Safety monitoring system for offshore wind power foundation structure

Abstract

The invention discloses a safety monitoring system for an offshore wind power foundation structure, and relates to the technical field of safety monitoring. Comprising a base monitoring module, a cable monitoring module, an environment monitoring module, a data transmission module and a gathering module, the output end of the base monitoring module, the output end of the cable monitoring module and the output end of the environment monitoring module are all connected with the input end of the data transmission module, and the output end of the data transmission module is connected with the input end of the gathering module; the data transmission module is used for transmitting the monitoring data of each monitoring module to the shore; the base monitoring module is used for monitoring the internal state of the wind power base; the cable monitoring module is used for monitoring the state of the cable; the environment monitoring module is used for monitoring a wind power surrounding environment state; and the summarizing module is used for carrying out data preprocessing on the data obtained through transmission, carrying out parameter prediction based on the cleaned data and judging the state of the fan. According to the invention, the operation condition of the fan can be obtained in time.

Description

Technical Field

[0001] The present invention relates to the technical field of safety monitoring, and in particular to an offshore wind power infrastructure safety monitoring system. Background Art

[0002] As a clean and renewable new energy, wind energy has gradually attracted people's attention in recent years. Due to the abundant offshore wind resources, it has the advantages of large power generation, long power generation time, no land occupation, and large-scale development. Wind power technology is gradually extending from land to sea. Offshore wind turbines have become a hot spot in the field of renewable energy development in the world. The monitoring of existing technologies considers each parameter individually, but only sets up monitoring at a certain structure. The monitoring information is low in accuracy and lacks diversification. If a monitoring failure occurs, there will be a greater safety hazard.

[0003] Therefore, it is an urgent problem for those skilled in the art to propose an offshore wind power infrastructure safety monitoring system to solve the problems of separate data processing and low accuracy of monitoring information in the prior art. Summary of the invention

[0004] In view of this, the present invention provides an offshore wind power infrastructure safety monitoring system, which can achieve the effect of timely obtaining the operating status of the wind turbine.

[0005] In order to achieve the above object, the present invention adopts the following technical solution:

[0006] An offshore wind power infrastructure safety monitoring system includes a base monitoring module, a cable monitoring module, an environment monitoring module, a data transmission module and a summary module, wherein the output end of the base monitoring module, the output end of the cable monitoring module and the output end of the environment monitoring module are all connected to the input end of the data transmission module, and the output end of the data transmission module is connected to the input end of the summary module;

[0007] A data transmission module, including a cloud unit and a submarine optical fiber unit, for transmitting the monitoring data of each monitoring module to the shore;

[0008] The base monitoring module is used to monitor the internal status of the wind turbine base;

[0009] Cable monitoring module, used to monitor the cable's own status;

[0010] Environmental monitoring module, used to monitor the environmental status around wind power;

[0011] The aggregation module pre-processes the transmitted data, predicts parameters based on the cleaned data, and determines the status of the fan.

[0012] In the above system, optionally, the data transmission module further comprises a cloud unit, a submarine optical fiber unit and a data storage unit, and the cloud unit and the submarine optical fiber unit are connected in parallel with the data storage unit;

[0013] The data transmission module transmits data at a certain interval.

[0014] In the above system, optionally, the base monitoring module includes a level meter, a stress sensor, and a pressure sensor; the environmental monitoring module includes wave frequency monitoring, water surface foreign matter monitoring, and climate monitoring; the base monitoring module and the environmental monitoring module transmit the monitored data to a data storage unit.

[0015] In the above system, optionally, the data storage unit is also used to store offshore wind turbine data and submarine cable data.

[0016] In the above system, optionally, data preprocessing in the summary module includes data cleaning and data integration.

[0017] In the above system, optionally, in the summary module, parameter prediction includes operation status prediction and life prediction.

[0018] It can be seen from the above technical solution that, compared with the prior art, the present invention provides an offshore wind power infrastructure safety monitoring system, which performs safety monitoring of offshore wind power foundations through comprehensive analysis of multiple parameters, and introduces optical fiber communication to ensure that the system can still monitor and transmit data when it is disconnected from the network, thereby achieving real-time monitoring of parameters of various components of offshore wind turbines, being able to know the operating status in a timely manner, and perform maintenance processing based on the operating status, thereby avoiding greater damage and causing greater economic losses. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0020] Figure 1 A block diagram of an offshore wind power infrastructure safety monitoring system disclosed in the present invention;

[0021] Figure 2 This is a parameter prediction flow chart disclosed in the present invention. DETAILED DESCRIPTION

[0022] 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.

[0023] In this application, relational terms such as first and second, etc. are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. The terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of more restrictions, the elements defined by the sentence "comprise one..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0024] Reference Figure 1 As shown, the present invention discloses an offshore wind power infrastructure safety monitoring system, including a base monitoring module, a cable monitoring module, an environmental monitoring module, a data transmission module and a summary module, wherein the base monitoring module, the cable monitoring module and the environmental monitoring module are connected to the data transmission module and the summary module in sequence;

[0025] A data transmission module, including a cloud unit and a submarine optical fiber unit, for transmitting the monitoring data of each monitoring module to the shore;

[0026] The base monitoring module is used to monitor the internal status of the wind turbine base;

[0027] Cable monitoring module, used to monitor the cable's own status;

[0028] Environmental monitoring module, used to monitor the environmental status around wind power;

[0029] The aggregation module pre-processes the transmitted data, predicts parameters based on the cleaned data, and determines the status of the fan.

[0030] Further, the data transmission module also includes a cloud unit, a submarine optical fiber unit and a data storage unit, and the cloud unit and the submarine optical fiber unit are connected in parallel with the data storage unit;

[0031] The data transmission module transmits data at a certain interval.

[0032] Furthermore, in the data transmission module, the wireless communication methods adopted by the cloud unit include microwave communication and satellite communication. Microwave communication is carried out by setting up microwave transmitters and receivers in the wind farm for point-to-point or point-to-multipoint communication. Satellite communication sets up signal transmitting and receiving devices and performs long-distance communication through satellite terminals. The submarine optical fiber unit communicates using optical fibers laid in the submarine cable system, and the data storage unit is used to store monitoring data unit information.

[0033] Furthermore, the base monitoring module includes a level meter, a stress sensor, and a pressure sensor; the environmental monitoring module includes wave frequency monitoring, water surface foreign matter monitoring, and climate monitoring; the base monitoring module and the environmental monitoring module transmit the monitored data to the data storage unit.

[0034] Furthermore, the spirit level includes a horizontal instrument panel and a pointer. The horizontal instrument panel is provided with scale bars. The angle between every two scale bars is 1° and the resistance is 1Ω. When the pointer rotates, it can contact and slide on the scale bars. When the wind turbine base is tilted, the resistance becomes larger and the current passing through decreases. The tilt amplitude of the base is judged according to the recorded current value. The stress sensor is placed inside the base. When the base is tilted, the material stress increases. The sensor records the value change and the stress change. The pressure sensor is placed on the surface of the base to measure the seawater pressure. When severe weather such as typhoons and tsunamis arrives, the seawater pressure increases and the water pressure change is recorded. Wave frequency monitoring uses a wave spectrum buoy system to measure the average wave height and average wave period. The wave spectrum buoy system can also be used to measure water quality and ocean hydrology. The surface foreign body monitoring uses an ultrasonic sensor arranged at the base. The sensor emits ultrasonic waves outward. When an obstacle is detected, the ultrasonic wave is reflected and received by the receiving probe to obtain the obstacle location information.

[0035] Specifically, each sensor needs to be installed in the designated position before the base is launched into the water, such as high stress areas of the structure and critical fatigue positions.

[0036] Furthermore, the data storage unit is also used to store offshore wind turbine data and submarine cable data.

[0037] Specifically, wind turbine data includes data on the group's blades, transmission chain, generator, etc., which are directly acquired by the manufacturer's built-in processor. Submarine cable data uses multi-mode fiber optic sensors and grating fiber optic sensors to acquire cable data.

[0038] Furthermore, the data storage unit transmits monitoring information to the summary module every 1 to 2 hours. When a large fluctuation range of the monitored data information is detected, the monitoring information is transmitted immediately without being restricted by time.

[0039] Furthermore, data preprocessing in the summary module includes data cleaning and data integration.

[0040] Furthermore, data cleaning includes removing error data and filling missing data; data integration includes merging the base monitoring data set, cable monitoring data set, and environmental monitoring data set into an overall data set.

[0041] Specifically, in data cleaning, the 3σ principle is used to eliminate error data, specifically: Where μ is the mean value, σ is the standard deviation. When the data is not in (μ-3σ,μ+3σ), it is judged as abnormal data and is eliminated. When there is sufficient data in the data set, the rows or columns corresponding to the actual data are deleted to ensure the integrity of the data set. When the missing data set leads to a decrease in calculation accuracy, the filling method is adopted to ensure the integrity of the data set. The filling method adopts the nearest neighbor difference method, that is, the closest data to the missing data is found in the database for interpolation, which is specifically measured based on the Euclidean distance between the calculation objects.

[0042] In data integration, merging into a single data set includes eliminating redundant data and merging data. The corresponding nominal attribute redundant data can be correlated by chi-square correlation test, specifically: Among them, i is the number of rows, j is the number of columns, o is the actual frequency, and e is the theoretical frequency. For redundant data of numerical attributes, correlation coefficients and covariance are used to evaluate the correlation between attributes.

[0043] Furthermore, in the summary module, parameter prediction includes operation status prediction and life prediction.

[0044] Further, see Figure 2 As shown, the parameter prediction process includes: inputting a data set, synchronously performing single-item scoring and life prediction on the data in the data set, and directly outputting the single-item scoring value and life prediction value when any of the single-item scoring value and life prediction value is lower than the threshold; when the value range does not exceed the threshold, weighting each value is assigned according to the single-item running value to obtain the weight of each single-item scoring value, generating an operation status prediction, performing a status judgment on the life prediction value, generating a life evaluation, and recording and outputting the operation status prediction and life evaluation data.

[0045] Furthermore, the operation status prediction includes constructing an evaluation system, using the evaluation system to perform numerical evaluation on the data stored in the data storage unit to obtain individual scores, performing positive processing on the individual scores to construct a positive matrix, standardizing the positive matrix and calculating the information entropy, and performing normalization operations to construct a scoring model.

[0046] Furthermore, the evaluation system includes national standards and expert ratings, and the calculation of information entropy includes constructing a probability matrix using the entropy weight method, that is, obtaining information weights of different indicators and constructing a scoring model.

[0047] Specifically, the single-item score is positively transformed into all indicators, which is to convert them into extremely large indicators. The extremely large indicators are processed to generate a matrix, the proportion of the ith sample under the jth indicator is calculated, and it is regarded as the probability used in the relative entropy calculation. The information entropy of each indicator is calculated, and the entropy weight of each indicator is normalized.

[0048] Furthermore, the life prediction method specifically includes:

[0049] The corrosion degradation data, fatigue degradation data and impact load history data of the base are obtained; the corrosion degradation data and fatigue degradation data of the base are based on the base monitoring data, and the impact load history data is based on the environmental monitoring module, including the historical impact intensity data and the historical impact number data suffered; the corrosion degradation prediction model, fatigue degradation prediction model and impact load prediction model are respectively constructed, and the prediction models are coupled into a three-dimensional prediction model based on the Copula function, and the life prediction is obtained based on the three-dimensional prediction model.

[0050] Specifically, the corrosion degradation prediction model includes obtaining the base prediction degradation function based on the gamma process, using the EM algorithm and the unscented particle filter algorithm, combining the corrosion degradation history data of the base, estimating the parameters of the base prediction degradation function, and obtaining the corrosion degradation process model. The fatigue degradation prediction model includes using the Monte Carlo method to simulate the degradation trajectory of the component, and analyzing the simulation results by statistical methods to obtain the fatigue degradation prediction model; the impact load prediction model includes using the Poisson process to construct a random process model of base impact load failure; using the expectation maximization algorithm, the parameters of the random process model of base impact load failure are estimated to obtain the impact load prediction model.

[0051] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can refer to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system or system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can refer to the partial description of the method embodiment. The system and system embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without creative work.

[0052] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. An offshore wind power infrastructure safety monitoring system, characterized in that: It includes a base monitoring module, a cable monitoring module, an environmental monitoring module, a data transmission module and a summary module, wherein the output end of the base monitoring module, the output end of the cable monitoring module and the output end of the environmental monitoring module are all connected to the input end of the data transmission module, and the output end of the data transmission module is connected to the input end of the summary module; A data transmission module, used to transmit the monitoring data of each monitoring module to the shore; The base monitoring module is used to monitor the internal status of the wind turbine base; Cable monitoring module, used to monitor the cable's own status; Environmental monitoring module, used to monitor the environmental status around wind power; The aggregation module pre-processes the transmitted data, predicts parameters based on the processed data, and determines the status of the fan.

2. An offshore wind power infrastructure safety monitoring system according to claim 1, characterized in that: The data transmission module also includes a cloud unit, a submarine optical fiber unit and a data storage unit, and both the cloud unit and the submarine optical fiber unit are connected to the data storage unit; The data transmission module transmits data at a certain interval.

3. An offshore wind power infrastructure safety monitoring system according to claim 2, characterized in that: The base monitoring module includes a level meter, a stress sensor, and a pressure sensor; the environmental monitoring module includes wave frequency monitoring, water surface foreign matter monitoring, and climate monitoring; the base monitoring module and the environmental monitoring module transmit the monitored data to the data storage unit of the data transmission module.

4. The offshore wind power infrastructure safety monitoring system according to claim 2, characterized in that: The data storage unit is also used to store offshore wind turbine data and submarine cable data.

5. The offshore wind power infrastructure safety monitoring system according to claim 1, characterized in that: Data preprocessing in the summary module includes data cleaning and data integration.

6. The offshore wind power infrastructure safety monitoring system according to claim 1, characterized in that: In the summary module, parameter prediction includes operating status prediction and life prediction.

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