plurality of candidate sensors and determines a reference coordinate system from a plurality of preset coordinate systems in response to an operation of a user on a display page; wherein the target sensor is arranged on the wind tower to be monitored; sends the reference coordinate system and the attitude quaternion corresponding to the target sensor at the current monitoring time to the server, so that the server determines the target coordinates of the target sampling point in the current carrier coordinate system of the target sensor in the reference coordinate system according to the attitude quaternion corresponding to the target sensor at the current monitoring time, and determines the current deformation information of the target sensor at the current monitoring time according to the target coordinates, and sends the current deformation information to the terminal; wherein the current deformation information includes at least one of the current verticality, the current tilt direction, and the current distortion, the current verticality is used to indicate the tilt degree of the wind tower to be monitored at the current monitoring time, and the current distortion is used to indicate the angle between the projection of the line between the target sampling point and the origin O on the XY plane and the Y axis at the current monitoring time; receives the current deformation information sent by the server, and displays the current deformation information. Therefore, it is possible to timely and effectively obtain the current deformation information of the wind tower to be monitored based on the target sensor and the reference coordinate system flexibly determined by the user.

[0372] In order to implement the above embodiments, the present disclosure also proposes an electronic device, wherein the electronic device can be the server or detection device in the aforementioned embodiments; it includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the program, it implements the wind tower deformation monitoring method proposed in the aforementioned first aspect embodiment of the present disclosure, or the wind tower deformation monitoring method proposed in the second aspect embodiment.

[0373] In order to implement the above embodiments, the present disclosure also proposes a non-temporary computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, it implements the wind tower deformation monitoring method proposed in the first aspect embodiment of the present disclosure, or the wind tower deformation monitoring method proposed in the second aspect embodiment.

[0374] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present disclosure. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0375] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of the present disclosure, "plurality" means at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0376] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code that includes one or more executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present disclosure includes additional implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present disclosure belong.

[0377] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute the instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purpose of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways if necessary, and then stored in a computer memory.

[0378] It should be understood that the various parts of the present disclosure can be implemented in hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used to implement: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0379] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0380] In addition, each functional unit in each embodiment of the present disclosure may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0381] The storage medium mentioned above may be a read-only memory, a disk or an optical disk, etc. Although the embodiments of the present disclosure have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations of the present disclosure. A person of ordinary skill in the art may change, modify, replace and modify the above embodiments within the scope of the present disclosure.

Claims

1. A method for monitoring deformation of a wind tower, characterized in that: Applied to the server, the method includes: The reference coordinate system sent by the receiving terminal and the attitude quaternion corresponding to the target sensor at the current monitoring time; wherein the target sensor is set on the wind tower to be monitored; Determine the target coordinates of the target sampling point in the current carrier coordinate system of the target sensor in the reference coordinate system according to the attitude quaternion corresponding to the target sensor at the current monitoring moment; Determine, according to the target coordinates, current deformation information of the target sensor at the current monitoring moment; wherein the current deformation information includes at least one of current verticality, current tilt direction, and current distortion; Sending the current deformation information to the terminal so that the terminal displays the current deformation information; Acquire a plurality of first deformation information of the target sensor within a first set time period before the current monitoring moment; wherein the first deformation information includes a first verticality and a first tilt direction; Based on each of the first verticalities, determine a plurality of target analysis samples from the plurality of first deformation information, and determine the quadrant in a set coordinate system where the first tilt direction in each of the target analysis samples is located; wherein the set coordinate system is divided into an even number of quadrants; For any of the quadrants in the set coordinate system, determining a first tilt frequency corresponding to the quadrant according to the number of first analysis samples in the quadrant; wherein the first analysis sample is a target analysis sample having a first tilt direction in the quadrant; Determine a first verticality mean value corresponding to the quadrant according to a first tilt frequency corresponding to the quadrant and a first verticality in each of the first analysis samples in the quadrant; For any quadrant pair in the set coordinate system, determine a symmetric value of the first tilt direction distribution corresponding to the quadrant pair according to a first tilt frequency corresponding to the first quadrant and a first tilt frequency corresponding to the second quadrant; wherein the first quadrant and the second quadrant are any two quadrants that have a matching relationship in the set coordinate system, the quadrant pair includes the first quadrant and the second quadrant, and the symmetric value of the first tilt direction distribution is used to indicate the distribution symmetry of the first tilt direction in the corresponding quadrant pair; Determine, according to the first verticality mean value corresponding to the first quadrant and the first verticality mean value corresponding to the second quadrant, a first verticality distribution symmetry value corresponding to the quadrant pair; wherein the first verticality distribution symmetry value is used to indicate the distribution symmetry of the first verticality in the corresponding quadrant pair; Based on the first tilt frequency and the first verticality mean corresponding to each of the quadrants, as well as the symmetrical values ​​of the first tilt direction distribution and the symmetrical values ​​of the first verticality distribution corresponding to the quadrant pair in which each of the quadrants is located, a target quadrant is determined from each of the quadrants, and the target quadrant is sent to the terminal, so that the user can pay attention to the stress condition of the target fiber rope located in the target quadrant; wherein the target fiber rope is a fiber rope set on the wind tower to be monitored.

2. The method according to claim 1, characterized in that The method further comprises: Acquire a plurality of second deformation information of the target sensor in any of the first monitoring periods in a plurality of first monitoring periods before the current monitoring moment; wherein the second deformation information includes a first distortion; According to each of the first distortions of the target sensor in the plurality of first monitoring periods, the distortion frequency corresponding to the target sensor is determined using the following formula: among them,f m -f m-1 ≠0, m=2, 3…n Among them, P φ represents the distortion frequency corresponding to the target sensor, n represents the total number of first distortions of the target sensor in the first monitoring cycles, φ m represents the mth first distortion degree of the target sensor in the plurality of first monitoring periods, COUNT(·) is a counting function; For the i-th first monitoring period among the multiple first monitoring periods, determining a standard deviation corresponding to the target sensor in the i-th first monitoring period based on multiple first distortions of the target sensor in the i-th first monitoring period; wherein i∈[1,r] and i is a positive integer, and r is the number of the first monitoring periods; Based on the distortion frequency corresponding to the target sensor and the standard deviation corresponding to the target sensor in the i-th first monitoring period, the distortion influence degree corresponding to the target sensor in the i-th first monitoring period is determined by using the following formula: Among them, Q i represents the distortion influence degree corresponding to the target sensor in the i-th first monitoring period, represents the standard deviation of the target sensor in the i-th first monitoring period, represents the normalized value of each standard deviation, min(σ φ ) represents the minimum value of the standard deviation of the target sensor corresponding to each of the first monitoring cycles, max(σ φ ) represents the maximum value of the standard deviation of the target sensor corresponding to each of the first monitoring periods; Determining a distortion influence level of the target sensor in the i-th first monitoring period based on the distortion influence level corresponding to the target sensor in the i-th first monitoring period; Based on the distortion influence level corresponding to the target sensor in each of the first monitoring periods, a first prediction level of the wind tower to be monitored is determined; wherein the first prediction level is used to indicate the tower collapse risk level of the wind tower to be monitored.

3. The method according to claim 2, characterized in that The determining, based on the distortion influence level corresponding to the target sensor in each of the first monitoring periods, the first prediction level of the wind tower to be monitored includes: Determining a first number of first monitoring cycles for each distortion impact level according to the type of distortion impact level corresponding to each first monitoring cycle; Determining a first ratio corresponding to a corresponding type of distortion impact level according to a first number of first monitoring periods for each type of distortion impact level and a total number of the first monitoring periods; The first prediction level is determined based on first ratios corresponding to various distortion influence levels.

4. The method according to claim 3, characterized in that The distortion impact levels include distortion impact level one, distortion impact level two, and distortion impact level three; The determining the first prediction level based on the first ratios corresponding to the various distortion influence levels includes: In response to the first ratio corresponding to the third level of distortion influence not being less than a first set threshold, determining the first prediction level as an extremely high risk; In response to the first ratio corresponding to the second level of the distortion influence being not less than a second set threshold, and the first ratio corresponding to the third level of the distortion influence being not less than a third set threshold, determining that the first prediction level is high risk; In response to the first ratio corresponding to the second level of the distortion influence being not less than a fourth set threshold, and the first ratio corresponding to the third level of the distortion influence being not less than a fifth set threshold, determining that the first prediction level is a medium risk; In response to the first ratio corresponding to the second level of the distortion influence being less than a sixth set threshold, and the first ratio corresponding to the third level of the distortion influence being not less than a seventh set threshold, determining that the first prediction level is a low risk; In response to the first ratio corresponding to the first distortion influence level being greater than the eighth set threshold, and the first ratio corresponding to the third distortion influence level being less than the ninth set threshold, the first prediction level is determined to be a safe level.

5. The method according to claim 1, characterized in that The set coordinate system is divided into 2m quadrants, the number of the target sensors is n, wherein any of the target sensors is arranged at a height corresponding to the wind tower to be monitored, and m and n are both natural numbers not equal to 0; The method further comprises: For any of the target sensors and any of the second monitoring periods in the plurality of second monitoring periods before the current monitoring moment, obtaining a plurality of third deformation information of the target sensor in the second monitoring period; wherein the third deformation information includes a second verticality and a second tilt direction; Determine, according to the plurality of third deformation information, that the target sensor is symmetrically distributed in the second tilt direction corresponding to the second monitoring period; For the i-th quadrant pair of the j-th target sensor, the first coefficient of variation α of the i-th quadrant pair of the j-th target sensor is determined by the following formula: θji : Wherein, i∈[1,m] and i is a positive integer, j∈[1,n] and j is a positive integer, k is the sequence number of the first monitoring period, S θjik The i-th quadrant pair of the j-th target sensor is characterized by a symmetrical distribution of values ​​in the second tilt direction corresponding to the k-th second monitoring period, min(S θji ) represents the minimum value of the symmetrical distribution of the second tilt direction corresponding to the i-th quadrant of the j-th target sensor in each of the second monitoring periods, max(S θji ) represents the maximum value of the symmetrical distribution of the second tilt direction corresponding to the i-th quadrant pair of the j-th target sensor in each of the second monitoring periods, is the normalized value corresponding to the i-th quadrant pair of the j-th target sensor in the k-th second monitoring period, and σ(n) is the standard deviation function; determining a first variation level of the i-th quadrant pair of the j-th target sensor according to a first variation coefficient of the i-th quadrant pair of the j-th target sensor; For the i-th quadrant pair, determining the highest level among the first variation levels of the i-th quadrant pair of each of the target sensors as the first reference level of the i-th quadrant pair; According to the first reference level of each quadrant pair, a second prediction level of the wind tower to be monitored is determined; wherein the second prediction level is used to indicate the tower collapse risk level of the wind tower to be monitored.

6. The method according to claim 5, characterized in that The method further comprises: For any of the target sensors and any of the second monitoring periods, determining, according to the plurality of third deformation information, a symmetrical value of a second verticality distribution corresponding to the target sensor in the second monitoring period; For the i-th quadrant pair of the j-th target sensor, the second coefficient of variation of the i-th quadrant pair of the j-th target sensor is determined by the following formula: Wherein, i∈[1,m] and i is a positive integer, j∈[1,n] and j is a positive integer, k is the serial number of the second monitoring period, S Δjik The second verticality distribution corresponding to the i-th quadrant of the j-th target sensor in the k-th second monitoring period is symmetrically distributed, min(S Δji ) represents the minimum value of the symmetrical values ​​of the second verticality distribution corresponding to the i-th quadrant pair of the j-th target sensor in each of the second monitoring periods, max(S Δji ) represents the maximum value of the symmetrical values ​​of the second verticality distribution corresponding to the i-th quadrant pair of the j-th target sensor in each of the second monitoring periods, is the normalized value corresponding to the i-th quadrant pair of the j-th target sensor in the k-th second monitoring period, and σ(·) is the standard deviation function; determining a second variation level of the i-th quadrant pair of the j-th target sensor according to a second variation coefficient of the i-th quadrant pair of the j-th target sensor; For the i-th quadrant pair, determining the highest level among the second variation levels of the i-th quadrant pair of each of the target sensors as the second reference level of the i-th quadrant pair; A third prediction level of the wind tower to be monitored is determined according to the second reference level of each quadrant pair; wherein the third prediction level is used to indicate the tower collapse risk level of the wind tower to be monitored.

7. A wind tower deformation monitoring device, characterized in that: Applied to the server, the device comprises: A receiving module, used for receiving the reference coordinate system sent by the terminal and the attitude quaternion corresponding to the target sensor at the current monitoring time; wherein the target sensor is arranged on the wind tower to be monitored; A first determination module, configured to determine the target coordinates of the target sampling point in the current carrier coordinate system of the target sensor in the reference coordinate system according to the attitude quaternion corresponding to the target sensor at the current monitoring moment; A second determination module is used to determine the current deformation information of the target sensor at the current monitoring time according to the target coordinates; wherein the current deformation information includes at least one of a current verticality, a current tilt direction, and a current distortion; A first sending module, configured to send the current deformation information to the terminal, so that the terminal displays the current deformation information; A first acquisition module, used to acquire a plurality of first deformation information of the target sensor within a first set time period before the current monitoring moment; wherein the first deformation information includes a first verticality and a first tilt direction; a third determination module, configured to determine a plurality of target analysis samples from the plurality of first deformation information based on the first perpendicularities, and determine a quadrant in a set coordinate system where the first tilt direction in each of the target analysis samples is located; wherein the set coordinate system is divided into an even number of quadrants; A fourth determination module is used to determine, for any quadrant in the set coordinate system, a first tilt frequency corresponding to the quadrant according to the number of first analysis samples in the quadrant; wherein the first analysis sample is a target analysis sample with a first tilt direction in the quadrant; a fifth determining module, configured to determine a first verticality mean value corresponding to the quadrant according to the first tilt frequency corresponding to the quadrant and the first verticality in each of the first analysis samples in the quadrant; a sixth determination module, configured to determine, for any quadrant pair in the set coordinate system, a symmetric value of the first tilt direction distribution corresponding to the quadrant pair according to the first tilt frequency corresponding to the first quadrant and the first tilt frequency corresponding to the second quadrant; wherein the first quadrant and the second quadrant are any two quadrants having a matching relationship in the set coordinate system, the quadrant pair includes the first quadrant and the second quadrant, and the symmetric value of the first tilt direction distribution is used to indicate the distribution symmetry of the first tilt direction in the corresponding quadrant pair; a seventh determination module, configured to determine a first verticality distribution symmetry value corresponding to the quadrant pair according to a first verticality mean value corresponding to the first quadrant and a first verticality mean value corresponding to the second quadrant; wherein the first verticality distribution symmetry value is used to indicate the distribution symmetry of the first verticality in the corresponding quadrant pair; A processing module is used to determine a target quadrant from each of the quadrants based on the first tilt frequency and the first verticality mean corresponding to each of the quadrants, as well as the symmetrical values ​​of the first tilt direction distribution and the symmetrical values ​​of the first verticality distribution corresponding to the quadrant pair where each of the quadrants is located, and send the target quadrant to the terminal so that the user can pay attention to the stress condition of the target fiber rope located in the target quadrant; wherein the target fiber rope is a fiber rope set on the wind tower to be monitored.

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