A wind turbine variable pitch bearing and connecting bolt condition monitoring method and system

Abstract

The application discloses a wind turbine variable pitch bearing and connecting bolt state monitoring method and system, and the system comprises a variable pitch bearing race (8), a race sensor (10) arranged on the variable pitch bearing race (8), a variable pitch bearing shaft ring (2), a first shaft ring sensor (11) and a second shaft ring sensor (12) horizontally and symmetrically arranged on the variable pitch bearing shaft ring (2), a data acquisition and analysis unit (13) and a wind farm control room (16), wherein the race sensor (10) is used for sensing the vibration of the variable pitch bearing race (8); the first shaft ring sensor (11) and the second shaft ring sensor (12) are used for sensing the vibration of the variable pitch bearing shaft ring (2); the data acquisition and analysis unit (13) is arranged in the hub and is used for synchronously collecting the first shaft ring sensor signal, the second shaft ring sensor signal and the race sensor signal, processing and analyzing the first shaft ring sensor signal, the second shaft ring sensor signal and the race sensor signal, determining whether the variable pitch bearing and the connecting bolt are faulty according to the processing and analysis results, and transmitting the fault monitoring results of the variable pitch bearing and the connecting bolt to the wind farm control room.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of wind power generators, in particular to a wind power generator variable pitch bearing and connecting bolt state monitoring method and system. BACKGROUND

[0002] The megawatt wind turbine basically adopts variable speed variable pitch control mode, and the essential mechanical component of the variable pitch control system is the variable pitch bearing. Through the variable pitch bearing, the variable pitch control system can control the blade angle by using electric variable pitch or hydraulic variable pitch. The blade is connected to the shaft ring of the variable pitch bearing by bolts, and the variable pitch bearing is connected to the hub flange by bolts, and the stress of the blade is transmitted to the hub through the bolts and the variable pitch bearing.

[0003] In recent years, a large number of wind farms have appeared blade root bolt fracture and variable pitch bearing cracking failures due to the influence of factors such as continuous operation of installed wind turbines and continuous lengthening of new input blades. These failures may cause wind turbine downtime for maintenance, or even cause serious accidents such as variable pitch bearing jamming and blade falling off. Due to the lack of effective monitoring methods and means, the inspection of the variable pitch bearing and connecting bolts can only be carried out by periodic visual inspection or bolt torque inspection by on-site operation and maintenance personnel, which cannot timely detect early damage, and often the bolt has been broken when the inspection is carried out, and the adjacent connecting bolts are also broken. This not only increases the risk of operation of the unit, but also increases the replacement cost.

[0004] Therefore, a wind power generator variable pitch bearing and connecting bolt state monitoring method and system are needed to automatically and real-time monitor the operating state of the variable pitch bearing and connecting bolts, and timely detect blade root bolt fracture and variable pitch bearing cracking failures. SUMMARY

[0005] The embodiments of the present application provide a wind power generator variable pitch bearing and connecting bolt state monitoring method and system, which can realize real-time monitoring of the operating state of the variable pitch bearing and connecting bolts, timely detect blade root bolt fracture and variable pitch bearing cracking failures, and reduce the risk of operation of the wind turbine and maintenance cost.

[0006] According to an aspect of an embodiment of the present application, a wind power generator variable pitch bearing and connecting bolt state monitoring system is provided, comprising: a variable pitch bearing seat ring (8); a seat ring sensor (10) arranged on the variable pitch bearing seat ring (8); a variable pitch bearing shaft ring (2); a first shaft ring sensor (11) and a second shaft ring sensor (12) horizontally and symmetrically arranged on the variable pitch bearing shaft ring (2); a data acquisition and analysis unit (13) and a wind farm control room (16);

[0007] The seat ring sensor (10) is used to sense the vibration of the variable pitch bearing seat ring (8);

[0008] The first shaft ring sensor (11) and the second shaft ring sensor (12) are used to sense the vibration of the pitch bearing shaft ring (2);

[0009] The data acquisition and analysis unit (13) is arranged inside the hub, is used for synchronously acquiring the first shaft ring sensor signal, the second shaft ring sensor signal and the raceway sensor signal, processing and analyzing the first shaft ring sensor signal, the second shaft ring sensor signal and the raceway sensor signal, determining whether the pitch bearing and the connecting bolt are faulty according to the processing and analyzing result, and transmitting the fault monitoring result of the pitch bearing and the connecting bolt to the wind field control room;

[0010] The wind field control room (16) is used for real-time display of the received fault monitoring result, and automatic alarm according to the monitoring result.

[0011] According to another aspect of the embodiment of the application, a wind turbine pitch bearing and connecting bolt state monitoring method is provided, comprising:

[0012] The first shaft ring sensor signal, the second shaft ring sensor signal and the raceway sensor signal of three blades of the wind turbine are acquired respectively;

[0013] The kurtosis index of the first shaft ring sensor signal, the second shaft ring sensor signal and the raceway sensor signal is calculated respectively for each blade;

[0014] The kurtosis index of the first shaft ring sensor signal, the kurtosis index of the second shaft ring sensor signal and the kurtosis index of the raceway sensor signal of the three blades are used to determine whether the blade connecting bolt and the hub connecting bolt are faulty;

[0015] The first shaft ring sensor signal of the three blades is processed;

[0016] The processing result of the first shaft ring sensor signal of the three blades is used to determine whether the pitch bearing is faulty.

[0017] The embodiment of the present application respectively installs a seat ring sensor on the pitch bearing seat ring and installs two horizontally symmetrical shaft ring sensors on the pitch bearing shaft ring, and analyzes and processes the obtained seat ring sensor signals and shaft ring sensor signals through a data acquisition and analysis unit, so that the bolt fracture and pitch bearing failure are monitored in real time, and the problem that the pitch bearing and connecting bolt cannot be monitored in real time in the current wind power operation is solved. The embodiment of the present application can monitor whether the bolt of the pitch bearing is fractured in real time, and automatically sends an alarm notification at the first time of fracture, without manual data analysis, and the analysis efficiency is high. Through the embodiment of the present application, real-time fault monitoring of the pitch bearing can also be realized, and automatic alarm can be realized in the early stage of failure, so that serious faults such as jamming and cracking are effectively avoided after the accumulation of bearing failure, and the operation safety of the wind turbine is greatly improved. BRIEF DESCRIPTION OF DRAWINGS

[0018] The present application will be further described in detail below according to the drawings and embodiments.

[0019] Figure 1 It is a schematic diagram of the monitoring structure of the pitch bearing and the connecting bolt of an embodiment of the present application.

[0020] Figure 2 It is a schematic diagram of the monitoring system of the pitch bearing and the connecting bolt of another embodiment of the present application.

[0021] Figure 3 It is a structural block diagram of the monitoring system of the pitch bearing and the connecting bolt of the wind turbine provided by the embodiment of the present application.

[0022] Figure 4 It is a flowchart of the state monitoring method of the pitch bearing and the connecting bolt of the wind turbine provided by the embodiment of the present application.

[0023] Figure 5 It is a state monitoring algorithm flow of the pitch bearing and the connecting bolt provided by the exemplary embodiment of the present application.

[0024] In the figure:

[0025] 1, blade root section; 2, pitch bearing shaft ring; 3, double-headed bolt; 4, blade root nut; pitch bearing rolling element; 6, hub nut; 7, hub flange; 8, pitch bearing seat ring; 9, hub bolt; 10, seat ring sensor; 11, shaft ring sensor 1; 12, shaft ring sensor 2; 13, data acquisition and analysis unit; 14, engine room control cabinet; 15, tower bottom exchange; 16, wind field central control room. DETAILED DESCRIPTION

[0026] The technical solutions of the embodiments of the present application will be further described in detail below with reference to the drawings. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without creative work fall within the protection scope of the present application.

[0027] Embodiment one

[0028] Figure 1 It is a schematic diagram of a monitoring structure of a wind turbine variable pitch bearing and connecting bolt provided according to an embodiment of the present application. The current mainstream model adopts a 3-blade mode, and the 3-blade variable pitch systems are the same. An embodiment of the present application takes one blade as an example for illustration. As shown in the figure, Figure 1 The schematic diagram of the monitoring structure of the variable pitch bearing and the connecting bolt is shown in the figure. The blade root 1 is connected together through the double-headed bolt 3, the blade root nut 4 and the variable pitch bearing shaft ring 2. The variable pitch bearing seat ring 8 is connected to the hub flange 7 through the hub bolt 9 and the hub nut 6, so that the variable pitch bearing shaft ring can rotate through the rolling body 5 and the variable pitch bearing seat ring. From the analysis of the failed variable pitch bearing, most of the bolt fractures and bearing failures occur in the shaft ring, and occur at 0 degree and 10 degree positions. Therefore, an embodiment of the present application respectively installs one seat ring sensor 10 on the variable pitch bearing seat ring 8 and installs two horizontally symmetrical second shaft ring sensors 11 and 12 on the variable pitch bearing shaft ring 2, so as to realize real-time monitoring of the bolt fracture and the variable pitch bearing failure.

[0029] Figure 2 It is a schematic diagram of a monitoring system of a wind turbine variable pitch bearing and connecting bolt provided according to an embodiment of the present application. The first shaft ring sensor 11 and the second shaft ring sensor 12 are horizontally symmetrically installed on the variable pitch bearing shaft ring, for sensing the vibration of the variable pitch bearing shaft ring (2). The seat ring sensor 10 is installed on the variable pitch bearing seat ring, for sensing the vibration of the variable pitch bearing seat ring (8). The data acquisition and analysis system 13 is arranged in the hub, for synchronously collecting the sensing signals of the seat ring sensor 10, the first shaft ring sensor 11 and the second shaft ring sensor 12, and processing and analyzing the sensing signals. At the same time, the data acquisition and analysis system 13 transmits the collected sensing signals and processing results to the nacelle control cabinet 14 through the slip ring wired communication or wireless communication mode, enters the tower bottom switch 15 through the nacelle control cabinet, and finally the tower bottom switch 15 transmits the received sensing signals and processing results to the wind farm control room 16. Therefore, the maintenance personnel can monitor the state of the variable pitch bearing and the connecting bolt in real time through the wind farm control room.

[0030] Embodiment two

[0031] Figure 3The structural block diagram of a wind turbine variable pitch bearing and connecting bolt monitoring system is provided according to an embodiment of the present application. The system comprises: a variable pitch bearing race 8; a race sensor 10 arranged on the variable pitch bearing race 8; a variable pitch bearing shaft ring 2; a first shaft ring sensor 11 and a second shaft ring sensor 12 horizontally and symmetrically arranged on the variable pitch bearing shaft ring 2; a data acquisition and analysis unit 13; and a wind farm control room 16.

[0032] The race sensor 10 is used to sense the vibration of the variable pitch bearing race; the first shaft ring sensor 11 and the second shaft ring sensor 12 are used to sense the vibration of the variable pitch bearing shaft ring. Optionally, the race sensor 10, the first shaft ring sensor 11 and the second shaft ring sensor 12 are all vibration sensors.

[0033] The data acquisition and analysis unit is used to synchronously acquire the first shaft ring sensor signal, the second shaft ring sensor signal and the race sensor signal, process and analyze the first shaft ring sensor signal, the second shaft ring sensor signal and the race sensor signal, determine whether the variable pitch bearing and the connecting bolt are faulty according to the processing and analysis results, and transmit the fault monitoring results of the variable pitch bearing and the connecting bolt to the wind farm control room.

[0034] The wind farm control room is used to display the state of the variable pitch bearing and the connecting bolt in real time according to the received monitoring results, and automatically alarm according to the monitoring results.

[0035] Optionally, the data acquisition and analysis unit comprises a bolt fracture monitoring subunit, a variable pitch bearing fault monitoring subunit and a sensing signal and monitoring result output subunit. The bolt fracture monitoring subunit is used to determine whether the blade connecting bolt and the hub connecting bolt are normal according to the kurtosis and other indicators of the first shaft ring sensor signal, the kurtosis and other indicators of the second shaft ring sensor signal and the kurtosis and other indicators of the race sensor signal; the variable pitch bearing fault monitoring subunit is used to process the first shaft ring sensor signal and determine whether the variable pitch bearing is faulty according to the processing results of the first shaft ring sensor signals of the three blades; and the sensing signal and monitoring result output subunit is used to transmit the acquired first shaft ring sensor signal, second shaft ring sensor signal and race sensor signal and the monitoring results to the wind farm control room.

[0036] Optionally, the system of the embodiment of the present application further comprises a nacelle control cabinet 14 and a tower bottom switch 15, the data acquisition and analysis unit 13 transmits the acquired first shaft ring sensor signal, second shaft ring sensor signal and race sensor signal and the processing results to the nacelle control cabinet 14 through slip ring wired communication or wireless communication, and sends the same to the tower bottom switch 15 through the nacelle control cabinet 14, and finally transmits the same to the wind farm control room 16.

[0037] Optionally, the race sensor 10, the first shaft ring sensor 11 and the second shaft ring sensor 12 are all vibration sensors.

[0038] The embodiment of the present application respectively installs a seat ring sensor on the pitch bearing seat ring and installs two horizontally symmetrical shaft ring sensors on the pitch bearing shaft ring, and analyzes and processes the acquired seat ring sensor signals and shaft ring sensor signals through a data acquisition and analysis unit, so as to realize real-time monitoring of bolt fracture and pitch bearing failure, and solve the problem that the pitch bearing and connecting bolt cannot be monitored in real time in the current wind power operation. The embodiment of the present application can monitor whether the bolt of the pitch bearing is fractured in real time, and automatically sends an alarm notification at the first time of fracture.

[0039] Embodiment three

[0040] The embodiment of the present application provides a wind turbine pitch bearing and connecting bolt state monitoring method, Figure 4 The embodiment of the present application provides a wind turbine pitch bearing and connecting bolt state monitoring method, and the method comprises the following steps 100 to 108.

[0041] Step 100, acquiring first shaft ring sensor signals, second shaft ring sensor signals and seat ring sensor signals of three blades of a wind turbine respectively.

[0042] Since bolt fracture or bearing damage will generate high-frequency impact signals, the first shaft ring sensor, the second shaft ring sensor and the third shaft ring sensor are all selected to be vibration sensors.

[0043] Step 102, for each blade, the kurtosis and other indicators of the first shaft ring sensor signal, the second shaft ring sensor signal and the seat ring sensor signal are calculated respectively.

[0044] Step 104, determining whether the blade connecting bolt and the hub connecting bolt are normal according to the kurtosis and other indicators of the first shaft ring sensor signals, the kurtosis and other indicators of the second shaft ring sensor signals and the kurtosis and other indicators of the seat ring sensor signals of the three blades.

[0045] According to the characteristics that a great attenuation occurs when a high-frequency signal is transmitted through the oil film between the pitch bearing rolling elements, if the blade and the pitch bearing shaft ring connecting bolt is fractured, the impact generated at the moment of fracture will make the response of the first shaft ring sensor and the second shaft ring sensor greater than that of the seat ring sensor. Similarly, if the hub and the pitch bearing seat ring connecting bolt is fractured, the impact generated at the moment of fracture will make the response of the seat ring sensor greater than that of the first shaft ring sensor and the second shaft ring sensor. If the pitch bearing rolling element fails, the impacts generated on the three sensors are basically the same.

[0046] Step 106, processing the first shaft ring sensor signals of the three blades.

[0047] Step 108, determining whether the pitch bearing fails according to the time domain processing result of the first shaft ring sensor signal of the three blades.

[0048] Optionally, before step 102, the method further comprises filtering the first shaft ring sensor signal, the second shaft ring sensor signal and the seat ring sensor signal.

[0049] Since a lot of mechanical vibration interference will be generated when the hub and the blades rotate, the frequency of the interference signals is basically low frequency, and filtering is performed first in order to reduce signal interference.

[0050] Optionally, step 104, determining whether the blade connecting bolt and the hub connecting bolt are abnormal according to the kurtosis and other indicators of the first shaft ring sensor signal, the kurtosis and other indicators of the second shaft ring sensor signal and the kurtosis and other indicators of the seat ring sensor signal, comprising:

[0051] For each blade, it is determined whether the kurtosis and other indicators of the first shaft ring sensor signal, the second shaft ring sensor signal and the seat ring sensor signal are all greater than a first predetermined threshold value; if all are greater than the first predetermined threshold value, the kurtosis and other indicators of the current first shaft ring sensor signal, the second shaft ring sensor signal and the seat ring sensor signal are saved;

[0052] The saved kurtosis and other indicators of the first shaft ring sensor signal, the second shaft ring sensor signal and the seat ring sensor signal of the three blades are synchronously analyzed, the maximum value A1max of the kurtosis and other indicators of the first shaft ring sensor signal, the maximum value A2max of the kurtosis and other indicators of the second shaft ring sensor signal and the maximum value A3max of the kurtosis and other indicators of the seat ring sensor signal are determined respectively, and the coefficients K1=A1max / A3max and K2=A2max / A3max are calculated.

[0053] If K1 or K2 is greater than a second predetermined threshold value, it is determined that the blade connecting bolt is abnormal, and if K1 or K2 is less than a third predetermined threshold value, it is determined that the hub connecting bolt is abnormal, wherein the second predetermined threshold value is greater than the third predetermined threshold value.

[0054] Optionally, the first predetermined threshold value is 4, the second predetermined threshold value is 8, and the third predetermined threshold value is 0.12.

[0055] Optionally, step 106, processing the sensor signals of the first shaft ring sensors of the three blades, comprising:

[0056] The root mean square values of the first shaft ring sensor signals of the three blades are calculated respectively to obtain the root mean square value Blade1-RMS1 of the first shaft ring sensor signal of the first blade, the root mean square value Blade2-RMS1 of the sensor signal of the first shaft ring sensor of the second blade and the root mean square value Blade3-RMS1 of the first shaft ring sensor signal of the third blade.

[0057] The first shaft ring sensor signal of each blade is high-pass filtered into three frequency band signals, and the effective values of the three frequency band signals are calculated respectively;

[0058] The standard deviations of the following data are calculated: the standard deviation σ1 of the root mean square values of the first shaft ring sensor signals of the three blades; the standard deviation σ2 of the effective values of the first frequency band signals of the three blades; the standard deviation σ3 of the effective values of the second frequency band signals of the three blades; and the standard deviation σ4 of the effective values of the third frequency band signals of the three blades.

[0059] Optionally, in step 108, whether the pitch bearing fails is determined according to the processing results of the first shaft ring sensor signals of the three blades, including: if the standard deviation σ1 is greater than a fourth predetermined threshold, and one of the standard deviations σ2, σ3 and σ4 is greater than a fifth predetermined threshold, it is determined that the pitch bearing fails.

[0060] Preferably, the fifth predetermined threshold is smaller than the fourth predetermined threshold. More preferably, the fourth threshold is 0.2, and the fifth threshold is 0.1.

[0061] The embodiments of the present application process and analyze the first shaft ring sensor signals, the second shaft ring sensor signals and the seat ring sensor signals of the three blades, and determine whether the pitch bearing and the connecting bolt fail according to the processing and analysis results. The system automatically sends an alarm notification at the first time of failure, realizes real-time monitoring of bolt fracture and pitch bearing failure, solves the problem that the pitch bearing and the connecting bolt cannot be monitored in real time in the current wind power operation, and greatly improves the operation safety of the wind turbine.

[0062] Exemplary embodiments

[0063] The bolt fracture and pitch bearing failure monitoring algorithm of the embodiments of the present application will be described below by way of example. Figure 5 is a state monitoring algorithm process of a pitch bearing and a connecting bolt according to an exemplary embodiment of the present application.

[0064] Bolt fracture and pitch bearing failure monitoring algorithm

[0065] Step 1: Obtain the first shaft ring sensor signal, the second shaft ring sensor signal and the seat ring sensor signal of the three blades of the wind turbine respectively, which are represented as sensor signal 1, sensor signal 2 and sensor signal 3 respectively. Correspondingly, the first shaft ring sensor, the second shaft ring sensor and the seat ring sensor are represented as sensor 1, sensor 2 and sensor 3 respectively.

[0066] Since bolt fracture or bearing damage will generate high-frequency impact signals, the sensors 1, 2 and 3 are vibration sensors.

[0067] Step 2: Since there are many mechanical vibration interferences when the hub and the blades rotate, the interference signal frequency is basically low frequency, in order to reduce signal interference, the sensor signal 1, sensor information 2, sensor signal 3 need to be filtered.

[0068] According to the characteristics that the high frequency signal will be greatly attenuated when passing through the oil film between the rolling body and the pitch bearing, if the blade and the pitch bearing ring connecting bolt breaks, the impact generated at the moment of breakage will make the response of sensor 1 and 2 greater than that of sensor 3. Similarly, if the hub and the pitch bearing seat connecting bolt breaks, the impact generated at the moment of breakage will make the response of sensor 3 greater than that of sensor 1 and 2. If the pitch bearing rolling body fails, the impact on the three sensors is basically the same.

[0069] Step 3: Real-time calculation of the kurtosis index Cp of sensor signals 1, 2 and 3, respectively denoted as Cp1, Cp2 and Cp3. The kurtosis index Cp of normal sensor signals 1, 2 and 3 is generally less than 3. When Cp1≥4 or Cp2≥4 or Cp3≥4, it indicates that there is obvious impact in the signal, and the current group data of the three sensors is saved to enter step 4, and other data that does not meet the requirement is not saved.

[0070] Step 4: Synchronous analysis of the data retained after step 3, respectively finding the maximum value of the kurtosis index signal, A1max, A2max and A3max, i.e. finding the maximum value A1max of Cp1 saved after step 3 for the three blades, finding the maximum value A2max of Cp2 saved after step 3 for the three blades, and finding the maximum value A3max of Cp3 saved after step 3 for the three blades. Determine the discrimination coefficient K1=A1max / A3max; K2=A1max / A3max.

[0071] If K1≥8 or K2≥8, the system outputs that the blade connecting bolt is abnormal, and if K1≤0.12 or K2≤0.12, the system outputs that the hub connecting bolt is abnormal.

[0072] Step 5: Time domain index calculation is performed on the original data of sensor 1 after step 1, the root mean square value (RMS value) is calculated, and the three blades are calculated synchronously. For example, pitch bearing 1 is denoted as Blade1-RMS1, pitch bearing 2 is denoted as Blade2-RMS1, and pitch bearing 3 is denoted as Blade3-RMS1.

[0073] Before calculating the root mean square value, the original sensor signal 1 of the three blades is filtered synchronously.

[0074] Step 6: The filtered data is subjected to FFT processing. Since the data is filtered, according to the sampling principle, the frequency spectrum range is fi-fo. The frequency between fi-fo is divided into 3 frequency bands, wherein the first frequency band fi-f1 is referred to as band1; the second frequency band f1-f2 Hz is referred to as band2; and the third frequency band f2-fo Hz is referred to as band3. The effective values of the 3 frequency band signals of blade 1 are calculated, i.e. (Blade1-band1-Rms, Blade1-band2-Rms, Blade1-band3-Rms), and the effective values of the 3 frequency band signals of blade 2 and blade 3 are (Blade2-band1-Rms, Blade2-band2-Rms, Blade2-band3-Rms) and (Blade3-band1-Rms, Blade3-band2-Rms, Blade3-band3-Rms) respectively.

[0075] Step 7: Since the probability of simultaneous failure of the pitch bearings of the 3 blades is low, the same position sensor values of the 3 blades are compared and the standard deviations of the following groups of data are calculated. The first group is the root mean square values of the 3 blades (Blade1-Rms1, Blade2-Rms1, Blade3-Rms1), and the standard deviation of the first group of data is referred to as σ1. The second group of data is the effective values of the first frequency band signals of the 3 blades (Blade1-band1-Rms, Blade2-band1-Rms, Blade3-band1-Rms), and the standard deviation of the second group of data is referred to as σ2. The third group of data is the effective values of the second frequency band signals of the 3 blades (Blade1-band2-Rms, Blade2-band2-Rms, Blade3-band2-Rms), and the standard deviation of the third group of data is referred to as σ3. The fourth group of data is the effective values of the third frequency band signals of the 3 blades (Blade1-band3-Rms, Blade2-band3-Rms, Blade3-band3-Rms), and the standard deviation of the fourth group of signals is referred to as σ4.

[0076] Step 8: If σ1≥0.2; and σ2≥0.1 or σ3≥0.1 or σ4≥0.1, the system outputs a pitch bearing failure.

[0077] The technical principles of the present application are described above in combination with specific embodiments. These descriptions are only for the purpose of explaining the principles of the present application, and cannot be interpreted in any way as a limitation on the scope of protection of the present application.

Claims

1. A monitoring system for the pitch bearing and connecting bolts of a wind turbine generator, characterized in that, The method comprises the following steps: A pitch bearing seat ring (8); a seat ring sensor (10) arranged on the pitch bearing seat ring (8); a pitch bearing shaft ring (2); a first shaft ring sensor (11) and a second shaft ring sensor (12) arranged horizontally and symmetrically on the pitch bearing shaft ring (2); a data acquisition and analysis unit (13) and a wind farm control room (16); The seat ring sensor (10) is used to sense the vibration of the pitch bearing seat ring (8); The first shaft ring sensor (11) and the second shaft ring sensor (12) are used to sense the vibration of the pitch bearing shaft ring (2); The data acquisition and analysis unit (13) is arranged inside the hub and is used to synchronously acquire the first shaft ring sensor signal, the second shaft ring sensor signal and the seat ring sensor signal, filter process the first shaft ring sensor signal, the second shaft ring sensor signal and the seat ring sensor signal, process and analyze the filtered signals, determine whether the pitch bearing and the connecting bolt are faulty according to the processing and analysis results, and transmit the fault monitoring results of the pitch bearing and the connecting bolt to the wind farm control room (16); The wind farm control room (16) is used to display the received fault monitoring results in real time and automatically alarm according to the monitoring results; The data acquisition and analysis unit (13) comprises a bolt fracture monitoring subunit (131), a pitch bearing fault monitoring subunit (132) and a sensing signal and monitoring result output subunit (133); The bolt fracture monitoring subunit (131) is used to determine whether the blade connecting bolt and the hub connecting bolt are normal according to the kurtosis index of the first shaft ring sensor signal, the kurtosis index of the second shaft ring sensor signal and the kurtosis index of the seat ring sensor signal; The pitch bearing fault monitoring subunit (132) is used to process the first shaft ring sensor signals of the three blades, calculate the root mean square values of the first shaft ring sensor signals of the three blades respectively, filter the first shaft ring sensor signal of each blade, divide the filtered first shaft ring sensor signal into three frequency band signals and calculate the effective values of the three frequency band signals respectively, calculate the standard deviation σ1 of the root mean square values of the first shaft ring sensor signals of the three blades, the standard deviation σ2 of the effective values of the first frequency band signals of the three blades, the standard deviation σ3 of the effective values of the second frequency band signals of the three blades, the standard deviation σ4 of the effective values of the third frequency band signals of the three blades, and determine whether the pitch bearing is faulty according to the processing results of the first shaft ring sensor signals of the three blades; The sensing signal and monitoring result output subunit (133) is used to transmit the acquired first shaft ring sensor signal, second shaft ring sensor signal and seat ring sensor signal and the monitoring result to the wind farm control room (16).

2. The system of claim 1, wherein, Further comprising: The nacelle control cabinet (14) and the tower bottom switch (15), wherein the sensing signal and monitoring result output subunit (133) transmits the collected first shaft ring sensor signal, second shaft ring sensor signal and seat ring sensor signal and monitoring result to the nacelle control cabinet (14) through slip ring wired communication or wireless communication, sends to the tower bottom switch (15) through the nacelle control cabinet (14), and finally transmits to the wind farm control room (16) through the tower bottom switch (15).

3. The system of any one of claims 1 to 2, wherein, The seat ring sensor (10), the first shaft ring sensor (11) and the second shaft ring sensor (12) are vibration sensors.

4. A method of monitoring a wind turbine generator variable pitch bearing and connecting bolt, characterized by, Comprise: Respectively acquiring the first shaft ring sensor signal, the second shaft ring sensor signal and the seat ring sensor signal of the three blades of the wind turbine; For each blade, the kurtosis indexes of the first shaft ring sensor signal, the second shaft ring sensor signal and the seat ring sensor signal are calculated respectively; According to the kurtosis indexes of the first shaft ring sensor signal, the second shaft ring sensor signal and the seat ring sensor signal of the three blades, it is determined whether the blade connecting bolt and the hub connecting bolt are faulty; The first shaft ring sensor signals of the three blades are processed; According to the processing results of the first shaft ring sensor signals of the three blades, it is determined whether the pitch bearing is faulty; Before calculating the kurtosis indexes of the first shaft ring sensor signal, the second shaft ring sensor signal and the seat ring sensor signal, the method further comprises filtering the first shaft ring sensor signal, the second shaft ring sensor signal and the seat ring sensor signal; The processing of the sensor signals of the first shaft ring sensors of the three blades comprises: The root mean square values of the first shaft ring sensor signals of the three blades are calculated respectively to obtain the root mean square value Blade1-RMS1 of the first shaft ring sensor signal of the first blade, the root mean square value Blade2-RMS1 of the sensor signal of the first shaft ring sensor of the second blade and the root mean square value Blade3-RMS1 of the first shaft ring sensor signal of the third blade; After filtering the first shaft ring sensor signal of each blade, three frequency band signals are obtained, and the effective values of the three frequency band signals are calculated respectively; The standard deviations of the following data are calculated: the standard deviation σ1 of the root mean square values of the first shaft ring sensor signals of the three blades; the standard deviation σ2 of the effective values of the first frequency band signals of the three blades; the standard deviation σ3 of the effective values of the second frequency band signals of the three blades; and the standard deviation σ4 of the effective values of the third frequency band signals of the three blades.

5. The method of claim 4, wherein, The determination of whether the blade connecting bolt and the hub connecting bolt are faulty according to the kurtosis indexes of the first shaft ring sensor signal, the second shaft ring sensor signal and the seat ring sensor signal of the three blades comprises: For each blade, it is determined whether the kurtosis indexes of the first shaft ring sensor signal, the second shaft ring sensor signal and the seat ring sensor signal are all greater than a first predetermined threshold value; if all are greater than the first predetermined threshold value, the current kurtosis indexes of the first shaft ring sensor signal, the second shaft ring sensor signal and the seat ring sensor signal are saved; The kurtosis indexes of the saved first shaft ring sensor signals, second shaft ring sensor signals and seat ring sensor signals of the three blades are synchronously analyzed, the maximum value A1max of the kurtosis index of the saved first shaft ring sensor signals, the maximum value A2max of the kurtosis index of the saved second shaft ring sensor signals and the maximum value A3max of the kurtosis index of the saved seat ring sensor signals are respectively determined, and the coefficients K1=A1max / A3max and K2=A2max / A3max are calculated. If K1 or K2 is greater than a second predetermined threshold value, it is determined that the blade connecting bolt is abnormal, and if K1 or K2 is less than a third predetermined threshold value, it is determined that the hub connecting bolt is abnormal, wherein the second predetermined threshold value is greater than the third predetermined threshold value.

6. The method of claim 4, wherein, The method further comprises: transmitting the fault information to the central control room in the wind farm.

7. The method of claim 4, wherein, The first predetermined threshold value is 4, the second predetermined threshold value is 8, and the third predetermined threshold value is 0.

12.

8. The method of claim 4, wherein, The fourth threshold value is 0.2, and the fifth threshold value is 0.

1.

9. The method of claim 6, wherein, ​

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