CN104391045A - Sound-wave-based square wood hole-defect recognition system and method - Google Patents
Sound-wave-based square wood hole-defect recognition system and method Download PDFInfo
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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
The present invention relates to wood nondestructive testing technical field, particularly relate to the square lumber hole defect recognition system based on sound wave and method
Background technology
China has achieved very fast development at the field of non destructive testing of defects in timber, in succession occur that many methods are to detect defect timber, utilize X ray, microwave, nuclear magnetic resonance, ultrasound wave, stress wave, infrared spectrum, specific inductive capacity and the method such as sound wave and image, in these methods, X ray has radiativity, harmful; Utilize microwave, nuclear magnetic resonance and infrared spectrum to detect the instrument cost used high, carry also inconvenient; Use during ultrasound examination and need to be coated with couplant on test specimen; Detected by stress wave and specific inductive capacity and then need sensor is affixed or hammer into wood internal, certain damage can be caused; And utilize the mode of sound wave and image to carry out detecting and just can improve the problems referred to above.Have in the Non-Destructive Testing of timber sound wave at present and collect acoustic signals by sound meter, by charge amplifier and low-pass filter, data are inputted data acquisition and analysis system, but set of system is obviously very huge like this, integrated level is low, and its data analysis system can only calculate and show sound vibration characteristic parameter, and can not extract and select validity feature value to identify; Also the sound vibration characteristic utilizing the test timber such as fft analysis instrument is had, although strength of wood can be advantageously applied to grade, the aspects such as mechanical property test, but cannot accomplish to identify wood internal defect fast and accurately, therefore lack a set of integrated system being exclusively used in defects in timber identification in this respect.
Summary of the invention
In order to overcome above-mentioned the deficiencies in the prior art, the invention provides the square lumber hole defect recognition system based on sound wave and method.Square lumber hole defect and position thereof can be identified.
The technical scheme adopted is: based on square lumber hole defect recognition system and the method for sound wave, this system comprises: hand hammer, Acoustic Signal Acquisition module, acoustic signals processing module, NiosII processor, outer memory module, usb communication module and host computer processing module.
Described Acoustic Signal Acquisition module drive interface adopts iic bus interface, and data transmission adopts spi bus interface, and for the collection of sound wave simulating signal, AD conversion, amplifies and low frequency filtering.
Described acoustic signals processing module realizes in fpga chip, be bi-directionally connected with Acoustic Signal Acquisition module, for receiving and buffer memory acoustic data signal, whether be greater than threshold value according to the acoustic signals gathered and differentiate that hand hammer knocks behavior and whether occurs, if occurred, start DMA and send acoustic data signal to NiosII processor, otherwise lose data.
Described NiosII processor is connected with acoustic signals processing module with 8 IO by 16 BITBUS network, realize the transmission of DMA data and steering order transmission, NiosII processor is by 8 BITBUS network and usb communication model calling simultaneously, by the data truncation, the data conversion also buffer memory that receive, if usb communication module sends communication request, connect, acoustic data signal is transferred to usb communication module.
Described outer memory module comprises EPCS config memory and SDRAM, is used for storage program and data and operation NiosII buffer memory.
Described usb communication module is connected with usb bus with host computer processing module, is used for digital signal data to be uploaded to upper computer software, row relax of going forward side by side.
Described host computer processing module possesses the display of time-domain and frequency-domain waveform, data preservation, time-domain and frequency-domain characteristics extraction and adopts the function of Fuzzy Pattern Recognition Method defect recognition.
Based on the square lumber hole defect recognition methods of sound wave, comprise the following steps:
A) knock tested square lumber end with hand hammer, gather acoustic signals at the other end, respectively AD conversion, amplification and low frequency filtering are carried out to acoustic signals
B) start DMA by threshold decision and signal data is transferred to NiosII processor from acoustic signals processing module, then call usb communication module and send signal data to host computer processing module
C) in host computer processing module, carry out the display of time-domain and frequency-domain waveform, preserve data etc., then extract and select time domain and frequency domain character value, adopt Fuzzy Pattern Recognition Method defect recognition
Compared with prior art, the invention has the beneficial effects as follows can be quick, detects easily and identify square lumber hole defect and position thereof, has without harm, cleans, do not damage tested timber, easy to use, the advantage that discrimination is high.
Accompanying drawing explanation
Fig. 1 is recognition system structural drawing of the present invention
Fig. 2 is recognition methods process flow diagram of the present invention
Embodiment
The invention provides a kind of square lumber hole defect recognition system based on sound wave and method, its structure as shown in Figure 1, comprises hand hammer, Acoustic Signal Acquisition module, acoustic signals processing module, NiosII processor, outer memory module, usb communication module and host computer processing module.
Acoustic Signal Acquisition module drive interface adopts iic bus interface, and data transmission adopts spi bus interface, and for the collection of sound wave simulating signal, AD conversion, amplifies and low frequency filtering.
Acoustic signals processing module realizes in fpga chip, be bi-directionally connected with Acoustic Signal Acquisition module, for receiving and buffer memory acoustic data signal, whether be greater than threshold value according to the acoustic signals gathered and differentiate that hand hammer knocks behavior and whether occurs, if occurred, start DMA and send acoustic data signal to NiosII processor, otherwise wait for.
Choosing sample frequency by NiosII processor is 96KHz, and sampled point is 2048.
NiosII processor is connected with acoustic signals processing module with 8 IO by 16 BITBUS network, realize the transmission of DMA data and steering order transmission, NiosII processor is by 8 BITBUS network and usb communication model calling simultaneously, by the data truncation, the data conversion also buffer memory that receive, if usb communication module sends communication request, connect, acoustic data signal is transferred to usb communication module.
Outer memory module comprises EPCS config memory and SDRAM, is used for storage program and data and operation NiosII buffer memory.
Described usb communication module is connected with usb bus with host computer processing module, is used for digital signal data to be uploaded to upper computer software, row relax of going forward side by side.
Use the state such as switch, operation of the LED of different colours display FPGA system whether normal.
Host computer processing module possesses the display of time-domain and frequency-domain waveform, data preservation, time-domain and frequency-domain characteristics extraction and adopts the function of Fuzzy Pattern Recognition Method defect recognition.
Based on sound wave the recognition methods of square lumber hole defect as shown in Figure 2, comprise the following steps:
A) knock tested square lumber end with hand hammer, gather acoustic signals at the other end, respectively AD conversion, amplification and low frequency filtering are carried out to acoustic signals
B) start DMA by threshold decision and signal data is transferred to NiosII processor from acoustic signals processing module, then call usb communication module and send signal data to host computer processing module
C) in host computer processing module, carry out the display of time-domain and frequency-domain waveform, preserve data etc., then extract and select time domain and frequency domain character value, adopt Fuzzy Pattern Recognition Method defect recognition
Adopt the method for Fuzzy Pattern Recognition as follows in described recognition methods c:
A) extract and select 3 characteristic quantities of all samples, obtain initial training sample
B) normalization training sample.X=[x
ij]
n × m(i=1,2 ..., n; J=1,2 ..., m) be original matrix, process that X is standardized obtain X '=[x '
ij]
n × m(i=1,2 ..., n; J=1,2 ..., m), formula used of standardizing is:
C) fuzzy similarity matrix is set up.Furthest Neighbor is utilized to calculate similarity coefficient r
ij, r
ij=1-cd (x '
i, x '
j), then obtaining fuzzy similarity matrix is R=[r
ij]
n × n, wherein d (x '
i, x '
j) be sample x '
ito x '
jeuclidean distance.
D) fuzzy similarity matrix being converted to transitive closure matrix is
then threshold value λ cut is adopted to t (R), choose different λ and analyze, find the λ that classification results can be made to reflect the actual conditions of wood damage.
E) more similar sampling feature vectors weighted mean is obtained fuzzy pattern categorization vector
F) extract the time-domain and frequency-domain eigenwert of sample to be tested, obtain degree of membership according to membership function, adopt maximum membership grade principle to identify.Wherein membership function is:
Above embodiment is only preferred embodiment of the present invention.
Claims (8)
1., based on the square lumber hole defect recognition system of sound wave, it is characterized in that this system comprises hand hammer, Acoustic Signal Acquisition module, acoustic signals processing module, NiosII processor, outer memory module, usb communication module and host computer processing module.
2. Acoustic Signal Acquisition module according to claim 1, it is characterized in that this module drive interface adopts iic bus interface, data transmission adopts spi bus interface, for the collection of sound wave simulating signal, AD conversion, amplification and low frequency filtering, the signal processed is passed to acoustic signals processing module.
3. acoustic signals processing module according to claim 1, it is characterized in that this module realizes in fpga chip, be bi-directionally connected with Acoustic Signal Acquisition module, for receiving and buffer memory acoustic data signal, whether be greater than threshold value according to the acoustic signals gathered and differentiate that hand hammer knocks behavior and whether occurs, if occurred, start DMA and send acoustic data signal to NiosII processor, otherwise wait for.
4. NiosII processor according to claim 1, it is characterized in that it is connected with acoustic signals processing module with 8 IO by 16 BITBUS network, realize the transmission of DMA data and steering order transmission, NiosII processor is by 8 BITBUS network and usb communication model calling simultaneously, by the data truncation, the data conversion also buffer memory that receive from sonicated module, if usb communication module sends communication request, connect, acoustic data signal is transferred to usb communication module.
5. outer memory module according to claim 1, is characterized in that this module comprises EPCS config memory and SDRAM, is used for storage program and data and operation NiosII buffer memory.
6. usb communication module according to claim 1, is characterized in that this module is connected with usb bus with host computer processing module, is used for digital signal data to be uploaded to upper computer software, row relax of going forward side by side.
7. host computer processing module according to claim 1, is characterized in that this module possesses the display of time-domain and frequency-domain waveform, data preservation, time-domain and frequency-domain characteristics extraction and adopts the function of Fuzzy Pattern Recognition Method defect recognition.
8., based on the square lumber hole defect recognition methods of sound wave, comprise the following steps:
A) knock tested square lumber end with hand hammer, gather acoustic signals at the other end, respectively AD conversion, amplification and low frequency filtering are carried out to acoustic signals.
B) start DMA by threshold decision and signal data is transferred to NiosII processor from acoustic signals processing module, then call usb communication module and send signal data to host computer processing module.
C) in host computer processing module, carry out the display of time-domain and frequency-domain waveform, preserve data etc., then extract and select time domain and frequency domain character value, adopt Fuzzy Pattern Recognition Method defect recognition.
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| CN105548359A (en) * | 2016-01-13 | 2016-05-04 | 东北林业大学 | Wood hole defect ultrasonic detection and feature extraction method |
| CN106198765A (en) * | 2015-04-29 | 2016-12-07 | 中国科学院声学研究所 | A kind of acoustic signal recognition methods for Metal Crack monitoring |
| CN107422038A (en) * | 2017-09-11 | 2017-12-01 | 重庆交通大学 | A kind of steel construction detection means and method that tuning fork resonance is instigated based on magnetic pull |
| CN106523928B (en) * | 2016-11-24 | 2018-08-03 | 东北大学 | Pipeline leakage detection method based on the screening of sound wave real time data two level |
| CN109142547A (en) * | 2018-08-08 | 2019-01-04 | 广东省智能制造研究所 | A kind of online lossless detection method of acoustics based on convolutional neural networks |
| CN116539722A (en) * | 2023-05-11 | 2023-08-04 | 江苏零界科技集团有限公司 | Wood surface pretreatment equipment for preparing anti-corrosion oil wood rod |
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