Wind turbine generator bolt fracture detection method, device and detection system

Abstract

The invention relates to the technical field of industrial detection equipment, in particular to a wind turbine generator bolt fracture detection method, device and system. An anti-electromagnetic interference signal line is used for constructing a signal loop, a to-be-detected bolt in a wind power cabin is physically connected with the anti-electromagnetic interference signal line, and whether the bolt is broken or not is judged by detecting a signal of the signal loop. The method has second-level fracture response capability and can guarantee safe operation of the wind turbine generator.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of industrial detection equipment, and in particular to a wind turbine bolt fracture detection method, device and system. BACKGROUND

[0002] Wind power equipment is becoming increasingly large and complex, and its operation stability and operation efficiency are particularly critical. Once a wind turbine fails, the cost of shutdown maintenance is high, the maintenance period is long, and the power generation income is affected. How to improve the fault detection accuracy, shorten the downtime, reduce the labor maintenance cost, and especially reduce the unplanned downtime events has become a core problem that wind power enterprises and operation units urgently need to solve.

[0003] Under the action of multiple loads such as strong wind impact, start-stop vibration, and cold-heat alternation, the connecting bolts in the nacelle have the risk of micro-sliding, loosening, and fracture. Most current wind turbines rely on manual torque inspection or visual inspection, which cannot real-time perceive the change of bolt pretightening force or the fatigue crack propagation process, and often are not discovered until structural failure occurs.

[0004] The fracture or shedding of a single bolt can cause the overall loosening of the coupling structure, and further cause serious accidents such as blade flying off, bearing offset, etc., affecting the safety and availability of the wind turbine, and even causing personal safety risks and significant economic losses.

[0005] The existing fracture detection methods for wind turbine bolts or nuts include manual inspection and online detection technology using electronic systems. Manual inspection is inefficient and not timely, and is time-consuming and labor-intensive. The online monitoring technology, such as the fracture monitoring scheme based on an electrical circuit as described in reference 1.

[0006] Reference 1: Chinese patent document with publication number CN 110778463 A.

[0007] Reference 1 describes a wind turbine blade bolt fracture monitoring and protection method and device. The wind turbine blade is assembled on the hub of the wind turbine and is fixedly connected with the hub by bolts. The method is characterized in that a closed circuit composed of a power supply and a load connected by wires is provided. When laying the wires, pass them through each wind turbine blade bolt, and fix them on each wind turbine blade bolt head with a fastener. In the closed circuit, an electric current detection device is provided to send the detected electric current signal to the wind turbine main control in the form of "1" and "0" logic expression. When any bolt is fractured, the fractured bolt head falls out of the bolt hole of the hub under the action of its own gravity and the inertia of the wind wheel movement, and the fastener fixed thereon is pulled off. The current of the closed circuit disappears, the signal logic sent by the electric current detection device to the wind turbine main control is "0", and the wind turbine main control controls the wind turbine to stop, thereby avoiding causing a major accident and ensuring the safety of the wind turbine operation.

[0008] However, the above technical solution can detect bolt fracture, but still has some limitations: the scheme relies on rigid optical fiber to build a loop, which has poor bending fatigue resistance and is difficult to adapt to the cabin vibration environment; and the scheme does not design an anti-interference mechanism, which is easily interfered by blade static electricity and variable frequency noise to cause false triggering. SUMMARY

[0009] The purpose of the present application is to solve the above-mentioned problems existing in the prior art, and to provide a wind turbine bolt fracture detection method, device and system.

[0010] To solve the above technical problems, the technical solution adopted by the present application is: a wind turbine bolt fracture detection method:

[0011] The anti-electromagnetic interference signal line is used to build a signal loop, and the bolt to be detected in the wind turbine cabin and the anti-electromagnetic interference signal line are physically connected together, and the signal of the signal loop is detected to determine whether there is a bolt fracture. When the anti-electromagnetic interference signal line is disconnected due to bolt fracture, the signal changes accordingly, indicating that there is a bolt fracture.

[0012] The environmental noise signal is collected in real time by a high-speed ADC, and the frequency spectrum is analyzed by a window function weighting and FFT module to dynamically identify the harmonic concentrated frequency band of the motor. When a specific motor characteristic frequency is detected, automatic spectrum avoidance is implemented to exclude the interference of wind turbine blade static electricity and variable frequency motor wideband noise on the detection result.

[0013] The phase of the output signal is kept synchronous with the phase of the input reference signal by a phase-locked loop, and a Kalman frequency predictor is built in the phase-locked loop to store the last 32 frequency points, construct a state prediction vector, eliminate noise by Kalman filtering, and quickly lock the phase-locked loop.

[0014] As a further optimization of the wind turbine bolt fracture detection method of the present application, the specific method of automatic spectrum avoidance is:

[0015] S1, add a Hanning window to the collected signal, and the specific formula is:

[0016]

[0017] Where 0≤n≤N-1;

[0018] The fast algorithm for calculating the discrete Fourier transform of the signal is:

[0019]

[0020] The sampling point is 1024;

[0021] S2, define mu as background noise average energy, sigma background noise standard deviation, detect energy peak value at integer multiple frequency point f0 of fundamental frequency f0, k=1, 2, 3,..., define adaptive threshold as Threshold=mu+3sigma, if three consecutive harmonic peak values are greater than Threshold, it is determined that it is a motor interference frequency band;

[0022] S3, implement a spectrum avoidance strategy, and the frequency hopping is as follows: f new =f current +Δf(Δf>interference bandwidth), the center frequency of the band-pass filter is dynamically adjusted to f new .

[0023] As a further optimization of the bolt fracture detection method of the wind turbine: the Kalman prediction phase-locked loop is specifically: a Kalman filter space soft state model is established, Kalman gain K k is calculated by using Kalman filter recursion, and the following formula is used to calculate the voltage-controlled oscillator (VCO) of the phase-locked loop: V ctrl (k)=K p ·θ e (k)+K i ∑θ e (k), where theta e (k) is the phase error output by the phase detector.

[0024] As a further optimization of the bolt fracture detection method of the wind turbine: the phase detector output is monitored in real time, and when a phase mutation caused by an electrostatic pulse is detected, a compensation current is automatically injected to offset the disturbance and maintain the continuity of the phase-locked state, and the specific process is as follows:

[0025] The mutation is detected by using a differential, when Delta theta=|theta e (t)-theta e (t-1)|>30 degrees, the compensation current is calculated; I comp =K c ·sgn(Delta theta)·e -α∣Δθ∣ ;

[0026] Wherein, alpha is the attenuation coefficient, alpha is 0.05; K c is the compensation gain;

[0027] The modified VCO input is: V ctrl′ (t)=V ctrl (t)+beta*I comp , wherein beta is the current-voltage conversion coefficient.

[0028] The application also provides a wind turbine bolt fracture detection device, comprising a cloud server, a station terminal, an AP gateway device, a plurality of detection hosts and a plurality of detection switches.

[0029] The cloud server comprises a data center module, an intelligent analysis and decision module and a device management and coordination module;

[0030] The station terminal comprises a man-machine interaction module and a communication module;

[0031] The AP gateway device comprises a wireless WIFI module, a 4G module, a LoRa module and an RS-485 interface module;

[0032] The detection host comprises a lora communication module, an adc conversion module, a cpu module, a cache module, a clock synchronization module and a power module;

[0033] The detection switch comprises a shell, a detection signal line and elastic sheets, the shell is a cylindrical structure, a plurality of elastic sheets are arranged in the shell, one end of the elastic sheet is fixedly connected with the inner wall of the shell, the other end of the elastic sheet is a free end, a bolt clamping cavity is formed between the plurality of elastic sheets, the detection signal line has a ring sleeve part and two wire terminals, the ring sleeve part is embedded on the shell, and the two wire terminals are used for connecting adjacent detection switches or a detection host.

[0034] As a further optimization of the wind turbine bolt fracture detection device, the end face of the elastic sheet facing the bolt clamping cavity is vertically provided with a locking fin, the locking fin is perpendicular to the axial direction of the shell, and the outer end of the locking fin is in a sawtooth structure.

[0035] As a further optimization of the wind turbine bolt fracture detection device, the material of the shell is pa66 plastic or PC plastic.

[0036] As a further optimization of the wind turbine bolt fracture detection device, the material of the elastic sheet is spring steel, and the thickness of the elastic sheet is 1mm.

[0037] The application also provides a wind turbine bolt fracture detection system, comprising a data application layer, a data transmission layer, a data acquisition layer and a data perception layer;

[0038] The data application layer comprises a cloud server and a station terminal, the station terminal is responsible for providing an entrance for users to access real-time monitoring data, the user inputs an account and a password to log in, and can realize remote monitoring of the real-time state of the bolts in the wind turbine cabin through a man-machine interaction display interface;

[0039] The data transmission layer is responsible for transmitting various parameter data collected by the data acquisition layer to the data application layer through wireless signals;

[0040] The data collection layer comprises a plurality of data collection devices, and the data collection device comprises a bolt fracture detection module.

[0041] The data sensing layer comprises a plurality of groups of detection units corresponding to the data collection devices, each group of detection units comprises a plurality of detection units, and the detection units in the same group can be connected in series to form a signal loop.

[0042] The application has the following beneficial effects: the application has a second-level fracture response capability, supports all-weather online monitoring of key bolts, and can guarantee safe operation of a wind turbine generator. BRIEF DESCRIPTION OF DRAWINGS

[0043] Figure 1 It is a logic block diagram of an automatic spectrum avoidance strategy in the detection method.

[0044] Figure 2 It is a logic block diagram of a Kalman prediction type phase-locked loop in the detection method.

[0045] Figure 3 It is a structural schematic diagram of the detection system.

[0046] Figure 4 It is a structural schematic diagram of a detection switch in the detection device.

[0047] Figure 5 It is a structural schematic diagram of the installation state of the detection switch.

[0048] Markings in the figure:

[0049] 1, shell;

[0050] 2, detection signal line;

[0051] 201, ring sleeve part;

[0052] 202, terminal;

[0053] 3, elastic sheet;

[0054] 4, locking fin. DETAILED DESCRIPTION

[0055] In order to better understand the application, the content of the application will be further illustrated below in combination with examples, but the content of the application is not limited to the following examples.

[0056] <Wind turbine bolt fracture detection method>

[0057] The signal loop is constructed by using the anti-electromagnetic interference signal line, the bolts to be detected in the wind turbine nacelle and the anti-electromagnetic interference signal line are physically connected together, and whether the bolts are broken is judged by detecting the signal of the signal loop. When the anti-electromagnetic interference signal line is disconnected due to the breakage of the bolts, the signal changes accordingly, indicating that the bolts are broken.

[0058] The detection switches are installed on each bolt, and the detection switches are connected in series through the anti-electromagnetic interference signal line and finally connected to the detection host. The anti-electromagnetic interference signal line connects the detection switches into a continuous signal loop. The detection host sends a specific detection signal to the signal loop and monitors the return of the signal to determine the state of the bolts. Under normal circumstances, the signal loop is complete, the detection signal can be smoothly transmitted in the loop, and the detection host can receive stable signal feedback. However, when a bolt breaks, the detection switch installed on the bolt will be pulled due to the breakage of the bolt, causing the anti-electromagnetic interference signal line connected thereto to be disconnected. The disconnection of the anti-electromagnetic interference signal line will directly cause the signal loop to be interrupted, and the detection host cannot receive the expected signal feedback after sending the detection signal, thereby determining that the signal loop has abnormally changed.

[0059] The detection host is equipped with a high-precision signal detection circuit, which can monitor the state of the signal loop in real time. Once the signal loop is interrupted, the detection host will immediately trigger an alarm mechanism. The alarm information will be uploaded to the cloud server through the AP gateway device, and the intelligent analysis and decision module of the cloud server will further analyze the alarm information to confirm the type and severity of the alarm. Then, the cloud server will display the bolt breakage alarm information and the specific bolt position information to the operation and maintenance personnel through the human-computer interaction module of the site terminal. The operation and maintenance personnel can quickly locate the broken bolt according to these information and take appropriate maintenance measures, such as replacing the bolt or checking the connection of the related parts.

[0060] During the operation of the wind turbine nacelle bolt state detection device, the detection host needs to monitor the signal loop in real time to determine whether the bolts are broken. However, the operating environment of the wind turbine is complex, and there are many interference sources, among which the wind turbine blade static electricity interference and the variable frequency motor wide frequency noise are two common interference factors. These interferences may affect the signal detection results of the detection host, leading to misjudgment of the on-off detection.

[0061] During high-speed rotation, the fan blades will generate static electricity through friction with the air. This static electricity accumulates on the surface of the blades, forming static electric charges. When the static electricity accumulates to a certain extent, it may discharge through the anti-electromagnetic interference signal lines or other metal components inside the wind turbine nacelle. Since the signal loop of the detection host is connected through the anti-electromagnetic interference signal lines, these anti-electromagnetic interference signal lines may become one of the paths for static discharge. Static discharge generates instantaneous high-voltage pulses, which propagate along the anti-electromagnetic interference signal lines and enter the signal detection circuit of the detection host, thereby interfering with signal detection. When the detection host is performing signal detection, it usually sends a low-voltage detection signal and monitors the on-off state of the signal loop. If the static interference generated by the fan blades enters the signal loop, it may cause the detection signal to be pulled up or pulled down instantaneously. For example, when the high-voltage pulse generated by static discharge is superimposed on the detection signal, the detection host may misjudge the state of the signal loop. If the detection signal is pulled up, the detection host may mistakenly think that the signal loop is on, even though the bolt has actually broken, causing the anti-electromagnetic interference signal line to be disconnected. Conversely, if the detection signal is pulled down, the detection host may mistakenly think that the signal loop is off, even though the bolt has not actually broken. This misjudgment will cause the maintenance personnel to receive false alarm information, thereby affecting the normal maintenance and operation of the equipment.

[0062] The variable frequency motor in the wind turbine generator set is an indispensable component during operation, which controls the speed and power of the motor through the frequency converter. The working principle of the frequency converter is to convert direct current into alternating current and adjust the voltage and frequency through high-frequency switching elements (such as IGBT). This high-frequency switching operation generates a large amount of electromagnetic noise, which has a wide frequency range and is usually referred to as broadband noise. Broadband noise can propagate to other equipment and anti-electromagnetic interference signal lines in the wind turbine nacelle through electromagnetic induction, conduction or radiation, etc.

[0063] The anti-electromagnetic interference signal lines in the signal loop of the detection host may be disturbed by the broadband noise of the variable frequency motor. When the broadband noise is coupled into the signal loop, a series of high-frequency noise components will be superimposed on the detection signal. These noise components will interfere with the detection host's judgment of the signal on-off state. For example, high-frequency noise may cause changes in the amplitude and frequency of the detection signal, causing the detection host to be unable to accurately identify the true state of the signal loop. If the noise amplitude is large, the detection host may misjudge the signal loop as being off, even though the signal loop is actually on. This misjudgment will cause the detection host to falsely issue an alarm for bolt breakage, even though the bolt has not actually broken. Conversely, if the noise causes the amplitude of the detection signal to decrease, the detection host may misjudge the signal loop as being on, thereby missing the bolt breakage fault.

[0064] In order to solve the problem of fan blade static interference and variable frequency motor wideband noise interference, a program with the following data processing method is built in the detection host:

[0065] The environmental noise signal is collected in real time by high-speed ADC, and the frequency spectrum is analyzed by window function weighting and FFT module, and the motor harmonic concentrated frequency band is dynamically identified. When the specific motor characteristic frequency is detected, automatic spectrum avoidance is implemented to exclude the interference of fan blade static interference and variable frequency motor wideband noise on the detection result.

[0066] As shown in Figure 1 , the specific method of automatic spectrum avoidance is:

[0067] S1, Hann window is added to the collected signal, and the specific formula is:

[0068]

[0069] Wherein, 0≤n≤N-1.

[0070] The fast algorithm for calculating the discrete Fourier transform of the signal is:

[0071]

[0072] The sampling point is 1024.

[0073] S2, define μ as the average energy of background noise, and σ as the standard deviation of background noise. The energy peak value is detected at the integer multiple frequency point f0·k, k=1, 2, 3,... of the fundamental frequency f0, and the adaptive threshold is defined as Threshold=μ+3σ. If the peak value of the continuous three harmonics is greater than Threshold, it is determined that it is the motor interference frequency band.

[0074] S3, implement the spectrum avoidance strategy, and the specific frequency jump is f new =f current +Δf(Δf>interference bandwidth), and the center frequency of the band-pass filter is dynamically adjusted to f new .

[0075] After calculating the interference frequency band, the circuit board ADC module adjusts the frequency according to the embedded software, and automatically jumps to the effective frequency band excluding the interference frequency band.

[0076] The phase of the output signal is kept synchronous with the phase of the input reference signal by phase-locked loop, and Kalman frequency predictor is built in the phase-locked loop to store the last 32 frequency points, construct the state prediction vector, and quickly lock the phase-locked loop by Kalman filtering to reduce the phase-locked time.

[0077] As shown in Figure 2The specific method for removing noise by Kalman filtering is shown as follows: a Kalman filtering space soft state model is established, and a Kalman gain K is recursively solved by Kalman filtering k The phase-locked loop control (VCO) of the voltage is calculated by the following formula: ctrl (k) = K p · θ e (k) + K i ∑ θ e (k), where θ e (k) is the phase error output by the phase detector.

[0078] The construction process of the Kalman filtering space soft state model is as follows:

[0079] S1, the continuous space domain is divided into discrete grid points, and each grid point represents a spatial position.

[0080] S2, the grid is divided by using finite difference FDM.

[0081] S3, the state equation is established:

[0082] Equation 1: x k = F k x k-1 + B k u k + w k .

[0083] x k is the state vector at the kth moment.

[0084] F k is the state transition matrix, which describes the evolution of the state from the (k-1)th moment to the kth moment.

[0085] B k is the control input matrix, which describes the influence of the control input uk on the state.

[0086] w k is the process noise.

[0087] Equation 2: x k，i = ∑ j∈N(i) a ij x k-1，j + w k，i .

[0088] x k，i is the state of the ith grid point at the kth moment.

[0089] N(i) is the set of neighboring grid points of the ith grid point.

[0090] a ija is the spatial auto-regressive coefficient, describing the influence of the jth grid point on the ith grid point.

[0091] w k，i is the phase error of the ith grid point at the kth time.

[0092] S4, establish the observation model:

[0093] y k = H k x k + v k .

[0094] y k is the observation vector at the kth time.

[0095] H k is the observation matrix, describing how the observation data is obtained from the state vector.

[0096] v k is the observation noise, describing the random error in the observation process.

[0097] S5, establish the spatial state model:

[0098]

[0099] x k，i is the state of the ith grid point at the kth time.

[0100] N(i) is the set of neighboring grid points of the ith grid point.

[0101] a ij is the spatial auto-regressive coefficient, describing the influence of the jth grid point on the ith grid point.

[0102] The Kalman filter algorithm estimates the system state recursively, including prediction and update steps. After obtaining the phase error using the Kalman filter algorithm, the spatial state model can be optimized using a regression optimization method to improve the accuracy of the model.

[0103] Real-time monitoring of the phase detector output, when detecting the phase mutation caused by the electrostatic pulse, automatically injecting compensation current to offset the disturbance, maintaining the continuity of the phase-locked state, specifically:

[0104] Using difference to realize mutation detection, when Δθ = |θ e (t) - θ e (t-1)|>30°, compensation current calculation is adopted; I comp = K c ·sgn(Δθ)·e -α∣Δθ∣ .

[0105] Wherein, a is attenuation coefficient, a takes 0.05;K c Gain is compensated.

[0106] The modified VCO input is: V ctrl′ (t) = V ctrl (t) + β·I comp Wherein, β is current-voltage conversion coefficient.

[0107] <Wind turbine bolt fracture detection system>

[0108] As Figure 3 shown, the detection system is composed of four core parts of data application layer, data transmission layer, data acquisition layer and data perception layer, which cooperate with each other to realize comprehensive monitoring and management of the bolt state in the wind turbine cabin.

[0109] The data application layer includes cloud server and site terminal, and the site terminal is responsible for providing an access entrance for users to access real-time monitoring data. The user inputs account and password to log in, and can realize remote monitoring of the real-time state of the bolt in the wind turbine cabin through the man-machine interaction display interface.

[0110] The data application layer is the top layer of the whole detection system, which is the interface for user interaction with the system, and is also the core area of data processing and storage. It mainly includes cloud server and site terminal. The site terminal is the front-end device for user operation, which provides a convenient access entrance for users to access real-time monitoring data. The user only needs to input the pre-set account and password, and after system verification, the user can successfully log in. After logging in, the user will monitor the real-time state of the bolt in the wind turbine cabin through the man-machine interaction display interface.

[0111] The man-machine interaction display interface can present various monitoring data of the bolt, including key information such as whether the bolt is broken. The user can quickly understand the health status of each bolt through various charts, data tables and real-time images in the interface.

[0112] The site terminal also has data storage function, which can save the user's historical operation records and monitoring data locally, so that the user can check and analyze at any time. The cloud server is the "brain" of the whole data application layer, which has strong data processing and storage capacity. After receiving various monitoring data uploaded from the data transmission layer, the cloud server will analyze and process it. The data transmission layer is responsible for transmitting various parameter data collected by the data acquisition layer to the data application layer through wireless signal. The data transmission layer is the bridge connecting the data acquisition layer and the data application layer, and its main responsibility is to ensure that the collected various parameter data can be stably and efficiently transmitted to the data application layer.

[0113] In the operating environment of wind power generation equipment, due to the fact that the nacelle is usually located at a high place and there may be some electromagnetic interference around, the reliability and stability of data transmission are crucial. This layer adopts an industrial Internet of Things (IIoT) architecture, integrating multiple transmission protocols through a redundantly designed wireless communication gateway. For high-priority alarm signals (such as fracture events), low-latency 5G URLLC or dedicated LoRa spread spectrum links are used to ensure that end-to-end transmission is completed within 200 ms; for massive displacement monitoring data, NB-IoT or 4G LTE Cat-M1 wide-area low-power networks are enabled for batch compression transmission.

[0114] During data transmission, data encryption and verification mechanisms can also be added to ensure the integrity and security of data during transmission. Data encryption technology can effectively prevent data from being stolen or tampered with, protecting the privacy of monitoring data; while the data verification mechanism can detect errors or losses in data transmission in real time and make timely corrections or retransmissions, thereby ensuring the accuracy and reliability of the data. In addition, the data transmission layer also has certain data caching functions. When the wireless signal is disturbed and the transmission is interrupted, the data collected by the data acquisition layer can be temporarily stored in the cache, and then the transmission will continue after the signal is restored, thereby avoiding the loss of data.

[0115] The data acquisition layer includes a plurality of data acquisition devices, and the data acquisition device includes a bolt fracture detection module. The bolt fracture detection module determines whether a bolt is fractured by detecting a signal of a signal loop.

[0116] The data acquisition layer is the core component of the entire detection system, which is directly responsible for collecting various state parameters of the bolts in the wind turbine nacelle.

[0117] The bolt fracture detection module is a key device for monitoring whether a bolt has fractured. It determines the state of the bolt by detecting changes in the signal of the signal loop. Specifically, when the bolt is in a normal connection state, the signal loop is complete and the signal can be transmitted normally; once the bolt is fractured, the signal loop is cut off and the signal transmission is interrupted. The bolt fracture detection module can monitor the state of the signal loop in real time and send the detected signal change data to the data transmission layer.

[0118] The data perception layer includes a plurality of groups of detection units consistent with the number of data acquisition devices. Each group of detection units includes a plurality of detection units, and the plurality of detection units in the same group can be connected in series to form a signal loop.

[0119] The data sensing layer is the bottom foundation part of the detection system, which is closely connected with the data acquisition layer, and provides necessary physical support and signal transmission channel for the data acquisition layer. The data sensing layer includes a plurality of groups of detection units consistent with the data acquisition equipment, and each group of detection units is composed of a plurality of detection units with different functions. A plurality of detection units in the same group are connected in series through a specific connection mode to form a signal loop. The detection unit adopts a solid and durable shell material, which can withstand high wind speed, low temperature, high humidity and other extreme conditions, and ensure stable and reliable performance in long-term operation.

[0120] The wind turbine nacelle bolt state detection system realizes the all-round real-time monitoring of the bolt state in the wind turbine nacelle through the cooperative work of the data application layer, the data transmission layer, the data acquisition layer and the data sensing layer, and can timely find the fracture problem of the bolt. In addition, the intelligent design and advanced technology application of the system make it have the characteristics of high efficiency, reliability and easy use, which can meet the high requirements of modern wind power equipment on operation and maintenance management, and provide strong technical support for the safe and stable development of the wind power industry.

[0121] <Wind turbine bolt fracture detection equipment>

[0122] The detection equipment includes a cloud server, a station terminal, an AP gateway device, a plurality of detection hosts and a plurality of detection switches.

[0123] The cloud server includes a data center module, an intelligent analysis and decision module, and a device management and coordination module.

[0124] The data center module is responsible for storing a large amount of monitoring data uploaded from the detection host, which includes the fracture information of the bolt. Through long-term accumulation and management of these data, the data center module provides rich resources for subsequent data mining and equipment health management. The intelligent analysis and decision module uses algorithms and models to deeply analyze the monitoring data, and judges whether the state of the bolt is normal in real time. Once potential fault risk is found, the module will immediately generate an early warning information, and provide corresponding processing suggestions for the operation and maintenance personnel according to the preset decision rule. The device management and coordination module is responsible for the unified management and coordination of each device in the whole detection system, to ensure that the components can work efficiently and stably.

[0125] The station terminal is the interface for users to interact with the detection system, which includes a human-computer interaction module and a communication module. The human-computer interaction module has an intuitive and easy-to-use operation interface, through which users can view the monitoring data of the bolts in the wind turbine nacelle in real time, including the real-time state of the bolts, historical data trends, and early warning information, etc. In addition, users can also set parameters and control devices through this module. The communication module is responsible for establishing a stable communication connection between the station terminal, the cloud server, and the detection host, ensuring that data can be transmitted in real time and accurately.

[0126] The station terminal also includes an identity authentication and login module and a permission management module. The identity authentication and login module verifies the user's identity information to ensure that only authorized personnel can access the system. When logging in, users need to enter the pre-registered account and password, and the system will strictly compare these information. If the entered account and password are consistent with the authorized information stored in the system, the user will be allowed to enter the system; if the information does not match, the system will reject the login request and record this unauthorized login attempt for subsequent security audit. To further enhance the security of the system, the identity authentication and login module can also support multi-factor authentication mechanisms. In addition to traditional account and password authentication, users can also choose to use mobile phone SMS verification code, fingerprint recognition, facial recognition, or security tokens for auxiliary authentication. These multi-factor authentication methods can effectively prevent unauthorized access caused by account password leakage, ensuring the security of the system.

[0127] The permission management module is a core component of the system security architecture, which is responsible for assigning different operation permissions according to the user's identity and role. In the wind turbine nacelle bolt state detection device, different users may have different responsibilities and operation needs. For example, ordinary maintenance personnel may only need to view the monitoring data of the bolts and receive early warning information, while system administrators need to have high-level permissions to configure, maintain, and manage the device. The permission management module assigns specific roles to each user and sets corresponding permissions according to the role, ensuring that users can only operate within their permission range.

[0128] The cooperation of the identity authentication and login module and the permission management module provides a strong guarantee for the safe operation of the wind turbine nacelle bolt state detection device. When a user attempts to log in to the system, the identity authentication and login module first verifies the user's identity. If the user passes the identity verification, the permission management module will load the corresponding operation interface and function module for the user according to the user's permission settings. All operations of the user in the system will be strictly monitored by the permission management module, and any operation beyond the permission range will be rejected by the system and recorded in the security log. This strict security management mechanism not only protects the data security of the system, but also ensures the orderly progress of the normal operation and maintenance work of the device.

[0129] Through the introduction of identity authentication and login module and permission management module, the field station terminal of the wind turbine nacelle bolt state detection equipment not only improves the security of the system, but also provides users with more flexible and personalized operation experience. Users can safely access various functions in the system according to their responsibilities and needs, while system administrators can effectively manage and monitor the use of the system to ensure the stable operation of the system and the security of the data.

[0130] The AP gateway device is a communication bridge connecting the detection host and the cloud server, which includes wireless WIFI module, 4G module, LoRa module and RS-485 interface module. These communication modules provide multiple communication methods for the detection system to adapt to different application scenarios and environmental conditions. The wireless WIFI module is suitable for short-distance high-speed data transmission, the 4G module can realize stable communication at a long distance, the LoRa module is suitable for distributed detection host communication due to its low power consumption and long distance transmission. The RS-485 interface module provides support for traditional wired communication to ensure the reliability of data transmission in poor wireless signal conditions.

[0131] The detection host is the core equipment for bolt state monitoring, which includes lora communication module, adc conversion module, cpu module, cache module, clock synchronization module and power module.

[0132] The detection switch is a key component installed on each bolt. These detection switches are connected in series to the detection host to form a complete signal loop. When a bolt in the wind turbine nacelle breaks, it will pull the detection signal line, causing the signal loop to be interrupted. The detection host can quickly detect signal abnormalities and determine that a bolt has broken by monitoring the status of the signal loop in real time. This bolt breakage detection method based on the signal loop is simple, reliable and fast, and can provide valuable processing time for maintenance personnel by sending an alarm as soon as the bolt breaks.

[0133] As shown in Figure 4 and 5 , the detection switch includes a shell 1, a detection signal line 2, and a plurality of elastic pieces 3. The shell 1 is a cylindrical structure, and the plurality of elastic pieces 3 are arranged inside the shell 1. One end of each elastic piece 3 is fixedly connected to the inner wall of the shell 1, and the other end is a free end. A bolt clamping cavity is formed between the plurality of elastic pieces 3. The detection signal line 2 has a ring sleeve part 201 and two wire terminals 202. The ring sleeve part 201 is embedded in the shell 1, and the two wire terminals 202 are used to connect adjacent detection switches or the detection host.

[0134] The detection signal line 2 is a uniquely designed signal line with a wire diameter <0.24 mm, and has the functions of flame retardation and electromagnetic interference shielding. The core of the signal line is a silver wire core, and the connector head 202 adopts the R11 plug-in interface standard, and the plug-in interface is disconnected under a plug-in torque >4N·m.

[0135] Compared with conventional signal lines, the following advantages are achieved:

[0136] 1. When bolt fracture occurs, the plug-in interface is disconnected instead of wire breakage;

[0137] 2. Electromagnetic interference can be reduced;

[0138] 3. The strength is within a certain upper and lower threshold, and decreases with the bolt fracture;

[0139] 4. After wire breakage, no leakage will occur due to the swing contact of the wire to other electronic devices or electrical equipment;

[0140] 5. Under normal cutting, swinging and friction, the sufficient strength of the insulation layer can prevent false alarms;

[0141] 6. Anti-vibration design, high-strength vibration condition, and clamping slot fastening.

[0142] The locking fin 4 is vertically arranged on the end surface of the elastic sheet 3 facing the bolt clamping cavity, and is perpendicular to the axial direction of the shell 1. The outer end of the locking fin 4 is in a sawtooth structure. The shell 1 is made of pa66 plastic or PC plastic, and the elastic sheet 3 is made of spring steel with a thickness of 1 mm.

[0143] When the bolt is pressed, a radial force of about 5 N and an axial force of about 50 N are required. The elastic sheet 3 and the locking fin 4 can realize the fastening connection between the detection switch and the bolt to be detected.

[0144] The operation process of the wind turbine bolt fracture detection device is as follows: when a bolt is fractured, the signal detection line of the detection switch is pulled off, causing the signal loop to be interrupted. The detection host can quickly detect the signal anomaly and determine that a bolt has been fractured by monitoring the state of the signal loop in real time. The detection host can immediately generate a fracture alarm signal and upload the alarm information to the cloud server. After receiving the fracture alarm, the cloud server will immediately notify the operation and maintenance personnel, reminding them to urgently handle the fractured bolt to prevent equipment damage and safety accidents caused by bolt fracture.

[0145] In terms of maintenance and management, the wind turbine bolt fracture detection equipment also has significant advantages. Through the device management and collaboration module of the cloud server, the operation and maintenance personnel can remotely manage and maintain each device in the detection system. They can view the running status of the device in real time through the human-computer interaction module of the site terminal, including the working temperature, power voltage, communication status and other information of the detection host. When the device fails, the operation and maintenance personnel can quickly locate the fault cause through remote diagnosis function and take corresponding maintenance measures. This remote management and maintenance method greatly reduces the operation and maintenance cost and work intensity, and improves the operation and maintenance efficiency.

[0146] The specific embodiments of the application are described above. It should be understood that the application is not limited to the specific implementation described above, and various modifications or changes can be made by those skilled in the art within the scope of the claims, which does not affect the essential content of the application.

Claims

1. A method for detecting bolt fracture in wind turbine units, characterized in that: A signal loop is constructed using an anti-electromagnetic interference signal line. The bolts to be tested inside the wind turbine nacelle are physically connected to the anti-electromagnetic interference signal line. The signal from the detection signal loop is used to determine whether a bolt is broken. When a bolt is broken, causing the anti-electromagnetic interference signal line to disconnect, the signal changes accordingly, indicating that a bolt is broken. The system acquires environmental noise signals in real time using a high-speed ADC, performs spectrum analysis using window function weighting and FFT module, dynamically identifies the concentrated frequency bands of motor harmonics, and implements automatic spectrum avoidance when a specific motor characteristic frequency is detected to eliminate the interference of electrostatic interference from fan blades and broadband noise from variable frequency motors on the detection results. The phase-locked loop (PLL) keeps the phase of the output signal synchronized with the phase of the input reference signal. A Kalman frequency predictor is built into the PLL to store the most recent 32 frequency points, construct a state prediction vector, and eliminate noise through Kalman filtering to quickly lock the PLL.

2. The method for detecting bolt fracture in a wind turbine as described in claim 1, characterized in that: The specific methods for automatic spectrum avoidance are as follows: S1. Add a Hanning window to the acquired signal. The specific formula is as follows: Where 0 ≤ n ≤ N-1; Fast algorithms for calculating the Discrete Fourier Transform of a signal: The sampling point is 1024; S2. Define μ as the average energy of background noise and σ as the standard deviation of background noise. Detect energy peaks at integer multiples of the fundamental frequency f0, f0·k, k=1,2,3,... Define an adaptive threshold as Threshold=μ+3σ. If three consecutive harmonic peaks > Threshold, it is determined to be a motor interference frequency band. S3. Implement a spectrum avoidance strategy, specifically the frequency jump to f. new =f current +Δf(,Δf(>interference bandwidth,dynamically adjust the center frequency of the bandpass filter to f new .

3. The method for detecting bolt fracture in a wind turbine as described in claim 1, characterized in that: The specific method for noise elimination using Kalman filtering is as follows: Establish a spatial soft-state model of the Kalman filter, and recursively calculate the Kalman gain K using Kalman filtering. k And calculate the voltage phase-locked loop control (VCO) using the following formula: V ctrl (k)=K p ·θ e (k)+K i ∑θ e (k), θ e (k) represents the phase error output by the phase detector; The phase detector output is monitored in real time. When a phase change caused by an electrostatic pulse is detected, a compensation current is automatically injected to cancel the disturbance and maintain the continuity of the phase-locked state. Specifically: Mutation detection is achieved using difference, when Δθ=|θ e (t)-θ e When (t-1)|>30°, the compensation current is used for calculation; I comp =K c ·sgn(Δθ)·e -α∣Δθ∣ ; Where α is the attenuation coefficient, and α is taken as 0.05; K c To compensate for the gain; The corrected VCO input is: V ctrl′ (t)=V ctrl (t)+β·I comp , where β is the current-to-voltage conversion coefficient.

4. A device for detecting bolt fracture in wind turbine units, characterized in that: Includes cloud servers, site terminals, AP gateway devices, several detection hosts, and several detection switches; The cloud server includes a data center module, an intelligent analysis and decision-making module, and a device management and collaboration module; The station terminal includes a human-computer interaction module and a communication module; The AP gateway device includes a wireless WIFI module, a 4G module, a LoRa module, and an RS-485 interface module; The detection host includes a LoRa communication module, an ADC conversion module, a CPU module, a cache module, a clock synchronization module, and a power supply module. The detection switch includes a housing, a detection signal line, and springs. The housing is a cylindrical structure, and several springs are arranged inside the housing. One end of the spring is fixedly connected to the inner wall of the housing, and the other end of the spring is a free end. A bolt clamping cavity is formed between the several springs. The detection signal line has a loop part and two terminals. The loop part is embedded in the housing, and the two terminals are used to connect to adjacent detection switches or detection host.

5. The wind turbine bolt fracture detection device as described in claim 4, characterized in that: The end face of the spring sheet facing the bolt clamping cavity is provided with a locking wing, which is perpendicular to the axis of the housing and has a serrated outer edge.

6. The wind turbine bolt fracture detection device as described in claim 4, characterized in that: The shell is made of PA66 plastic or PC plastic.

7. The wind turbine bolt fracture detection device as described in claim 4, characterized in that: The spring is made of spring steel and has a thickness of 1mm.

8. A wind turbine bolt fracture detection system, characterized in that: It includes the data application layer, data transmission layer, data acquisition layer, and data perception layer; The data application layer includes cloud servers and field terminals. The field terminals are responsible for providing users with an entry point for real-time monitoring data access. Users can log in by entering their account and password, and then remotely monitor the real-time status of bolts inside the wind turbine nacelle through a human-computer interaction display interface. The data transmission layer is responsible for transmitting various parameter data collected by the data acquisition layer to the data application layer via wireless signals; The data acquisition layer includes several data acquisition devices, including a bolt breakage detection module. The bolt breakage detection module determines whether a bolt is broken by detecting the signal from the signal circuit. The data sensing layer includes several groups of detection units, the same number as the data acquisition equipment. Each group of detection units includes several detection units, and the detection units in the same group can be connected in series to form a signal loop.

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