An Aircraft Pallet Damage Monitoring Method Based on Damage Subarea Identification and Probability-Based Diagnostic Imaging

Abstract

To improve the safety and economy of aircraft pallet use, an aircraft pallet damage monitoring method based on damage subarea identification and probability-based diagnostic imaging is proposed. In the proposed method, first, the large aircraft pallet monitoring area is divided into rectangular subareas, and a piezoelectric transducer sensor is pasted on each vertex of the rectangular subarea that is used to excitation and sensing the Lamb wave. Second, the damage subarea is identified according to the diagonal damage indexes. Third, the damage position in the damage subarea is calculated using the probability-based diagnostic imaging method and coordinate probability weighted algorithm. Finally, the aircraft pallet damage can be localized based on the damage subarea position. Frequency selection and damage simulation study results show that the Lamb wave is sensitive to aircraft pallet damage whose centre frequency ranges from 50 kHz to 150 kHz, and the damage index of a steel ball is less than that of all real aircraft pallet damage from 95 kHz to 125 kHz. The verification results show that the proposed method can locate aircraft pallet damage with an error of less than 2 cm.

Frequency Aliasing-Based Spatial-Wavenumber Filter for Online Damage Monitoring

“…Next, the designed spatial-wavenumber filter is applied to the received Lamb wave signal when the wavenumber filtering range is (−k s , k s ), as shown in (14). e filtered wavenumber response of the received Lamb wave signal can be expressed as…”

“…In the existing SHM technologies, the damage imaging method which has high signal-to-noise ratio can visually indicate damage location and size. Examples of these imaging techniques include the delay-and-sum method [6][7][8][9], time reversal method [10][11][12][13], probabilistic diagnostic algorithm [14][15][16][17], phased array method [18][19][20][21], multisignal classification method [22][23][24][25][26], and spatial-wavenumber filter method [27][28][29][30][31][32][33][34][35]. Among them, the spatial-wavenumber filter method, which has been extensively studied, can extract the specific mode of the Lamb wave, distinguish the incident wave and damage scattering wave, and reduce the overlap of Lamb wave signals [33][34][35].…”

Application of Piezoelectric Technology in Nondestructive Testing of Wooden Pallets for Falling Damage Prediction

“…The histogram of connected elements (HCE) concept (Patricio et al, 2007) was presented and applied in some manufacturers' vision-based inspection systems to complete the automated inspection of used wooden pallets, thereby reducing the error rate caused by manual detection. The damage in aircraft pallets can be successfully located with an error of less than 2 cm using the damage subarea identi cation method and probabilistic diagnostic imaging (Liu et al, 2019). Li et al (2020) developed a device for detecting damaged wooden pallets by combining image processing and detection technology, further improving the detection accuracy of broken wooden pallets.…”

Determination of Detection Probability and Localization Accuracy for a Guided Wave-Based Structural Health Monitoring System on a Composite Structure

“…Liu et al [21] improved the ability of damage localization with higher precision and lower error on a CFRP composite panel with four T-shaped stiffeners and compared between a developed PDI approach and a developed weight compensated-based damage PDI algorithm. Liu et al [22] developed a PDI algorithm that localizes the damage within an aircraft pallet. Liu et al [23] developed an improved PDI algorithm to localize artificial and impact damage on a stiffed composite panel.…”

“…Nevertheless, all these references mainly use exemplary damages, locations, and data to quantify the localization error as distance between the center of the actual damage position and the estimated one, while not giving a statistically based analysis on localization accuracy. In [21,22], analysis is performed only for one damage size at different damage positions, and for these positions, values for localization error are given. In [21], an average over all damage positions to quantify the localization accuracy was also calculated.…”