A wallboard structure health monitoring (SHM) sensor node network construction method

Abstract

The application discloses a kind of wallboard structure health monitoring SHM sensor node network construction methods, first, the transmission coefficient spectrum of Lamb wave is calculated, as the basis of frequency selection when Lamb wave carries out structure health monitoring to overall wallboard.The contour line of transmission Lamb wave energy is reasonably threshold set, in combination with the detection ability of sensor to defect and detection requirement, the coverable range of single sensor node is determined.The first receiving sensor is taken as starting point, based on the layout strategy of step-by-step recursion, the spatial layout of monitoring sensor network in overall wallboard is constructed, using the principle of minimum total length of all node links in overall sensor network, two competitive nodes with very close distance and approximately same coverage range are screened and removed, to achieve the purpose of optimizing sensor network constructed by step-by-step recursion method.The method can realize the layout of Lamb wave structure health monitoring sensor network in overall wallboard, and solve the monitoring problem in practical engineering.

Description

TECHNICAL FIELD

[0001] The application is a construction method of a wallboard structure health monitoring (SHM) sensor node network, belonging to the technical field of ultrasonic guided wave nondestructive testing and communication control, aiming at the structural health monitoring problem of large monolithic wallboards commonly used in aerospace, the monitoring sensor network of ultrasonic Lamb waves is constructed through the method, and large-area full-coverage monitoring of defects in the wallboard is realized. BACKGROUND

[0002] Metal monolithic wallboard is an important part of the aerodynamic shape of advanced aircraft in the field of aerospace, and is also the main load-bearing component of the wings, fuselages and fuel tanks of the aircraft. The monolithic wallboard adopts integrated forming processing technology, and there is no mechanical connection between the skin and the stiffener and other structural elements. Compared with the traditional riveted combined wallboard, the monolithic wallboard structure can reduce weight by 10%-30% and significantly improve strength, stiffness and sealing. The large metal monolithic wallboard structure of the wings, fuselages and fuel tanks of the aerospace aircraft is subjected to fatigue load and high-speed impact of external particles (such as hail, raindrops and dust, etc.) for a long time under the condition of high-speed variable load and extreme environment, which leads to frequent defects such as skin impact damage and fatigue cracks, seriously threatening the structural integrity and flight safety of the aircraft. Therefore, how to effectively obtain the defect information in the monolithic wallboard structure in real time is a hot and difficult problem in the field of aircraft health monitoring and life prediction.

[0003] Intelligent sensor network is the core foundation to solve the major engineering demand of aircraft structural health monitoring. Ultrasonic Lamb waves suitable for propagation in thin-walled plate and shell structures have been developed for Lamb wave detection technology of structural defects at home and abroad, and experiments have fully verified that Lamb waves have the advantages of long propagation distance and sensitivity to structural defects. Lamb wave technology has important application prospects in the structural health monitoring of aircraft metal monolithic wallboards, but there are still serious deficiencies, such as unclear propagation characteristics of Lamb waves in metal monolithic wallboard structures containing complex feature structures, and it is difficult to construct and design the Lamb wave sensor node network and optimize the selection of sensor network parameters.

[0004] In view of the above deficiencies, the application discloses a construction method of a wallboard structure health monitoring (SHM) sensor node network, which realizes the health monitoring of the plate structure by the Lamb wave through the reasonable arrangement of the sensor network monitoring nodes.

[0005] In the present application, the propagation characteristics of Lamb waves in metal monolithic wallboard are quantitatively characterized by calculating the transmission coefficient spectrum, which is used as the basis for frequency selection when Lamb waves are used for structural health monitoring of monolithic wallboard. In the frequency band with high transmission coefficient, the Lamb wave contour is drawn based on the equal-energy wave front of the transmitted Lamb wave, thereby guiding the spatial layout of the monitoring nodes on the contour. The construction of a lightweight, non-electromagnetic wave wireless communication sensor network that meets the airworthiness requirements of aircraft can effectively solve the problem of sensor spatial layout in monitoring the health status of complex structures using existing ultrasonic Lamb waves. SUMMARY

[0006] The present application aims to solve the problem of constructing a sensor network for health monitoring of complex geometric structures using ultrasonic Lamb waves, to reveal the propagation characteristics of Lamb waves in complex geometric structures, to determine the spatial layout of the Lamb wave transmission wave front, to guide the construction of the sensor network based on the energy density contour formed by multiple transmission wave fronts, and to achieve the purpose of comprehensive coverage of large monolithic wallboards and minimal energy consumption of the wireless sensor network.

[0007] To achieve the above-mentioned purpose, the present application proposes a wireless sensor network construction method based on ultrasonic Lamb waves for monitoring metal monolithic wallboards, which mainly includes the following steps:

[0008] 1) Simulation analysis of the frequency dispersion characteristics of Lamb waves in the monolithic wallboard structure. Based on the finite element simulation software, a variable-thickness, curved wallboard structure model is established to simulate the propagation process of Lamb waves in the monolithic wallboard. The Lamb wave response signals at different positions in space are densely extracted, and the frequency-wave number relationship is obtained based on two-dimensional Fourier transform to identify the modal components of Lamb waves, thereby obtaining the component information of Lamb waves under different plate thickness conditions as a reference for dispersion compensation of the Lamb wave receiving signal.

[0009] 2) Reveal the influence law of different geometric characteristic structures in the wallboard structure on the propagation characteristics of Lamb waves. Keep the thickness of the monolithic wallboard unchanged, and perform dispersion compensation based on the conclusion in step 1). Analyze the influence of geometric features such as stiffeners and covers in the wallboard structure on the propagation characteristics of Lamb waves, and focus on the influence of stiffener structures with different cross-section types on the propagation characteristics of Lamb waves in the plate. Compare and analyze the modal components and amplitude spectrum of the incident and transmitted Lamb wave signals in a certain frequency band to reveal the influence law of geometric characteristic structures on the modal conversion and energy distribution of Lamb waves.

[0010] 3) Calculate the transmission coefficient spectrum of Lamb waves in the monolithic wallboard structure to guide the selection of the best excitation frequency band of Lamb waves. According to the selected main modal components in the results of 2), the time-domain waveforms of several observation points located before and after the geometric feature are extracted for two-dimensional Fourier transform, and the transmission coefficient spectrum of Lamb waves is calculated by the ratio of the amplitude ridge lines in the frequency domain (the latter to the former), which reveals the comb filtering effect of geometric features on the transmitted Lamb waves in the wallboard structure.

[0011] 4) Extract the contour of the transmitted Lamb wave energy wavefront. Select the frequency band with high Lamb wave transmission coefficient in the transmission coefficient spectrum in 3) to excite, and monitor the health of the overall wallboard structure. Extract the time domain signal of the Lamb wave under different propagation paths in the wallboard, and draw the wavefront with the same Lamb wave energy. Set a reasonable threshold (such as-12dB) to construct the transmission Lamb wave energy contour, and determine the coverage range of a single sensor node according to the detection ability of the sensor to the defect and the detection requirement.

[0012] 5) Construct a wireless sensor network based on the step-by-step recursive layout strategy of the transmission energy density contour. Set the starting point (summary node) of the sensor network, obtain the Lamb wave transmission energy contour corresponding to the node under the set threshold and the monitoring range of a single sensor node from 4), determine the number and position of the receiving sensor nodes on the contour according to the angle range requirement of defect positioning, and define it as a first-level receiving node. Take the first-level receiving sensor as the starting point, repeat the above steps to determine the number and position of the second-level nodes, and recursively complete the spatial layout of the monitoring sensor network in the overall wallboard.

[0013] 6) Optimize the sensor network constructed by the step-by-step recursive method. In order to reduce the redundancy of the sensor network, two nodes with close distance and approximately the same coverage range are defined as competitive nodes. With the highest detection rate and the lowest correlation between two adjacent sensors as the optimization index, and using the principle of minimizing the total length of all node links in the overall sensor network, the competitive nodes are screened and removed. The optimized sensor network has the characteristics of comprehensive coverage and minimum redundancy.

[0014] Compared with the prior art, the present application has the ability to monitor the health of the metal overall wallboard structure containing complex features. By exploring the influence of different feature structures on the propagation characteristics of Lamb waves in large overall wallboards, the Lamb wave transmission coefficient spectrum is calculated to guide the selection of frequencies in health monitoring. And through the drawing of contour lines, the design of sensor spatial layout in the wallboard structure can be realized. The patent has a lightweight, non-electromagnetic wave wireless communication sensor network, and after optimization, it not only ensures the monitoring ability of the defect, but also minimizes the number of sensors, which meets the stringent requirements of aircraft on onboard equipment. BRIEF DESCRIPTION OF DRAWINGS

[0015] Figure 1 is a schematic diagram of a typical metal overall wallboard and its reinforcing rib cross-section shape.

[0016] Figure 2 is the comb filter effect of the structure on the Lamb wave transmission coefficient spectrum.

[0017] Figure 3is a schematic diagram of Lamb wave transmission energy contour.

[0018] Figure 4 is a schematic diagram of the method for constructing an ultrasonic Lamb wave wireless sensor network.

[0019] Figure 5 is a sensor spatial layout optimization and network construction method. DETAILED DESCRIPTION

[0020] The present application will be described in detail below in conjunction with the accompanying drawings and examples:

[0021] The present application proposes a method for constructing a wallboard structure health monitoring (SHM) sensor node network to solve the sensor layout problem in metal monolithic wallboard structure health monitoring. Lamb waves have the advantages of long propagation distance and sensitivity to structural defects in thin-walled plate shell structures, and can be used as a dual medium for sensing structural defect information and communication transmission between sensor nodes. The key to realizing plate structure health monitoring is to reasonably arrange the monitoring nodes of Lamb wave sensors.

[0022] The present application first calculates the transmission coefficient spectrum of Lamb waves as the basis for frequency selection in the structure health monitoring of monolithic wallboards. In the frequency band with high transmission coefficient, the energy wavefront of Lamb waves in different propagation directions is extracted, and the closed curve formed by the boundary constitutes the Lamb wave energy contour. Further, a reasonable threshold is set for the transmitted Lamb wave energy contour, and the detection capability and requirements of the sensor for defects are combined to determine the coverable range of a single sensor node. Considering the angle range requirement of defect positioning, the number and position of the first level receiving sensor nodes on the contour are determined. Taking the first level receiving sensor as the starting point, the spatial layout of the monitoring sensor network in the monolithic wallboard is constructed based on the step-by-step recursive layout strategy. Finally, using the principle of minimizing the total length of all node links in the overall sensor network, two competing nodes with very close distance and approximately the same coverage range are screened and removed to reduce the redundancy of the sensor network, achieving the purpose of optimizing the sensor network constructed by the step-by-step recursive method. The method of the present application can realize the layout of the Lamb wave structure health monitoring sensor network in the monolithic wallboard and solve the monitoring problem in practical engineering.

[0023] The technical scheme adopted by the present application is a method for constructing a wallboard structure health monitoring (SHM) sensor node network, comprising the following steps:

[0024] S1. To reveal the distribution pattern of the Lamb wave transmission coefficient spectrum in the wall panel structure to guide frequency selection. The specific implementation steps are as follows: Extract the time-domain waveforms from several observation points before and after the geometric feature, and perform two-dimensional Fourier transforms. The positive wavenumber portion of the two-dimensional Fourier transform result from the observation points before the geometric feature structure represents the incident signal. The two-dimensional Fourier transform result from the observation points after the geometric feature structure represents the transmitted signal. The amplitude ratio of the transmitted signal to the incident signal in the frequency domain is the Lamb wave transmission coefficient spectrum, such as... Figure 2 As shown in the figure, the results reveal the comb-like filtering effect of geometric features on transmitted Lamb waves in the wall panel structure at different frequencies, indicating that the frequency band with a high transmission coefficient is more suitable for selection as the excitation frequency in structural health monitoring.

[0025] S2. Drawing Lamb wave transmission energy contour lines in a monolithic metal panel structure. The specific implementation steps are: densely extracting the time-domain signals of the Lamb wave under different propagation paths, quantitatively describing the propagation process of the Lamb wave in the monolithic panel structure, and drawing Lamb wave transmission wavefronts with equal energy. The closed curves formed by their boundaries resemble contour lines on a topographic map and are called Lamb wave transmission energy contour lines, such as... Figure 3 As shown, by setting a reasonable threshold (e.g., -12dB) for the Lamb wave transmission energy contour lines, the effective spatial range for ultrasonic Lamb wave defect monitoring and communication transmission can be quantitatively evaluated. This will provide a quantitative criterion for the coverage range of a single sensor node, guiding the optimization of node spatial layout in structural health monitoring sensor networks.

[0026] S3. A hierarchical recursive layout strategy for a wireless sensor network based on transmission energy density contour lines. The specific method is as follows: Set a starting point (summary node) for the sensor network; set a threshold for the Lamb wave transmission energy contour line corresponding to this node; and determine the number and location of receiving sensor nodes along the contour lines based on the angle range requirements for defect location. Starting with the receiving sensors, repeat the above steps to determine the number and location of secondary nodes, and recursively complete the spatial layout of sensor nodes within the overall wall panel, such as... Figure 4 As shown. To reduce the redundancy of the sensor network, competing nodes are further screened and eliminated based on the principle of minimizing the total link length of nodes in the overall sensor network. The optimized sensor network features comprehensive coverage and minimal redundancy.

Claims

1. A method for constructing an SHM sensor node network for health monitoring of wall panel structures, characterized in that, The method includes the following steps: Step 1) Simulation analysis of Lamb wave dispersion characteristics in integral wall panel structure; Based on finite element simulation software, establish a variable thickness, curved surface wall panel structure model to simulate the propagation process of Lamb wave in integral wall panel; Densely extract Lamb wave response signals at different spatial locations, obtain frequency-wavenumber relationship based on two-dimensional Fourier transform to identify the modal components of Lamb wave, and obtain the component information of Lamb wave under different plate thickness conditions as a reference for Lamb wave received signal dispersion compensation; Step 2) Reveal the influence of different geometric features on the propagation characteristics of Lamb waves in the wall panel structure; keep the overall wall panel thickness constant and perform dispersion compensation based on the conclusions in Step 1); analyze the influence of the geometric features of the stiffeners and cover in the wall panel structure on the propagation characteristics of Lamb waves, and explore the influence of different cross-sectional stiffener structures on the propagation characteristics of Lamb waves in the plate; compare and analyze the modal components and amplitude spectra of incident and transmitted Lamb wave signals in a certain frequency band, and reveal the influence of geometric features on the mode conversion and energy distribution of Lamb waves; Step 3) Calculate the transmission coefficient spectrum of the Lamb wave in the overall wall panel structure to guide the selection of the optimal excitation frequency band of the Lamb wave; based on the selected mode components of the Lamb wave in the results of Step 2), extract the time-domain waveforms of several observation points before and after the geometric features and perform two-dimensional Fourier transforms. The ratio of the amplitude ridges in the frequency domain is used to calculate the transmission coefficient spectrum of the Lamb wave, revealing the comb filtering effect of the geometric features in the wall panel structure on the transmitted Lamb wave. Step 4) Extract Lamb wave energy wavefronts from different directions to construct contour lines; select the frequency band with high Lamb wave transmission coefficient in the transmission coefficient spectrum from Step 3) for excitation, and perform health monitoring on the overall wall panel structure; densely extract the time-domain signals of Lamb waves under different propagation paths in the wall panel, and draw wavefronts with the same Lamb wave energy; construct transmission Lamb wave energy contour lines by setting reasonable thresholds for them, and determine the coverage range of a single sensor node based on the sensor's defect detection capability and detection requirements; Step 5) Construct a wireless sensor network based on a step-by-step recursive layout strategy using transmission energy density contour lines; Set the starting point of the sensor network, and obtain the Lamb wave transmission energy contour line and the monitorable range of a single sensor node corresponding to the set threshold from Step 4). Combined with the angle range requirements for defect location, determine the number and location of receiving sensor nodes on the contour lines, and define them as first-level receiving nodes; Starting from the first-level receiving sensor, repeat the above steps to determine the number and location of second-level nodes, and complete the spatial layout of the monitoring sensor network in the overall wall panel step by step. 6) Optimize the design of the sensor network constructed by the step-by-step recursive method; define two nodes that are close to each other and have the same coverage as competing nodes; use the highest detection rate and the lowest correlation between two adjacent sensors as optimization indicators, and use the principle of minimizing the total link length of all nodes in the sensor network to screen and eliminate competing nodes.

2. The method for constructing an SHM sensor node network for health monitoring of wall panel structures according to claim 1, characterized in that, The time-domain signals of Lamb waves under different propagation paths are extracted intensively to quantitatively describe the propagation process of Lamb waves in the overall wall panel structure. Lamb wave transmission wavefronts with equal energy are plotted, and the closed curves formed by their boundaries are similar to contour lines on a topographic map, which are called Lamb wave transmission energy contour lines. By setting a threshold for the Lamb wave transmission energy contour lines, the effective spatial range of ultrasonic Lamb wave defect monitoring and communication transmission is quantitatively evaluated.

3. The method for constructing an SHM sensor node network for health monitoring of wall panel structures according to claim 1, characterized in that, The step-by-step recursive layout strategy for wireless sensor networks based on transmission energy density contour lines is as follows: Set the starting point of the sensor network, i.e., the summary node, and set the threshold for the Lamb wave transmission energy contour line corresponding to the summary node. Combined with the angle range requirements for defect location, determine the number and location of receiving sensor nodes for the contour lines. Starting from the receiving sensors, determine the number and location of secondary nodes, and complete the spatial layout of sensor nodes in the overall wall panel step by step.

4. The method for constructing an SHM sensor node network for health monitoring of wall panel structures according to claim 3, characterized in that, To reduce the redundancy of the sensor network, the principle of minimizing the total length of the node links in the sensor network is used to filter and eliminate competing nodes.

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