JPH0418164A - Method for inspecting long cloth - Google Patents

Abstract

PURPOSE:To carry out detection of defect in good reappearance by using a pickup element having spectrosensitive characteristics close to color tone related with complementary color of color tone of a long cloth, based on spectroreflection curve read at a basic part of the long cloth. CONSTITUTION:A long cloth is illuminated while continuously or intermittently carrying the long cloth and detection of defect of the long cloth is carried out using a pickup element having spectrosensitive characteristics nearest to color tone being relationship of complementary color with color tone of the above-mentioned long cloth based on spectroreflection curve obtained by reading reflection light or transmitted light emitted from the long cloth at a basic part of the long cloth.

Description

DETAILED DESCRIPTION OF THE INVENTION (Field of Industrial Application) The present invention relates to an inspection method for detecting defects inherent in fiber structures such as woven fabrics, knits, and nonwoven fabrics, or elongated objects such as film-like objects. More specifically, the present invention relates to an inspection method for detecting defects caused by optical density modulation or defects that cause optical density modulation in the fiber structure or film-like material. More specifically, examples of defects targeted by the present invention include, but are not limited to, "stains", "wrinkles", "dirt", "fading", "scratches", "protrusions", and "blurring". ""hole""
dent,” “cloudy,” “foreign object,” “uneven color,” “scratches,” “pockmarks,” “craters,” and “strings.”
"Uneven weaving" etc. can be mentioned.

(Prior Art) Conventionally, inspection of defects inherent in these fibrous structures or film-like materials has relied entirely on the visual or tactile sense of an expert.

Detection of the presence of a defect by a skilled person is not simply based on the results obtained by observing the object to be inspected from a certain direction. Although it is extremely difficult to quantify or even explain qualitatively, it is known that humans recognize events based on extremely multidimensional information. This also applies to defect detection, and the recognition of a defect is the result of observing the object to be inspected from many different angles.

For example, when inspecting an object to be inspected while continuously transporting it, humans may be able to recognize defects simply by looking at the image of the object at a certain moment, according to their sense of vision. Instead, defects are detected from the subtle movements of the image that continuously change from moment to moment due to vibrations caused by transportation, fluctuations in lighting, and other factors.

As mentioned above, the mechanism by which human senses detect defects is astonishing and even mysterious.

However, while humans have excellent judgment, recognition, and discrimination abilities, human visual and tactile inspection requires skill on the part of those conducting the inspection, and is not always efficient and accurate. That cannot be said. These problems are fatal when inspecting fibrous structures or film-like products that are produced in large quantities using a large number of production machines. In particular, fiber structures have extremely complex structures even in normal parts, and detection of defects is based on this complex structure, in other words, from among "variations" and also due to other disturbances such as noise. This is a process of extracting particularly large deviations after taking into account the influence, and a certain standard should be set for this. However, even with the eyes of an experienced expert, it is virtually impossible to constantly inspect many fiber structures with a constant standard.

In recent years, COD sensors have become available at low cost as solid-state imaging devices that replace image pickup tubes, and with the development of signal processing technology and image processing technology, these sensory tests that have previously relied on human vision have changed. Many attempts are being made to replace them with machines.

However, as mentioned above, compared to humans who make comprehensive judgments, recognition, and identification based on multifaceted information, the information obtained when observing an object with a machine, such as an optical sensor, is , it is literally just the result of observing the object to be inspected from one side, and the amount of information obtained is extremely small.

With the current signal processing technology and computer image processing technology, it is not possible to automatically make advanced judgments such as defect detection in real time from such a small amount of information using a machine within a practical range and in real time. However, it is extremely difficult.

(Problems to be Solved by the Invention) In other words, in the conventional defect detection that relies on the visual or tactile sense of an expert, the person performing the inspection requires skill, and it is not always efficient and accurate. This cannot be said to be sufficient, and problems remain in terms of reproducibility, etc. In addition, as for fabric inspection devices that can automatically detect defects mechanically in real time within a practical range, we have not yet found anything that can be used at a practical level.

As a result, even though the efficiency and accuracy are not necessarily sufficient, and there are still problems with reproducibility, inspections still rely on the eyes of experts.
The reality is that this is being done.

In recent years, it has become possible to stabilize the quality of industrial products at a high level through QC, that is, thorough quality control.In recent years, it has become possible to stabilize the quality of industrial products at a high level through thorough quality control. I cannot hide my surprise at the quality control that has been carried out.

In view of this situation, the present inventors have conducted extensive research, and as a result,
We have achieved the next invention related to a method for detecting defects with good reproducibility and according to a certain standard.

(Means for Solving the Problems) That is, the present invention illuminates the long object while conveying the long object continuously or intermittently, and illuminates the reflected light or transmitted light from the long object due to the illumination. In a long object inspection method that uses multiple image sensors with different spectral sensitivity characteristics to determine defects, the color tone of the long object is determined based on the spectral reflection curve read from the reference part of the long object. This is a long object inspection method characterized by detecting defects using an image sensor having spectral sensitivity characteristics closest to complementary color tones.

In the present invention, for example, in a part of a roller system that continuously conveys a fibrous structure or a film-like object to be inspected, the fibrous structure or film-like object is illuminated, and the fibrous structure or film-like object is illuminated. The purpose of this method is to use a sensor to observe the modulation of optical density due to defects inherent in objects, and to detect defects.

The "plurality of image sensors having different spectral sensitivity characteristics" used in the present invention include, for example, a color sensor that can obtain signal output in the form of color separation into the three primary colors of RGB. As the color sensor, for example, a color image pickup tube, a color 〇〇D1 color line sensor, etc. can be used.

Further, if necessary, a sensor sensitive to the visible light region and a sensor sensitive to the infrared region or ultraviolet region, for example, may be combined. Furthermore, if necessary, these sensors may be combined with a filter having more preferable spectral transmission characteristics.

In the present invention, a particularly preferred combination of spectral sensitivities is 370±75 nm, preferably ±50 nm, 450±
75, nm preferably ±50 nm 650 ± 100, nm
Preferably a combination of three sensors with peak spectral sensitivity at ±50 nm, or 300 ± 75, nm preferably ±50 nm 450 ±
75, nm preferably ±50 nm 1200 ± 150, n
Preferably, a combination of three types of sensors having a spectral sensitivity peak at ±75 nm, or a combination of a COD sensor sensitive to 3θO to 750 nm and an infrared sensor sensitive to 1200 to 3500 nm, etc. can be used.

In the present invention, image sensors having different spectral characteristics do not necessarily need to be installed at the same location. In addition, it is not necessary to use one sensor each with different spectral characteristics; the same sensor on the object to be inspected detected by multiple sensors (in this case, sensors with the same spectral characteristics may be included) By calculating the "sum" of the signal parts corresponding to the two locations, the noise is canceled out,
It is also possible to perform signal processing such as emphasizing signals caused by defects.

In the present invention, a single image sensor among a plurality of image sensors having different spectral sensitivity characteristics may be used, or if necessary, a sum, difference, product, quotient, logical sum, and logical product of a plurality of image sensors may be used. It is also possible to detect defects from such methods.

In particular, when the difference between the combination with the largest product of the spectral reflection curve, the emission spectral characteristics of the illumination light, and the spectral sensitivity characteristics of each image sensor and the next largest combination is 10% or less. The "sum" of the outputs obtained from both may be used.

In the present invention, there are no particular limitations on the means of illumination. However, as a preferred illumination method, a method can be used in which different illumination means having preferable spectral radiation characteristics are used in combination for each sensor having different spectral characteristics.

When using a color sensor, when using R output, it is preferable to use "light generated from a heating element", more specifically, a halogen lamp, an incandescent bulb, a reflex lamp, etc., especially with wavelengths extending to the long wavelength side. It is preferable to use a lighting fixture with a distribution, and the color temperature of the light source is preferably 3100 or higher. Further, when using G output or B output, it is preferable to use a lighting fixture having a wavelength distribution particularly extending toward the short wavelength side, such as a "blue-white fluorescent lamp."

Further, in special cases, a light source having extremely narrow spectral radiation characteristics such as a laser beam may be used, and when such a light source is used, an illumination method such as scanning laser light may be used.

More preferably, these illumination means should be set so that the most preferable method can be switched in consideration of the color tone of the object to be inspected, the reflection spectral characteristics, the level of the defect to be detected, etc.

Regarding the position where the illumination means is provided in the present invention,
Although not particularly limited, it is preferable to provide it in a direction perpendicular to the object to be inspected. However, this is not the case especially when the focus is on detecting a specific type of defect.
For example, it may be preferable that the center of the device for illuminating the fibrous structure or film is located at an angle of 0 to 15 degrees from the horizontal direction of the fibrous structure or film that is the object to be inspected. be. Preferably, the illumination means in the present invention should be arranged so that illumination means from a plurality of directions can be switched or used in combination as necessary.

In the present invention, a preferred signal processing means is a method for detecting defects by binarizing the outputs obtained from "a plurality of sensors having different spectral characteristics" at an appropriate threshold level. In the present invention, in order to increase the ability to detect defects, shading correction of the signal output of the sensor and γ
It is also possible to perform detection by applying a threshold after (gamma) correction. In this case, the γ (gamma) correction level and threshold may vary depending on the color tone, surface texture, etc. of the inspected object.
A method of setting levels may also be used. Furthermore, signal expansion with a different algorithm may be performed.

When a plurality of image sensors are used in combination, defects may be determined by finally calculating the logical sum of the results obtained by signal processing their outputs.

(Function) The defects that the present invention attempts to detect in the object to be inspected, that is, fiber structures such as woven fabrics, knits, nonwoven fabrics, or film-like objects, are defects caused by optical density modulation. , or a defect that results in a modulation of optical density.

As mentioned above, when these detections and outputs are performed by the visual sense of an expert, judgments are not made based on the results obtained by simply observing the object to be inspected from a single direction; Judgments are made based on the results of observing the inspected object dimensionally and from multiple angles.

However, when automatically detecting defects based on one-dimensional information obtained by machines and taking into account the effects of other disturbance noise, some kind of filtering and enhancement as well as optimization of observation conditions are essential. .

The present invention shows that optimizing observation conditions by paying particular attention to the color tone of the object to be inspected, that is, the color coordinates, results in a very large effect on defect detection. Furthermore, the present invention simultaneously achieves the filtering and enhancement effects described above.

EXAMPLES The present invention will be explained in more detail by way of Examples below, but the present invention is not limited thereto.

(Examples) Example 1 FIG. 1 is a schematic explanatory diagram showing a detection portion of a fabric inspection device according to the present invention. As shown in the figure, two feed rollers are installed as part of the roller system that continuously conveys the fibrous structure or film-like object to be inspected, and the fibrous structure or film is transported at the center of the two rollers. This method illuminates the object, observes the fiber structure or film-like object using a color linear sensor, and detects defects.

A Dlii5 standard light source is used for illumination, and the light source is provided at a position perpendicular to the center of the object to be inspected. Roller width is 19
The feeding speed of the fiber structure or film-like material was varied between 0 and 75 m/min by controlling the drive motor of the conveying system with an inverter.

This inspection device operates based on the flowchart shown in FIG. The "color coordinate values" of the reference portion of the object to be inspected are measured using a colorimeter at an appropriate portion of the introduction section of the object to be inspected each time the object is set up. The measured values are read into the CPU online, and based on a predetermined numerical table, the CPU determines which RGB output should be used, and the switching is automatically performed.

Among the outputs of the color linear sensor, the signal used for defect detection is binarized by a predetermined threshold after passing through a shading correction circuit and a γ (gamma) correction circuit, and the presence or absence of a defect is determined.

FIG. 2 is an example of a signal obtained from a normal part without defects when the object to be inspected is a plain fabric. You can see noise components unique to textiles. Figure 3 shows a defect.

In this case, this is an example of a signal obtained from a location where there is a "stain". Changes in the concentration of the inspected object due to defects are very clearly captured, and there is no problem in detecting defects even in the noise peculiar to textiles.

For a total of 40 types of fabrics with a total length of 5000 m, defects were detected separately using this fabric inspection device and a skilled inspector at an average conveyance speed of 50 m/min.

The fabrics used in the tests are repeatedly and carefully inspected by multiple experienced inspectors, and defects are mapped out.

Now, the defect detection rate of the fabric inspection device was 87%, and the defect detection rate of the skilled inspector was 91%. The location of the detected defect is
At least it matched the defect map previously obtained.

Comparative Example 1 Using the same device as in the example, the color linear sensor output was fixed at the B output, and the following tests were conducted in the same manner as in the example. The defect detection rate was only 67%, a result that should be judged to be of no value for practical use.

(Effects of the Invention) According to the present invention, compared to human visual inspection, it does not require skill and is superior in terms of efficiency and accuracy, and it is also possible to quantitatively determine judgment criteria. .

[Brief explanation of drawings]

FIG. 1 is a schematic explanatory diagram of a fabric inspection device according to the present invention. FIG. 2 is an example of a signal obtained from a defect-free portion in the embodiment. FIG. 3 is an example of a signal obtained from a defective portion in the embodiment. FIG. 4 is an example of an operation flowchart of the fabric inspection apparatus according to the present invention. ■ Textile structure or film-like material ■ Feed roller ■ Standard light source ■ Color linear sensor ■ Switch ■ Shading correction circuit ■ Gamma correction circuit ■ Judgment and display section ■ Colorimeter @IcPU

Claims (1)

[Claims] (1) While conveying long objects continuously or intermittently,
In a long object inspection method, the long object is illuminated and defects are determined using a plurality of imaging elements having different spectral sensitivity characteristics using reflected light or transmitted light from the long object caused by the illumination,
Defect detection is performed based on a spectral reflection curve read from a reference portion of the long object using an image sensor having spectral sensitivity characteristics closest to a color tone complementary to the color tone of the long object. A method for inspecting long objects.