Method for identifying grade of wood for Chinese zither panel through near infrared spectrum based on neural network

A near-infrared spectroscopy and neural network technology, applied in the field of high-level testing, can solve the problems of decreasing year by year, the subjective influence of the discriminator on the number of relevant practitioners, and the long discrimination time, so as to achieve a low misjudgment rate and more objective discrimination results. , the effect of high accuracy

Active Publication Date: 2019-01-22
NORTHEAST FORESTRY UNIVERSITY +1
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  • Application Information

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Problems solved by technology

[0003] In order to overcome the existing problems such as long discrimination time, judgment results easily subject to the subjective influence of judges, and the number of relevant practitioners decreasing year by year, the present invention provides a method for identifying wood grades for guzheng panels based on neural network near-infrared spectroscopy

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  • Method for identifying grade of wood for Chinese zither panel through near infrared spectrum based on neural network
  • Method for identifying grade of wood for Chinese zither panel through near infrared spectrum based on neural network
  • Method for identifying grade of wood for Chinese zither panel through near infrared spectrum based on neural network

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specific Embodiment approach 1

[0024] Specific implementation mode one: this implementation mode provides a kind of method based on neural network near-infrared spectrum identification paulownia wood grade for guzheng panel, such as figure 1 As shown, the method includes the following steps:

[0025] Step (1): Perform Savitzky-Golay convolution smoothing and first-order derivative preprocessing and principal component analysis on the near-infrared spectral data of N groups of different bands containing different grades of guzheng panel wood, and transform the near-infrared spectral data of different bands Infrared spectrum data are randomly grouped, and n sets of data are used as training sample sets, and N-n sets of data are used as test sample sets.

[0026] Step (2): construct the improved BP neural network model, the improved BP neural network model comprises input layer, hidden layer and output layer, uses Softmax function as the classification function of model, and concrete construction steps are as ...

specific Embodiment approach 2

[0034] Embodiment 2: This embodiment is a further description of Embodiment 1. The specific implementation steps of this embodiment are as follows:

[0035] (1) Collect the near-infrared spectral data of the wood used for the guzheng panel to be tested.

[0036] (2) Spectral data analysis:

[0037] (2a) Observing the original spectral curve, it is found that the spectra overlap and the spectral peaks overlap. This embodiment combines the improved BP neural network algorithm to extract spectral features. Observing the original spectrum, it can be found that the wood is at a wavenumber of 10000cm -1 to 7100cm -1 The absorption is the smallest near the area, at the wave number 6806cm -1 to 5192cm -1 Absorption area is slightly higher at wavenumber 4400cm -1 to 4016cm -1 The area around the district is the highest;

[0038] (2b) Refer to Figure 4 , spectral data at 6806cm -1 、5804cm -1 、5602cm -1 、5192cm -1 、4760cm -1 、4400cm-1 、4286cm -1 、4016cm -1 There is an ob...

specific Embodiment approach 3

[0056] Specific embodiment three: In this embodiment, three grades of paulownia wood suitable for guzheng panels and three unknown grades of wood samples for panels are used as analysis objects.

[0057] Such as figure 1 As shown, the near-infrared-based method for class recognition of wood for guzheng panels in this embodiment uses Savitzky-Golay convolution smoothing and first-order derivative methods to preprocess data sets, perform principal component analysis operations, and analyze spectra to determine the absorption of certain chemical bonds Peak position, determine the band data sent to the neural network model, and divide it into a training sample set and a test sample set, use the improved BP neural network model, send the feature vector to the Softmax classifier, adjust the number of nodes in the hidden layer and participate in The band of the experiment, the best result of the plate grade classification of the training sample set is obtained, and the final spectral...

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Abstract

The invention discloses a method for identifying the grade of wood for a Chinese zither panel through the near infrared spectrum based on a neural network. The method comprises the steps of: (1), performing Savitzky-Golay convolution smoothing, first-order derivative pre-processing and principal component analysis on near infrared spectrum data including the wood for the Chinese zither panel in different grades; (2), constructing an improved BP neural network model; (3), training the improved BP neural network model; and (4), classifying the near infrared spectrum data of the wood for the Chinese zither panel by utilizing the trained improved BP neural network model, so that grade identification of the wood for the Chinese zither panel is realized. According to the method in the invention,judgement is carried out based on the near infrared spectrum data covering chemical substances of the wood for the Chinese zither panel in different grades; data measurement is rapid; the cost is low; the judgement time is short; the calculation data volume is effectively reduced; the subjective assume is not doped; the stability is relatively high; and the method is relatively robust.

Description

technical field [0001] The invention belongs to the technical field of grade identification of zither panels, and relates to a method for grading identification of wood used in zither panels, in particular to a method based on identifying information such as compound characteristic peaks in the near-infrared spectrum band of the panel and extracting feature vectors by neural networks, thereby identifying Test methods for their grades. Background technique [0002] With the rapid development of my country's economy and the continuous improvement of living standards, people's demand for high-grade zither products is also increasing, and people's requirements for the sound quality of zither are also getting higher and higher. High-quality zither products have very high performance value. Vibration is caused by plucking the strings, which is transmitted to the panel through the zither code, thereby producing a beautiful melody. It can be seen that in the case of other materials ...

Claims

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Application Information

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IPC IPC(8): G01N21/359G01N21/3563G06N3/08
CPCG06N3/084G01N21/3563G01N21/359
Inventor 黄英来孟诗语苗红曲玉利于鸣温馨
Owner NORTHEAST FORESTRY UNIVERSITY
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