Sound-wave-based square wood hole-defect recognition system and method

Abstract

The invention discloses a sound-wave-based square wood hole-defect recognition system and a sound-wave-based square wood hole-defect recognition method, which mainly solve the problem of difficulty for nondestructive detection of a hole defect of square wood. The system comprises a small hammer, a sound wave signal acquisition module, a sound wave signal processing module, a NiosII processor, an external storage module, a USB (universal serial bus) communication module and a principal computer processing module. The sound wave signal acquisition module is used for completing the sound wave acquisition, AD conversion, amplification and low-frequency filtering; the sound wave signal processing module is used for driving the acquisition module and processing a sound wave digital signal; the external storage module comprises an SDRAM (synchronous dynamic random access memory) and an EPCS (electronic propulsion control system) configuration memory; the NiosII processor is used for processing and caching the signal and calling the USB communication module to upload the data to the principal computer processing module; a sound wave signal time-domain and frequency-domain waveform characteristic value is extracted from the principal computer processing module, and the defect is recognized by adopting a fuzzy model recognition method. The system and the method are pollution-free, harmless, simple and convenient to use, high in recognition rate and suitable for detecting the hole defect of the square wood, and the detected wood is not damaged.

Description

Technical field [0001] The invention relates to the technical field of wood non-destructive testing, in particular to a system and method for identifying square wood hole defects based on sound waves Background technique [0002] China has achieved rapid development in the field of non-destructive testing of wood defects. Many methods have emerged to detect defective wood, including X-ray, microwave, nuclear magnetic resonance, ultrasonic, stress wave, infrared spectroscopy, dielectric constant, acoustic waves and images. In these methods, X-rays are radiant and harmful to the human body; the instruments used in microwave, nuclear magnetic resonance and infrared spectroscopy detection are expensive and inconvenient to carry; when ultrasonic detection is used, it is necessary to coat the test piece Coupling agent; through stress wave and dielectric constant detection, the sensor needs to be attached or nailed into the wood, which will cause certain damage; and the detection of sou...

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Problems solved by technology

[0002] my country has achieved rapid development in the field of non-destructive testing of wood defects, and many methods have emerged to detect defective wood, including the use of X-rays, microwaves, nuclear magnetic resonance, ultrasonic waves, stress waves, infrared spectroscopy, dielectric constants, and sound waves and images. In these methods, X-rays are radiative and harmful to the human body; the instruments used for microwave, nuclear magnetic resonance and infrared spectrum testing are expensive and inconvenient to carry; when using ultrasonic testing, it is necessary to paint on the test piece Coupling agent; through stress wave and dielectric constant detection, the sensor needs to be attached or nailed into the wood, which will cause certain damage; and the use of sound waves and images for detection will improve the above problems

At present, in the aspect of non-destructive testing of wood acoustic waves, sound wave signals are collected by sound level meters, and the data is input into the data acquisition and analysis system through charge amplifiers and low-pass filters. It can only calculate and display the acoustic and vibration characteristic parameters, but cannot extract and select effective eigenvalues ​​for identification; FFT analyzers are also used to test the acoustic and vibration characteristics of wood, although it can be well applied to wood strength grading, mechanical property testing, etc. However, it is impossible to quickly and accurately identify internal defects of wood, so there is a lack of an integrated system dedicated to wood defect identification in this regard

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