A passive wireless intelligent microsystem for monitoring the condition of wind turbine blades

Abstract

This paper proposes a passive wireless intelligent microsystem for wind turbine blade condition monitoring. This system harvests energy from the operating environment of the wind turbine blades and uses this energy for blade condition monitoring. It eliminates the need for external power cables and signal transmission cables, significantly improving on-site construction and maintenance efficiency. Furthermore, by using passive wireless power supply and information transmission, the installation location of the blade monitoring sensors can overcome the limitations of existing blade installation locations, allowing for closer proximity to ideal positions and thus improving the accuracy of blade health status assessment. The passive wireless intelligent microsystem includes: an environmental energy harvesting module, a blade condition sensing module, a power management module, an intelligent microsystem management module, a wireless communication module, a local edge computing module, a local storage module, and a human-machine interaction module.

Description

Technical Field

[0001] This method belongs to the field of wind power generation, specifically involving a passive wireless intelligent microsystem for monitoring the condition of wind turbine blades. Background Technology

[0002] Wind power generation is a typical distributed power generation system. Wind turbines are characterized by small unit capacity and wide distribution areas, and they are mostly used in remote areas with harsh climates and inconvenient transportation. These characteristics bring great challenges to the operation and maintenance of wind turbine units.

[0003] Blades are important energy-receiving devices in wind turbine generators. They are characterized by high cost and insufficient spare parts. Failures can lead to prolonged downtime and significantly reduce the power output of wind turbine generators. Therefore, monitoring the operating status of blades and assessing their health level, and formulating wind farm operation and maintenance resource scheduling and spare parts strategies based on the health status assessment results, is of great practical significance.

[0004] The wind turbine blade condition monitoring system monitors and assesses the health status of the blades. It consists of blade monitoring sensors, data acquisition equipment, a communication system, and host computer monitoring and analysis software. The sensors are installed inside the blades, the data acquisition equipment is installed inside the wind turbine hub, and the host computer monitoring and analysis software is installed in the central monitoring center of the wind farm. The communication system transmits the information collected and processed by the monitoring sensors from the data acquisition equipment to the host computer for centralized monitoring and analysis, thereby achieving the assessment of the wind turbine blade health level.

[0005] The wind turbine blade condition monitoring system has two shortcomings in actual operation: First, the cables from the blade monitoring sensors to the data acquisition equipment are relatively long. To prevent the cables from breaking during blade operation, a special wiring pattern and special adhesive are required, resulting in a long construction period and more downtime for the unit. Second, the blade monitoring sensors are installed inside the blade, but the internal space of the blade is limited, which restricts the space accessible to on-site construction and maintenance personnel when installing the blade monitoring sensors. Therefore, a balance needs to be struck between the constraints of on-site installation space and the ideal installation location of the blade monitoring sensors, which to some extent affects the accuracy of the assessment of the health level of the wind turbine blades. Summary of the Invention

[0006] This paper proposes a passive wireless intelligent microsystem for monitoring the condition of wind turbine blades. This system obtains energy from the operating environment of the wind turbine blades and uses the obtained energy for monitoring the condition of the wind turbine blades. It does not require external power cables and signal transmission cables, which greatly improves the efficiency of on-site construction and operation and maintenance. In addition, since it uses passive wireless power supply and information transmission, the installation position of the blade monitoring sensor can break through the limitations of the existing installation position of the blade and get closer to the ideal position, thereby improving the accuracy of blade health status assessment.

[0007] Passive wireless intelligent microsystems, such as Figure 1 As shown, it includes: an environmental energy acquisition module, a blade status sensing module, a power energy management module, an intelligent microsystem management module, a wireless communication module, a local edge computing module, a local storage module, and a human-machine interaction module.

[0008] The environmental energy harvesting module harvests energy from the operating environment of the wind turbine blades and converts this energy into electrical energy required for the operation of the intelligent microsystem. The environmental energy harvesting module includes an environmental energy conversion module and a power generation module. The environmental energy conversion module converts the energy from the wind turbine blade operating environment into an energy mode that can be used for direct power generation. The power generation module converts the energy converted by the environmental energy conversion module into electrical energy to power the passive wireless intelligent microsystem. The design flow of the environmental energy harvesting module is as follows:

[0009] Step 1: Estimate the energy consumption of the passive wireless intelligent microsystem.

[0010] The energy consumption E required by a passive wireless intelligent microsystem, in joules, can be estimated using the following formula:

[0011]

[0012] E1 represents the energy required for data acquisition, measured in joules.

[0013] E2 represents the energy required for local storage operations, measured in joules.

[0014] E3 represents the energy required for long-distance transmission, measured in joules.

[0015] E4 represents the energy required for edge computing operations, measured in joules.

[0016] E5 represents the energy required for human-computer interaction, measured in joules.

[0017] E6 indicates the energy required for the power management module to operate.

[0018] Step 2: Estimate the energy range that the environmental energy acquisition module can acquire.

[0019] Sub-step 1: Assess the available vibration energy, electromagnetic energy, noise energy, electrostatic energy, temperature difference, and strain energy present in the environment;

[0020] Sub-step 2: Calculate the environmental energy density distribution and determine the frequency range with the largest environmental energy distribution;

[0021] Sub-step 3: For the frequency range corresponding to the maximum environmental energy, estimate the theoretical energy range that the environmental energy acquisition module can acquire;

[0022] Sub-step 4: Based on the total energy amount and energy margin determined in sub-step 4 and step 1, determine the number of environmental energy acquisition modules to ensure that the energy requirements of the passive wireless intelligent microsystem are met.

[0023] Step 3: Determine the structure of the environmental energy harvesting module.

[0024] Sub-step 1: Determine the structure of the environmental energy conversion module where resonance occurs. During the operation of the wind turbine generator, the natural frequency of the environmental energy conversion module resonates with the frequency corresponding to the maximum distribution of environmental energy. Under this condition, the environmental energy conversion module converts environmental energy into an energy form that can be directly used for power generation to the greatest extent possible.

[0025] Sub-step 2: Determine the impedance-matched power generation module structure. The power generation module itself has internal impedance, and the passive wireless intelligent microsystem itself, as a load, also has impedance. When the internal impedance of the power generation module matches the load impedance, the power output of the power generation module is maximized.

[0026] Step 4: Determine the parameters of the environmental energy conversion module.

[0027] Sub-step 1: Based on the spatial constraints around the wind turbine components and the characteristics of the lightning environment of the wind farm, determine the geometric size range and mass range of the environmental energy harvesting module;

[0028] Sub-step 2: Determine the initial values ​​of the environmental energy conversion module parameters based on the frequency range corresponding to the maximum environmental energy distribution determined in sub-step 2 of step 2;

[0029] Sub-step 3: After the initial values ​​of the environmental energy conversion module parameters are determined, the final values ​​of the environmental energy conversion module parameters are determined based on the optimization method and the field test method.

[0030] Step 5: Determine the parameters of the power generation module.

[0031] The parameters of the power generation module include the coil length L, the number of turns N, and the coil internal resistance R. n The coil material ρ and the fixed center position of the coil.

[0032] Sub-step 1: Determine the fixed center position of the generator coil.

[0033] The fixed position of the power generation coil is the distance between the center of the power generation coil and the vibration equilibrium position of the moving permanent magnet, which is determined by the equilibrium position of the moving permanent magnet in the environmental energy conversion module.

[0034] Sub-step 2: The coil length is determined by the following formula:

[0035] e=BLω0l

[0036] In the above formula,

[0037] L represents the overall length of the coil.

[0038] B represents the magnetic flux of the permanent magnet, which is determined by the permanent magnet selected in step 1;

[0039] ω0 represents the hub rotation speed during the operation of the wind turbine generator set;

[0040] l represents the distance between the center position of the wind turbine hub and the equilibrium position of the permanent magnet;

[0041] e represents the open-circuit voltage of the generator coil, which is determined by the minimum voltage of the power management module.

[0042] Sub-step 3: The number of coil turns is determined by the following formula:

[0043] L=πD c N

[0044] D c Indicates the diameter of the generating coil;

[0045] N represents the number of turns in the generator coil winding.

[0046] Sub-step 4: Internal resistance R of the generator coil n With load resistance R load When the values ​​are equal, the power output of the generator module is the maximum, and the coil material is determined by the following formula:

[0047]

[0048] R n This indicates the internal resistance of the generating coil;

[0049] ρ represents the resistivity of the power generation coil material;

[0050] L represents the length of the generator coil;

[0051] S represents the cross-sectional area of ​​the generator coil conductor.

[0052] The blade condition sensing module refers to the module that monitors the overall external motion characteristics and internal structural characteristics of wind turbine blades. The overall external motion characteristics are manifested as the blade's vibration acceleration, vibration velocity, vibration displacement, and strain, while the internal structural characteristics are manifested as the normal deformation, damage, and fracture of the blade's internal structure.

[0053] The power management module includes a rectifier module, a charging module, an energy storage module, and a voltage conversion module, such as... Figure 2 As shown. The rectifier module rectifies the AC voltage generated by the ambient energy harvesting module and converts it into DC voltage. The charging module stores the rectified DC voltage into an energy storage capacitor. The voltage conversion module converts the stable voltage from the energy storage module into the stable operating voltage required by each module of the intelligent microsystem. The power management module design flow is as follows:

[0054] Step 1: Determine the energy storage capacitor.

[0055] The rectified output DC voltage is V dc And for storing electrical energy C res The acquired vibration energy is stored in a storage capacitor during charging. The parameters of the storage capacitor are designed according to the following formula:

[0056]

[0057] E represents the energy required for the passive wireless intelligent microsystem to operate normally, measured in joules.

[0058] C res Indicates the capacitance value of the energy storage capacitor, expressed in units;

[0059] V dc This indicates the maximum DC voltage output by the rectifier module, in volts.

[0060] V min This indicates the threshold voltage of the rectifier module, in volts.

[0061] Step 2: Determine the voltage regulator capacitor.

[0062] The parameters of the voltage regulator capacitor are designed according to the following formula:

[0063]

[0064] C out This indicates the capacitance value of the voltage regulator capacitor, expressed in units.

[0065] I load This represents the current required for the normal operation of a passive wireless intelligent microsystem, measured in amperes.

[0066] I dis The current of a passive wireless intelligent microsystem under no-load conditions is expressed in amperes.

[0067] t load This indicates the normal operating time of the passive wireless intelligent microsystem, in seconds.

[0068] This indicates the maximum voltage fluctuation of the load in a passive wireless intelligent microsystem, expressed in volts.

[0069] This represents the minimum operating voltage fluctuation of the passive wireless intelligent microsystem load, expressed in volts.

[0070] Step 3: Determine the chopper sleep time.

[0071] The DC / DC converter module uses a chopping method for voltage conversion. The chopping sleep parameters are calculated using the following formula:

[0072]

[0073] t sleep This indicates the chopper sleep time, in seconds;

[0074] C out This indicates the capacitance value of the voltage regulator capacitor, expressed in units.

[0075] This represents the forward chopper threshold voltage, measured in volts.

[0076] This represents the reverse chopper threshold voltage, in volts.

[0077] I load This represents the current required for the passive wireless intelligent microsystem to operate normally, measured in amperes.

[0078] The intelligent microsystem management module balances environmental energy acquisition and intelligent microsystem energy consumption to monitor the operating status of wind turbine blades. The workflow of the intelligent microsystem management module is as follows: Figure 3 As shown, the energy obtained from the environment is denoted as E0, the energy required for the data acquisition module to operate is denoted as E1, the energy required for the local storage module to operate is denoted as E2, the energy required for the remote transmission module to operate is denoted as E3, the energy required for the local edge computing module to operate is denoted as E4, the energy required for the human-computer interaction module to operate is denoted as E5, and the energy required for the power management module to operate is denoted as E6.

[0079] Definition: Minimum energy requirement is E min And the following formula is given:

[0080] E min =E1+E2+E5+E6;

[0081] The intelligent microsystem management module works as follows:

[0082] First, determine if E1 > E min If the system is established, it will collect data from the wind turbine blade monitoring sensors and store the collected data locally; otherwise, it will control the power energy management module to continue energy storage operations and display the working status of the intelligent microsystem in the human-machine interaction module.

[0083] Second, determine if (E1-E min If E3 is true, the collected blade operating status information will be transmitted remotely; otherwise, the power energy management module will continue to perform energy storage operations, and the working status of the intelligent microsystem will be displayed in the human-machine interaction module.

[0084] Third, determine if (E1-E min If -E3) > E4 is true, then local edge computing is performed on the collected blade operating status data, and the results of the local edge computing are stored in the local storage module; otherwise, the power energy management module is controlled to continue energy storage operation, and the working status of the intelligent microsystem is displayed in the human-machine interaction module.

[0085] The wireless communication module transmits the raw data of the wind turbine blade operating status sensed by the intelligent microsystem and the results of local edge computing processing wirelessly to the local wireless communication terminal of the wind turbine. The local wireless communication terminal then transmits the wind turbine blade operating status information to the wind farm control center through the field fiber optic ring network, realizing centralized display and control of the wind turbine blade operating status information.

[0086] The local edge computing module includes a data preprocessing module, a state information feature extraction module, a health status assessment module, and a data compression module. The data preprocessing module performs noise reduction and trend term removal on the digital information reflecting the blade's operating status to obtain a high signal-to-noise ratio (SNR) digital signal. The state information feature extraction module processes the high SNR digital signal to obtain feature information reflecting the blade's operating modes. The health status assessment module, starting from the feature information of the operating modes and combining it with health status pattern features, assesses the health status of the wind turbine blades. The data compression module compresses the raw data obtained from the wind turbine blade state sensing module and the output information obtained from the edge computing module, reducing the amount of data transmitted wirelessly and lowering the energy requirements of the passive wireless intelligent microsystem.

[0087] The local storage module stores the compressed raw data of the wind turbine blade status and the health status information obtained by the edge computing module locally. This allows the two energy-intensive tasks of local edge computing and wireless transmission to be staggered in time, avoiding the two processes from running simultaneously and reducing energy consumption.

[0088] The human-machine interface (HMI) module provides real-time feedback on the operating status of the passive wireless intelligent microsystem. Through this module, users can monitor the system's energy storage, energy consumption, and operational node information in real time. The HMI module includes a local information interaction module and a remote information interaction module. The local module displays the system's operating information locally, while the remote module wirelessly transmits this information to the wind farm's central control center for display. Attached Figure Description

[0089] Figure 1 Passive wireless intelligent microsystem architecture diagram.

[0090] Figure 2 Power management module structure diagram.

[0091] Figure 3 Workflow diagram of the intelligent microsystem management module.

[0092] Figure 4 Structure diagram of an environmental energy harvesting module based on mechanoelastic damping.

[0093] Figure 5 Structure diagram of an environmental energy harvesting module based on electromagnetic damping.

[0094] Figure 6 Power management module implementation structure diagram.

[0095] Figure 7 Structure diagram of intelligent microsystem management module. Detailed Implementation

[0096] The environmental energy harvesting module includes an environmental energy conversion module and a power generation module. Its implementation methods include, but are not limited to, converting environmental vibration energy into electrical energy. The steps for harvesting energy based on environmental vibration are as follows:

[0097] Step 1: Estimate the energy consumption E of the passive wireless intelligent microsystem.

[0098] Step 2: Estimate the energy range that the environmental energy acquisition module can acquire.

[0099] Vibration data of wind turbine blades during power generation and operation are collected, and power spectrum analysis is performed on the data. The frequency range corresponding to the maximum energy in the power spectrum is analyzed, and parameters for an environmental energy acquisition module are designed for this frequency range. The maximum vibration energy that an environmental energy acquisition module can acquire from the blade's operating environment is estimated using the following formula:

[0100]

[0101] Pmax This indicates the maximum energy that the environmental energy harvesting module can harvest from the blade vibration environment, measured in joules.

[0102] m represents the mass of the permanent magnet in the environmental energy conversion module, and the unit is kilograms;

[0103] ω0 represents the frequency corresponding to the maximum value of vibration energy distribution in the environment, and the unit is radians per second;

[0104] x max This represents the maximum vibration displacement of the permanent magnet, expressed in meters.

[0105] ξ represents the damping ratio of the vibration environment acquisition module, which is dimensionless.

[0106] The x value is determined based on the internal installation location of the wind turbine blades and the lightning protection requirements. max value;

[0107] ω0 is determined based on the energy distribution characteristics of the vibration power spectrum of wind turbine blades;

[0108] Estimate the density, shape, geometric parameters, and mass m of the permanent magnet based on the internal installation space constraints of the wind turbine blade;

[0109] Based on the frictional forces of the permanent magnet material and the external environment of the permanent magnet's motion, the damping ratio ξ of the vibration environment acquisition module is determined experimentally.

[0110] According to P max The size of E and the energy threshold determine the number of environmental energy harvesting modules to ensure that the energy requirements of the passive wireless intelligent microsystem are met.

[0111] Step 3: Determine the structure of the environmental energy harvesting module.

[0112] The structure of the environmental energy harvesting module can be implemented in ways including, but not limited to, an environmental energy harvesting structure based on a mechanical elastic damping structure and an environmental energy harvesting structure based on an electromagnetic damping structure.

[0113] Environmental energy harvesting structures based on mechanoelastic damping structures, such as Figure 4 As shown, it includes: an environmental energy harvesting module fixing surface (1), an environmental energy harvesting module shell (2), a power generation coil winding tube (3), a power generation coil (4), a moving permanent magnet (5), a spring (6), and a mechanical damper (7). The moving permanent magnet (5), spring (6), and mechanical damper (7) are defined as an environmental energy conversion module, which converts the vibration energy in the environment into the kinetic energy of the permanent magnet (5). The power generation coil winding tube (3) and power generation coil (4) are defined as a power generation module, which converts the kinetic energy of the permanent magnet (5) into electrical energy.

[0114] Environmental energy harvesting structures based on electromagnetic damping structures, such as Figure 5 As shown, the module includes: an environmental energy harvesting module shell (1), a top permanent magnet (2), a power generation coil winding tube (3), a top power generation cable (4), a moving permanent magnet (5), a bottom power generation coil (6), a bottom permanent magnet (7), and an environmental energy harvesting module fixing surface (8). The top permanent magnet (2), the moving permanent magnet (5), and the bottom permanent magnet (7) are defined as an environmental energy conversion module, which converts the vibration energy in the environment into the kinetic energy of the moving permanent magnet (5). The power generation coil winding tube (3), the top power generation coil (4), and the bottom power generation coil (6) are defined as a power generation module, which converts the kinetic energy of the moving permanent magnet (5) into electrical energy.

[0115] Step 4: Determine the parameters of the environmental energy conversion module.

[0116] The motion characteristics of the permanent magnet in an environmental energy harvesting structure based on a mechanoelastic damping structure are described by the following equation:

[0117]

[0118] In the above formula:

[0119] x represents the vibration displacement of the moving permanent magnet, in meters;

[0120] m represents the mass of the moving permanent magnet, and the unit is kilogram;

[0121] c represents mechanical damping, which is dimensionless;

[0122] k represents the spring constant, measured in Newtons per meter (N / m).

[0123] g represents the acceleration due to gravity, and the unit is meters per second squared.

[0124] ω0 represents the rotational speed of the wind turbine hub during operation, measured in radians per second.

[0125] t represents the operating time of the wind turbine generator, in seconds;

[0126] θ0 represents the initial phase between the wind turbine blade and the vertical plane, and the unit is radians;

[0127] l represents the distance between the center of the wind turbine hub and the equilibrium position of the permanent magnet, in meters.

[0128] When the natural frequency ω of the environmental energy conversion module is equal to the hub rotation frequency during wind turbine operation, the vibration energy acquired by the environmental energy conversion module is at its maximum. At this time, the parameters k and m of the environmental energy conversion module satisfy the following formula:

[0129]

[0130] After determining the permanent magnet m in step 2, the elastic coefficient k of the environmental energy conversion module can be determined using the above formula.

[0131] The vibration characteristics of the moving permanent magnet in an environmental energy harvesting structure based on electromagnetic damping are described by the following equation:

[0132]

[0133] In the above formula:

[0134] x represents the vibration displacement of the moving permanent magnet, and the unit is meters;

[0135] m represents the mass of the moving permanent magnet, and the unit is kilogram;

[0136] c represents mechanical damping, which is dimensionless;

[0137] B1 represents the magnetic field strength of the top permanent magnet at the vibration displacement x, and the unit is Tesla;

[0138] B2 represents the magnetic field strength of the bottom permanent magnet at the vibration displacement x, and the unit is Tesla;

[0139] V represents the volume of the moving permanent magnet, measured in cubic meters;

[0140] g represents the acceleration due to gravity, and the unit is meters per second squared.

[0141] ω0 represents the rotational speed of the wind turbine hub during operation, measured in radians per second.

[0142] t represents the operating time of the wind turbine generator, in seconds;

[0143] θ0 represents the initial phase between the wind turbine blade and the vertical plane, and the unit is radians;

[0144] l represents the distance between the center of the wind turbine hub and the equilibrium position of the permanent magnet, in meters.

[0145] B1 is expressed by the following formula:

[0146]

[0147] B r1 The remanence of the top permanent magnet is expressed in Tesla.

[0148] D1 represents the height of the top permanent magnet, in millimeters;

[0149] r represents the radius of the top permanent magnet, in millimeters;

[0150] l0 represents the equilibrium position of the moving permanent magnet, in millimeters;

[0151] x represents the distance from the surface of the top permanent magnet, in millimeters;

[0152] B2 is expressed by the following formula:

[0153]

[0154] B r2 This indicates the remanence of the permanent magnet at the bottom, measured in Tesla.

[0155] D2 represents the height of the bottom permanent magnet, in millimeters;

[0156] r represents the radius of the bottom permanent magnet, in millimeters;

[0157] l0 represents the equilibrium position of the moving permanent magnet, in millimeters;

[0158] x represents the distance from the surface of the top permanent magnet, in millimeters.

[0159] After determining the moving permanent magnet m in step 2, based on the fact that the natural frequency described by the vibration characteristics of the moving permanent magnet is equal to the frequency corresponding to the maximum distribution of vibration energy in the operating environment of the wind turbine blade, the mass, material, height, and remanence of the top and bottom permanent magnets are determined by optimization method and field experiment method.

[0160] The blade state sensing module can be implemented using, but is not limited to, vibration acceleration sensors, vibration velocity sensors, vibration displacement sensors, strain sensors, temperature sensors, acoustic fingerprint sensors, acoustic emission sensors, ultrasonic sensors, and infrared sensors.

[0161] The power management module is implemented in ways including but not limited to... Figure 7 The diagram shows the use of a dedicated power management chip. The input to this chip is the AC voltage output from the ambient energy harvesting module. This AC voltage is converted to DC voltage by the chip's internal integrated rectifier module and used to charge the energy storage capacitor. The chip's internal integrated DC / DC converter module then converts the energy storage capacitor voltage to different voltage levels. A voltage regulator capacitor provides a stable and consistent operating voltage for the chip's normal operation.

[0162] The intelligent microsystem management module can be implemented in ways including but not limited to... Figure 7The diagram shows interfaces for the environmental energy harvesting module, power management module, power bus, management unit, data bus, edge computing module, communication module, storage module, and status awareness module. The environmental energy harvesting module interface connects multiple environmental energy harvesting modules via fixed slots to meet the energy requirements of the passive wireless intelligent microsystem. The power management module interface connects to the power management module via a plug-in connection, adapting to different application scenarios. The power bus provides power to the various modules of the intelligent microsystem by laying different voltage levels on the main board of the intelligent microsystem management module. The management unit, the core unit of the intelligent microsystem management module, is implemented using an MCU intelligent microprocessor chip. The data bus connects the various modules of the intelligent microsystem and the management unit via data lines of different protocols laid on the main board of the intelligent microsystem management module. The edge computing module, communication module, storage module, and status awareness module all interact with the management unit through the data bus.

[0163] The wireless communication module can be implemented using, but is not limited to, Zigbee, LoRa, WiFi, and BLE wireless communication methods.

[0164] The edge computing module is implemented in ways including but not limited to signal denoising, time-domain waveform feature value calculation, spectrum analysis, envelope spectrum analysis, time-spectrum analysis, and fault mode identification.

[0165] The local storage module can be implemented in ways including but not limited to internal and external FLASH storage, CF card storage, and SD card storage.

[0166] The human-computer interaction module can be implemented in ways including but not limited to using different combinations of lighting and flashing of multi-digit indicator lights to indicate the working status of the passive wireless intelligent microsystem.

Claims

1. A passive wireless smart microsystem for wind turbine blade condition monitoring, comprising: The environmental energy acquisition module, the blade state sensing module, the power energy management module, the intelligent microsystem management module, the wireless communication module, the edge computing module, the local storage module and the human-computer interaction module; The environmental energy acquisition module includes an environmental energy conversion module and a power generation module, and the design process of the environmental energy acquisition module is as follows: Step 1: Estimate the energy consumption of the passive wireless intelligent microsystem: Energy consumption required for passive wireless smart microsystems in joules, is estimated as follows: represents the energy required for the data collection work, in joules; Elocal represents the energy required for the local storage work, in joules; Erepresents the energy required for the remote transmission work, in joules; E represents the energy required for the edge computing job, in joules; E represents the energy required for human-computer interaction work, unit joule; E represents the energy required for the power energy management module to work, in joules; Step 2: Estimate the energy range that can be acquired by the environmental energy acquisition module: Substep 1: Evaluate the available vibration energy, electromagnetic energy, noise energy, static energy, temperature difference energy and strain energy in the environment; Substep 2: Calculate the environmental energy density distribution to determine the frequency interval with the maximum environmental energy distribution; Substep 3: Estimate the energy range that can be acquired by the environmental energy acquisition module in theory according to the frequency interval corresponding to the maximum environmental energy distribution; Substep 4: Determine the number of environmental energy acquisition modules according to the total energy and energy margin determined in substep 1 and step 1 to ensure that the energy demand of the passive wireless intelligent microsystem is met; Step 3: Determine the structure of the environmental energy acquisition module: Substep 1: Determine the structure of the environmental energy conversion module that resonates, in the operation process of the wind turbine generator set, the natural frequency of the environmental energy conversion module resonates with the frequency corresponding to the maximum environmental energy distribution, in this working condition, the environmental energy conversion module converts the environmental energy into the energy form that can be directly used for power generation to the greatest extent; Substep 2: Determine the structure of the power generation module that matches the impedance, the power generation module itself has an internal impedance, and the passive wireless intelligent microsystem itself as a load also has an impedance, when the internal impedance of the power generation module and the load impedance match, the power output by the power generation module is maximum; Step 4: Determine the parameters of the environmental energy conversion module: Substep 1: Determine the geometric size range and mass range of the environmental energy acquisition module according to the spatial constraints around the components of the wind turbine generator set and the lightning environment characteristics of the wind farm; Substep 2: Determine the initial value of the parameters of the environmental energy conversion module according to the frequency interval corresponding to the maximum environmental energy distribution determined in substep 2 of step 2; Substep 3: After the initial value of the parameters of the environmental energy conversion module is determined, the final value of the parameters of the environmental energy conversion module is finally determined according to the optimization method and the field test method; Step 5: Determine the parameters of the power generation module: The power generation module parameters include the overall length of the coil , the number of turns of the coil , the internal resistance of the coil , the coil material and the coil fixed center position; Substep 1: Determine the fixed center position of the power generation coil: The fixed center position of the power generation coil is the distance between the center position of the power generation coil and the vibration balance position of the moving permanent magnet, which is determined by the balance position of the moving permanent magnet in the environmental energy conversion module; Substep 2: The length of the coil is determined by the following formula: In the formula, denotes the total length of the coil; representing the magnetic flux of the permanent magnet, determined by the permanent magnet selected in sub-step 1 ; ωrepresents the hub rotational speed during operation of the wind turbine generator set; represents the distance between the center of the hub of the wind turbine generator and the balance position of the permanent magnet; represents the open circuit voltage of the generator coil, determined by the minimum voltage of the power supply energy management module; Substep 3: The number of turns of the coil is determined by the following formula: Indicates the diameter of the generating coil; Indicates the number of turns in the generator coil winding; Sub-step 4: Internal resistance of power generation coil When the load resistance is equal to the internal resistance of the power generation coil, the power generation module outputs the maximum power, and the coil material is determined by the following formula: This indicates the internal resistance of the generating coil; represents the resistivity of the power coil material; Ltotal represents the overall length of the power coil; denotes the cross-sectional area of the conductor wire of the power generation coil.

2. The passive wireless smart microsystem for wind turbine blade condition monitoring of claim 1, wherein: The power energy management module includes a rectifier module, a charging module, an energy storage module and a voltage conversion module, and the design process of the power energy management module is as follows: Step 1: Determine the energy storage capacitor: The rectifier module outputs a direct current voltage And the energy storage capacitor is charged, and the obtained vibration energy is stored in the energy storage capacitor. The parameters of the energy storage capacitor are designed according to the following formula: E represents the energy required for the passive wireless smart microsystem to work properly, in joules; C represents the capacitance of the energy storage capacitor, in Farads; Vdc represents the DC voltage output by the rectifier module, in volts; Vth represents a threshold voltage of the rectifier module, in volts; Step 2: Determine the voltage stabilizing capacitor: The parameters of the voltage stabilizing capacitor are designed according to the following formula: represents the capacitance value of the voltage stabilizing capacitor, unit: F I represents the current required for the passive wireless smart microsystem to work properly, in amperes; I0represents the current of the passive wireless smart microsystem in the idle state, in amperes; T represents the normal working time of the passive wireless intelligent microsystem, in seconds; Vmax represents the maximum value of the passive wireless smart microsystem load operating voltage fluctuation, in volts; Vmin represents the minimum value of the passive wireless smart microsystem load operating voltage fluctuation, in volts; Step 3: Determine the chopping sleep time: The DC / DC conversion module adopts the chopping method for voltage conversion, and the chopping sleep parameter is calculated according to the following formula: represents the chopping sleep time in seconds; represents the capacitance value of the voltage stabilizing capacitor, unit: F Vth represents a forward chopper threshold voltage, in volts; represents the reverse chopping threshold voltage in volts; I represents the current in amperes required for the passive wireless smart microsystem to function properly.

3. The passive wireless smart micro system for wind turbine blade condition monitoring of claim 1, wherein: The intelligent micro-system management module balances the energy acquisition from the environment and the energy consumption of the intelligent micro-system. The energy acquired from the environment is denoted as , the energy required for the data acquisition module to work is denoted as , the energy required for the local storage module to work is denoted as , the energy required for the remote transmission module to work is denoted as , the energy required for the local edge computing module to work is denoted as , the energy required for the human-computer interaction module to work is denoted as , and the energy required for the power energy management module to work is denoted as ; Definition: The minimum energy requirement is and has the following formula: The intelligent microsystem management module works as follows: First, if is established, the wind turbine blade state monitoring sensor data acquisition is carried out, and the collected data is stored locally; otherwise, the power energy management module is controlled to continue the energy storage operation, and the working state of the intelligent microsystem is displayed in the human-computer interaction module. Second, if the following is true, then the collected blade operating state information is transmitted remotely; otherwise, the power energy management module is controlled to continue the energy storage operation, and the working state of the intelligent microsystem is displayed in the human-machine interaction module. Second, if the following is true, then the collected blade operating state information is transmitted remotely; otherwise, the power energy management module is controlled to continue the energy storage operation, and the working state of the intelligent microsystem is displayed in the human-machine interaction module. Third, if the following condition is met then the collected blade operating state data is subjected to local edge computing, and the result of the local edge computing is stored in the local storage module. If not, the power energy management module is controlled to continue the energy storage operation, and the working state of the intelligent micro system is displayed in the human-computer interaction module.

4. The passive wireless smart microsystem for wind turbine blade condition monitoring of claim 1, wherein: The intelligent micro system management module includes an environment energy acquisition module interface, a power energy management module interface, a power bus, a management unit, a data bus, an edge computing module interface, a communication module interface, a storage module interface, and a state sensing module interface; the environment energy acquisition module interface connects multiple environment energy acquisition modules according to actual needs on site through a fixed card slot mode to meet the energy needs of the passive wireless intelligent micro system; the power energy management module interface connects the power energy management module through a plug-in fixed mode to adapt to different application scenarios; The power bus realizes power supply to each module of the intelligent micro system by laying different voltage lines on the mainboard of the intelligent micro system management module; The management unit is the core unit of the intelligent micro system management module and is realized by using an MCU intelligent microprocessor chip; the data bus is realized by laying different protocol data lines on the mainboard of the intelligent micro system management module, and the data bus connects the data communication between each module of the intelligent micro system and the management unit; the edge computing module, the communication module, the storage module, and the state sensing module interact with the management unit through the data bus.

5. The passive wireless smart micro system for wind turbine blade condition monitoring of claim 1, wherein: The environment energy acquisition module structure based on a mechanical elastic damping structure includes an environment energy acquisition module fixing surface, an environment energy acquisition module shell, a power generation coil winding pipe, a power generation coil, a moving permanent magnet, a spring, and a mechanical damping; the moving permanent magnet, the spring, and the mechanical damping are defined as an environment energy conversion module to convert vibration energy in the environment into kinetic energy of the moving permanent magnet; the power generation coil winding pipe and the power generation coil are defined as a power generation module to convert the kinetic energy of the moving permanent magnet into electric energy.

6. The passive wireless smart micro system for wind turbine blade condition monitoring of claim 1, wherein: The environment energy acquisition module structure based on an electromagnetic damping structure includes an environment energy acquisition module shell, a top permanent magnet, a power generation coil winding pipe, a top power generation coil cable, a moving permanent magnet, a bottom power generation coil, a bottom permanent magnet, and an environment energy acquisition module fixing surface; the top permanent magnet, the moving permanent magnet, and the bottom permanent magnet are defined as an environment energy conversion module to convert vibration energy in the environment into kinetic energy of the moving permanent magnet; the power generation coil winding pipe, the top power generation coil, and the bottom power generation coil are defined as a power generation module to convert the kinetic energy of the moving permanent magnet into electric energy.

7. The passive wireless smart micro system for wind turbine blade condition monitoring of claim 1, wherein: The motion characteristics of the moving permanent magnet of the environment energy acquisition module structure based on a mechanical elastic damping structure are described by the following equation: In the above equation: represents the vibrational displacement of the moving permanent magnet in meters; m represents the mass of the moving permanent magnet, in kilograms; represents the mechanical damping, dimensionless; k represents the spring constant of the spring, in N / m; g represents the acceleration due to gravity, in meters per second squared; ω represents the hub rotational speed during the wind turbine operation process, in units of rad / s; represents the wind turbine operating time in seconds; initial phase between the wind turbine blade and the vertical plane, in radian; D represents the distance between the center of the hub of the wind turbine generator and the balance position of the permanent magnet, in meters; When the natural frequency of the environmental energy conversion module is equal to the hub rotation frequency during operation of the wind turbine generator set, the environmental energy conversion module obtains the maximum vibration energy, at this time, the environmental energy conversion module parameters and satisfy the following formula: 。 8. The passive wireless smart micro system for wind turbine blade condition monitoring of claim 1, wherein: The vibration characteristics of the moving permanent magnet of the environment energy acquisition module structure based on an electromagnetic damping structure are described by the following equation: In the above equation: represents the vibrational displacement of the moving permanent magnet in meters; m represents the mass of the moving permanent magnet, in kilograms; represents the mechanical damping, dimensionless; Htop represents the magnetic field strength of the top permanent magnet at the vibration displacement in Tesla; Hb represents the magnetic field strength of the bottom permanent magnet at the vibration displacement Hb represents the magnetic field strength of the bottom permanent magnet at the vibration displacement V represents the volume of the moving permanent magnet in cubic meters; g represents the acceleration due to gravity, in meters per second squared; ω represents the hub rotational speed during the wind turbine operation process, in units of rad / s; represents the wind turbine operating time in seconds; initial phase between the wind turbine blade and the vertical plane, in radian; D represents the distance between the center of the hub of the wind turbine generator and the balance position of the permanent magnet, in meters; is represented by the formula: represents the remanence of the top permanent magnet in Tesla; Htop represents the height of the top permanent magnet in millimeters; RPMG represents the radius of the top permanent magnet in millimeters; represents the equilibrium position of the moving permanent magnet in millimeters; represents the distance from the top permanent magnet surface in millimeters; is represented by the formula: represents the remanence of the bottom permanent magnet in Tesla; Hbot represents the height of the bottom permanent magnet in millimeters; RPMG represents the radius of the bottom permanent magnet in millimeters; represents the equilibrium position of the moving permanent magnet in millimeters; represents the distance from the top permanent magnet surface in millimeters.

Images