High-frequency narrow-band stress wave wireless sensing system for structural damage detection

Abstract

A high-frequency narrowband stress wave wireless sensing system for structural damage detection belongs to the technical field of stress wave sensing, and comprises a high-frequency narrowband stress wave wireless sensor used for sensing high-frequency narrowband stress waves generated by mechanical structural damage; the signal conditioning and processing unit is used for AD acquisition and characteristic calculation processing of the high-frequency narrow-band analog electrical signals; the intelligent gateway is used for gathering the characteristic parameter data of each wireless sensor and reporting the characteristic parameter data to the server in a communication mode; the data monitoring terminal is used for realizing data monitoring and realizing data processing, local calculation and downloading storage by accessing the intelligent gateway; and the power supply management unit is used for supplying power to the high-frequency narrow-band stress wave wireless sensor and the signal conditioning and processing unit. The reliability and the detection efficiency of early-stage damage monitoring are remarkably improved, and the service life is prolonged.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of stress wave sensing and relates to a high-frequency narrow-band stress wave wireless sensing system for structural damage detection. BACKGROUND

[0002] In the modern engineering field, structural damage detection is crucial to ensure the safe operation of mechanical structures and equipment. With the development of material science and engineering technology, mechanical equipment has shown significant characteristics of large-scale and precision. At the same time, the alternating load and multi-source interference borne by the structure are increasingly complex, and the traditional periodic manual detection method has been difficult to meet the real-time, accurate and quantitative monitoring needs. High-frequency stress wave detection technology can sense the stress wave signals generated inside the structure due to damage in real time, thereby realizing the advantage of early warning of structural damage, and gradually becoming one of the important means of structural health monitoring.

[0003] Currently, high-frequency wired narrow-band stress wave sensors have been widely used in the field of structural damage detection. The core components of such sensors usually use piezoelectric ceramics of specific materials as sensitive elements. By carefully designing the piezoelectric material, size and geometry, the natural frequency is concentrated in the high-frequency narrow-band range, and the stress wave response in the frequency band of 100 kHz - 500 kHz can generally be achieved. When the structure produces high-frequency narrow-band stress waves due to damage, the piezoelectric ceramic rapidly generates electric charges, and the charge quantity is proportional to the stress wave intensity. In the signal transmission link, it relies on coaxial cables or specially designed shielded cables to connect the sensor and the signal acquisition and processing equipment. The cable has low resistance and high shielding characteristics, which can effectively reduce signal attenuation and external electromagnetic interference during transmission. For example, in the local damage detection of mechanical structures, the sensor is directly pasted on the key stress part, and the cable is extended along the structure surface slot or internal reserved pipeline to the special detection instrument to ensure stable signal transmission. In a similar cable stress monitoring scenario of large bridges, multiple high-frequency wired narrow-band stress wave sensors are evenly distributed along the cable, and the cables are collected to the signal acquisition station of the bridge management center to realize continuous monitoring of the health status of the cable. However, such sensors require a lot of manpower and material resources when wiring, and the cable route needs to be planned in advance to avoid conflicts with other facilities, and it is difficult to find cable fault points in subsequent maintenance. In the detection of complex and large structures, the disadvantages are particularly obvious.

[0004] In addition to the wired high-frequency narrow-band stress wave sensor, the low-frequency narrow-band stress wave wireless sensor has developed rapidly in recent years, aiming to solve the wiring problem of traditional wired sensors. It is often based on micro-electro-mechanical system (MEMS) technology to build a small and portable sensor node. In the sensor unit, low-frequency sensitive piezoelectric film or specially designed piezoresistive elements can respond to <20 kHz low-frequency narrow-band stress waves. For example, the low-frequency narrow-band stress wave wireless sensor commonly used for industrial pipeline leakage detection, the piezoelectric film is attached to the outer wall of the pipeline. When the pipeline produces low-frequency stress waves due to corrosion, cracks, etc., the film generates a weak electrical signal. In terms of signal processing and transmission, the sensor node integrates a low-power microprocessor and a wireless communication module. Common wireless communication protocols include Bluetooth Low Energy (BLE), ZigBee, etc. The microprocessor performs preliminary amplification, filtering, and feature extraction on the collected signals, and then sends the data to the receiving terminal through the wireless communication module after reducing the data volume. However, low-frequency stress wave signals are easily disturbed by mechanical background interference such as medium inhomogeneity and environmental noise, resulting in signal distortion. At the same time, Bluetooth, ZigBee, and other wireless communication technologies are prone to signal packet loss and delay in complex electromagnetic environments, which cannot meet the demand for accurate and real-time detection of early structural damage. For example, the Chinese invention patent with patent application number 202411967914.5 discloses a stress testing device, equipment and system.

[0005] Existing high-frequency wired narrow-band stress wave sensors rely on coaxial cables or shielded cables to transmit signals, and require physical connections between the measured structure and the equipment. Due to the need to deploy cables across complex obstacles, adapt to high-altitude or narrow-space operations, resulting in high installation costs, long time-consuming, and long-term use prone to environmental corrosion or mechanical wear and tear, making maintenance difficult. The core disadvantage is that high-frequency signal transmission relies on wired connections, and a workbench computer is required for data processing, which is bulky and has poor deployment flexibility in complex scenarios such as large mechanical equipment, making it difficult to meet the demand for convenient detection.

[0006] Existing low-frequency narrow-band stress wave wireless sensors use Bluetooth, ZigBee, and other wireless transmission technologies, but due to the design principles of the sensor, they can only respond to <20 kHz low-frequency stress waves. However, 100-500 kHz high-frequency narrow-band stress waves generated by early structural damage (such as micro-crack propagation signals) cannot be effectively captured, and low-frequency signals are easily disturbed by environmental noise, resulting in inaccurate damage feature extraction and delayed early warning. The core disadvantage is that low-frequency detection cannot match the high-frequency signal characteristics of structural damage, resulting in insufficient detection accuracy and lack of real-time performance. SUMMARY

[0007] In order to overcome the low detection accuracy and the lack of real-time performance of the existing low-frequency narrow-band stress wave wireless sensor, the application provides a high-frequency narrow-band stress wave wireless sensing system for structural damage detection, which adopts a wireless transmission architecture to replace the traditional wired connection, breaks away from the wiring restriction, and realizes flexible installation of the sensor in a complex structure; meanwhile, according to different structural damage frequency bands, the piezoelectric structure of the high-frequency narrow-band stress wave sensor is customized to make the working bandwidth consistent with the damage frequency band; when the working bandwidth of the high-frequency narrow-band stress wave sensor is consistent with the damage frequency band, due to the resonance effect, the sensor mainly senses the high-frequency damage stress wave and has no response to the low-frequency interference, realizes accurate sensing of the high-frequency damage stress wave, and greatly improves the anti-low-frequency interference capability of the sensor. In addition, combined with edge computing and feature extraction algorithm, only the damage feature parameters are transmitted, the accurate sensing of the high-frequency stress wave of the early structural damage is realized without physical wiring, and the low-power operation is realized by only transmitting the feature parameters, which significantly improves the reliability, detection efficiency and service life of the early damage monitoring.

[0008] The technical solution adopted by the application to solve the technical problems is: A high-frequency narrow-band stress wave wireless sensing system for structural damage detection, comprising: A high-frequency narrow-band stress wave wireless sensor is used to realize sensing of the high-frequency narrow-band stress wave generated by mechanical structural damage, first, the piezoelectric ceramic resonance characteristic is used to realize electromechanical conversion of the high-frequency stress wave; second, a high-frequency narrow-band filter circuit is used to realize amplification and filtering of the electrical signal, and a high signal-to-noise ratio damage high-frequency narrow-band analog electrical signal is output through the sensor SMA interface; A signal conditioning and processing unit is used for AD acquisition and feature calculation processing of the high-frequency narrow-band analog electrical signal, first, the analog electrical signal is converted into a digital electrical signal through AD acquisition; second, the key feature parameters of the signal are obtained by calculating the digital electrical signal sequence; An intelligent gateway is used to gather the feature parameter data of each wireless sensor and report to the server through communication; A data monitoring terminal is used to realize data monitoring, data processing, local calculation and download saving by accessing the intelligent gateway; A power management unit is used to supply power to the high-frequency narrow-band stress wave wireless sensor and the signal conditioning and processing unit.

[0009] Further, the high-frequency narrow-band stress wave wireless sensor is designed with a low-impedance matching layer and a temperature compensation circuit, and the low-impedance matching layer is connected with the piezoelectric ceramic. This scheme accurately senses the high-frequency information of structural damage.

[0010] Further, in the signal conditioning and processing unit, the key feature parameters include amplitude, energy, rise time and fall time.

[0011] In the signal conditioning and processing unit, the edge computing and feature extraction algorithm comprises the following steps: Step 1, collecting a high-frequency stress wave response original signal sequence; Step 2, signal filtering processing; Step 3, calculating amplitude, energy, rise time and fall time based on threshold value.

[0012] The intelligent gateway reports to the server through 4G or wired communication mode, and the key feature parameters are transmitted to the intelligent gateway through the industrial LoRa modulation chip.

[0013] The intelligent gateway has a secondary development interface to meet the needs of custom software in different scenarios.

[0014] The power management unit is provided with a wake-up and collection strategy module, which can prolong the service life of the power supply.

[0015] In the application, the high-frequency narrow-band piezoelectric sensor optimized for metal materials and fiber composite materials accurately perceives high-frequency band information of structural damage through low-impedance matching layer design and temperature compensation circuit, and improves the anti-interference ability of the sensor in a multi-source interference environment. At the same time, multiple filters can further improve the signal-to-noise ratio level; the feature parameters of the high-frequency damage stress wave signal after filtering are extracted, and then the feature parameters are transmitted by the LoRa line communication module to realize low-power long-distance transmission. Such transmission architecture not only effectively reduces the power consumption of wireless transmission, but also ensures the practicability and reliability of the high-frequency stress wave data evaluation results.

[0016] The beneficial effects of the application mainly include: 1. The application adopts a wireless transmission architecture, which is free from cable constraints and can be quickly deployed in complex environments such as large mechanical structures and wind turbine generators. At the same time, the edge computing module can calculate key feature parameters after an event is triggered. The feature parameters of the high-frequency signal are transmitted to the data transmission terminal through the LoRa wireless networking protocol, which realizes real-time and accurate detection of high-frequency signals while significantly reducing sensor power consumption. The power consumption is reduced by more than 75%, the single node endurance is more than 5 years, the deployment and operation cost is significantly reduced, and the stability of the detection system is improved. 2. The application customizes high-frequency narrow-band stress wave wireless sensors, which can accurately perceive 300kHz-500kHz high-frequency stress waves, effectively solving the detection lag and high energy consumption problems of the prior art. BRIEF DESCRIPTION OF DRAWINGS

[0017] Figure 1 It is a principle block diagram of a high-frequency narrow-band stress wave wireless sensing system for structural damage detection.

[0018] Figure 2 It is a flowchart of edge computing and feature extraction algorithm.

[0019] Figure 3 is a schematic diagram of a high-frequency narrow-band stress wave wireless sensor, wherein 1 is a shell, 2 is a backing layer, 3 is a piezoelectric ceramic, 4 is a low-impedance matching layer, 5 is a pin, and 6 is a temperature compensation circuit.

[0020] Figure 4 is a principle block diagram of a high-frequency narrow-band stress wave wireless sensor.

[0021] Figure 5 is a flowchart of a wake-up and collection strategy. DETAILED DESCRIPTION

[0022] The application will be further described below with reference to the accompanying drawings.

[0023] With reference to Figures 1-5 A high-frequency narrow-band stress wave wireless sensing system for structural damage detection comprises: A high-frequency narrow-band stress wave wireless sensor is used to realize sensing of high-frequency narrow-band stress waves generated by mechanical structural damage. First, electromechanical conversion of high-frequency stress waves is realized through piezoelectric ceramic resonance characteristics. Second, amplification and filtering of electrical signals are realized through a high-frequency narrow-band filtering circuit. The cascade of the two can greatly reduce structural low-frequency vibration and other external interference, realize sensing of early damage, and finally output high signal-to-noise ratio damage high-frequency narrow-band analog electrical signals through a sensor SMA interface. A signal conditioning and processing unit is used for AD collection and feature calculation and processing of high-frequency narrow-band analog electrical signals. First, AD collection can convert analog electrical signals into digital electrical signals. Second, calculation on the digital electrical signal sequence obtains key feature parameters of the signals. The feature parameters can directly reflect the structural damage state, and compared with traditional transmission of complete digital signal sequences, the data volume is greatly reduced, laying a foundation for lightweight low-power wireless transmission. An intelligent gateway is used to converge feature parameter data of various wireless sensors and report to a server through 4G or wired communication. Key feature parameters can be transparently transmitted to the intelligent gateway through an industrial LoRa modulation chip. In addition, the intelligent gateway also has a secondary development interface to meet the needs of customized software in different scenarios. A data monitoring terminal is used to realize data monitoring. Through access to the intelligent gateway, data processing, local calculation, download and saving can be realized. In addition, data model development can be carried out for different scenarios. A power management unit is used for power supply of the high-frequency narrow-band stress wave wireless sensor and the signal conditioning and processing unit. Through the development of a wake-up and collection strategy, the service life of the power supply can be prolonged.

[0024] With reference to Figure 2The signal conditioning and processing unit, wherein the key characteristic parameters include amplitude, energy, rise time and fall time. The edge computing and feature extraction algorithm comprises the following steps: Step 1, collect the high-frequency stress wave response original signal sequence; Step 2, signal filtering processing; Step 3, calculate the amplitude, energy, rise time and fall time based on the threshold value.

[0025] Referring to Figure 3 The high-frequency narrow-band stress wave wireless sensor is designed through a low-impedance matching layer and a temperature compensation circuit, and the low-impedance matching layer is connected with the piezoelectric ceramic. This scheme accurately perceives the high-frequency information of structural damage.

[0026] First, an axial blind hole for packaging the internal structure of the sensor and a radial through hole for connecting the pin 5 are processed on the shell 1; then the temperature compensation circuit 6 is placed at the bottom of the axial blind hole, the backing layer 2 is located in the axial blind hole, and the inner end of the backing layer 2 is in contact with the temperature compensation circuit 6; the piezoelectric ceramic 3 is arranged inside the backing layer close to the outer end; finally, the outer end of the piezoelectric ceramic 3 is connected with the low-impedance matching layer 4. In actual use, the low-impedance matching layer is in contact with the detection object (the fan blade in this embodiment).

[0027] Since the fan blade in this embodiment is a composite material, the traditional matching layer is mainly for metal materials, and the metal material has large density and high sound speed, that is, the acoustic impedance of the material is large, so if it is directly used, it will cause inaccurate perception of the damage signal and reduce the performance of the sensor. Therefore, the low-impedance matching layer is more suitable for early damage detection and online monitoring of the composite material of the fan blade.

[0028] Referring to Figure 4 The signal transmission process of the high-frequency narrow-band stress wave wireless sensor is as follows: Step 1, the blade stress wave mechanical signal is transmitted to the low-impedance matching layer; Step 2, the piezoelectric ceramic stress wave mechanical signal is converted into an electrical signal through electromechanical coupling; at the same time, the stress wave mechanical signal radiated from the rear end of the piezoelectric ceramic is transmitted to the backing layer and absorbed by the backing layer, preventing interference with the electrical signal generated by the piezoelectric ceramic.

[0029] Step 3, the stress wave electrical signal of the piezoelectric ceramic is transmitted to the temperature compensation circuit, and the compensated electrical signal is output through the pin.

[0030] Referring to Figure 5 The power management unit can prolong the service life of the power supply by formulating a wake-up and collection strategy.

[0031] In this embodiment, the sensor arrangement position is determined: when detecting early damage of large structure, sensor arrangement is the key to ensure accurate signal acquisition. Through the method of combining finite element modal analysis, stress field simulation and historical damage data, the damage-prone area is determined, and then combined with the stress wave propagation characteristics, the sensor arrangement position is optimized to eliminate mechanical background noise interference. At the same time, combined with historical damage data, redundant sensors are added in the damage-prone area to improve monitoring reliability. All sensors are designed with environmental adaptability to ensure stable operation under complex working conditions, and finally realize high-precision damage positioning and identification.

[0032] The sensor is tightly attached to the monitored structure by high-rigidity coupling agent or magnetic attraction, bolt fixation, etc., to ensure that the stress wave can be efficiently transmitted to the sensing part of the sensor.

[0033] Taking a large wind turbine blade as an example, through finite element mechanics analysis, the stress concentration parts and overall stress distribution of the blade structure can be determined, and on this basis, combined with historical damage cases, the scientific sensor arrangement points can be determined.

[0034] Based on the characteristics of large mechanical structure and high-frequency resonance principle, a high-frequency narrow-band piezoelectric sensor probe is designed. The sensor embeds the probe in the main body. Using the positive piezoelectric effect, the multi-frequency stress wave excited by early damage of the structure is converted into a micro-volt level charge signal. This sensor structure makes the sensor have extremely high sensitivity in the high-frequency band (100-500 kHz), and at the same time shows excellent suppression performance to low-frequency noise. It can achieve more than -40 dB significant attenuation to low-frequency vibration signals below 20 kHz.

[0035] In addition, the sensor has a low-impedance matching layer, which is suitable for metal, composite materials, etc.; it is pasted tightly on the surface of the blade through a high-strength epoxy adhesive layer, and the top is connected to the signal conditioning and processing unit in a low-noise connection mode (instead of traditional coaxial shielded cable, reducing wiring restrictions), to suppress electromagnetic interference. The wireless sensor adopts low-power design as a whole, integrates industrial-grade lithium battery inside, and has a working life of more than 5 years, which meets the lightning protection requirements. The built-in temperature compensation circuit ensures stable frequency response from -30℃ to 70℃, which meets the long-term monitoring requirements, and fully guarantees the ability to accurately capture early damage high-frequency stress waves.

[0036] In view of the problems of weak early damage high-frequency stress wave signals of large structure and complex environmental interference, a low-noise charge amplifier (input impedance > 1MΩ) is used. Through dynamic gain adjustment, the ability to acquire and amplify weak voltage signals at the acquisition port is improved. The design and working mode of the filter part are as follows: Detection threshold triggering mechanism: The edge collection system can exclude noise signals with amplitudes below a certain threshold by setting a certain threshold voltage. Threshold discrimination includes real-time detection threshold discrimination and post-evaluation threshold discrimination. Detection threshold discrimination refers to a noise exclusion method that sets the threshold type and threshold value to exclude noise from the acoustic emission raw data during real-time acoustic emission signal collection. For example, setting a 40 dB detection threshold in the detection process will exclude any stationary random interference signals with amplitudes below 40 dB from the collected data, which meets the detection requirements of high-frequency stress waves for early damage in large structures.

[0037] The high-frequency narrow-band stress wave wireless sensor has multiple adjustable bandwidth (20-400 kHz) analog filters built-in, which can further reduce low-frequency interference in the stress wave response signal and achieve amplification and conditioning of early damage stress wave signals.

[0038] The transmission part is based on the design concept of "feature parameter lightweight-low power consumption transmission", which realizes the balance between monitoring performance and energy consumption through high-frequency signal dimension reduction processing and LoRa technology optimization. The low-power master chip SCM621 supports DSP instruction set and integrates a floating-point operation unit FPU, which can control ADC sampling and data processing. The chip can extract stress wave feature parameters. The parameter calculation method is shown in Table 1;

[0039] After extracting the feature parameters, the signal conditioning and processing unit transmits them to the intelligent gateway through the industrial-grade LoRa modulation chip. The intelligent gateway aggregates data from various points and reports it to the server through 4G or wired communication for visual display and real-time monitoring of blade operating conditions. The intelligent gateway uses a self-developed SCM625 high-performance master core board developed with a Linux operating system, an Ethernet interface, and support for 10 / 100M adaptation. It provides multiple hardware communication interfaces and secondary software development interfaces to meet different application requirements and customize specialized application software. For industrial application scenarios, it uses anti-interference and anti-static design to cope with various complex and harsh industrial environments.

[0040] Conventional data uses event-driven transmission (transmission time interval or damage threshold trigger can be defined according to requirements), reducing invalid power consumption. Single-node endurance > 5 years, with an integrated industrial-grade replaceable lithium battery, meeting the wind turbine blade life cycle state monitoring requirements. Based on the feature parameters and damage mode recognition algorithm, the health status of each monitoring node is analyzed in real time.

[0041] The embodiment is verified by large-scale wind farm measurement, and the effectiveness and feasibility are verified. Through the whole link optimization of high-frequency stress wave accurate perception, feature parameter directional extraction and low-power wireless transmission, the deployment and energy consumption problem of high-frequency monitoring scene is solved, and the long-term online monitoring demand of large structures such as wind turbine blades is adapted.

[0042] The content described in the embodiments of the present specification is only a list of implementation forms of the inventive concept, and is only for the purpose of description. The protection scope of the present application should not be regarded as being limited to the specific forms described in the embodiments, and the protection scope of the present application also extends to equivalent technical means that can be thought of by those skilled in the art according to the inventive concept.

Claims

1. A high-frequency narrowband stress wave wireless sensing system for structural damage detection, characterized in that, The system includes: A high-frequency narrowband stress wave wireless sensor is used to sense high-frequency narrowband stress waves generated by mechanical structure damage. First, the electromechanical conversion of high-frequency stress waves is achieved through the resonant characteristics of piezoelectric ceramics. Second, the electrical signal is amplified and filtered through a high-frequency narrowband filter circuit, and a high signal-to-noise ratio high-frequency narrowband analog electrical signal of the damage is output through the sensor's SMA interface. The signal conditioning and processing unit is used for AD acquisition and feature calculation processing of high-frequency narrowband analog electrical signals. First, AD acquisition can convert analog electrical signals into digital electrical signals; second, the key feature parameters of the signal are calculated from the digital electrical signal sequence. The intelligent gateway is used to collect the characteristic parameter data of various wireless sensors and report them to the server via communication. The data monitoring terminal is used to monitor data and processes, calculates, and downloads data by accessing the smart gateway. The power management unit provides power to the high-frequency narrowband stress wave wireless sensor and the signal conditioning and processing unit.

2. The high-frequency narrowband stress wave wireless sensing system for structural damage detection as described in claim 1, characterized in that, The high-frequency narrowband stress wave wireless sensor uses a low-impedance matching layer design and a temperature compensation circuit, with the low-impedance matching layer connected to piezoelectric ceramics.

3. A high-frequency narrowband stress wave wireless sensing system for structural damage detection as described in claim 1 or 2, characterized in that, In the signal conditioning and processing unit, the key characteristic parameters include amplitude, energy, rise time, and fall time.

4. The high-frequency narrowband stress wave wireless sensing system for structural damage detection as described in claim 3, characterized in that, The signal conditioning and processing unit includes the following steps for edge computing and feature extraction algorithms: Step 1: Acquire the original signal sequence of high-frequency stress wave response; Step 2: Signal filtering processing; Step 3: Calculate the amplitude, energy, rise time, and fall time based on the threshold.

5. A high-frequency narrowband stress wave wireless sensing system for structural damage detection as described in claim 1 or 2, characterized in that, The smart gateway reports to the server via 4G or wired communication, and key characteristic parameters are transmitted to the smart gateway through an industrial-grade LoRa modulation chip.

6. A high-frequency narrowband stress wave wireless sensing system for structural damage detection as described in claim 1 or 2, characterized in that, The smart gateway has a secondary development interface to meet the needs of customized software in different scenarios.

7. A high-frequency narrowband stress wave wireless sensing system for structural damage detection as described in claim 1 or 2, characterized in that, The power management unit includes a wake-up and acquisition strategy module.

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