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Terrain classification and recognition method based on learned vibration information

A technology of terrain classification and recognition method, which is applied in the field of recognition and classification, can solve the problem of low accuracy and achieve the effect of low calculation consumption

Inactive Publication Date: 2018-11-16
HARBIN INST OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] The purpose of the present invention is to solve the shortcoming of the low accuracy rate of the existing classification and recognition methods, and propose a learning-based vibration information terrain classification and recognition method

Method used

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  • Terrain classification and recognition method based on learned vibration information
  • Terrain classification and recognition method based on learned vibration information
  • Terrain classification and recognition method based on learned vibration information

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specific Embodiment approach 1

[0028] Specific implementation mode one: as figure 1 As shown, a learning-based vibration information terrain classification and recognition method includes the following steps:

[0029] Step 1: Collect the raw data of the vibration information of the sensor in the x-axis, y-axis and z-axis directions in the body coordinate system;

[0030] Step 2: Segment and process the raw data of the vibration information collected in step 1 to form n vectors with a duration of t;

[0031] Step 3: mark the n vectors after the step 2 segmentation process with terrain types (each vector corresponds to a terrain);

[0032] Step 4: Convert the divided n vectors to the frequency domain;

[0033] Step 5: use the multi-layer feed-forward neural network to perform offline learning and training on the n vectors converted to the frequency domain, and obtain the trained multi-layer feed-forward neural network;

[0034] Step 6: Obtain vibration data online in real time. Perform steps 2 to 4. After ...

specific Embodiment approach 2

[0040] Embodiment 2: This embodiment differs from Embodiment 1 in that: the value of t in Step 2 is 1s˜5s.

[0041] Other steps and parameters are the same as those in Embodiment 1.

specific Embodiment approach 3

[0042] Specific embodiment 3: The difference between this embodiment and specific embodiments 1 or 2 is that the size of the vector with a duration of 1s in step 2 is 1×100.

[0043] Other steps and parameters are the same as those in Embodiment 1 or Embodiment 2.

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Abstract

The invention relates to a terrain classification and recognition method based on learned vibration information, which aims to solve a problem of low accuracy of the existing classification and recognition method. The terrain classification and recognition method comprises the steps of first, collecting original data of vibration information of a sensor in the x-axis, y-axis and z-axis directionsin a coordinate system; second, performing segmentation processing on the original data to form n vectors with the time length being 1s; third, performing terrain type marking on the n vectors; fourth, converting the segmented n vectors into a frequency domain; fifth, performing off-line learning training on the n vectors converted into the frequency domain by using a multilayer feedforward neuralnetwork to obtain a trained multilayer feedforward neural network; and sixth, obtaining vibration data online in real time, executing the step two to the step four, and performing online classification and recognition by using the trained multilayer feedforward neural network in the step five to obtain the terrain type. The terrain classification and recognition method is applied to the technicalfield of recognition and classification.

Description

technical field [0001] The invention relates to the technical field of identification and classification, in particular to a learning-based vibration information terrain classification and identification method. Background technique [0002] 1) Fast Fourier transform [0003] FFT (Fast Fourier Transformation) is Fast Fourier Transformation, which is an accelerated algorithm of DFT (Discrete Fourier Transformation). It is obtained by improving the discrete Fourier transform algorithm according to the odd, even, imaginary, and real characteristics of the discrete Fourier transform. [0004] The basic idea is to decompose the original N-point sequence into a series of short sequences in turn. By making full use of the symmetric and periodic properties of the exponential factor in the DFT calculation formula, the corresponding DFTs of these short sequences are obtained and combined appropriately, so as to achieve the purpose of deleting repeated calculations, reducing multipli...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06K9/00
CPCG06V20/13G06F18/24G06F18/214
Inventor 白成超郭继峰宋俊霖
Owner HARBIN INST OF TECH
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