Ultrasonic double-wave-based bolt axial stress measurement method and device, and electronic equipment

Abstract

The disclosure provides a bolt axial stress measurement method and device based on ultrasonic double waves, electronic equipment and storage medium, the method comprising: obtaining a wind turbine bolt transmission signal wave and a wind turbine bolt reception signal wave; uploading the wind turbine bolt transmission signal wave and the wind turbine bolt reception signal wave to a wind turbine bolt signal analysis module for denoising and filtering processing to obtain a standard bolt transmission signal wave and a standard bolt reception signal wave; obtaining a first bolt axial stress analysis model; inputting ultrasonic measurement sound velocity information, ultrasonic longitudinal wave measurement sound time, ultrasonic transverse wave measurement sound time, bolt basic information, ultrasonic longitudinal wave acoustic elasticity coefficient and ultrasonic transverse wave acoustic elasticity coefficient into the first bolt axial stress analysis model for processing to obtain a bolt axial stress measurement result. Through the disclosure, the interference existing in the ultrasonic monitoring process can be effectively reduced, thereby the measurement error of the bolt axial stress can be effectively reduced, and the state of the bolt can be more accurately judged.

Description

Technical Field

[0001] This disclosure relates to the field of wind power generation technology, and in particular to a method, apparatus, electronic device and storage medium for measuring bolt axial stress based on ultrasonic dual waves. Background Technology

[0002] Currently, wind energy is mainly converted into mechanical energy through wind turbine units, and then the mechanical energy is converted into electrical energy. To ensure the normal operation of wind turbine units, it is necessary to diagnose and monitor the condition of the bolts.

[0003] In related technologies, the main approach is to establish a field monitoring and management system for bolts, and to diagnose the condition of bolts through ultrasonic monitoring combined with manual inspection.

[0004] In this method, due to interference during the monitoring process and limitations of the bolt material, the ultrasonic monitoring of the bolt's axial stress has a large error, which in turn makes it impossible to accurately monitor the bolt's failure state. Because of interference during the ultrasonic monitoring process, the measured bolt axial stress has a large error, making it impossible to accurately determine the bolt's condition. Summary of the Invention

[0005] This disclosure aims to at least partially address one of the technical problems in the related art.

[0006] Therefore, the purpose of this disclosure is to propose a method, device, electronic equipment, storage medium, and computer program product for measuring bolt axial stress based on ultrasonic dual-wavelength, which can effectively reduce interference in the ultrasonic monitoring process, thereby effectively reducing the measurement error of bolt axial stress and achieving a more accurate judgment of bolt condition.

[0007] The bolt axial stress measurement method based on ultrasonic dual-wavelengths proposed in the first aspect of this disclosure includes: acquiring a wind turbine bolt transmitted signal wave and a wind turbine bolt received signal wave; uploading the wind turbine bolt transmitted signal wave and the wind turbine bolt received signal wave to a wind turbine bolt signal analysis module for noise reduction and filtering to obtain a standard bolt transmitted signal wave and a standard bolt received signal wave; performing waveform analysis on the standard bolt transmitted signal wave and the standard bolt received signal wave to obtain the ultrasonic longitudinal wave measurement time and the ultrasonic transverse wave measurement time; determining the ultrasonic longitudinal wave acoustic elastic coefficient and the ultrasonic transverse wave acoustic elastic coefficient based on the basic bolt information; acquiring a first bolt axial stress analysis model, and inputting the ultrasonic measurement sound velocity information, the ultrasonic longitudinal wave measurement time, the ultrasonic transverse wave measurement time, the basic bolt information, the ultrasonic longitudinal wave acoustic elastic coefficient, and the ultrasonic transverse wave acoustic elastic coefficient into the first bolt axial stress analysis model for processing to obtain the bolt axial stress measurement result.

[0008] The bolt axial stress measurement method based on ultrasonic dual-wavelength measurement proposed in the first aspect of this disclosure acquires the transmitted and received signal waves of a wind turbine bolt. These signals are then uploaded to a wind turbine bolt signal analysis module for noise reduction and filtering to obtain standard bolt transmitted and received signal waves. Waveform analysis is performed on these standard bolt transmitted and received signal waves to obtain the ultrasonic longitudinal wave measurement time and ultrasonic transverse wave measurement time. Based on the bolt's basic information, the ultrasonic longitudinal wave acoustic elastic coefficient and ultrasonic transverse wave acoustic elastic coefficient are determined, and a first bolt axial stress analysis model is obtained. The ultrasonic measurement velocity information, ultrasonic longitudinal wave measurement time, ultrasonic transverse wave measurement time, bolt basic information, and ultrasonic longitudinal wave and transverse wave acoustic elastic coefficients are input into the first bolt axial stress analysis model for processing to obtain the bolt axial stress measurement result. This method effectively reduces interference during ultrasonic monitoring, thereby reducing the measurement error of bolt axial stress and achieving a more accurate judgment of bolt condition.

[0009] The second aspect of this disclosure discloses a bolt axial stress measurement device based on ultrasonic dual-wavelengths, comprising: a first acquisition module for acquiring a wind turbine bolt transmitted signal wave and a wind turbine bolt received signal wave; a first processing module for uploading the wind turbine bolt transmitted signal wave and the wind turbine bolt received signal wave to a wind turbine bolt signal analysis module for noise reduction and filtering to obtain a standard bolt transmitted signal wave and a standard bolt received signal wave; a second processing module for performing waveform analysis on the standard bolt transmitted signal wave and the standard bolt received signal wave to obtain ultrasonic longitudinal wave measurement time and ultrasonic transverse wave measurement time; a first determination module for determining the ultrasonic longitudinal wave acoustic elastic coefficient and the ultrasonic transverse wave acoustic elastic coefficient based on the basic bolt information; and a third processing module for acquiring a first bolt axial stress analysis model, inputting ultrasonic measurement sound velocity information, ultrasonic longitudinal wave measurement time, ultrasonic transverse wave measurement time, bolt basic information, ultrasonic longitudinal wave acoustic elastic coefficient, and ultrasonic transverse wave acoustic elastic coefficient into the first bolt axial stress analysis model for processing to obtain the bolt axial stress measurement result.

[0010] The bolt axial stress measurement device based on ultrasonic dual-wavelength measurement proposed in the second aspect of this disclosure acquires the transmitted and received signal waves of a wind turbine bolt. These signals are then uploaded to a wind turbine bolt signal analysis module for noise reduction and filtering to obtain standard bolt transmitted and received signal waves. Waveform analysis is performed on these standard bolt transmitted and received signal waves to obtain the ultrasonic longitudinal wave measurement time and ultrasonic transverse wave measurement time. Based on the bolt's basic information, the ultrasonic longitudinal wave acoustic elastic coefficient and ultrasonic transverse wave acoustic elastic coefficient are determined, and a first bolt axial stress analysis model is obtained. The ultrasonic measurement velocity information, ultrasonic longitudinal wave measurement time, ultrasonic transverse wave measurement time, bolt basic information, and ultrasonic longitudinal wave acoustic elastic coefficient and ultrasonic transverse wave acoustic elastic coefficient are input into the first bolt axial stress analysis model for processing to obtain the bolt axial stress measurement result. This effectively reduces interference during ultrasonic monitoring, thereby reducing the measurement error of bolt axial stress and achieving a more accurate judgment of the bolt's condition.

[0011] The electronic device proposed in the third aspect of this disclosure includes: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the bolt axial stress measurement method based on ultrasonic dual waves proposed in the first aspect of this disclosure.

[0012] The fourth aspect of this disclosure provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the bolt axial stress measurement method based on ultrasonic dual waves as proposed in the first aspect of this disclosure.

[0013] The fifth aspect of this disclosure provides a computer program product that, when executed by a processor, performs a bolt axial stress measurement method based on ultrasonic dual waves as described in the first aspect of this disclosure.

[0014] Additional aspects and advantages of this disclosure will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this disclosure. Attached Figure Description

[0015] The above and / or additional aspects and advantages of this disclosure will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, in which:

[0016] Figure 1 This is a schematic flowchart of a bolt axial stress measurement method based on ultrasonic dual-wavelength according to an embodiment of this disclosure;

[0017] Figure 2This is a schematic flowchart of a bolt axial stress measurement method based on ultrasonic dual waves proposed in another embodiment of this disclosure;

[0018] Figure 3 This is a schematic flowchart of a bolt axial stress measurement method based on ultrasonic dual waves proposed in another embodiment of this disclosure;

[0019] Figure 4 This is a schematic diagram of the structure of a bolt axial stress measuring device based on ultrasonic dual waves according to an embodiment of this disclosure;

[0020] Figure 5 This is a schematic diagram of the structure of a bolt axial stress measuring device based on ultrasonic dual waves according to another embodiment of this disclosure;

[0021] Figure 6 A block diagram of an exemplary electronic device suitable for implementing embodiments of the present disclosure is shown. Detailed Implementation

[0022] Embodiments of this disclosure are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are used only to explain this disclosure, and should not be construed as limiting this disclosure. Rather, embodiments of this disclosure include all variations, modifications, and equivalents falling within the spirit and scope of the appended claims.

[0023] Figure 1 This is a schematic flowchart of a bolt axial stress measurement method based on ultrasonic dual waves proposed in an embodiment of this disclosure.

[0024] It should be noted that the main body executing the bolt axial stress measurement method based on ultrasonic dual waves in this embodiment is a bolt axial stress measurement device based on ultrasonic dual waves. This device can be implemented by software and / or hardware. The device can be configured in an electronic device, which may include, but is not limited to, a terminal, a server, etc.

[0025] like Figure 1 As shown, this method for measuring bolt axial stress based on ultrasonic dual-wavelengths includes:

[0026] S101: Acquire the signal wave transmitted by the wind turbine bolt and the signal wave received by the wind turbine bolt.

[0027] There is a corresponding relationship between the axial stress of the bolt and the longitudinal and transverse waves of the ultrasonic wave. Therefore, it is necessary to first obtain the transmitted signal wave and the received signal wave of the wind turbine bolt through an ultrasonic measuring device.

[0028] Among them, the signal wave sent by the wind turbine bolt refers to the signal wave sent from the ultrasonic measuring device to the wind turbine bolt.

[0029] Among them, the signal wave received by the wind turbine bolt refers to the signal wave fed back from the wind turbine bolt to the ultrasonic measuring device.

[0030] In this embodiment of the disclosure, when acquiring the transmitted signal wave and received signal wave of the wind turbine bolt, an ultrasonic measuring device can be used to acquire the transmitted signal wave and received signal wave of the wind turbine bolt. The ultrasonic measuring device can convert the ultrasonic signals sent to and received by the wind turbine bolt into other signals and acquire the transmitted and received waveforms converted into other signals.

[0031] Optionally, other signals can be electrical signals.

[0032] In this embodiment of the disclosure, by acquiring the signal waves transmitted and received by the wind turbine bolt, a foundation is laid for subsequent analysis and measurement of the bolt's axial stress by analyzing the waveforms, thereby further improving the accuracy of bolt axial force measurement.

[0033] S102: Upload the wind turbine bolt transmitted signal wave and the wind turbine bolt received signal wave to the wind turbine bolt signal analysis module for noise reduction and filtering to obtain the standard bolt transmitted signal wave and the standard bolt received signal wave.

[0034] In this embodiment of the invention, after acquiring the transmitted and received signal waves of the wind turbine bolts using the ultrasonic measuring device, the transmitted and received signal waves of the wind turbine bolts can be uploaded to the wind turbine bolt signal analysis module for noise reduction and filtering to obtain the transmitted and received signal waves of the standard bolts.

[0035] Specifically, after acquiring the transmitted and received signal waves of the wind turbine bolts, they can be uploaded to the corresponding wind turbine bolt signal analysis module via a wireless network.

[0036] Optionally, the wireless network can be: Wireless Wide Area Network (WWAN), Wireless Metropolitan Area Network (WMAN), Wireless Local Area Network (WLAN), Wireless Personal Area Network (WPAN), and Wireless Body Area Network (WBAN), etc., which can be selected according to actual needs.

[0037] The wind turbine bolt signal analysis module is used to analyze and process the signal waves transmitted and received by the wind turbine bolts. The wind turbine bolt signal analysis module can be used to perform noise reduction filtering and waveform analysis on the signal waves. After processing the signal waves, it can accurately obtain information related to the axial stress of the bolts.

[0038] The standard bolt transmitted signal wave refers to the transmitted signal wave obtained after filtering by the wind power bolt signal analysis module.

[0039] The standard bolt received signal wave refers to the received signal wave obtained after filtering by the wind power bolt signal analysis module.

[0040] In this embodiment of the disclosure, when the wind turbine bolt transmitted signal wave and the wind turbine bolt received signal wave are uploaded to the wind turbine bolt signal analysis module for noise reduction and filtering, the ultrasonic measurement is interfered with by factors such as the structure and inclusions of the wind turbine bolt. The wind turbine bolt signal analysis module can perform noise reduction and filtering on the wind turbine bolt transmitted signal wave and the wind turbine bolt received signal wave to remove the waveforms that are irrelevant to the measurement, and obtain the effective waveform after noise reduction and filtering. The effective waveform after noise reduction and filtering is used as the corresponding standard bolt transmitted signal wave and standard bolt received signal wave.

[0041] In this embodiment, by uploading the transmitted and received signal waves of the wind turbine bolts to the wind turbine bolt signal analysis module for noise reduction and filtering, standard bolt transmitted and received signal waves are obtained. This can effectively improve the accuracy of the measurement information, filter out irrelevant signal waves, and lay the groundwork for improving the accuracy of bolt axial stress measurement.

[0042] S103: Perform waveform analysis and processing on the standard bolt transmitted signal wave and the standard bolt received signal wave to obtain the ultrasonic longitudinal wave measurement acoustic time and the ultrasonic transverse wave measurement acoustic time.

[0043] Among them, the longitudinal wave acoustic time of ultrasound refers to the time elapsed from the emission of the longitudinal wave to its reception.

[0044] Among them, ultrasonic transverse wave acoustic time refers to the time elapsed from the emission of an ultrasonic transverse wave to its reception.

[0045] In this embodiment, the waveforms of the standard bolt transmitted signal wave and the standard bolt received signal wave can be analyzed by the wind power bolt signal analysis module to obtain acoustic time information related to the axial stress of the wind power bolt, and the propagation time of the ultrasonic wave can be obtained. The ultrasonic propagation time corresponding to the standard bolt transmitted signal wave after analysis is used as the ultrasonic longitudinal wave measurement acoustic time, and the ultrasonic propagation time corresponding to the standard bolt received signal wave after analysis is used as the ultrasonic transverse wave measurement acoustic time.

[0046] In this embodiment, since there is a relationship between the acoustic time of ultrasound and axial stress, the axial stress of the wind turbine bolt can be further measured by obtaining the acoustic time information.

[0047] S104: Determine the ultrasonic longitudinal wave acoustic elastic coefficient and ultrasonic transverse wave acoustic elastic coefficient based on the basic information of the bolt.

[0048] The basic information about the bolts includes: specifications, materials, and uses of the wind turbine bolts.

[0049] Optional specifications for wind turbine bolts include: nominal diameter of the wind turbine bolt, bolt length, thread type, coefficient of thermal expansion of bolt material, and yield strength of bolt material.

[0050] In this embodiment, the acoustoelastic coefficient is related to the properties of the wind turbine bolt. The basic information of the bolt can be measured, such as its specifications, materials, and uses. Based on this information, the ultrasonic longitudinal wave acoustoelastic coefficient and the ultrasonic transverse wave acoustoelastic coefficient can be determined. Since these coefficients can be used to calculate the axial stress of the wind turbine bolt, they provide a quantitative coefficient for measuring the axial stress of the bolt, effectively improving the accuracy of the axial stress measurement.

[0051] S105: Obtain the first bolt axial stress analysis model, input the ultrasonic measurement sound velocity information, ultrasonic longitudinal wave measurement sound time, ultrasonic transverse wave measurement sound time, bolt basic information, ultrasonic longitudinal wave acoustoelastic coefficient and ultrasonic transverse wave acoustoelastic coefficient into the first bolt axial stress analysis model for processing, and obtain the bolt axial stress measurement results.

[0052] Among them, the ultrasonic measurement of sound velocity information includes ultrasonic longitudinal wave velocity and ultrasonic transverse wave velocity. The sound velocity in solids is related to stress. Within the yield strength of the material, the elongation of the material is proportional to the applied stress. Therefore, ultrasonic longitudinal and transverse wave velocities are very important for measuring the axial stress of bolts.

[0053] Among them, the bolt axial stress measurement result refers to the state information of bolt axial stress obtained after comprehensively analyzing various influencing factors.

[0054] The first bolt axial stress analysis model is a data processing model used to comprehensively summarize and analyze parameter information related to the axial stress of wind turbine bolts. The first bolt axial stress analysis model is constructed by training all the obtained ultrasonic measurement sound velocity information, ultrasonic longitudinal wave measurement sound time, ultrasonic transverse wave measurement sound time, basic information of the measured bolt, ultrasonic longitudinal wave acoustoelastic coefficient and ultrasonic transverse wave acoustoelastic coefficient as input data to obtain a mathematical model that can comprehensively process the relevant factors affecting the axial stress of the bolt.

[0055] In this embodiment, factors related to the axial stress of the wind turbine bolt can be input into the axial stress analysis model to obtain the first bolt axial stress analysis model. The obtained ultrasonic measurement velocity information, ultrasonic longitudinal wave measurement time, ultrasonic transverse wave measurement time, bolt basic information, ultrasonic longitudinal wave acoustic elastic coefficient, and ultrasonic transverse wave acoustic elastic coefficient are input into the first bolt axial stress analysis model for processing. The first bolt axial stress analysis model is used to analyze and calculate the input data to obtain the bolt axial stress measurement result output by the first bolt axial stress analysis model.

[0056] In this embodiment of the disclosure, after obtaining the bolt axial stress measurement results, the wind turbine unit is maintained and managed according to the bolt axial stress measurement results. For example, the operating status of the wind turbine unit is adjusted according to the bolt axial stress measurement results, and it is determined whether it is necessary to stop the machine to replace the bolts. In this way, the bolt condition can be accurately and efficiently monitored without processing the bolts or changing the stress structure, effectively reducing damage to the bolts, improving the accuracy of bolt axial stress measurement, reducing errors, and thus achieving precise monitoring of the condition of the wind turbine unit bolts, improving the safety and economy of the unit equipment operation.

[0057] In this embodiment, by using the first bolt axial stress analysis model to analyze the data, a comprehensive and thorough analysis of the factors affecting the bolt's axial stress can be achieved, thereby improving the accuracy of bolt axial stress measurement.

[0058] In this embodiment, by acquiring the transmitted and received signal waves of the wind turbine bolts, and uploading them to the wind turbine bolt signal analysis module for noise reduction and filtering, standard bolt transmitted and received signal waves are obtained. Waveform analysis is then performed on these standard bolt transmitted and received signal waves to obtain the ultrasonic longitudinal wave measurement time and ultrasonic transverse wave measurement time. Based on the bolt's basic information, the ultrasonic longitudinal wave acoustic elastic coefficient and ultrasonic transverse wave acoustic elastic coefficient are determined, and a first bolt axial stress analysis model is obtained. The ultrasonic measurement velocity information, ultrasonic longitudinal wave measurement time, ultrasonic transverse wave measurement time, bolt basic information, and ultrasonic longitudinal wave acoustic elastic coefficient and ultrasonic transverse wave acoustic elastic coefficient are input into the first bolt axial stress analysis model for processing, resulting in bolt axial stress measurement results. This effectively reduces interference during ultrasonic monitoring, thereby reducing measurement errors in bolt axial stress and enabling a more accurate assessment of bolt condition.

[0059] Figure 2 This is a schematic flowchart of a bolt axial stress measurement method based on ultrasonic dual waves proposed in another embodiment of this disclosure.

[0060] like Figure 2 As shown, this method for measuring bolt axial stress based on ultrasonic dual-wavelengths includes:

[0061] S201: Acquire the signal wave transmitted by the wind turbine bolt and the signal wave received by the wind turbine bolt.

[0062] For a detailed description of S201, please refer to the above embodiments, which will not be repeated here.

[0063] S202: Upload the wind turbine bolt transmitted signal wave and the wind turbine bolt received signal wave to the wind turbine bolt signal analysis module for noise reduction and filtering to obtain the standard bolt transmitted signal wave and the standard bolt received signal wave.

[0064] Optionally, in some embodiments, the transmitted and received signal waves of the wind turbine bolts are uploaded to the wind turbine bolt signal analysis module for denoising and filtering to obtain standard bolt transmitted and received signal waves. Wavelet decomposition can be performed on the transmitted and received signal waves to obtain ultrasonic transmitted and received wavelet coefficients. Based on the ultrasonic measurement environment of the bolt, an ultrasonic signal wavelet threshold is determined, and wavelet coefficients of the transmitted and received signals smaller than the ultrasonic signal wavelet threshold are extracted to obtain noise signal information. Noise signal information is then denoised and filtered to obtain standard bolt transmitted and received signal waves. This reduces the measurement error of bolt axial stress, laying the foundation for determining the working state of the bolt based on its axial stress and effectively improving the accuracy of the determined working state.

[0065] Specifically, due to factors such as the structure and inclusions of wind turbine bolts, ultrasonic measurements may be interfered with. The transmitted and received signal waves of the wind turbine bolts may contain waveforms unrelated to the axial stress of the bolts. By performing wavelet decomposition on the transmitted and received signal waves of the wind turbine bolts, useful waveforms can be retained while irrelevant waveforms can be removed.

[0066] Wavelet decomposition refers to the process of gradually refining a signal at multiple scales through scaling and translation operations. Ultimately, based on the different wavelet coefficients generated by the decomposition of useful and irrelevant signals, the useful waveform is separated, preparing for the subsequent provision of standard bolt transmitting and receiving signal waves.

[0067] Among them, the wavelet coefficients of the ultrasonic transmission signal refer to the coefficients generated after wavelet decomposition of the ultrasonic transmission signal.

[0068] Among them, the wavelet coefficients of the ultrasonic received signal refer to the coefficients generated after wavelet decomposition of the ultrasonic received signal.

[0069] In this embodiment of the disclosure, wavelet decomposition processing can be performed on the transmitted signal wave and the received signal wave of the wind turbine bolt to obtain the wavelet coefficients of the transmitted ultrasonic signal and the wavelet coefficients of the received ultrasonic signal. After obtaining all the wavelet coefficients of the transmitted ultrasonic signal and the wavelet coefficients of the received ultrasonic signal, they need to be filtered. Optionally, a threshold range can be set to filter out the useful wavelet coefficients. The wavelet coefficients generated by the useful signal are larger than the wavelet coefficients generated by the useless noise signal.

[0070] In this embodiment of the present disclosure, a suitable threshold can be selected as the ultrasonic signal wavelet threshold according to the ultrasonic measurement environment of the bolt. The wavelet coefficients of the ultrasonic transmitted signal and the ultrasonic received signal are truncated according to the ultrasonic signal wavelet threshold. Wavelet coefficients greater than the ultrasonic signal wavelet threshold are considered to be generated by useful signals, and the wavelet coefficients of useful signals are retained to the maximum extent. Wavelet coefficients less than the threshold are considered to be generated by noise. In this way, the useless signals can be filtered out by noise signal information that is less than the ultrasonic signal wavelet selection threshold.

[0071] In this embodiment of the disclosure, the coefficient corresponding to the useless signal can be set to 0 to filter out the waveform generated by the useless signal. The signal wave after filtering out the useless signal can be used as the standard bolt sending signal wave and the standard bolt receiving signal wave.

[0072] S203: Perform waveform analysis and processing on the standard bolt transmitted signal wave and the standard bolt received signal wave to obtain the ultrasonic longitudinal wave measurement acoustic time and the ultrasonic transverse wave measurement acoustic time.

[0073] S204: Determine the ultrasonic longitudinal wave acoustic elastic coefficient and ultrasonic transverse wave acoustic elastic coefficient based on the basic information of the bolt.

[0074] For a detailed description of S203 and S204, please refer to the above embodiments, which will not be repeated here.

[0075] S205: Classify the basic information of bolts to obtain bolt classification information.

[0076] Among them, bolt classification information refers to data information used to facilitate the search and classification of wind power bolts. This bolt classification information can include, for example, information related to the bolt material and information related to the thermal expansion coefficient of the bolt material, which lays the groundwork for the subsequent determination of bolt measurement calibration coefficients.

[0077] In this embodiment of the disclosure, the basic information of the bolt can be classified to obtain data such as the bolt's material information and the thermal expansion coefficient of the bolt material, and the classified data is used as the bolt classification information.

[0078] S206: Determine the bolt measurement calibration coefficient based on the bolt classification information.

[0079] Among them, the bolt measurement calibration coefficient refers to the data coefficient used to index bolt classification information.

[0080] In this embodiment, data coefficients for indexing bolt classification information can be determined, and these index coefficients can be used as bolt measurement calibration coefficients. Bolt classification feature information is a summary of information in whole blocks. When searching based on several factors simultaneously, bolt measurement calibration coefficients can be determined to reduce the inaccuracy and error value of the search. Bolt measurement calibration coefficients can serve as an index, facilitating the retrieval of the first bolt axial stress analysis model from the bolt axial stress analysis model library. This enables rapid selection of the corresponding bolt axial stress analysis model, improving the efficiency and accuracy of bolt axial stress measurement.

[0081] S207: Based on the bolt measurement calibration coefficient, obtain the first bolt axial stress analysis model from the bolt axial stress analysis model library, and input the ultrasonic measurement sound velocity information, ultrasonic longitudinal wave measurement sound time, ultrasonic transverse wave measurement sound time, bolt basic information, ultrasonic longitudinal wave acoustoelastic coefficient and ultrasonic transverse wave acoustoelastic coefficient into the first bolt axial stress analysis model for processing to obtain the bolt axial stress measurement result.

[0082] In this embodiment of the present disclosure, after classifying the basic information of the bolts to obtain bolt classification information and determining the bolt measurement calibration coefficient based on the bolt classification information, the first bolt axial stress analysis model can be obtained from the bolt axial stress analysis model library based on the bolt measurement calibration coefficient.

[0083] In this embodiment of the disclosure, the bolt axial stress analysis model library contains multiple bolt axial stress analysis models. The bolt measurement calibration coefficient can be used as an index. The corresponding bolt axial stress analysis model is called from the bolt axial stress analysis model library as the first bolt axial stress analysis model. Then, the ultrasonic measurement sound velocity information, ultrasonic longitudinal wave measurement sound time, ultrasonic transverse wave measurement sound time, bolt basic information, ultrasonic longitudinal wave acoustoelastic coefficient, and ultrasonic transverse wave acoustoelastic coefficient can be input into the first bolt axial stress analysis model for processing to obtain the bolt axial stress measurement result.

[0084] Optionally, in some embodiments, when determining the bolt measurement calibration coefficient based on bolt classification information, a bolt calibration coefficient coordinate system can be constructed. This bolt calibration coefficient coordinate system is a multi-dimensional coordinate system. The bolt calibration coefficient coordinate system is subjected to regional label classification processing to obtain coordinate region label classification results. The basic information of the bolt is input into the bolt calibration coefficient coordinate system to obtain bolt classification feature vector information. The bolt classification feature vector information and the coordinate region label classification results are mapped and matched to obtain the bolt measurement calibration coefficient.

[0085] Among them, the bolt calibration coefficient coordinate system is a multi-dimensional coordinate system. There are many factors that affect the axial stress of the bolt. When determining the bolt calibration coefficient, the bolt calibration coefficient coordinate system is a multi-dimensional coordinate system. The coordinates in the multi-dimensional coordinate system are: the nominal diameter of the wind turbine bolt, the bolt length, the thread type, the thermal expansion coefficient of the bolt material, and the yield strength of the bolt material, etc.

[0086] In this embodiment, a multi-dimensional coordinate system can be determined, including the nominal diameter of the wind turbine bolt, bolt length, thread type, coefficient of thermal expansion of the bolt material, and yield strength of the bolt material. This determined coordinate system is used as the bolt calibration coefficient coordinate system. Then, the bolt calibration coefficient coordinate system is classified by region labeling to obtain the coordinate region label classification result. The bolt calibration coefficient coordinate system is classified by labeling, and the data on each coordinate axis is divided into a certain range. After combining the data, the resulting regions are labeled. When the basic information of the bolt is input into the bolt calibration coefficient coordinate system, the corresponding region label can be found, and the bolt classification feature vector information can be obtained. By mapping and matching the bolt classification information with the coordinate region label classification result one by one, the bolt measurement calibration coefficient corresponding to the bolt is obtained.

[0087] The bolt calibration coefficient coordinate system can be used to determine the first bolt axial stress analysis model, thereby enabling a more accurate measurement of the bolt axial stress.

[0088] In this embodiment, the transmitted and received signal waves of the wind turbine bolts are acquired and uploaded to the wind turbine bolt signal analysis module for noise reduction and filtering to obtain standard bolt transmitted and received signal waves. Waveform analysis is then performed on these standard bolt transmitted and received signal waves to obtain the ultrasonic longitudinal wave measurement time and ultrasonic transverse wave measurement time. Based on the bolt's basic information, the ultrasonic longitudinal wave acoustic elastic coefficient and ultrasonic transverse wave acoustic elastic coefficient are determined, and a first bolt axial stress analysis model is obtained. The ultrasonic measurement velocity information, ultrasonic longitudinal wave measurement time, ultrasonic transverse wave measurement time, bolt basic information, and ultrasonic longitudinal wave acoustic elastic coefficient and ultrasonic transverse wave acoustic elastic coefficient are input into the first bolt axial stress analysis model for processing to obtain the bolt axial stress measurement results. This method effectively reduces interference during ultrasonic monitoring, thereby minimizing measurement errors in bolt axial stress and enabling more accurate assessment of bolt condition. Wavelet decomposition is performed on the transmitted and received signal waves of the wind turbine bolts to obtain wavelet coefficients for the transmitted and received ultrasonic signals. Based on the bolt's ultrasonic measurement environment, an ultrasonic signal wavelet threshold is determined. Wavelet coefficients smaller than this threshold are extracted to obtain noise signal information. This noise signal information is then denoised and filtered to obtain standard bolt transmitted and received signal waves. This reduces measurement errors in bolt axial stress, laying the foundation for determining the bolt's working condition based on its axial stress and effectively improving the accuracy of the determined bolt working condition.

[0089] Figure 3 This is a schematic flowchart of a bolt axial stress measurement method based on ultrasonic dual waves proposed in another embodiment of this disclosure.

[0090] like Figure 3 As shown, this method for measuring bolt axial stress based on ultrasonic dual-wavelengths includes:

[0091] S301: Acquire the signal waves transmitted and received by the wind turbine bolts.

[0092] S302: Upload the wind turbine bolt transmitted signal wave and the wind turbine bolt received signal wave to the wind turbine bolt signal analysis module for noise reduction and filtering to obtain the standard bolt transmitted signal wave and the standard bolt received signal wave.

[0093] S303: Perform waveform analysis and processing on the standard bolt transmitted signal wave and the standard bolt received signal wave to obtain the ultrasonic longitudinal wave measurement acoustic time and the ultrasonic transverse wave measurement acoustic time.

[0094] S304: Determine the ultrasonic longitudinal wave acoustic elastic coefficient and ultrasonic transverse wave acoustic elastic coefficient based on the basic information of the bolt.

[0095] S305: Obtain the axial stress analysis model of the first bolt, input the ultrasonic measurement sound velocity information, ultrasonic longitudinal wave measurement sound time, ultrasonic transverse wave measurement sound time, bolt basic information, ultrasonic longitudinal wave acoustoelastic coefficient and ultrasonic transverse wave acoustoelastic coefficient into the axial stress analysis model of the first bolt for processing, and obtain the bolt axial stress measurement results.

[0096] For a detailed description of S301 to S305, please refer to the above embodiments, which will not be repeated here.

[0097] S306: Based on a temperature sensor, acquire bolt measurement temperature information.

[0098] Among them, bolt temperature measurement information refers to the temperature information measured at a certain moment for the wind turbine bolts.

[0099] In this embodiment of the disclosure, the temperature of the wind turbine bolt can be tested based on a temperature sensor, and the measured temperature information can be stored in a database. The temperature of the wind turbine bolt measured at a certain moment can be used as the bolt measurement temperature information.

[0100] In this embodiment of the disclosure, the elongation of the wind turbine bolt during the tensile process of force change is also related to the temperature. The specific change of the bolt elongation at a certain temperature is related to the thermal expansion coefficient of the wind turbine bolt material. Therefore, it is necessary to obtain the bolt measurement temperature information through a temperature sensor.

[0101] S307: Perform temperature compensation processing based on the bolt temperature measurement information to obtain temperature compensation parameter information.

[0102] Among them, the temperature compensation parameter information refers to the parameter information determined by the specific temperature change amount when temperature compensation is performed based on the bolt temperature measurement information.

[0103] In this embodiment of the disclosure, temperature compensation processing can be performed based on the bolt temperature measurement information, and parameter information can be determined based on the specific temperature change during the temperature compensation process. The determined parameter information is then used as the temperature compensation parameter information.

[0104] S308: Determine the ultrasonic velocity influence coefficient based on the temperature compensation parameter information.

[0105] In this embodiment of the present disclosure, after performing temperature compensation processing based on the bolt temperature measurement information to obtain temperature compensation parameter information, the ultrasonic velocity influence coefficient can be determined based on the temperature compensation parameter information.

[0106] In this disclosure, it is determined that the material of the wind turbine bolt will undergo thermal expansion due to temperature changes, which will cause changes in the ultrasonic velocity. In order to overcome and eliminate the influence of temperature, the ultrasonic velocity influence coefficient can be determined based on the temperature compensation parameter information to correct the axial stress analysis results of the measured bolt.

[0107] S309: Correct the bolt axial stress measurement results based on the ultrasonic velocity influence coefficient.

[0108] In this embodiment of the invention, after determining the ultrasonic velocity influence coefficient based on the temperature compensation parameter information, the bolt axial stress measurement results can be corrected based on the ultrasonic velocity influence coefficient.

[0109] In this embodiment, the bolt axial stress measurement results are corrected based on the ultrasonic velocity influence coefficient, thereby effectively improving the accuracy of bolt axial force measurement and enhancing the stability and safety of the wind turbine unit operation.

[0110] S310: Determine the working state of the bolt based on the measurement results of the bolt axial stress.

[0111] The bolt working state refers to the specific working state of the bolt determined by the magnitude of the axial stress of the bolt. The bolt working state can be normal operation or abnormal operation.

[0112] In this embodiment of the disclosure, the bolt shaft can be determined to be in a normal working state or an abnormal working state based on the bolt axial stress measurement results, and the obtained results can be used as the working state of the bolt.

[0113] S311: When the axial stress of the bolt reaches the preset stress yield value, a fault warning is given for the working condition of the bolt.

[0114] In this embodiment, the abnormal working state of the bolt is the working state when the axial stress of the bolt reaches the preset stress yield value. When the axial stress of the bolt reaches the preset stress yield value, it indicates that the bolt is in a dangerous working state and there is a risk that the bolt may break at any time. At this time, the bolt can be given a fault warning, so that the bolt can be dealt with in a timely manner. This enables more accurate monitoring of the status of the wind turbine bolts and effectively improves the safety and economy of the wind turbine equipment operation.

[0115] In this embodiment, by acquiring the transmitted and received signal waves of the wind turbine bolts, and uploading them to the wind turbine bolt signal analysis module for noise reduction and filtering, standard bolt transmitted and received signal waves are obtained. Waveform analysis is then performed on these standard bolt transmitted and received signal waves to obtain the ultrasonic longitudinal wave measurement time and ultrasonic transverse wave measurement time. Based on the bolt's basic information, the ultrasonic longitudinal wave acoustic elastic coefficient and ultrasonic transverse wave acoustic elastic coefficient are determined, and a first bolt axial stress analysis model is obtained. The ultrasonic measurement velocity information, ultrasonic longitudinal wave measurement time, ultrasonic transverse wave measurement time, bolt basic information, and ultrasonic longitudinal wave acoustic elastic coefficient and ultrasonic transverse wave acoustic elastic coefficient are input into the first bolt axial stress analysis model for processing, resulting in bolt axial stress measurement results. This effectively reduces interference during ultrasonic monitoring, thereby reducing measurement errors in bolt axial stress and enabling a more accurate assessment of bolt condition.

[0116] Figure 4 This is a schematic diagram of the structure of a bolt axial stress measuring device based on ultrasonic dual waves according to another embodiment of this disclosure.

[0117] like Figure 4 As shown, the bolt axial stress measuring device 40 based on ultrasonic dual-wavelength measurement includes:

[0118] The first acquisition module 401 is used to acquire the signal wave transmitted by the wind turbine bolt and the signal wave received by the wind turbine bolt.

[0119] The first processing module 402 is used to upload the wind power bolt transmitted signal wave and the wind power bolt received signal wave to the wind power bolt signal analysis module for noise reduction and filtering to obtain the standard bolt transmitted signal wave and the standard bolt received signal wave.

[0120] The second processing module 403 is used to perform waveform analysis and processing on the standard bolt transmitted signal wave and the standard bolt received signal wave to obtain the ultrasonic longitudinal wave measurement acoustic time and the ultrasonic transverse wave measurement acoustic time.

[0121] The first determining module 404 is used to determine the ultrasonic longitudinal wave acoustic elastic coefficient and the ultrasonic transverse wave acoustic elastic coefficient based on the basic information of the bolt.

[0122] The third processing module 405 is used to obtain the first bolt axial stress analysis model. It inputs the ultrasonic measurement sound velocity information, ultrasonic longitudinal wave measurement sound time, ultrasonic transverse wave measurement sound time, bolt basic information, ultrasonic longitudinal wave acoustic elastic coefficient and ultrasonic transverse wave acoustic elastic coefficient into the first bolt axial stress analysis model for processing, and obtains the bolt axial stress measurement results.

[0123] In some embodiments of this disclosure, the third processing module 405 is specifically used for:

[0124] The basic information of bolts is classified to obtain bolt classification information;

[0125] Determine the bolt measurement calibration coefficient based on the bolt classification information;

[0126] Based on the bolt measurement calibration coefficient, the first bolt axial stress analysis model is obtained from the bolt axial stress analysis model library.

[0127] In some embodiments of this disclosure, the third processing module 405 is further configured to:

[0128] Construct a bolt calibration coefficient coordinate system, wherein the bolt calibration coefficient coordinate system is a multi-dimensional coordinate system;

[0129] The coordinate system of bolt calibration coefficients is classified by region labeling to obtain the coordinate region labeling results.

[0130] Input the basic information of the bolt into the bolt calibration coefficient coordinate system to obtain the bolt classification feature vector information;

[0131] The bolt classification feature vector information and the coordinate region label classification results are mapped and matched to obtain the bolt measurement calibration coefficient.

[0132] In some embodiments of this disclosure, the first processing module 402 is specifically used for:

[0133] Wavelet decomposition was performed on the transmitted and received signal waves of the wind turbine bolts to obtain the wavelet coefficients of the ultrasonic transmitted signal and the ultrasonic received signal.

[0134] Determine the wavelet threshold of the ultrasonic signal based on the ultrasonic measurement environment of the bolt;

[0135] By extracting wavelet coefficients of the transmitted and received ultrasonic signals that are smaller than the wavelet threshold of the ultrasonic signal, noise signal information is obtained.

[0136] The noise signal information is denoised and filtered to obtain the standard bolt transmitted signal wave and the standard bolt received signal wave.

[0137] In some embodiments of this disclosure, it also includes:

[0138] The second acquisition module 406 is used to acquire bolt measurement temperature information based on a temperature sensor;

[0139] The fourth processing module 407 is used to perform temperature compensation processing based on the bolt measurement temperature information to obtain temperature compensation parameter information;

[0140] The second determining module 408 is used to determine the ultrasonic velocity influence coefficient based on the temperature compensation parameter information.

[0141] The fifth processing module 409 is used to correct the bolt axial stress measurement results based on the ultrasonic velocity influence coefficient.

[0142] In some embodiments of this disclosure, it also includes:

[0143] The third determining module 410 is used to determine the working state of the bolt based on the bolt axial stress measurement results;

[0144] The sixth processing module 411 is used to provide fault warning for the working state of the bolt when the axial stress of the bolt reaches the preset stress yield value.

[0145] With the above Figures 1 to 3 Corresponding to the bolt axial stress measurement method based on ultrasonic dual-wavelength provided in the embodiments, this disclosure also provides a bolt axial stress measurement device based on ultrasonic dual-wavelength. Since the bolt axial stress measurement device based on ultrasonic dual-wavelength provided in the embodiments of this disclosure is similar to the one described above... Figures 1 to 3 The embodiment provides a bolt axial stress measurement method based on ultrasonic dual waves. Therefore, the implementation method of the bolt axial stress measurement method based on ultrasonic dual waves is also applicable to the bolt axial stress measurement device based on ultrasonic dual waves provided in this disclosure embodiment. It will not be described in detail in this disclosure embodiment.

[0146] In this embodiment, by acquiring the transmitted and received signal waves of the wind turbine bolts, and uploading them to the wind turbine bolt signal analysis module for noise reduction and filtering, standard bolt transmitted and received signal waves are obtained. Waveform analysis is then performed on these standard bolt transmitted and received signal waves to obtain the ultrasonic longitudinal wave measurement time and ultrasonic transverse wave measurement time. Based on the bolt's basic information, the ultrasonic longitudinal wave acoustic elastic coefficient and ultrasonic transverse wave acoustic elastic coefficient are determined, and a first bolt axial stress analysis model is obtained. The ultrasonic measurement velocity information, ultrasonic longitudinal wave measurement time, ultrasonic transverse wave measurement time, bolt basic information, and ultrasonic longitudinal wave acoustic elastic coefficient and ultrasonic transverse wave acoustic elastic coefficient are input into the first bolt axial stress analysis model for processing, resulting in bolt axial stress measurement results. This effectively reduces interference during ultrasonic monitoring, thereby reducing measurement errors in bolt axial stress and enabling a more accurate assessment of bolt condition.

[0147] To implement the above embodiments, this disclosure also proposes a non-transitory computer-readable storage medium storing a computer program that, when executed by a processor, implements the bolt axial stress measurement method based on ultrasonic dual waves as proposed in the foregoing embodiments of this disclosure.

[0148] To implement the above embodiments, this disclosure also proposes a computer program product that, when executed by an instruction processor, performs the bolt axial stress measurement method based on ultrasonic dual waves as proposed in the foregoing embodiments of this disclosure.

[0149] Figure 6 A block diagram of an exemplary electronic device suitable for implementing embodiments of the present disclosure is shown.

[0150] Figure 6 The computer device 12 shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments disclosed herein.

[0151] like Figure 6 As shown, the computer device 12 is represented in the form of a general-purpose computing device. The components of the computer device 12 may include, but are not limited to: one or more processors or processing units 16, system memory 28, and a bus 18 connecting different system components (including system memory 28 and processing unit 16).

[0152] Bus 18 represents one or more of several bus architectures, including a memory bus or memory controller, a peripheral bus, a graphics acceleration port, a processor, or a local bus using any of the various bus architectures. Examples of these architectures include, but are not limited to, the Industry Standard Architecture (ISA) bus, the Micro Channel Architecture (MAC) bus, the Enhanced ISA bus, the Video Electronics Standards Association (VESA) local bus, and the Peripheral Component Interconnect (PCI) bus.

[0153] Computer device 12 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by computer device 12, including volatile and non-volatile media, removable and non-removable media.

[0154] Memory 28 may include computer system readable media in the form of volatile memory, such as Random Access Memory (RAM) 30 and / or cache memory 32. Computer device 12 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, storage system 34 may be used to read and write non-removable, non-volatile magnetic media (…). Figure 6 Not shown; usually referred to as a "hard drive".

[0155] although Figure 6 Not shown, a disk drive for reading and writing to a removable non-volatile disk (e.g., a "floppy disk") and an optical disc drive for reading and writing to a removable non-volatile optical disc (e.g., a compact disc read-only memory (CD-ROM), a digital video disc read-only memory (DVD-ROM), or other optical media) may be provided. In these cases, each drive may be connected to bus 18 via one or more data media interfaces. Memory 28 may include at least one program product having a set (e.g., at least one) of program modules configured to perform the functions of the embodiments of this disclosure.

[0156] A program / utility 40 having a set (at least one) of program modules 42 may be stored, for example, in memory 28. Such program modules 42 include, but are not limited to, an operating system, one or more application programs, other program modules, and program data. Each or some combination of these examples may include an implementation of a network environment. Program modules 42 typically perform the functions and / or methods described in the embodiments of this disclosure.

[0157] Computer device 12 can also communicate with one or more external devices 14 (e.g., keyboard, pointing device, display 24, etc.), and with one or more devices that enable human interaction with the computer device 12, and / or with any device that enables the computer device 12 to communicate with one or more other computing devices (e.g., network card, modem, etc.). This communication can be performed via input / output (I / O) interface 22. Furthermore, computer device 12 can also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public networks, such as the Internet) via network adapter 20. As shown, network adapter 20 communicates with other modules of computer device 12 via bus 18. It should be understood that, although not shown in the figures, other hardware and / or software modules can be used in conjunction with computer device 12, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0158] The processing unit 16 executes various functional applications and parameter information determination by running programs stored in the system memory 28, such as implementing the bolt axial stress measurement method based on ultrasonic dual waves mentioned in the foregoing embodiments.

[0159] It should be noted that in the description of this disclosure, the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance. Furthermore, in the description of this disclosure, unless otherwise stated, "a plurality of" means two or more.

[0160] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing a particular logical function or process, and the scope of preferred embodiments of this disclosure includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the function involved, as will be understood by those skilled in the art to which embodiments of this disclosure pertain.

[0161] It should be understood that various parts of this disclosure can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0162] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0163] Furthermore, the functional units in the various embodiments of this disclosure can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0164] The storage media mentioned above can be read-only memory, disk, or optical disk, etc.

[0165] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this disclosure. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0166] Although embodiments of the present disclosure have been shown and described above, it is to be understood that the above embodiments are exemplary and should not be construed as limiting the present disclosure. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present disclosure.

Claims

1. A method for measuring bolt axial stress based on ultrasonic dual-wavelengths, characterized in that, include: Acquire the signal waves transmitted and received by the wind turbine bolts; The transmitted signal wave and the received signal wave of the wind turbine bolt are uploaded to the wind turbine bolt signal analysis module for noise reduction and filtering to obtain the standard bolt transmitted signal wave and the standard bolt received signal wave. Waveform analysis and processing are performed on the transmitted signal wave and received signal wave of the standard bolt to obtain the ultrasonic longitudinal wave measurement acoustic time and ultrasonic transverse wave measurement acoustic time. Based on the basic information of the bolt, determine the ultrasonic longitudinal wave acoustic elastic coefficient and the ultrasonic transverse wave acoustic elastic coefficient. A first bolt axial stress analysis model is obtained. The ultrasonic velocity measurement information, the ultrasonic longitudinal wave measurement time, the ultrasonic transverse wave measurement time, the basic information of the bolt, the ultrasonic longitudinal wave acoustoelastic coefficient, and the ultrasonic transverse wave acoustoelastic coefficient are input into the first bolt axial stress analysis model for processing to obtain the bolt axial stress measurement results. The process of obtaining the axial stress analysis model for the first bolt includes: The basic information of the bolts is classified to obtain bolt classification information; Based on the bolt classification information, determine the bolt measurement calibration coefficient; Based on the bolt measurement calibration coefficient, the first bolt axial stress analysis model is obtained from the bolt axial stress analysis model library; The step of determining the bolt measurement calibration coefficient based on the bolt classification information includes: Construct a bolt calibration coefficient coordinate system, wherein the bolt calibration coefficient coordinate system is a multi-dimensional coordinate system; The coordinate system of the bolt calibration coefficients is subjected to regional labeling classification to obtain the coordinate region labeling classification results; The basic information of the bolt is input into the bolt calibration coefficient coordinate system to obtain the bolt classification feature vector information; The bolt classification feature vector information and the coordinate region label classification result are mapped and matched to obtain the bolt measurement calibration coefficient.

2. The method as described in claim 1, characterized in that, The process of uploading the transmitted signal wave and the received signal wave of the wind turbine bolt to the wind turbine bolt signal analysis module for noise reduction and filtering to obtain the standard bolt transmitted signal wave and the standard bolt received signal wave includes: Wavelet decomposition is performed on the transmitted signal wave and the received signal wave of the wind turbine bolt to obtain the wavelet coefficients of the ultrasonic transmitted signal and the ultrasonic received signal. Determine the wavelet threshold of the ultrasonic signal based on the ultrasonic measurement environment of the bolt; By extracting wavelet coefficients of the transmitted ultrasound signal and the received ultrasound signal that are smaller than the wavelet threshold of the ultrasound signal, noise signal information is obtained. The noise signal information is subjected to noise reduction filtering to obtain the standard bolt transmitted signal wave and the standard bolt received signal wave.

3. The method as described in claim 1, characterized in that, Also includes: Based on a temperature sensor, obtain bolt measurement temperature information; Temperature compensation processing is performed based on the measured temperature information of the bolt to obtain temperature compensation parameter information; Based on the temperature compensation parameter information, determine the ultrasonic velocity influence coefficient; The measurement results of the bolt axial stress are corrected based on the ultrasonic velocity influence coefficient.

4. The method as described in claim 3, characterized in that, Also includes: The working state of the bolt is determined based on the axial stress measurement results of the bolt; When the axial stress of the bolt reaches the preset stress yield value, a fault warning is issued for the working state of the bolt.

5. A bolt axial stress measuring device based on ultrasonic dual-wave, characterized in that, include: The first acquisition module is used to acquire the signal waves transmitted by the wind turbine bolts and the signal waves received by the wind turbine bolts. The first processing module is used to upload the transmitted signal wave and the received signal wave of the wind turbine bolt to the wind turbine bolt signal analysis module for noise reduction and filtering to obtain the standard bolt transmitted signal wave and the standard bolt received signal wave. The second processing module is used to perform waveform analysis and processing on the signal wave sent by the standard bolt and the signal wave received by the standard bolt to obtain the ultrasonic longitudinal wave measurement acoustic time and the ultrasonic transverse wave measurement acoustic time. The first determining module is used to determine the ultrasonic longitudinal wave acoustic elastic coefficient and the ultrasonic transverse wave acoustic elastic coefficient based on the basic information of the bolt. The third processing module is used to obtain the first bolt axial stress analysis model, and input the ultrasonic measurement sound velocity information, the ultrasonic longitudinal wave measurement sound time, the ultrasonic transverse wave measurement sound time, the basic information of the bolt, the ultrasonic longitudinal wave acoustoelastic coefficient and the ultrasonic transverse wave acoustoelastic coefficient into the first bolt axial stress analysis model for processing to obtain the bolt axial stress measurement result; The process of obtaining the axial stress analysis model for the first bolt includes: The basic information of the bolts is classified to obtain bolt classification information; Based on the bolt classification information, determine the bolt measurement calibration coefficient; Based on the bolt measurement calibration coefficient, the first bolt axial stress analysis model is obtained from the bolt axial stress analysis model library; The step of determining the bolt measurement calibration coefficient based on the bolt classification information includes: Construct a bolt calibration coefficient coordinate system, wherein the bolt calibration coefficient coordinate system is a multi-dimensional coordinate system; The coordinate system of the bolt calibration coefficients is subjected to regional labeling classification to obtain the coordinate region labeling classification results; The basic information of the bolt is input into the bolt calibration coefficient coordinate system to obtain the bolt classification feature vector information; The bolt classification feature vector information and the coordinate region label classification result are mapped and matched to obtain the bolt measurement calibration coefficient.

6. An electronic device, characterized in that, include: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-4.

7. A non-transitory computer-readable storage medium storing computer instructions, characterized in that, in, The computer instructions are used to cause the computer to perform the method according to any one of claims 1-4.

8. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the steps of the method according to any one of claims 1-4.

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