Abstract: A sound source device and a signal receiver are disposed at first and second ports of a target object, respectively. A sound of a specific frequency of the sound source device is introduced into the target object to generate a resonant sound wave. A computer simulates a signal generated when the resonant sound wave is received by the signal receiver and regarding the signal as reference information. The reference information comprises first data having characteristics of the resonant sound wave, and data having features of an imaginary defect formed on the target object. The features of the imaginary defect correspond to the characteristics of the resonant sound wave. When the target object has a real defect, the sound of the specific frequency of the sound source device is introduced into the target object. Features of the real defect are derived by comparing the first data with the second data.

Abstract: An acoustic resonance diagnostic method for detecting structural degradation is provided. The method includes steps as follows: Firstly, a training model is built using a deep neural network. At least two training acoustic signals are inputted to the training model to carry a training. A diagnostic model is built according to a result of the training using a CNN. A plurality of under-test sound wave signals are captured from an under-test section of an under-test structure. An AI is used to filter data invalid for detecting structural degradation from the under-test sound wave signals. A structural degradation state of the under-test section is determined according to a remaining portion of the under-test sound wave signals through the diagnostic model.

Abstract: An acoustic resonance diagnostic method for detecting structural degradation is provided. The method includes steps as follows: Firstly, a training model is built using a deep neural network. At least two training acoustic signals are inputted to the training model to carry a training. A diagnostic model is built according to a result of the training using a convolutional neural network. An under-test sound wave signal is captured from an under-test section of an under-test structure through direct contact, non-contact, or indirect contact. A structural degradation state of the under-test section is determined according to the under-test sound wave signal through the diagnostic model.

Abstract: A positioning method for a specific sound source is provided. An acoustic signal in each of multiple positions of on a preset path is respectively collected through a sensor. A pre-processing is performed on the acoustic signal to obtain multiple signal features. The signal features are used as an input of a deep learning model. The deep learning model is used for a signal recognition to obtain multiple specific sound signals of each position. An autocorrelation function operation is performed on the specific sound signals obtained at a same position to obtain multiple autocorrelation coefficients. A representative value among the autocorrelation coefficients is selected as a representative coefficient corresponding to each position. A specific sound source position is found according to the representative coefficient of each position.

Abstract: A method for detecting a deterioration defect of a structural part using a structural unit includes: defining a first base structural unit and obtaining N first base modal parameters of the first base structural unit; detecting a respective one of M first subject structural units of a subject structural part by each of M first sensors to obtain N first actual modal parameters of each of the M first subject structural units; calculating N first subject modal parameters of each of the M first subject structural units according to the N first actual modal parameters of each of the M first subject structural units and M*N first predetermined ratios; and comparing the N first subject modal parameters of each of the M first subject structural units to the N first base modal parameters to determine whether each of the M first subject structural units has a deterioration defect.

Abstract: A sound source device and a signal receiver are disposed at first and second ports of a target object, respectively. A sound of a specific frequency of the sound source device is introduced into the target object to generate a resonant sound wave. A computer simulates a signal generated when the resonant sound wave is received by the signal receiver and regarding the signal as reference information. The reference information comprises first data having characteristics of the resonant sound wave, and data having features of an imaginary defect formed on the target object. The features of the imaginary defect correspond to the characteristics of the resonant sound wave. When the target object has a real defect, the sound of the specific frequency of the sound source device is introduced into the target object. Features of the real defect are derived by comparing the first data with the second data.

Abstract: A method for detecting deterioration of a structural part includes: detecting a waveform of time domain of the structural part by a sensor disposed on the structural part; performing a conversion of time domain to frequency domain for the waveform of time domain by a processor electrically connected to the sensor so as to obtain an actual modal parameter of each of a plurality of modals related to a waveform of frequency domain of the structural part; comparing the actual modal parameter of each of the plurality of modals to modal parameter information stored in a database to determine whether a deterioration defect exists in the structural part; and determining a degree and a position of the deterioration defect when the deterioration defect exists in the structural part.

Abstract: A method for detecting a deterioration defect of a structural part using a structural unit includes: defining a first base structural unit and obtaining N first base modal parameters of the first base structural unit; detecting a respective one of M first subject structural units of a subject structural part by each of M first sensors to obtain N first actual modal parameters of each of the M first subject structural units; calculating N first subject modal parameters of each of the M first subject structural units according to the N first actual modal parameters of each of the M first subject structural units and M*N first predetermined ratios; and comparing the N first subject modal parameters of each of the M first subject structural units to the N first base modal parameters to determine whether each of the M first subject structural units has a deterioration defect.

Abstract: A method for detecting deterioration of a structural part includes: detecting a waveform of time domain of the structural part by a sensor disposed on the structural part; performing a conversion of time domain to frequency domain for the waveform of time domain by a processor electrically connected to the sensor so as to obtain an actual modal parameter of each of a plurality of modals related to a waveform of frequency domain of the structural part; comparing the actual modal parameter of each of the plurality of modals to modal parameter information stored in a database to determine whether a deterioration defect exists in the structural part; and determining a degree and a position of the deterioration defect when the deterioration defect exists in the structural part.