JPH04220344A - Printed matter monitoring device - Google Patents

Abstract

PURPOSE:To detect inferior printing and identify the contents thereof by calculating fraction defective of a non-image area and an image area in each unit region of a printing surface based on reflection density information of each picture element and comparing the fraction defective with fraction defective distribution values set beforehand. CONSTITUTION:Fraction defectives in a non-image area and image area in each unit region of a printing surface are calculated at a central processing device. Reflection density information is obtained in such a manner that a plurality of light receiving elements 1 of a detection sensor 100 for monitoring the printing surface receive reflected light from the printing surface to generate photocurrent, which is subjected to current-voltage logarithmic conversion at a logarithmic converter 13, which information is divided and converted to digital values and stored for each picture element in a storage device 8. Arithmatic processing is applied to the values and fraction defective matrix area ERR (i) and ERR (i) of non-image and image areas are stored in memories 23,24. The values for each picture element in longitudinal direction and fraction defective distribution values 34 are compared at a defective content identification unit 32 to identify defective contents such as oil leak, stripe-like stain to generate identification signal.

Description

[Detailed description of the invention]

0001

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention is used in various printing machines such as rotary offset printing machines, and more particularly relates to a printed matter monitoring device for detecting defects such as stains on printed matter.

0002

2. Description of the Related Art Conventionally, as a printed matter monitoring device for detecting defects such as stains on printed matter, for example, Japanese Patent Laid-Open No. 60-5853
5 and JP-A-56-98638 are known. These monitor stains and the like occurring on the printing surface using detection sensors. The detection sensor extends in a direction perpendicular to the direction of movement of the printing surface. Then, as the print surface moves, the entire print surface is monitored in a linear manner by sequentially scanning the detection sensor.

In other words, in the direction perpendicular to the direction of movement of the printing surface (longitudinal direction), the number of light-receiving elements arranged varies, and in the direction of movement of the printing surface (flow direction), the total number of light receiving elements changes depending on the movement of the printing surface. Divide the print surface into one divided zone (
It monitors each pixel (pixel by pixel).

[0004] Then, after printing adjustment, a predetermined number of printed materials are measured with a non-defective product produced, and by determining the average value, maximum value, minimum value, etc., the reference value of each pixel {reference value matrix Ao ); i is the longitudinal pixel number, j is the longitudinal pixel number} and the tolerance {tolerance matrix △ (i, j)
} to make. Thereafter, the measured values for each printed matter {measured value matrix Ak (i, j); k is the kth printed matter} are determined.

[0005] When the difference between the reference value and the measured value is within a tolerance value, the product is determined to be good, and when it deviates from the tolerance value, it is determined to be defective. That is, |Ao(i,j)−Ak(i
, j) | is less than or equal to △ (i, j), the product is good, |Ao(i
, j)-Ak(i, j)| is larger than Δ (i, j), the product is determined to be defective.

[0006]

SUMMARY OF THE INVENTION According to the above-mentioned prior art, a defect can be determined when the variation value of a pixel exceeds a permissible value.

[0007] However, defects on the printing surface include not only those that suddenly occur at unspecified locations, such as ink flying, water dripping, and oil dripping, but also those that occur suddenly at unspecified positions, such as ink splatter, water dripping, oil dripping, etc.; There are density irregularities that occur in the flow direction related to this, and streak defects that occur in the flow direction due to blanket defects and the like. Unlike temporary defects such as ink flying, water dripping, oil dripping, etc., density unevenness and streaky defects are continuous and require adjustment of the printing press.

As described above, there are two types of defects in printed matter, so it is necessary to identify them and notify the operator, or
It is desired that the printed matter monitoring device be able to take measures such as automatically adjusting the machine or stopping the machine.

However, the prior art cannot identify the content of such defects and can only treat them as defects in printed matter.

[0010] The present invention has been made to solve the above-mentioned problems, and its purpose is to solve the problem of printing defects.
Printing defects such as ink flying, water dripping, oil dripping, uneven density, etc.
To provide a printed matter monitoring device capable of identifying and monitoring streaky defects.

[0011]

[Means for Solving the Problems] In order to achieve the above object, in the present invention, the defect rate in the non-image area within each unit area of the printing surface to be monitored is a central processing unit that calculates the defective rate in the non-image area and the defective rate in the image area calculated by the central processing unit based on reflection density information for each pixel of the printing surface; and a defect content identification unit that determines the defect content of the printed surface by comparing the defect rate classification value set in advance.

0012

[Operation] The defective rate in the non-image area within each unit area of the printing surface to be monitored and the defective rate in the image area within the same area are determined based on the reflection density information for each pixel on the printing surface. It is calculated by the central processing unit.

[0013] Then, the defective rate in the non-image area and the defective rate in the image area determined by the central processing unit are compared with a preset defective rate classification value in the defect content identification section. This determines the content of the defect on the printed surface.

[0014] This not only detects printing defects but also identifies the details of the defects.

[0015]

DESCRIPTION OF THE PREFERRED EMBODIMENTS FIGS. 1 and 2 schematically show the configuration of a printed matter monitoring apparatus according to an embodiment of the present invention, in which a detection sensor 100 monitors dirt and the like occurring on a printed surface 101 to be monitored. Note that stains on the printing surface 101 occur due to accidents such as flying ink, water dripping, oil dripping, etc., so it is necessary to constantly monitor it. The detection sensor 100 extends in a direction (longitudinal direction χ of the printing surface) perpendicular to the moving direction of the printing surface 101 (flow direction y of the printing surface), and a plurality of sensors are arranged at appropriate intervals in the longitudinal direction χ of the printing surface. (l) light receiving elements 1.

The light receiving element 1 detects reflected light from the printing surface 101.

The photocurrent generated in the light receiving element 1 in response to the reflected light from the printing surface 101 is subjected to current-voltage logarithmic conversion by the logarithmic conversion section 2, thereby converting it into reflection density information and converting it to the necessary voltage level. amplified.

Reflection density information for each pixel is sent to the sample and hold amplifier 3. Sample hold amplifier 3
is given a sample signal from an encoder unit 4 that generates a signal according to the pixel size in the web flow direction χ in accordance with the movement of the printing surface 101. 101 in the fine pixel e as shown in FIG.
It is divided into m pieces.

The reflection density information for each pixel sampled and held in accordance with the pixel by the sample and hold amplifier 3 is time-divided by the multiplexer 5, and is sequentially A/
The signal is sent to the D converter 6. A plurality of multiplexers 5 and A/D converters 6 may be used in parallel to shorten processing time.

The A/D converter 6 converts the reflection density information for each pixel from an analog value to a digital value.

Each piece of reflection density information converted into a digital value is stored by the memory controller 7 in a predetermined memory location of the storage device 8 for each pixel position.

The storage device 8 is divided into the following parts depending on its memory contents. That is, memory 9 (blank page matrix section Dw(i)), memory 10 (blank page tolerance matrix section Dwa(i)), memory 11 (reference value matrix section Ds(i,j)), memory 12 (tolerance value matrix section Dwa(i)), matrix section Da(i,j)), memory 13 (image judgment matrix section Z1(i,j)), memory 14 (image judgment matrix section Z2(i,j)), memory 15 (measurement value matrix section Dk(i, , j)), memory 16 (judgment result matrix section Dout (i, j)), memory 17 (product matrix section ZD1 (i, j)), memory 18 (product matrix section ZD2 (i, j)), memory 19 (addition matrix section Z1 SUM(i)), memory 20 (addition matrix section Z2 SUM(i)), memory 21 (addition matrix section ZD1 SUM(i)), memory 22
(addition matrix section ZD2 SUM(i)), memory 23 (defective rate matrix section ERR1(i)), memory 24 (defective rate matrix section ERR2(i)), memory 25 (light receiving element number memory l), memory 26 ( Print surface flow direction resolution number memory m), memory 27 (predetermined number of sheets memory n
), memory 28 (maximum value matrix section MAX (i,
j)), memory 29 (minimum value matrix section MIN (
i, j)), and a memory 30 (coefficient memory α).

The arithmetic device 31 performs a specified arithmetic operation (
It performs addition, subtraction, multiplication, division, and comparison).

This arithmetic unit 31 and memory controller 7
A central processing unit 35 is constituted by the storage device 8 and the storage device 8 mentioned above.

The defect content identifying section 32 determines the defective rate matrix section ERR1 (i
), ERR2(i) and the defect rate classification value stored in the defect content identifying section 32 to identify the defect content and generate an identification signal.

The identification signal is sent to the print control device 33, and the print control device 33 displays information to the operator, stops the printing press, and instructs the printing press adjustment device.

It should be noted that the defect rate classification value 34 can be rewritten as appropriate by the print control device 33.

Next, a series of procedures for determining the defect content of the printed surface 101 will be explained using FIGS. 4(a) to 4(c). <Pre-monitoring preparation steps><Step1> Blank paper (white background)
Prepare a predetermined number of sheets (appropriately determined depending on the capacity of the printed matter monitoring device and the fluctuation status of the printing press).

The reflection density information of each pixel from the first blank page is stored at a predetermined location in the memory 15 as a reflection density value. At the same time, it is also stored in the memory 28 and the memory 29. From the second blank page, the value is added and stored in the memory 15, compared with the value previously stored in the memory 28, and if it is larger, it is stored again in the memory 29.
If the value is smaller than the previously stored value, it is stored again. This process is repeated for a predetermined number of sheets (n sheets) stored in the memory 27 (predetermined number of sheets memory). After processing a predetermined number of images, the contents of the memory 15 are divided by the value n of the memory 27, and the average value of each pixel is determined and stored in the memory 15. Then, all the contents of the memory 15 are added for each pixel in the longitudinal direction for each pixel in the longitudinal direction, divided by the value in the memory 26, and stored in the memory 9.

In this way, the blank matrix D is stored in the memory 9.
w(i) is formed.

[0031] This blank matrix is grouped together for each flow direction as Dw(i) because, although there is not much variation in the reflection density value in the flow direction, there is a difference in the light source of the monitoring device in the longitudinal direction. - This is because there are variations due to unevenness in the light receiving system, unevenness in the light receiving element, etc.

[0032] The same reason will be used below when the matrix is grouped for each longitudinal pixel. The flow direction pixels e, which are grouped for each longitudinal direction pixel, constitute a unit area f.

Next, all the contents of the memory 28 are added for each longitudinal pixel, and this is divided by the value of the memory 26 and stored in the memory 10. Then, add all the contents of the memory 29 for each longitudinal pixel and the flow direction pixels,
This is divided by the value in memory 26, subtracted from the value in memory 10, and stored back into memory 10. Further, the value in the memory 10 for each pixel is multiplied by the value α in the memory 30 (coefficient memory) and then stored in the memory 10 again.

In this way, the blank surface tolerance matrix Dwa (i) is formed in the memory 10.

<Step 2> Next, when the printing operator recognizes that good products have been printed after the print adjustment work, reference data is created using these non-defective products as reference printing surfaces. Each pixel reflection density value from the first reference print surface is stored at a predetermined location in the memory 11. At the same time, the data is also stored in predetermined locations in the memory 28 and the memory 29. From the second reference print surface, the value is added and stored in the memory 11, and the value is compared in size with the value previously stored in the memory 28, and if it is larger, it is stored again in the memory 28, and then stored in the memory 29. is compared in magnitude with the value previously stored in the memory 29, and if it is smaller, it is stored again in the memory 29. This process is repeated for a predetermined number of sheets (n sheets) stored in the memory 27. After processing a predetermined number of images, the contents of the memory 11 are divided by the value n of the memory 27 to obtain the average value of each pixel, which is then stored back into the memory 11. In this way, the reference value matrix D is stored in the memory 11.
s(i,j) is formed.

Next, the contents of the memory 29 are subtracted from the contents of the memory 28 and stored in the memory 12. The contents of the memory 12 are multiplied by the value α of the memory 30 (coefficient memory) and then stored back into the memory 12.

In this way, the tolerance matrix Da(i,j) is formed in the memory 12.

<Step 3> Standard value matrix Ds (
For each pixel in the longitudinal direction (i, j), calculate the difference from the blank surface matrix Dw (i) for all pixels in the flow direction, and if the absolute value of this difference is smaller than the blank surface tolerance matrix Dwa (i), that pixel is determined to be a white background area (non-image area). At this time, 0 is given to the corresponding position Z1 (i, j) of the memory 13, and 1 is given to the corresponding position Z2 (i, j) of the memory 14.
give. The absolute value of the difference is the blank surface tolerance matrix Dw
If it is larger than a (i), the pixel is determined to be in the image portion. At this time, the corresponding position Z1(i,j) of the memory 13
1 and 0 to the corresponding location Z2(i,j) in the memory 14.
give. In this way, an image determination matrix Z1 (i, j) having image information is formed in the memory 13, and an image determination matrix Z2 having white background information is formed in the memory 14.
(i,j) is formed.

Next, the image judgment matrix Z1(i,j)
The memory 19 stores the summation value obtained by adding up all the pixels in the longitudinal direction for each pixel in the longitudinal direction. In addition, the sum value obtained by adding all the pixels in the longitudinal direction of the memory 14 for each pixel in the longitudinal direction is stored in the memory 14.
Store as 0.

In this way, the addition matrix Z is stored in the memory 19.
1 SUM(i) is formed and a summing matrix Z2 SUM(i) is formed in the memory 20.

[0041] Up to this point, the pre-monitoring preparation operation is completed.

Note that in the above explanation, the value n of the predetermined number of sheets memory in the memory 27 and the value α of the coefficient memory in the memory 30 are always treated as the same, but they are different values depending on the blank surface and the reference surface. It's good as well. <<Defective Product Monitoring Step>> Next, the following processing is performed on the printed surface to be monitored to determine a defective product.

<Step 4> The reflection density value of each pixel on the printing surface 101 is stored in a predetermined position in the memory 15. A measured value matrix Dk(i,j) is thus formed in the memory 15. (Note that k represents the k-th printing surface.) Measured value matrix Dk (i, j) and reference value matrix Ds
(i, j), and the difference is the tolerance matrix D
If it is larger than the value of a(i, j), it is judged as a defective product,
Give 1 to the contents of memory 16, otherwise give 0.

In this way, the determination result matrix D0ut(i,j) is formed in the memory 16. <Step 5> Next, image judgment matrix Z1(i, j
) and the determination result matrix Dout (i, j) for each pixel, and the calculation result is stored in the memory 17. In addition, the image determination matrix Z2 (i, j) is multiplied by the determination result matrix Dout (i, j) for each pixel,
The calculation results are stored in the memory 18.

In this way, the product matrix ZD1 (
i, j) is formed. Similarly, a product matrix ZD2(i,j) is formed in the memory 18, which indicates the position of a defective pixel occurring in a white background area as a non-image area of the printing surface.

<Step 6> Next, the product matrix ZD
1 (i, j) The sum value obtained by adding all the pixels in the longitudinal direction for each pixel in the longitudinal direction is stored in the memory 21. Further, the sum value obtained by adding all the pixels in the longitudinal direction of the product matrix ZD2 (i, j) for each pixel in the longitudinal direction is stored in the memory 22.

In this way, the addition matrix Z is stored in the memory 21.
D1 SUM(i) is formed and a summing matrix ZD2 SUM(i) is formed in memory 22.

Next, the addition matrix ZD1 SUM(
i) is divided by the corresponding value of the product matrix ZD1 (i, j) and stored in the memory 23 at a position corresponding to each pixel. Further, the content of the addition matrix ZD2 SUM(i) is divided by the corresponding value of the product matrix ZD2(i, j) and stored in the memory 24 at a position corresponding to each pixel.

In this way, the defective rate matrix ERR1(i) for the image portion of the printed surface is formed in the memory 23, and the defective rate matrix ERR2(i) for the white background portion of the printed surface is stored in the memory 24.
i) is formed.

<Step 7> Defective rate matrix ERR
1(i) and ERR2(i) are determined by the defect content identification unit 32.
If the defective rate classification value 34 for each longitudinal pixel is defined as "large" when it is larger than the defective rate classification value 34, and "small" when it is smaller than the defective rate classification value 34, then the defective rate matrix ERR1(i),ER
Depending on the value of R2(i), the following four cases may occur.

■ ERR1(i) is “large” and ERR2
When (i) is “large” ■ When ERR1 (i) is “large” and ERR2 (i) is “small” ■ When ERR1 (i) is “small” and ERR2 (i) is “large” ■ If ERR1(i) is "small" and ERR2(i) is "small", in the case of ■, many defects occur in the white background area of the printed surface, and defects also occur in the image area. , it is thought that streak-like stains that were darker than the density of the image area were generated on the printed surface.

[0052] In the case of ■, many defects occur in the white background area of the printed surface, and not so many defects occur in the image area, so streak-like stains with a relatively light density compared to the density of the image area occur. It is thought that this occurred on the printed surface.

Thus, in the cases of (1) and (2), it is determined that streak-like stains have occurred on the printed surface. In the case of (2), there were few defects in the white background area of the printed surface, but many defects occurred in the image area, so it is considered that there was a defect in image formation. That is, the formed image has streak-like portions having a density different from that of the reference image. From this, in the case of ■, it is determined that streak-like density unevenness has occurred in the image area of the printed surface.

In the case of ■, since there are not many defects in either the image area or the white background area of the printed surface, it is determined that dotted stains have occurred on the printed surface.

<Step 8> If the defect content is striped density unevenness (■), the defect content identifying section 32 further performs the following process.

[0056] For example, the control width of the printing press ink drawing device is set to 3.
0mm, and if the longitudinal pixel width of the monitoring device is, for example, 5mm, then the width within one control width of the ink fountain device is 30÷5=
It is composed of 6 pixels. From this, if the defect content determination result is ``■'' and this is the same for, for example, six consecutive pixels in the longitudinal direction, it is determined that this is a streak-like density unevenness caused by the control width of the ink fountain device.

[0057] The above steps (Step 1 to Step 8)
), it is possible to know not only that a defect has occurred on the printed surface, but also the details of the defect.

[0058] Then, the defective product monitoring step (steps 4 to 8) is repeated for each printing surface from the second sheet onwards.
By displaying information to the operator or providing feedback to the printing press adjustment device for automatic adjustment, automatic stop, etc. according to the determination result, it is possible to prevent a large number of defects from occurring and contribute to improving the operating rate of the printing press.

In this embodiment, even if the printed image is monochrome or four-color printing, the image is not perceived as color but simply as shading. However, it is obvious that more detailed printing error information can be obtained by performing color separation processing in the sensor section and using the same method for each color.

[0060]

[Effects of the Invention] As explained above, in the present invention,
By comparing the defective rate and the defective rate separation value, we can distinguish between temporary defects such as ink splatter, water dripping, oil dripping, etc., and printing defects such as streaky density unevenness and streaky stains. It can be divided into continuous failure. As a result, in the case of continuous defects, by instructing the operator to adjust the printing press, automatically adjusting it, stopping the printing press, etc., it is possible to prevent a large number of defects from occurring and contribute to improving the operating rate of the printing press.

[Brief explanation of the drawing]

FIG. 1 is a schematic perspective view of a printed matter monitoring device according to an embodiment of the present invention.

FIG. 2 is a schematic diagram of the main parts of the device.

FIG. 3 is a diagram showing a state in which the printing surface monitored by the apparatus is divided into pixels.

FIG. 4(a) is a flowchart showing a series of steps in determining the content of defects on the printed surface in the same apparatus.

FIG. 4(b) is a flowchart showing the same procedure.

FIG. 4(c) is a flowchart showing the same procedure.

[Explanation of symbols]

32 Defect content identification section 35 Central processing unit 101 Printing surface e pixel f Unit area

Claims (1)

[Claims] Claim 1: The defective rate in the non-image area in each unit area of the printing surface to be monitored and the defective rate in the image area in the same area are determined based on reflection density information for each pixel on the printing surface. The central processing unit calculates the printing process by comparing the defective rate in the non-image area and the defective rate in the image area calculated by the central processing unit with a preset defective rate classification value. A printed matter monitoring device comprising: a defect content identification unit that determines defect content of a surface.