Discrete fourier transform (DFT) frequency sampling-based sliver spectrum analysis IP soft core and test method thereof

Abstract

The invention discloses a discrete fourier transform (DFT) frequency sampling-based sliver spectrum analysis IP soft core and a test method thereof. The DFT frequency sampling-based sliver spectrum analysis IP soft core comprises a sliver spectrum analysis computing unit. The sliver spectrum analysis computing unit comprises field programmable gate array (FPGA) device hardware. In the FPGA device hardware, through a HDL language, a DFT frequency sampling-based sliver spectrum analysis algorithm is encapsulated into the DFT frequency sampling-based sliver spectrum analysis IP soft core having 55 channels. The DFT frequency sampling-based sliver spectrum analysis IP soft core having the 55 channels comprises the 55 channels having different center frequency values and different band width values. Each one of the 55 channels comprises a DFT frequency sampling-based IP sub-core and the DFT frequency sampling-based IP sub-core comprises an input module, a state machine, a multiplier, an accumulator module and an output module. The DFT frequency sampling-based sliver spectrum analysis IP soft core can be transplanted into a FPGA device hardware platform through simple configuration, can independently complete a digital sliver signal spectrum analysis task, and has characteristics of strong generality, good portability and high parallel computation real-time property.

Description

technical field [0001] The invention belongs to the technical field of textile on-line monitoring and signal processing equipment, and relates to an online detection system for textile yarn evenness, in particular to a yarn spectrum analysis IP soft core based on DFT frequency sampling, and the invention also relates to the above-mentioned yarn spectrum Analyze the test method of IP soft core. Background technique [0002] Sliver unevenness is one of the main indicators to measure yarn quality, and it is also a decisive factor affecting the appearance quality of cloth surface. The detection of sliver unevenness is an important means to implement effective quality control in spinning production. In the textile industry, spectral analysis is usually used to detect yarn unevenness, and the essence of spectral analysis is spectrum analysis. [0003] Theoretically, the sliver uneven signal contains countless wavelengths, which are continuously distributed in the interval from 0 ...

AI Technical Summary

Problems solved by technology

This method uses Fourier transform to obtain the full-channel spectrum of the sliver signal. However, the spectrum analysis is only concerned with the spectrum of some channels within the frequency range of 0-300 Hz, so directly calculating the spectrum of the full channel will have a large problem. The calculation of a part of useless data greatly increases the time complexity and space complexity of the calculation

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