A fan blade fracture detection and early warning device and early warning method

Abstract

The present application relates to the field of wind power generation equipment early warning, in particular to a kind of fan blade fracture detection early warning device, including the vibration sensor of installation in the center of gravity position of fan blade, data acquisition and sending device being connected with vibration sensor communication, for collecting fan blade rotating speed signal and fan blade variable pitch signal rotating speed sensor and data collector;Data collector is used to collect the signal of data acquisition and sending device and rotating speed sensor, and the rotating speed signal is handled according to the processing result to judge whether data acquisition and sending device is issued data acquisition instruction;Data collector is installed in the cabin of fan generator set, and is connected with background server terminal communication, for sending the data collected to background server terminal.The present application also discloses fan blade fracture detection early warning method.The present application can collect data under the condition of triggering setting, realize the effectiveness management of data and can early warn whether fan impeller exists fracture risk.

Description

Technical Field

[0001] This invention relates to the field of early warning for wind power generation equipment, specifically to a wind turbine blade fracture detection and early warning device and method. Background Technology

[0002] In recent years, with the rapid development of the wind power industry, the single unit capacity of wind turbines has gradually increased. As one of the key components of wind turbine generators, the length of wind turbine blades has gradually increased from 15m in the early days to 148m. With the increase in the length of wind turbine generator blades, blade breakage failures have occurred continuously. Blade breakage not only affects the normal operation of the main unit of the wind turbine generator, but also poses a potential risk of tower collapse.

[0003] Current technology involves placing vibration sensors within the blade cavity of wind turbine generator sets to monitor blade operation. These sensors are biaxial piezoelectric sensors used to monitor blade flapping and oscillation vibrations, positioned at approximately one-third of the blade length. The sensor signals are connected to a data acquisition device via cables. This device is mounted on the turbine hub and rotates with the impeller. 2.4G wireless communication is used between the hub and the nacelle, and data is transmitted through the turbine's own network to a fiber optic ring network and then uploaded to the substation server. The collected blade vibration data is analyzed to assess the stress on the blades. Through background data comparison and algorithm support, early warning monitoring for blade breakage is achieved.

[0004] However, the data acquisition in the aforementioned monitoring system for wind turbine generator blades cannot be automatically triggered and is in a continuous data acquisition mode. The large amount of data collected cannot be extracted into usable data, resulting in low data utilization efficiency. It is impossible to accurately distinguish the blade operating conditions through the analysis of effective data, and it is impossible to provide blade fault early warning. Consequently, the false alarm rate of the aforementioned system is high. Summary of the Invention

[0005] The purpose of this invention is to address the problems existing in the background technology by proposing a wind turbine blade fracture detection and early warning device and method.

[0006] The technical solution of the present invention: a wind turbine blade fracture detection and early warning device, comprising...

[0007] Vibration sensors are installed at the center of gravity of the wind turbine blades, with each vibration sensor corresponding to a wind turbine blade.

[0008] The data acquisition and transmission device is connected to the vibration sensor and is used to be installed on the hub of the wind turbine generator set and rotate with the wind turbine blades.

[0009] The speed sensor is used to collect the wind turbine blade speed signal and the wind turbine blade pitch signal of the wind turbine generator set; the speed sensor is installed in the nacelle of the wind turbine generator set.

[0010] The data acquisition unit is communicatively connected to the data acquisition and transmission device and the speed sensor. It is used to collect signals from the data acquisition and transmission device and the speed sensor, process the speed signals, and determine whether to issue a data acquisition command to the data acquisition and transmission device based on the processing results. The data acquisition unit is installed in the nacelle of the wind turbine generator set and is communicatively connected to the back-end server terminal to send the collected data to the back-end server terminal.

[0011] Preferably, the data acquisition device establishes a communication connection with the data acquisition and transmission device using wireless transmission.

[0012] Preferably, it also includes a switch, which communicates with the data collector and is used to send the data collected by the data collector to the backend server terminal via wired transmission.

[0013] Preferably, the method for issuing data acquisition instructions to the data acquisition and transmission device includes the following specific steps:

[0014] S110, The data acquisition unit collects the speed signal of the wind turbine blades monitored by the speed sensor in real time;

[0015] S111. Determine whether the rotational speed of the fan blades is greater than or equal to the set threshold.

[0016] If so, then execute S112;

[0017] If not, then execute S113;

[0018] S112, The data acquisition unit sends an instruction to the data acquisition and transmission device to perform data acquisition by the acquisition module, and simultaneously executes S110;

[0019] S113, The data acquisition unit sends an instruction to the data acquisition and transmission device to perform data acquisition using the interrupt module, and simultaneously executes S110.

[0020] Preferably, the data acquisition module performs data acquisition in the following way:

[0021] Under the condition of sampling frequency of 1280Hz, data is continuously collected to obtain multiple sets of data a; the data collection time for each set of data a is 120s.

[0022] Preferably, the interrupt module performs data acquisition as follows:

[0023] Under the condition of sampling frequency of 50Hz, data is collected at intervals to obtain multiple sets of data b; the data collection time for each set of data b is 60s, and the time interval between two adjacent sets of data b is 10min.

[0024] Preferably, the vibration sensor is a biaxial vibration acceleration sensor.

[0025] A warning method using the aforementioned wind turbine blade fracture detection and warning device specifically includes the following steps:

[0026] S210. Obtain historical vibration and flapping data of the wind turbine impeller. Use a bandpass filter to remove the wind turbine impeller speed frequency from the flapping and vibration data to obtain data group c.

[0027] S211. Using time as the X-axis, the effective value of vibration in the waving direction as the Y-axis, and the effective value of vibration in the swinging direction as the Z-axis, a two-dimensional spatial model of wind turbine blade vibration is constructed using data group c.

[0028] S212. Constructing the trajectory critical surface of a two-dimensional spatial model of wind turbine blade vibration:

[0029] Take 0.5 times and 1.2 times the effective value of vibration in the flapping direction and 0.5 times and 1.2 times the effective value of vibration in the oscillation direction to construct a circular area of ​​blade vibration trajectory, which is marked as the normal area. The area outside this area is marked as the vibration trajectory exceeding the limit area.

[0030] S213. Based on the acquired pitch signal, mark the annular region of the wind turbine blade vibration trajectory at different pitch angles, and divide it into nine regions:

[0031] 0.0°~20.0°, 20.1°~30.0°, 30.1°~35.0°, 35.1°~40.0°, 40.1°~45.0°, 45.1°~50.0°, 50.1°~60.0°, 60.1°~70.0°, and 70.1°~90.0°;

[0032] S214. Real-time acquisition of wind turbine blade flapping and oscillation data. After removing the wind turbine blade rotation speed frequency, if the running trajectory falls within the constructed blade vibration trajectory ring area, it is considered normal; otherwise, it is considered abnormal and an early warning is triggered.

[0033] Preferably, data whose operating trajectory falls within the constructed blade vibration trajectory annular area are included in historical data, and the obtained historical data is used to continuously correct the two-dimensional spatial model of wind turbine blade vibration.

[0034] Compared with the prior art, the above-mentioned technical solution of the present invention has the following beneficial technical effects:

[0035] This invention can automatically control the acquisition of relevant data of wind turbine blades in real time according to set conditions during the monitoring process, so as to obtain effective data for wind turbine blade early warning analysis, and then effectively manage the data. Through the obtained two-dimensional spatial model of wind turbine blade vibration, it can accurately predict whether there is a risk of wind turbine blade breakage, so as to replace wind turbine blades with potential safety hazards in a timely manner, thereby improving the service life and power generation efficiency of wind turbine generator sets. Attached Figure Description

[0036] Figure 1 This is a schematic diagram of one embodiment of the present invention.

[0037] Figure 2 This is a flowchart of one embodiment of the present invention. Detailed Implementation

[0038] Example 1

[0039] like Figure 1 As shown, the present invention proposes a wind turbine blade fracture detection and early warning device, which includes a vibration sensor, a data acquisition and transmission device, a speed sensor, and a data acquisition unit.

[0040] Vibration sensors are installed at the center of gravity of the wind turbine blades. Each vibration sensor corresponds to a wind turbine blade. The vibration sensors are passive wired dual-axis vibration accelerometers used to collect vibration signals in two directions: flapping and swaying of the wind turbine blades.

[0041] Based on the vibration dynamics analysis, the maximum excitation amplitude of the single-point excitation system on the wind turbine blades is:

[0042] Where m is the mass of the eccentric block, e is the cantilever length of the eccentric wheel, k is the excitation position, c is the damping coefficient, and M is the fixed mass of the wind turbine blades and the excitation system.

[0043] The data acquisition and transmission device is connected to the vibration sensor. The data acquisition and transmission device is installed on the hub of the wind turbine generator set and rotates with the wind turbine blades. The data acquisition and transmission device is used to acquire the data signals monitored by the vibration sensor in real time after receiving the data acquisition command.

[0044] The speed sensor is installed in the nacelle of the wind turbine generator set and is stationary relative to the wind turbine blades; the speed sensor is used to collect the wind turbine blade speed signal and the wind turbine blade pitch signal of the wind turbine generator set.

[0045] The data acquisition unit is used to acquire signals from the data acquisition and transmission device and the speed sensor, and to process the speed signal. Based on the processing results, it determines whether to send a data acquisition command to the data acquisition and transmission device.

[0046] In an optional embodiment, the data acquisition device establishes a communication connection with the data acquisition and transmission device via wireless transmission; the wireless transmission method may be, but is not limited to, using a 2.4G wireless communication module, a 5G communication module, or a 4G communication module to achieve the communication connection between the data acquisition device and the data acquisition device.

[0047] The data acquisition unit is connected to the data acquisition and transmission device and the speed sensor. The data acquisition unit is installed in the nacelle of the wind turbine generator set and is connected to the back-end server terminal to send the acquired data to the back-end server terminal. The back-end server terminal is used to store and analyze the data, and the construction of the two-dimensional spatial model of the wind turbine blade vibration is completed in the back-end server terminal.

[0048] Example 2

[0049] like Figure 1 As shown, the wind turbine blade fracture detection and early warning device proposed in this invention, compared with Embodiment 1, also includes a switch. The switch is connected to the data collector and is used to send the data collected by the data collector to the back-end server terminal via wired transmission.

[0050] A switch is a conversion device that enables wireless access to a wired ring network.

[0051] Example 3

[0052] The wind turbine blade fracture detection and early warning device proposed in this invention, compared with Embodiment 1, includes the following specific steps in the method of issuing data acquisition instructions to the data acquisition and transmission device:

[0053] S110, The data acquisition unit collects the speed signal of the wind turbine blades monitored by the speed sensor in real time;

[0054] S111. Determine whether the rotational speed of the wind turbine blades is greater than or equal to a set threshold; wherein, the threshold is set according to the length of the wind turbine blades in the wind turbine blade breakage early warning system, and in an optional embodiment of the present invention, the threshold is set, but not limited to, 8 rpm / min.

[0055] If so, then execute S112;

[0056] If not, then execute S113;

[0057] S112, The data acquisition unit sends an instruction to the data acquisition and transmission device to perform data acquisition by the acquisition module, and simultaneously executes S110;

[0058] S113, The data acquisition unit sends an instruction to the data acquisition and transmission device to perform data acquisition using the interrupt module, and simultaneously executes S110.

[0059] Example 4

[0060] The wind turbine blade fracture detection and early warning device proposed in this invention, compared with Embodiment 3, uses the following method for data acquisition by the acquisition module:

[0061] Under the sampling frequency of 1280Hz, data is continuously collected to obtain multiple sets of data a; the data collection time for each set of data a is 120s. Data a that is collected for less than 120s is discarded. That is, when the speed of the wind turbine blades is less than the threshold, the data collection time for this set of data a is less than 120s, and the current data a is discarded.

[0062] The collected data is transmitted wirelessly to the data acquisition unit. The data acquisition unit collects data using time as a label. The data collected in this mode is valid for subsequent data analysis and avoids the collection of invalid data on blade vibration in windless or lightly windy weather.

[0063] Example 5

[0064] The wind turbine blade fracture detection and early warning device proposed in this invention, compared with Embodiment 3, uses the following method for data acquisition by the interrupt module:

[0065] Under the condition of sampling frequency of 50Hz, data is collected at intervals to obtain multiple sets of data b; the data collection time for each set of data b is 60s, and the time interval between two adjacent sets of data b is 10min.

[0066] Specifically, data b collected in less than 60 seconds is discarded. That is, when the speed of the wind turbine blades is greater than or equal to the threshold, the data collection time of this set of data b is less than 60 seconds, so the current data b is discarded.

[0067] The collected data is transmitted wirelessly to the data acquisition unit; the data acquisition unit collects data using time as a label. The data collected in this mode is the heartbeat data of the wind turbine generator set, which constantly monitors whether the wind turbine generator set is working properly.

[0068] Example 6

[0069] like Figure 2 As shown, a method for early warning of wind turbine blade fracture detection and early warning using any one of the wind turbine blade fracture detection and early warning devices described in Examples 1-5 specifically includes the following steps:

[0070] S210. Obtain historical vibration and flapping data of the wind turbine impeller. Use a bandpass filter to remove the wind turbine impeller speed frequency from the flapping and vibration data to obtain data group c.

[0071] S211. Using time as the X-axis, the effective value of vibration in the waving direction as the Y-axis, and the effective value of vibration in the oscillation direction as the Z-axis, a two-dimensional spatial model of wind turbine blade vibration is constructed using data group c.

[0072] S212. Constructing the trajectory critical surface of a two-dimensional spatial model of wind turbine blade vibration:

[0073] Take 0.5 times and 1.2 times the effective value of vibration in the flapping direction and 0.5 times and 1.2 times the effective value of vibration in the oscillation direction to construct a circular area of ​​blade vibration trajectory, which is marked as the normal area. The area outside this area is marked as the vibration trajectory exceeding the limit area.

[0074] S213. Based on the acquired pitch signal, mark the annular region of the wind turbine blade vibration trajectory at different pitch angles, and divide it into nine regions:

[0075] 0.0°~20.0°, 20.1°~30.0°, 30.1°~35.0°, 35.1°~40.0°, 40.1°~45.0°, 45.1°~50.0°, 50.1°~60.0°, 60.1°~70.0°, and 70.1°~90.0°;

[0076] S214. Real-time acquisition of wind turbine blade flapping and oscillation data. After removing the wind turbine blade rotation speed frequency, the blade's trajectory is considered normal if it falls within the constructed blade vibration trajectory annular area, and abnormal if it does not, triggering an early warning. The data whose trajectory falls within the constructed blade vibration trajectory annular area are included in historical data, and the obtained historical data is used to continuously correct the two-dimensional spatial model of wind turbine blade vibration.

[0077] In summary, this invention can automatically control the real-time acquisition of relevant data of wind turbine blades according to set conditions during the monitoring process, so as to obtain effective data for wind turbine blade early warning analysis, and then effectively manage the data. Through the obtained two-dimensional spatial model of wind turbine blade vibration, it can accurately predict whether there is a risk of breakage of wind turbine blades, so as to replace wind turbine blades with potential safety hazards in a timely manner, thereby improving the service life and power generation efficiency of wind turbine generator sets.

[0078] The embodiments of the present invention have been described in detail above with reference to the accompanying drawings. However, the present invention is not limited thereto. Various changes can be made within the scope of knowledge possessed by those skilled in the art without departing from the spirit of the present invention.

Claims

1. A wind turbine blade fracture detection and early warning device, characterized in that, include Vibration sensors are installed at the center of gravity of the wind turbine blades, with each vibration sensor corresponding to a wind turbine blade. The data acquisition and transmission device is connected to the vibration sensor and is used to be installed on the hub of the wind turbine generator set and rotate with the wind turbine blades. Speed ​​sensor is used to collect wind turbine blade speed signals and wind turbine blade pitch signals from wind turbine generator sets; The speed sensor is installed inside the nacelle of the wind turbine generator set; The data acquisition unit is communicatively connected to the data acquisition and transmission device and the speed sensor. It is used to collect signals from the data acquisition and transmission device and the speed sensor, process the speed signals, and determine whether to send a data acquisition command to the data acquisition and transmission device based on the processing results. The data acquisition unit is installed in the nacelle of the wind turbine generator set and is communicatively connected to the back-end server terminal to send the collected data to the back-end server terminal. The method for issuing data acquisition commands to the data acquisition and transmission device includes the following specific steps: S110, The data acquisition unit collects the speed signal of the wind turbine blades monitored by the speed sensor in real time; S111. Determine whether the rotational speed of the fan blades is greater than or equal to the set threshold. If so, then execute S112; If not, then execute S113; S112, The data acquisition unit sends an instruction to the data acquisition and transmission device to have the acquisition module perform data acquisition, and simultaneously executes S110; the method by which the acquisition module performs data acquisition is as follows: Under the condition of sampling frequency of 1280Hz, data is continuously collected to obtain multiple sets of data a; the data collection time for each set of data a is 120s. S113, The data acquisition unit sends an instruction to the data acquisition and transmission device to perform data acquisition using the interrupt module, and simultaneously executes S110; the method for the interrupt module to perform data acquisition is as follows: Under the condition of sampling frequency of 50Hz, data is collected at intervals to obtain multiple sets of data b; the data collection time for each set of data b is 60s, and the time interval between two adjacent sets of data b is 10min. The data acquisition unit establishes a communication connection with the data acquisition and transmission device using wireless transmission. It also includes a switch, which is a communication connection to the data collector and is used to send the data collected by the data collector to the back-end server terminal via wired transmission. The vibration sensor selected is a biaxial vibration acceleration sensor; The early warning method using the aforementioned wind turbine blade fracture detection and early warning device specifically includes the following steps: S210. Obtain historical vibration and flapping data of the wind turbine impeller. Use a bandpass filter to remove the wind turbine impeller speed frequency from the flapping and vibration data to obtain data group c. S211. Using time as the X-axis, the effective value of vibration in the waving direction as the Y-axis, and the effective value of vibration in the oscillation direction as the Z-axis, a two-dimensional spatial model of wind turbine blade vibration is constructed using data group c. S212. Constructing the trajectory critical surface of a two-dimensional spatial model of wind turbine blade vibration: Take 0.5 times and 1.2 times the effective value of vibration in the flapping direction and 0.5 times and 1.2 times the effective value of vibration in the oscillation direction to construct a circular area of ​​blade vibration trajectory, which is marked as the normal area. The area outside this area is marked as the vibration trajectory exceeding the limit area. S213. Based on the acquired wind turbine blade pitch signal, mark the annular region of the wind turbine blade vibration trajectory at different pitch angles, dividing it into nine regions: 0.0°~20.0°, 20.1°~30.0°, 30.1°~35.0°, 35.1°~40.0°, 40.1°~45.0°, 45.1°~50.0°, 50.1°~60.0°, 60.1°~70.0°, and 70.1°~90.0°; S214. Real-time acquisition of the flapping and oscillation data of the wind turbine blades. After removing the wind turbine blade speed frequency, the running trajectory is considered normal if it falls within the constructed blade vibration trajectory ring area, otherwise it is considered abnormal and an early warning is triggered. Data that falls within the constructed blade vibration trajectory annular area are incorporated into historical data, and the obtained historical data is used to continuously revise the two-dimensional spatial model of wind turbine blade vibration.

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