Integrated monitoring system for offshore wind power pile foundation

Abstract

The invention belongs to the field of wind power monitoring, and discloses an offshore wind power pile foundation integrated monitoring system which comprises a sensor module, a data transmission module, a central processing system, a user terminal and an unmanned patrol device. The sensor module is used for acquiring monitoring data of a preset monitoring position of the wind power pile foundation; the data transmission module is used for sending the monitoring data obtained by the sensor module to the central processing system; the central processing system is used for analyzing the monitoring data, judging whether the monitoring data meet patrol conditions or not, and if yes, sending a patrol command to the unmanned patrol device; the unmanned patrolling device is used for patrolling the monitoring position corresponding to the monitoring data meeting the early warning condition after receiving the patrolling command, and obtaining a patrolling image; the central processing system is further used for judging whether an early warning condition is met or not based on the patrol image, and if yes, sending an early warning notification to the user terminal; and the user terminal is used for sending out early warning to personnel responsible for monitoring after receiving the early warning notification.

Description

Technical Field

[0001] The present invention relates to the field of wind power monitoring, and in particular to an integrated monitoring system for offshore wind power pile foundations. Background Art

[0002] With the development of offshore wind power, the stability requirements for wind turbine pile foundations are getting higher and higher. The existing monitoring method usually monitors the corrosion of wind turbine pile foundations by setting sensors. However, since the sensors are used in a high-salt and easily corrosive environment, they may fail after a long period of operation, so the probability of false alarms is high. Summary of the invention

[0003] The purpose of the present invention is to disclose an integrated monitoring system for offshore wind power pile foundations, so as to solve the technical problem of how to reduce the probability of false alarm events when monitoring offshore wind power pile foundations.

[0004] In order to achieve the above object, the present invention provides the following technical solutions:

[0005] The present invention provides an integrated monitoring system for offshore wind power pile foundations, including a sensor module, a data transmission module, a central processing system, a user terminal and an unmanned inspection device;

[0006] The sensor module is used to obtain monitoring data of a preset monitoring position of the wind power pile foundation;

[0007] The data transmission module is used to send the monitoring data obtained by the sensor module to the central processing system;

[0008] The central processing system is used to analyze the monitoring data and determine whether the monitoring data meets the inspection conditions. If so, it sends an inspection command to the unmanned inspection device;

[0009] The unmanned patrol device is used to patrol the monitoring location corresponding to the monitoring data that meets the early warning conditions after receiving the patrol command, and obtain the patrol image;

[0010] The central processing system is also used to determine whether the warning conditions are met based on the inspection images, and if so, send a warning notification to the user terminal;

[0011] The user terminal is used to send an early warning to the person responsible for monitoring after receiving the early warning notification.

[0012] Preferably, the sensor module includes a tilt sensor and a corrosion sensor;

[0013] Monitoring data include tilt angle and corrosion depth;

[0014] The tilt sensor is used to obtain the tilt angle of the monitoring location;

[0015] Corrosion sensors are used to obtain the corrosion depth at the monitoring location.

[0016] Preferably, the data transmission module is connected to the sensor module.

[0017] After obtaining the monitoring data, the sensor module transmits the monitoring data to the data transmission module;

[0018] The data transmission module transmits the monitoring data to the central processing system via submarine optical cables or wireless communication networks.

[0019] Preferably, the monitoring data is analyzed to determine whether the monitoring data meets the inspection conditions, including:

[0020] Determine whether the monitoring data exceeds the set value range. If so, it means that the inspection conditions are met.

[0021] Preferably, sending a patrol command to the unmanned patrol device includes:

[0022] Obtain the monitoring location corresponding to the monitoring data that meets the inspection conditions;

[0023] The unmanned patrol device that is closest to the monitoring location and is in an idle state is used as the transmission target;

[0024] A patrol command containing monitoring positions corresponding to monitoring data satisfying the patrol conditions is sent to the transmission target.

[0025] Preferably, obtaining the inspection image includes:

[0026] The monitoring position is photographed so that the width of the patrol image is perpendicular to the sea level, and the length of the patrol image is parallel to the sea level.

[0027] Preferably, obtaining monitoring data of a preset monitoring position of a wind power pile foundation includes:

[0028] An adaptive collection cycle is used to obtain monitoring data of a preset monitoring position of a wind power pile foundation.

[0029] Preferably, the central processing system comprises a database for storing the monitoring data and a set value range for each type of monitoring data.

[0030] Preferably, the user terminal includes an interaction module and an early warning module;

[0031] The interactive module is used to provide a graphical interface, so that the monitoring personnel can set the numerical range corresponding to each type of monitoring data in the graphical interface;

[0032] The early warning module is used to issue an early warning to the person responsible for monitoring after receiving the early warning notification.

[0033] Preferably, it also includes a remote calibration module;

[0034] The remote calibration module is used to remotely calibrate the sensor in the sensor module.

[0035] Beneficial effects:

[0036] Compared with the prior art, the present invention not only uses sensors for monitoring, but also adds an unmanned patrol device for secondary review. In this way, comprehensive confirmation can be performed through two different monitoring methods, effectively reducing the probability of false alarms. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0038] Figure 1 It is a schematic diagram of an integrated monitoring system for offshore wind power pile foundations of the present invention.

[0039] Figure 2 This is the process of determining the overlap ratio T of the present invention. DETAILED DESCRIPTION

[0040] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0041] The present invention provides an integrated monitoring system for offshore wind power pile foundations, including a sensor module, a data transmission module, a central processing system, a user terminal and an unmanned inspection device;

[0042] The sensor module is used to obtain monitoring data of a preset monitoring position of the wind power pile foundation;

[0043] The data transmission module is used to send the monitoring data obtained by the sensor module to the central processing system;

[0044] The central processing system is used to analyze the monitoring data and determine whether the monitoring data meets the inspection conditions. If so, it sends an inspection command to the unmanned inspection device;

[0045] The unmanned patrol device is used to patrol the monitoring location corresponding to the monitoring data that meets the early warning conditions after receiving the patrol command, and obtain the patrol image;

[0046] The central processing system is also used to determine whether the warning conditions are met based on the inspection images, and if so, send a warning notification to the user terminal;

[0047] The user terminal is used to send an early warning to the person responsible for monitoring after receiving the early warning notification.

[0048] In addition to monitoring through sensors, unmanned patrol devices are added for secondary review. In this way, comprehensive confirmation can be carried out through two different monitoring methods, effectively reducing the probability of false alarms.

[0049] Preferably, the unmanned patrol device includes an unmanned aerial vehicle, an unmanned ship and an unmanned submarine.

[0050] Drones are mainly used to patrol areas where wind turbine pile foundations are higher than sea level, unmanned boats are used to patrol areas where wind turbine pile foundations are lower than sea level, and unmanned submarines are used to patrol areas where wind turbine pile foundations are below sea level.

[0051] For example, drones are used to inspect areas 2 meters above sea level, while unmanned boats are used to inspect areas less than 2 meters above sea level, because if the drone flies too low, it is easily affected by the waves.

[0052] Preferably, the sensor module includes a tilt sensor and a corrosion sensor;

[0053] Monitoring data include tilt angle and corrosion depth;

[0054] The tilt sensor is used to obtain the tilt angle of the monitoring location;

[0055] Corrosion sensors are used to obtain the corrosion depth at the monitoring location.

[0056] Preferably, judging whether the warning condition is met based on the inspection image includes:

[0057] Obtain the type of monitoring data that meets the warning conditions;

[0058] Determine events that meet warning conditions based on the type of monitoring data;

[0059] The inspection image is identified to determine whether there is an event that meets the warning conditions in the inspection image. If so, it means that the warning conditions are met; if not, it means that the warning conditions are not met.

[0060] The type of monitoring data that meets the warning conditions is the tilt angle or corrosion depth;

[0061] Based on the type of monitoring data, it is determined that the events that meet the warning conditions are corrosion depth exceeding a set numerical range or inclination angle exceeding a set numerical range.

[0062] Preferably, the inspection image is identified to determine whether there is an event that meets the warning condition in the inspection image, including:

[0063] Identify patrol images and obtain monitoring data based on patrol images;

[0064] It is determined whether the monitoring data obtained based on the patrol image exceeds the set value range. If so, it means that there is an event that meets the warning conditions; if not, it means that there is no event that meets the warning conditions.

[0065] For example, when the monitoring data that meets the warning condition is the corrosion depth, the event that meets the warning condition is that the corrosion depth exceeds the set numerical range (the numerical range here is the depth range). After that, the inspection image corresponding to the monitoring position of the monitoring data is identified to determine whether the corrosion depth exceeds the set numerical range.

[0066] When photographing the monitoring location, the depth data of the object can be obtained by taking a depth image, so that the corrosion depth can be obtained based on the depth image. Afterwards, by judging whether the corrosion depth obtained based on the sequential image exceeds the set numerical range, it can be determined whether there is an event that meets the warning conditions.

[0067] For another example, when the monitoring data that meets the warning condition is the inclination angle, the event that meets the warning condition is that the inclination angle exceeds the set numerical range (the numerical range here is the angle range). Afterwards, the inspection image corresponding to the monitoring position of the monitoring data is identified to determine whether the inclination angle of the wind turbine pile foundation exceeds the set numerical range.

[0068] During the shooting process, the length direction of the image can be kept parallel to the sea level, and the width direction can be kept perpendicular to the sea level. In this way, the edge of the wind turbine pile foundation can be obtained by edge recognition. After that, linear regression is performed on the edge pixel points to obtain a straight line. The angle between the straight line and the length direction of the image is less than or equal to 90 degrees as the inclination angle of the wind turbine pile foundation. After that, it is determined whether the inclination angle obtained based on the inspection image exceeds the set value range, so as to determine whether there is an event that meets the warning conditions.

[0069] Preferably, the inspection image is identified and monitoring data is acquired based on the inspection image, including:

[0070] Preprocessing the inspection image to obtain a preprocessed image;

[0071] The preprocessed images are recognized and monitoring data is obtained based on the preprocessed images.

[0072] By preprocessing the inspection images, the image quality can be effectively improved, which is beneficial to improving the accuracy of monitoring data obtained based on the inspection images.

[0073] Preferably, preprocessing the inspection image to obtain the preprocessed image includes:

[0074] Obtain the grayscale image corresponding to the inspection image;

[0075] Partition the grayscale image to obtain multiple areas to be processed;

[0076] Performing noise reduction processing on each area to be processed respectively to obtain multiple areas to be processed after noise reduction;

[0077] Multiple denoised areas to be processed are spliced ​​to obtain a preprocessed image.

[0078] By performing noise reduction processing after partitioning, a more appropriate noise reduction algorithm can be selected based on the actual conditions of different areas to be processed, thereby achieving a better noise reduction effect on the image obtained after stitching.

[0079] Preferably, the grayscale image is partitioned to obtain a plurality of areas to be processed, including:

[0080] Partition the grayscale image to obtain multiple regions to be processed with a side length of K;

[0081] The overlap rate between two adjacent areas to be processed is T. bN represents the total number of pixels contained in two adjacent areas to be processed.

[0082] The adjacent here includes adjacent up and down and adjacent left and right.

[0083] Preferably, the value of K is one twentieth of the length of the grayscale image.

[0084] Preferably, if Figure 2 As shown, the process of determining the overlap rate T includes:

[0085] The first step is to initialize the value of T to 0.1;

[0086] The second step is to divide the grayscale image into multiple processing regions with a side length of K, and the overlap rate between two adjacent processing regions is T;

[0087] The third step is to calculate the edge overlap coefficient based on the area to be processed obtained in the second step;

[0088] Step 4: determine whether the value of T is greater than the set overlap rate threshold. If so, proceed to step 6; if not, proceed to step 5.

[0089] Step 5: Add 0.1 to the value of T and go to step 2;

[0090] In the sixth step, the overlap rate corresponding to the maximum edge overlap coefficient is used as the final overlap rate.

[0091] The overlap rate of the present invention is determined in an iterative manner, and the final overlap rate can make the pixel points near the edge of the image as much as possible in the overlapping area. In this way, when the subsequent splicing is performed, since the pixel points in the overlapping area are weighted based on the grayscale values ​​of the same pixel point in the two areas to be processed, for example, the weight of the grayscale value in each area to be processed is 0.5, the probability of the pixel points at the edge being denoised by different noise reduction algorithms based on different neighborhoods can be increased, so that after the image is spliced, the edge of the image can be more effectively retained. It is conducive to obtaining more accurate monitoring data through the subsequent calculation process.

[0092] Preferably, the overlap rate threshold is set to 0.5.

[0093] Preferably, the calculation process of the edge overlap coefficient includes:

[0094] Use edge detection algorithm to calculate the segmentation threshold of grayscale image;

[0095] Get the connected domain composed of all pixels greater than the segmentation threshold;

[0096] Store the pixel points at the edge of the connected domain into the set Z;

[0097] Store all the obtained areas to be processed into set V;

[0098] Obtain the overlapping area between each to-be-processed area in V and another adjacent to-be-processed area, and store the pixel points of the overlapping area into the set U;

[0099] The edge overlap coefficient is calculated using the following formula:

[0100]

[0101] orpcoef represents the edge overlap coefficient, numegUZ represents the total number of pixels in set U that belong to set Z, numU represents the total number of pixels in set U, numK represents the total number of areas to be processed contained in V, topnum represents the total number of areas to be processed with a side length of K obtained by partitioning the grayscale image when the overlap rate is equal to the overlap rate threshold, and α1 and α2 represent the first weight and the second weight, respectively.

[0102] The edge overlap coefficient of the present invention is considered from different directions. When the value of numegUZ is larger and the number of areas to be processed is smaller, the edge overlap coefficient is larger. In this way, while avoiding obtaining too many areas to be processed, as many pixels in Z as possible can be placed in the overlapping area, which is conducive to obtaining more accurate denoising results and more effective retention of edges.

[0103] Preferably, the edge detection algorithm comprises a maximum inter-class variance method.

[0104] Preferably, the first weight and the second weight are 0.55 and 0.45 respectively.

[0105] Preferably, each area to be processed is subjected to noise reduction processing to obtain a plurality of areas to be processed after noise reduction, including:

[0106] Calculate the variance of the grayscale value of each pixel in the area to be processed respectively;

[0107] Obtain the median of the variance of the grayscale values ​​of all pixels in the area to be processed;

[0108] For the area to be processed where the variance is greater than the median, the wavelet denoising algorithm is used for denoising, and for the area to be processed where the variance is less than or equal to the median, the Gaussian filtering algorithm is used for denoising.

[0109] In the noise reduction process of the present invention, when the variance is large, an algorithm with stronger noise reduction performance can be selected to perform noise reduction to ensure the effect of noise reduction. When the variance is small, a Gaussian filtering algorithm is used to perform noise reduction to ensure the overall noise reduction efficiency, thereby achieving a balance between the noise reduction effect and the noise reduction efficiency, and avoiding noise reduction taking too long.

[0110] Preferably, identifying the preprocessed image and acquiring monitoring data based on the preprocessed image includes:

[0111] The preprocessed image is identified to obtain the inclination angle of the wind power pile foundation or the preprocessed image is identified to obtain the corrosion depth of the monitoring position.

[0112] Preferably, the sensor module further includes a strain sensor, and the strain sensor is used to obtain the strain amount at the monitoring position.

[0113] Preferably, the data transmission module is connected to the sensor module.

[0114] After obtaining the monitoring data, the sensor module transmits the monitoring data to the data transmission module;

[0115] The data transmission module transmits the monitoring data to the central processing system via submarine optical cables or wireless communication networks.

[0116] For example, the monitoring data can be transmitted to the data transmission module via a satellite communication network or a 4G, 5G or other network.

[0117] Preferably, the monitoring data is analyzed to determine whether the monitoring data meets the inspection conditions, including:

[0118] Determine whether the monitoring data exceeds the set value range. If so, it means that the inspection conditions are met.

[0119] Preferably, determining whether the monitoring data exceeds a set value range includes:

[0120] If the monitoring data is a tilt angle, it is determined whether the tilt angle exceeds a set angle range [0, Q], where Q represents a preset angle;

[0121] If the monitoring data is the corrosion depth, it is determined whether the corrosion depth exceeds a set depth range [0, H], where H represents a preset depth.

[0122] Preferably, the preset angle may be 10°, and the preset depth may be 5 cm.

[0123] Preferably, sending a patrol command to the unmanned patrol device includes:

[0124] Obtain the monitoring location corresponding to the monitoring data that meets the inspection conditions;

[0125] The unmanned patrol device that is closest to the monitoring location and is in an idle state is used as the transmission target;

[0126] A patrol command containing monitoring positions corresponding to monitoring data satisfying the patrol conditions is sent to the transmission target.

[0127] Preferably, obtaining the inspection image includes:

[0128] The monitoring position is photographed so that the width of the patrol image is perpendicular to the sea level, and the length of the patrol image is parallel to the sea level.

[0129] Preferably, obtaining monitoring data of a preset monitoring position of a wind power pile foundation includes:

[0130] An adaptive collection cycle is used to obtain monitoring data of a preset monitoring position of a wind power pile foundation.

[0131] Adopting an adaptive collection cycle can prevent sensors from collecting monitoring data too frequently, thus extending their service life. It can also prevent the collection cycle set in advance from being too long and failing to identify changes in the wind turbine pile foundation in a timely manner.

[0132] Preferably, the calculation process of the adaptive collection period is as follows:

[0133] After each acquisition is completed, the next acquisition cycle is calculated.

[0134]

[0135] E represents the collection cycle, tph represents the designed service days of the wind turbine pile foundation, yth represents the cumulative service days of the wind turbine pile foundation, numful represents the total number of collection cycles in which the monitoring data that meets the inspection conditions are obtained in the monitoring data obtained in the most recent numget collection cycles, Emx represents the maximum value of the set collection cycle, β1 and β2 represent the third weight and the fourth weight respectively.

[0136] When calculating the collection cycle, the greater the number of days the wind pile foundation has been in service, and the more times the monitoring data obtained in the recent period meets the inspection conditions, the smaller the next collection cycle will be. In this way, the collection cycle can change with the cumulative number of days in service and the number of times the inspection conditions are met, thereby avoiding the sensor collecting monitoring data too frequently and also avoiding the collection cycle set in advance being too long to promptly identify changes in the wind pile foundation.

[0137] Preferably, the value of numget is 10.

[0138] Preferably, the value of Emx is 30 minutes.

[0139] Preferably, the third weight and the fourth weight are both 0.5.

[0140] Adopting an adaptive collection cycle to obtain monitoring data of the preset monitoring position of the wind power pile foundation, including:

[0141] After the countdown of the previous collection cycle ends, the monitoring data is acquired. After the monitoring data is acquired, the duration of the next collection cycle is calculated. After the calculation is completed, the countdown of the next collection cycle is performed.

[0142] Preferably, the central processing system comprises a database for storing the monitoring data and a set value range for each type of monitoring data.

[0143] Preferably, the user terminal includes an interaction module and an early warning module;

[0144] The interactive module is used to provide a graphical interface, so that the monitoring personnel can set the numerical range corresponding to each type of monitoring data in the graphical interface;

[0145] The early warning module is used to issue an early warning to the person responsible for monitoring after receiving the early warning notification.

[0146] Specifically, after receiving the early warning notification, an early warning sound can be played to the personnel responsible for monitoring, thereby providing early warning to the monitoring personnel.

[0147] Preferably, it also includes a remote calibration module;

[0148] The remote calibration module is used to remotely calibrate the sensor in the sensor module.

[0149] Specifically, the remote calibration module may send a calibration instruction to the sensor module. After receiving the calibration instruction, the sensor module performs calibration using the monitoring data obtained by the adjacent sensors.

[0150] For example, for a sensor for acquiring an inclination angle, the inclination angles obtained by a plurality of sensors (three or more) located adjacent to each other are compared, and the measurement parameters of the sensor having an inclination angle with an excessively large deviation are calibrated.

[0151] The preferred embodiments of the present invention disclosed above are only used to help illustrate the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to the specific implementation methods described. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. An integrated monitoring system for offshore wind power pile foundation, characterized in that: It includes sensor module, data transmission module, central processing system, user terminal and unmanned patrol device; The sensor module is used to obtain monitoring data of a preset monitoring position of the wind power pile foundation; The data transmission module is used to send the monitoring data obtained by the sensor module to the central processing system; The central processing system is used to analyze the monitoring data and determine whether the monitoring data meets the inspection conditions. If so, it sends an inspection command to the unmanned inspection device; The unmanned patrol device is used to patrol the monitoring location corresponding to the monitoring data that meets the early warning conditions after receiving the patrol command, and obtain the patrol image; The central processing system is also used to determine whether the warning conditions are met based on the inspection images, and if so, send a warning notification to the user terminal; The user terminal is used to send an early warning to the person responsible for monitoring after receiving the early warning notification.

2. An integrated monitoring system for offshore wind power pile foundation according to claim 1, characterized in that: The sensor module includes a tilt sensor and a corrosion sensor; Monitoring data include tilt angle and corrosion depth; The tilt sensor is used to obtain the tilt angle of the monitoring location; Corrosion sensors are used to obtain the corrosion depth at the monitoring location.

3. The integrated monitoring system for offshore wind power pile foundation according to claim 1 is characterized in that: The data transmission module is connected with the sensor module. After obtaining the monitoring data, the sensor module transmits the monitoring data to the data transmission module; The data transmission module transmits the monitoring data to the central processing system via submarine optical cables or wireless communication networks.

4. The integrated monitoring system for offshore wind power pile foundation according to claim 1 is characterized in that: Analyze the monitoring data to determine whether the monitoring data meets the inspection conditions, including: Determine whether the monitoring data exceeds the set value range. If so, it means that the inspection conditions are met.

5. The integrated monitoring system for offshore wind power pile foundation according to claim 1 is characterized in that: Send patrol commands to unmanned patrol devices, including: Obtain the monitoring location corresponding to the monitoring data that meets the inspection conditions; The unmanned patrol device that is closest to the monitoring location and is in an idle state is used as the transmission target; A patrol command containing monitoring positions corresponding to monitoring data satisfying the patrol conditions is sent to the transmission target.

6. An integrated monitoring system for offshore wind power pile foundation according to claim 1, characterized in that: Obtain inspection images, including: The monitoring position is photographed so that the width of the patrol image is perpendicular to the sea level, and the length of the patrol image is parallel to the sea level.

7. An integrated monitoring system for offshore wind power pile foundation according to claim 1, characterized in that: Obtain monitoring data of the preset monitoring location of the wind power pile foundation, including: An adaptive collection cycle is used to obtain monitoring data of a preset monitoring position of a wind power pile foundation.

8. The integrated monitoring system for offshore wind power pile foundation according to claim 1, characterized in that: The central processing system includes a database for storing monitoring data and a set value range for each type of monitoring data.

9. The integrated monitoring system for offshore wind power pile foundation according to claim 1, characterized in that: The user terminal includes an interaction module and an early warning module; The interactive module is used to provide a graphical interface, so that the monitoring personnel can set the numerical range corresponding to each type of monitoring data in the graphical interface; The early warning module is used to issue an early warning to the person responsible for monitoring after receiving the early warning notification.

10. An integrated monitoring system for offshore wind power pile foundation according to claim 1, characterized in that: Also included is a remote calibration module; The remote calibration module is used to remotely calibrate the sensor in the sensor module.

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