CN111139582A - Textile machine yarn monitoring method based on edge projection analysis - Google Patents

Abstract

The invention discloses a textile machine yarn monitoring method based on edge projection analysis, which is provided with a shell and an electronic control device arranged in the shell, wherein the electronic control device comprises a power supply circuit, a processor, an infrared emission unit and an image sensor, the infrared emission unit and the image sensor are connected with the processor, an infrared filter is arranged on the image sensor, the infrared emission unit is arranged right above the image sensor, and the textile machine yarn monitoring method is arranged in the processor and comprises the following steps: (1) every fixed period T, the processor collects the image data output by the image sensorf _t(x, y); (2) using a binarization algorithm to convert the image data into image dataf _t(x, y) performing binarization processing to obtain a binary functiony _t(x, y); (3) binary functiony _tProjecting the (x, y) projection area to the x axis to obtain a histogram W_t[M](ii) a (4) If W_t[i]>N/2, then let W_t[i]Is 0; calculating a histogram W_t[M]And S_t(ii) a (5) Calculating histogram and S_tAnd S_t‑1Difference Δ S of (d): when the delta S is larger than or equal to a preset threshold value K, judging that the yarn is in a motion state; otherwise, the yarn is judged to be in a static state.

Description

Textile machine yarn monitoring method based on edge projection analysis

Technical Field

The invention relates to a textile machine yarn monitoring method based on edge projection analysis, and belongs to the technical field of textile electronics.

Background

The seamless underwear machine is a special device for producing one-step formed underwear. The seamless underwear uses the high and new technology of producing high-elasticity knitted outerwear, underwear and high-elasticity sports wear, so that the positions of neck, waist, hip and the like do not need to be seamed. The seamless underwear is completely comfortable, fashionable and changes. In order to improve the working efficiency and reduce the production cost, the prior seamless underwear machine realizes unmanned production. However, seamless underwear machines are typically woven from multiple or even ten sets of yarns, even if a yarn break or lack of yarn in one set of yarns results in scrapping of the currently woven clothing. Therefore, monitoring of yarn breakage and yarn shortage is particularly important. The currently used yarn state sensor uses a differential infrared photodiode to detect. The mode has the advantages of simple principle and low cost, but the gain of the amplifying circuit is very large and is easy to be interfered, and the detection area is very narrow and has high installation requirements.

Machine vision can simulate human eyes, can collect rich information of detection objects, and can realize analysis and identification of information such as shapes, colors, gradients and the like. Thus, yarn condition detection based on image analysis becomes possible.

Disclosure of Invention

The invention aims to overcome the defects in the prior art, adopts the detection mode of an image sensor, provides a textile machine yarn monitoring method based on edge projection analysis, calculates the projection histogram of the yarn, extracts the edge projection area of the yarn and performs analysis and comparison, and the scheme has simple principle and reliable work and is a non-contact detection scheme.

The technical scheme adopted by the invention for solving the technical problems is as follows:

the yarn monitoring method of the textile machine based on edge projection analysis, set up the outer cover of the U-shape, and set up the electronic control device in the said outer cover, the said electronic control device includes the power supply circuit providing power, processor carrying on operation processing, infrared emission unit and image sensor connected with said processor, the said image sensor sets up the infrared filter, the said infrared emission unit sets up directly over the said image sensor, the yarn passes from the below of the said infrared emission unit, and project to the said image sensor, the said inside of processor sets up the yarn monitoring method of the textile machine, its step is:

(1) every fixed period T, the processor collects the image data output by the image sensorf _t(x,y)，x=1~M，y = 1-N, wherein M is the maximum pixel number in the x-axis direction, and N is the maximum pixel number in the y-axis direction;

(2) adopting a binarization algorithm to image dataf _t(x, y) performing binarization processing to obtain a binary functiony _t(x, y), and the projected area of the yarny _t(x, y) =1, non-projection areay _t(x,y)=0；

(3) Binary functiony _tProjecting the (x, y) projection area to the x axis to obtain a histogram W_t[M]Wherein W is_t[i]=

，i=1~M；

(4) If W_t[i]>N/2, then let W_t[i]Is 0; calculating a histogram W_t[M]And S_t=

；

(5) Calculating the histogram sum S of the current acquisition_tSum and histogram sum S of previous acquisition_t-1Difference Δ S = | S_t-S_t-1L: when the delta S is larger than or equal to a preset threshold value K, judging that the yarn is in a motion state; and when the Delta S is smaller than a preset threshold value K, judging that the yarn is in a static state.

The implementation of the invention has the positive effects that: 1. calculating a projection histogram of the yarn by adopting a detection mode of an image sensor, extracting a projection area of the edge of the yarn, analyzing and comparing the projection area, and judging the micro-motion state of the yarn; 2. the principle is simple, and the work is reliable; 3. and the non-contact detection has no influence on the yarn.

Drawings

Fig. 1 is an installation diagram of an electronic control device;

FIG. 2 is a schematic diagram of a binary function;

fig. 3 is a schematic diagram of a histogram.

Detailed Description

The invention will now be further described with reference to the accompanying drawings in which:

referring to fig. 1-3, the method for monitoring the yarns of the spinning machine based on the edge projection analysis comprises a U-shaped shell and an electronic control device arranged in the shell, wherein the electronic control device comprises a power circuit for providing power, a processor for performing operation processing, an infrared emission unit 1 and an image sensor 2 which are connected with the processor, and an infrared filter 3 is arranged on the image sensor 2.

The power supply circuit performs level conversion on an input power supply, stabilizes voltage and provides power for other circuits.

The image sensor 2 is configured as a CCD linear image sensor or a CMOS linear image sensor sensitive to infrared rays, and the processor can read image data as needed.

Infrared filter 3, can filter the light except infrared light, can improve environmental suitability like this greatly, avoid external light source's interference. In order to enhance the definition and contrast of the yarn image, the infrared emission unit 1 is arranged right above the image sensor 2, and the yarn passes through the lower part of the infrared emission unit 1 and is projected on the image sensor 2.

The yarn state identification method is arranged in the processor, can detect the motion state and the static state of the yarn, and comprises the following steps:

(1) every fixed period T, the processor collects the image data output by the image sensorf _t(x, y), x = 1-M, y = 1-N, wherein M is the maximum pixel number in the x-axis direction, and N is the maximum pixel number in the y-axis direction;

in step (1), the processor 1 samples every fixed period T to obtain an image sequence of a two-dimensional matrixf _t(x,y)，f _t-1(x,y)，f _t-2(x,y)，．．．．．

(2) Adopting a binarization algorithm to image dataf _t(x, y) performing binarization processing to obtain a binary functiony _t(x, y), and the projected area of the yarny _t(x, y) =1, non-projection areay _t(x,y)=0；

(3) Binary functiony _tProjecting the (x, y) projection area to the x axis to obtain a histogram W_t[M]Wherein W is_t[i]=

，i=1~M；

Histogram W_t[M]The yarn projection area or the distribution pile body of the yarn body on the x axis is described, the characteristics of the yarn are reflected, and state recognition can be carried out.

(4) If W_t[i]>N/2, then let W_t[i]Is 0; calculating a histogram W_t[M]And S_t=

；

Removing the trunk part of the yarn projection area, leaving the projections of the yarn edge and the pile edge, and summing to obtain a numerical value S representing the yarn characteristics_t。

(5) Calculating the histogram sum S of the current acquisition_tSum and histogram sum S of previous acquisition_t-1Difference Δ S = | S_t-S_t-1L: when the delta S is larger than or equal to a preset threshold value K, judging that the yarn is in a motion state; and when the Delta S is smaller than a preset threshold value K, judging that the yarn is in a static state.

And judging according to the principle that the difference value delta S is close to zero when the yarn is static.

Claims (1)

1. The textile machine yarn monitoring method based on edge projection analysis is characterized in that a U-shaped shell is arranged, an electronic control device is arranged in the shell and comprises a power circuit for providing a power supply, a processor for performing operation processing, an infrared emission unit and an image sensor, the infrared emission unit and the image sensor are connected with the processor, an infrared filter is arranged on the image sensor, the infrared emission unit is arranged right above the image sensor, and yarns penetrate through the lower part of the infrared emission unit and are projected onto the image sensor, and the textile machine yarn monitoring method based on edge projection analysis is characterized in that: the method for monitoring the yarns of the spinning machine is arranged in the processor and comprises the following steps:

(1) every fixed period T, the processor collects the image data output by the image sensorf _t(x, y), x = 1-M, y = 1-N, wherein M is the maximum pixel number in the x-axis direction, and N is the maximum pixel number in the y-axis direction;

(2) adopting a binarization algorithm to image dataf _t(x, y) performing binarization processing to obtain a binary functiony _t(x, y), and the projected area of the yarny _t(x, y) =1, non-projection areay _t(x,y)=0；

(3) Binary functiony _tProjecting the (x, y) projection area to the x axis to obtain a histogram W_t[M]Wherein W is_t[i]=

，i=1~M；

(4) If W_t[i]>N/2, then let W_t[i]Is 0; calculating a histogram W_t[M]And S_t=

；

(5) Calculating the histogram sum S of the current acquisition_tSum and histogram sum S of previous acquisition_t-1Difference Δ S = | S_t-S_t-1L: when the delta S is larger than or equal to a preset threshold value K, judging that the yarn is in a motion state; and when the Delta S is smaller than a preset threshold value K, judging that the yarn is in a static state.

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