In this study, we propose nondestructive testing methods and combined forecasting models-based stress wave and impedance measurements to obtain accurate internal defects information for wooden building components. Internal defects data for major wooden components of an ancient building in China and reverse laboratory test data on matching tree species indicated various degrees of damage on the pavilion wood structure surface and internal defects in certain pillars. The stress wave method enabled rapid acquisition of two-dimensional plots of test sections; however, the results revealed that the area of stress wave detection was greater than the actual defect area. Moreover, the impedance meter was able to determine the defect position and type in a single path, and the actual defect area was proportional to the absolute error of the drilling resistance. By distributing the errors from the two nondestructive testing methods on the basis of a Shapley value algorithm, we determined the weights of stress wave and impedance meter data in the forecasting models and established combined forecasting models that showed greater accuracy with a mean relative error of less than 6%. This method can improve the prediction accuracy of internal defects in ancient buildings and provide effective data support for practical engineering repair and reinforcement schemes.
Based on the experimental idea of reverse simulation, a quantitative area of hole was excavated at the sectional center of a wood specimen. The excavation area was 1/32S, 1/16S, 1/8S, 1/4S, and 1/2S (where S represents cross-sectional area of the complete specimen) and stress wave nondestructive testing of six sensors was performed. The stress wave propagation paths were statistically summarized to obtain the stress wave propagation velocity (Va) for two adjacent sensors, the stress wave propagation velocity (Vb) for two separated sensors, and the stress wave propagation velocity (Vc) for two opposite sensors. Furthermore, by analyzing the advantages and disadvantages of grey relation and stepwise discriminant model when both of them were used alone, a coupling model generated from them was established to dispose the test data. The attenuation ratios Ψa, Ψb, and Ψc of stress wave under three propagation paths and their relation ratios Va/Vb, Vb/Vc, and Va/Vc, a total of six groups of measured data, were selected as discriminant factors for the hole area grade of the wood specimen. The verification results showed that the discriminant accuracy of the coupling model was 100%, and it was concluded that the attenuation ratio (Ψb) of the stress wave propagation velocity for two separated sensors had the strongest discriminant ability against cross-sectional area of the specimen.
To quickly evaluate the material properties of ancient wooden structure members on site, the larch species of northeastern China was used as the research object, and the nondestructive testing method of the stress wave and the micro-drill resistance meter were used to measure it. The variation laws of the larch wood’s cross and longitudinal property indexes were determined. According to the variation law of material property indexes, the detection divisions under the nondestructive testing technology of stress wave and micro-drill resistance instruments were divided, which provides a basis for improving the accuracy of on-site nondestructive testing. From the comparison of shade and light side data, it was found that there was little difference in material properties indexes. According to the change trend of larch wood with density, the pith, juvenile wood, mature wood, and overmature wood were divided, which provided a reference value for the study of wood growth laws.
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