JP2014085221A - Surface defect inspection method and device - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a surface defect inspection method and device capable of rating an object to be inspected on the basis of a minute defect that becomes a problem if occurring in series.SOLUTION: A surface defect inspection method includes: a first step of extracting a minute defect in each unit area formed by dividing an object to be inspected in a longitudinal direction and a width direction and calculating the number of defects in the unit area; a second step of calculating the longitudinal moving average number of defects in the unit areas adjacent in the longitudinal direction; a third step of comparing the calculated longitudinal moving average number of defects with a predetermined threshold and extracting the calculated longitudinal moving average number of defects as an area exceeding the threshold of the longitudinal moving average number of defects when the number exceeds the threshold; and a fourth step of calculating the number of extracted areas exceeding the threshold of the longitudinal moving average number of defects and rating the object to be inspected on the basis of the calculated number of the areas exceeding the threshold of the longitudinal moving average number of defects.

Description

  The present invention relates to a surface defect inspection method and apparatus for inspecting a surface defect of a strip-shaped object to be continuously conveyed, and particularly relates to a rating of an object to be inspected such as a metal band or a film such as a steel plate or an aluminum plate. It is.

  Conventionally, surface defects of a strip-shaped object such as a steel plate or an aluminum plate have been inspected. If a surface defect is detected in such an inspection, remove the surface defect part or mark the surface defect part so that the surface defect part can be easily re-inspected. Shipped. However, removing the surface defect portion or marking the surface defect portion is an over action depending on the quality required by the customer, and increases the manufacturing cost of the object to be inspected.

  Against this background, in recent years, surface defect inspection devices have been proposed that rank an object to be inspected in order to determine whether the object to be inspected can be shipped according to the quality required by the customer (Patent Literature). 1). Specifically, this apparatus determines a representative defect of each unit length region formed by dividing the object to be inspected for each unit length based on the type and degree of the defect, and the determined representative defect is covered. The pass / fail determination of the object to be inspected is performed based on the ratio of being mixed into the inspection object and the preset allowable range. According to such a surface defect inspection apparatus, it is possible to prevent overaction such as removing the surface defect portion or marking the surface defect portion, and to ship the inspection object according to the required quality on the customer side. At the same time, the manufacturing cost can be reduced.

JP 2006-242906 A

  In recent years, the level of customer requirements for the surface quality of the object to be inspected has increased, and there have been an increasing number of cases where minute defects of φ0.2 to 0.5 mm, which have not been a problem until now, become a problem at customers. Yes. Such a micro defect is not a problem with a single shot, but is a level that causes a problem when swarmed. However, the surface defect inspection apparatus described in Patent Document 1 can perform the rating of the inspected object based on the defect that causes a problem in a single shot. Can't do it. For this reason, it has been expected to provide a technique capable of grading an object to be inspected based on minute defects that become a problem when swarming.

  The present invention has been made in view of the above problems, and an object of the present invention is to provide a surface defect inspection method and apparatus capable of grading an object to be inspected based on minute defects that are problematic when clustered.

  The above problems can be solved by the following invention.

[1] A first step of extracting a minute defect in each unit region formed by dividing the object to be inspected in the longitudinal direction and the width direction, and calculating the number of defects in the unit region;
A second step of calculating the number of moving average defects in the longitudinal direction of unit regions adjacent in the longitudinal direction;
A third step of comparing the calculated number of moving average defects in the longitudinal direction with a predetermined threshold value and, if the calculated number of moving average defects in the length direction exceeds the threshold value, extracting as a region exceeding the threshold value in the lengthwise moving average defect number;
A fourth step of calculating the number of the areas that exceed the extracted longitudinal moving average defect count threshold value, and classifying the object to be inspected based on the calculated number of areas exceeding the longitudinal moving average defect count threshold value;
A surface defect inspection method characterized by comprising:

[2] In the surface defect inspection method according to [1] above,
The first step calculates the number of weighted defects by multiplying the number of defects by a predetermined weighting factor determined according to the type and degree of surface defects, and calculates the sum of the calculated number of weighted defects. A surface defect inspection method comprising the step of calculating the number of defects in a unit region.

[3] In the surface defect inspection method according to [1] or [2] above,
A calculation step for determining a representative defect in each unit length region formed by dividing the object to be inspected in the longitudinal direction based on the type and degree of the surface defect, and calculating a mixing rate of the representative defect in the object to be inspected When,
A rating step that ranks the object to be inspected based on the mixing ratio of the representative defects, and performs pass / fail determination of the object to be inspected based on the rating result;
A surface defect inspection method characterized by comprising:

[4] In the surface defect inspection method according to [3] above,
The calculation step and the determination step are executed before executing the first to fourth steps, and only the first object to be inspected is determined to be acceptable by the rating based on the mixing rate of the representative defects. A surface defect inspection method characterized by executing the fourth step.

[5] First means for extracting a minute defect in each unit region formed by dividing the object to be inspected in the longitudinal direction and the width direction, and calculating the number of defects in the unit region;
A second means for calculating the number of moving average defects in the longitudinal direction of unit regions adjacent in the longitudinal direction;
A third means for comparing the calculated number of moving average defects in the longitudinal direction with a predetermined threshold and, if the calculated number of moving average defects in the longitudinal direction exceeds the threshold value, extracting as a region exceeding the threshold value in the lengthwise moving average defect number;
A fourth means for calculating the number of the longitudinal moving average defect count exceeding the threshold value extracted, and grading the object to be inspected based on the calculated longitudinal moving average defect count threshold exceeding area number;
A surface defect inspection apparatus comprising:

  According to the surface defect inspection method and apparatus according to the present invention, it is possible to rank an object to be inspected based on a minute defect that becomes a problem when clustering.

It is a block diagram which shows the structure of the surface defect inspection apparatus which is one Embodiment of this invention. It is a flowchart which shows the flow of the single defect rating process which is one Embodiment of this invention. It is a schematic diagram for demonstrating a unit length area | region. It is a flowchart which shows the flow of the cluster defect rating process which is one Embodiment of this invention. It is a schematic diagram for demonstrating a unit area | region. It is a schematic diagram for demonstrating the determination process of a longitudinal direction moving average defect number threshold value excess area | region. It is a flowchart which shows the flow of the pass / fail determination process which is one Embodiment of this invention.

Hereinafter, a surface defect inspection apparatus and a surface defect inspection method thereof according to an embodiment of the present invention will be described with reference to the drawings.
[Configuration of surface defect inspection equipment]
First, with reference to FIG. 1, the structure of the surface defect inspection apparatus which is one Embodiment of this invention is demonstrated.

  FIG. 1 is a block diagram showing a configuration of a surface defect inspection apparatus according to an embodiment of the present invention. As shown in FIG. 1, the surface defect inspection apparatus according to an embodiment of the present invention includes a front surface side and a back surface of a strip-shaped object 10 having a relatively thin thickness, such as a steel plate or an aluminum plate that is continuously conveyed. Image input units 11a and 11b are provided opposite to each other. The image input units 11a and 11b perform optical correction with an image input unit such as a CCD camera or a photomultiplier tube, an optical system for guiding light from the front or back surface of the inspection object 10 to the image input unit. And a filter.

  Image processing units 12a and 12b are connected to the image input units 11a and 11b, respectively. The image processing units 12a and 12b include an amplifier that amplifies the electric signal from the image input units 11a and 11b, a filter that cuts a noise signal included in the electric signal from the image input units 11a and 11b, and the image input units 11a and 11b. Input means such as an A / D converter that converts an analog signal from a digital signal into a digital signal, various correction processes such as shading correction to remove the influence of formation noise from the input signal, preprocessing such as a spatial filter, and A processing unit that executes processing such as n-value conversion processing for classifying the obtained image into two or more values and extraction processing for extracting defect (fats) candidates based on a predetermined threshold.

  Feature amount calculation units 13a and 13b are connected to the image processing units 12a and 12b, respectively. The feature amount calculation units 13a and 13b are the length, width, and area of the defect candidates extracted by the image processing units 12a and 12b, the distance in the longitudinal direction from the inspected object reference line, and the width from the inspected object reference end. A feature amount of a defect candidate such as a direction distance is calculated. A storage unit 16 is connected to the feature amount calculation units 13a and 13b. The storage unit 16 stores the feature amounts of defect candidates calculated by the feature amount calculation units 13a and 13b.

  The defect type determination unit 14 determines the type of defect candidate from the feature amount of the defect candidate according to a predetermined algorithm as will be described later. Further, the defect type determination unit 14 is connected to the defect degree determination unit 15, and the defect degree determination unit 15 determines the defect candidate from the defect candidate feature amount and the defect candidate type determined by the defect type determination unit 14. Determine the degree. Data relating to the types and degrees of defect candidates obtained by the defect type determination unit 14 and the defect level determination unit 15 are stored in the storage unit 16.

  A determination unit 17 is connected to the defect type determination unit 14 and the defect degree determination unit 15. Based on the data regarding the type and degree of defect candidates stored in the storage unit 16, the determination unit 17 determines the defect contamination rate on the surface, back surface, and both surfaces of the object to be inspected, the defect contamination rate for each defect degree, and the defect occurrence factor. The other defect mixing rate and the combined defect mixing rate are calculated, and the inspected object 10 is rated based on the calculation result. A result output unit 18 is connected to the determination unit 17, and the result output unit 18 outputs the determination defect to a display device such as a CRT, a printing device, a lighting device, and an annunciator such as a buzzer.

  The surface defect inspection apparatus having such a configuration performs a single defect rating process, a cluster defect rating process, and a pass / fail judgment process described below, and a single defect (defect that is a problem even with a single shot) and a cluster defect (single shot). In this case, the inspection object 10 is rated based on the minute defect that causes a problem when swarming, and the pass / fail determination of the inspection object 10 is performed based on the rating result.

In the present embodiment, the size of the micro defect has a size less than a threshold value set in the range of 0.5 to 1.0 mm, and the size of the single defect is newly determined to be greater than or equal to the threshold value. It shall have the magnitude | size beyond a threshold value. However, this threshold value can be adjusted according to the quality level required for the device under test 10. As for the cluster defect, when there are two or more micro defects in the unit region, a group of these micro defects is collectively referred to as a cluster defect.
Hereinafter, with reference to the flowcharts shown in FIGS. 2, 4, and 7, the operation of the surface defect inspection apparatus when executing the single defect determination process, the cluster defect determination process, and the pass / fail determination process will be described.

[Single defect rating process]
First, with reference to the flowchart shown in FIG. 2, the operation of the surface defect inspection apparatus when executing the single defect rating process for rating the inspected object 10 based on the single defect will be described.

  FIG. 2 is a flowchart showing a flow of single defect rating processing according to an embodiment of the present invention. The flowchart shown in FIG. 2 starts at the timing when the defect type determination unit 14 and the defect degree determination unit 15 determine data regarding the type and degree of the defect candidate, and the single defect determination process proceeds to step S1.

In the process of step S <b> 1, the determination unit 17 reads single defect data from the storage unit 16 and extracts a single defect for each unit length of the inspected object 10. In the present embodiment, as shown in FIG. 3, the determination unit 17 divides the longitudinal direction (length L) of the device under test 10 into a plurality of unit length regions _RA having a unit length n, Single defects are extracted for each of a plurality of unit length regions _RA . Further, when the single defect extends over two regions divided by the unit length, the determination unit 17 has a single defect in both regions, or, for example, a single defect having a longer single defect exists. A single defect is extracted as existing in either one of the regions.

  In addition, when there is a very long single defect extending over three or more regions, the determination unit 17 may exceptionally include single defects in all three or more regions. There is no limit. Thereby, the process of step S1 is completed and the single defect rating process proceeds to the process of step S2.

  In the process of step S2, the determination unit 17 determines a representative defect for each unit length of the object 10 to be inspected based on the process result of step S1. The representative defect is the single defect with the lowest degree. If there are a plurality of single defects of the same degree, the determination unit 17 sets the single defect having the highest priority according to the priority order of single defects as the representative defect.

  This is the case where, for example, “Defect type: Hege, degree: C”, “Defect type: Scratch, degree: C”, “Defect type: Pushing, degree: C” is detected, and the priority order is When it is higher in the order of the pressing bar, the scratch, and the scab, the determination unit 17 determines the representative defect as “defect type: scab, degree: C”. Thereby, the process of step S2 is completed and the single defect rating process proceeds to the process of step S3.

  In the process of step S3, the determination part 17 calculates the mixing rate in the to-be-inspected object 10 of the representative defect determined in the process of step S2 as a defect mixing rate using the following (1) Formula. The parameter m in the equation (1) indicates the number of representative defects in the entire inspection object 10, the parameter n indicates the unit length, and the parameter L indicates the length of the inspection object 10.

  Then, the determination unit 17 calculates a surface defect mixing rate, a back surface defect mixing rate, a double-sided defect mixing rate, a defect mixing rate by defect degree, a defect mixing rate by defect occurrence factor, and a combined defect mixing rate described below. Thereby, the process of step S3 is completed and the single defect rating process proceeds to the process of step S4.

[Surface defect contamination rate, back surface defect contamination rate, double-sided defect contamination rate]
The determination unit 17 calculates the defect contamination rate due to the representative defects on the front surface and the back surface as the surface defect contamination rate and the back surface defect contamination rate, respectively. Further, the determination unit 17 determines the representative defects on both surfaces in the same manner as described above by comparing the representative defects on the front and back surfaces in the same unit length region, and the defect calculated from the determined representative defects. The mixing rate is calculated as the double-sided defect mixing rate.

  This means that the double-sided defect mixing rate is not counted separately for the front surface and the back surface, but as a single object. Specifically, there are “Defect type: Hege, degree: C” and “Defect type: Scratch, degree: B” on the front surface, and “Defect type: Pushing, degree: C” on the back surface. The determination unit 17 sets “defect type: scratch, degree: B” on the surface as a representative defect on both sides. If the representative defects on the front and back are the same defect type and the same degree, the defect on either side will be the same result as the representative defect, but for example, the defect on the front side is set to be preferentially adopted. It is desirable to keep it.

[Defect mixing rate by defect level]
The determination unit 17 calculates the defect mixing rate for each defect level when the defect level is divided into a plurality of ranks as the defect mixing rate for each defect level. Further, the determination unit 17 calculates an accumulation of all defect mixture rates that are worse than a certain defect.

  Specifically, as shown in Table 1 below, when the degree of defects is set to five ranks A to E (the degree of defects worsens in the order of A, B, C, D, and E), the determination unit 17 calculates the defect mixing rate (defect mixing rate by defect level) x1 to x5 for each of the defects A to E. Note that the cumulative value of the defect mixing ratios x1 to x5 according to the degree of defects is 100% at the maximum. Further, when ranks C to E of the degree of defects are set as management items, the determination unit 17 calculates a value obtained by accumulating the defect mixture rates x3 to x5 of the ranks C to E of the degree of defects.

[Defect mixing rate by defect cause]
The determination unit 17 refers to the data stored in the storage unit 16 and displays representative defects according to the cause of the defect such as an original plate defect that occurs before the upper process and a self-line defect that occurs in the self-line. Classify and calculate the defect mixing rate (defect mixing rate by defect occurrence factor) for each factor of the representative defect. Specifically, the determination unit 17 classifies the representative defects based on the defect types, and controls the defect mixture rate for each defect type as shown in Table 2 below.

  Here, the defect types and the cause of defects are as follows: Hege and sliver are caused by steelmaking, scale is caused by hot-rolling, dross and non-plating are caused by plating, and scratches and pressing are caused by plate trouble There is a relationship like a defect.

[Combination defect mixing rate]
The determination unit 17 calculates a defect mixing rate by combining the above-described defect mixing rates. Specifically, in the case shown in Table 2, the determination unit 17 has a degree of C to E in each of a defect caused by steelmaking, a defect caused by hot rolling, a defect caused by plating, and a defect caused by a plate trouble. The cumulative value of the defect mixing rate is calculated, or the cumulative value of the defect mixing rate that combines the steel-making defect and the hot-rolling defect is calculated. The combination of defect types is appropriately set according to necessary information.

  In the process of step S4, the determination unit 17 ranks the inspected object 10 by comparing each defect mixture rate calculated by the process of step S3 with the allowable range of the defect mixture rate determined in advance for each customer requirement specification. I do. Examples of the allowable range of the defect mixing rate include the following ranges. Thereby, the process of step S4 is completed and a series of single defect rating processes are complete | finished.

[Example of acceptable range of defect contamination]
(1) Grade A products (products that can be sold to customers (or uses) α, β, γ) → The contamination rate of defects of grade C or higher (bad grades including grades C to E) is less than 1% (2 ) Grade B products (products that can be sold to customers (or uses) β and γ) → Less than 2% of defects with a degree C or higher (3) Grade C products (to customers (or uses) γ) Products that can be sold) → Less than 5% defect mixing rate (4) Products subject to scrap → More than 5% defect mixing rate> 5%

[Group defect rating processing]
Next, with reference to the flowchart shown in FIG. 4, operation | movement of the surface defect inspection apparatus at the time of performing the cluster defect rating process which ranks the to-be-inspected object 10 based on a cluster defect is demonstrated.

  FIG. 4 is a flowchart showing a flow of cluster defect rating processing according to an embodiment of the present invention. The flowchart shown in FIG. 4 starts at the timing when the data regarding the type and degree of the defect candidate is determined by the defect type determination unit 14 and the defect degree determination unit 15, and the swarm defect determination process proceeds to the process of step S11.

In the process of step S11, the determination unit 17 divides the device under test 10 into a plurality of unit areas. Specifically, determining unit 17, as shown in FIG. 5, to form a plurality of unit regions R _B by dividing the object to be inspected 10 in the longitudinal direction and the width direction. Then, the determination unit 17 divides the defect information stored in the storage unit 16 into each unit region, and extracts data on a minute defect whose center position is within the unit region for each unit region. Thereby, the process of step S11 is completed and the swarm defect rating process proceeds to the process of step S12.

  In the process of step S12, the determination unit 17 calculates the number of weighted defects of minute defects for each unit region using the process result of step S11. Specifically, the determination unit 17 assumes that there are m types of minute defects (m = 1 to m), the number of defects of the mth minute defect is Nm, and the weight of the mth minute defect is Km. The sum of the number of weighted defects for each type of micro defect is calculated for each unit region as the number of weighted defects in the unit region by using the following formula (2).

  More specifically, there are four types (m = 4) of large, medium, small, and minute micro defects, and the number (Nm) of each micro defect in a unit region is 0, 1, 3, and 4, respectively. If the weight coefficient (Km) of each micro defect is 10, 8, 6, 2, respectively, the determination unit 17 calculates the number of weighted defects in the unit area as shown in Table 3 below. Thereby, the process of step S12 is completed and the swarm defect rating process proceeds to the process of step S13.

  In the process of step S13, the determination unit 17 determines the number of weighted defects in the target unit area (i, j) calculated by the process of step S12 and the front area adjacent to the longitudinal direction (area on the downstream side in the transport direction). The number of weighted defects (i-1, j) is calculated from the number of defects and the moving average number of defects in the longitudinal direction.

Specifically, the defect number threshold value is 50, and the weights of the unit regions R _B 1, R _B 2, R _B 3, R _B 4, R _B 5, R _B 6, R _B 7, R _B 8 When the numbers of attached defects are 20, 40, 70, 90, 30, 70, 10, and 70, respectively, as shown in FIG. 6, the determination unit 17 substitutes into the following equation (3) to obtain the unit The longitudinal moving average number of defects in the regions R _B 1, R _B 2, R _B 3 and R _B 4 are calculated as 25, 55, 40 and 80, respectively. Thereby, the process of step S13 is completed and the swarm defect rating process proceeds to the process of step S14.

  Here, as an example, the two areas of the unit area and the front area are described as moving average target areas, but three or more areas in the longitudinal direction and the width direction may be calculated as moving average target areas. . In the present invention, by setting the size of the unit area (how to divide) and the number of target areas for which a moving average is taken, swarm defect rating described later can be performed more accurately.

In the process of step S14, the determination unit 17 uses the processing result of step S13 to convert the unit area (i, j) whose longitudinal moving average defect count is equal to or larger than the defect count threshold to the longitudinal moving average defect count threshold. Judged as an over-range. Specifically, as shown in FIG. 6, the determination unit 17 has a defect count threshold value of 50, and the moving average defect in the longitudinal direction of the unit regions R _B 1, R _B 2, R _B 3, R _B 4. When the numbers are 25, 55, 40, and 80, respectively, as illustrated in FIG. 6, the determination unit 17 sets the values of the determination flags M of the unit regions R _B 1, R _B 2, R _B 3, and R _B 4. Set to 0, 1, 0, 1 respectively.

  In the present embodiment, the determination flag M = 1 indicates that the number of longitudinal moving average defects is equal to or greater than the defect number threshold, and the determination flag M = 0 indicates that the number of longitudinal moving average defects is less than the defect number threshold. Indicates. The initial value of the determination flag M is set to 0. Thereby, the process of step S14 is completed, and the cluster defect rating process proceeds to the process of step S15.

  In the process of step S15, the determination unit 17 calculates the number of longitudinal moving average defect count threshold value exceeding regions in the inspection object 10 using the processing result of step S14. Specifically, the determination unit 17 substitutes the value of the determination flag M (i, j) of each unit region (i, j) into the following expression (4), thereby increasing the length in the object 10 to be inspected. The number of areas whose direction moving average defect count exceeds the threshold is calculated. Thereby, the process of step S15 is completed and the swarm defect rating process proceeds to the process of step S16.

  In the process of step S16, the determination unit 17 performs the longitudinal moving average defect determined in advance according to the number of the longitudinal moving average defect number exceeding the threshold value in the inspected object 10 calculated by the process of step S15 and the customer requirement specification. The to-be-inspected object 10 is rated by comparing with the allowable range of the number of areas exceeding the threshold value. Examples of the allowable range of the number of areas that exceed the longitudinal moving average defect count threshold include the following ranges. Thereby, the process of step S16 is completed and a series of swarm defect rating processes are completed.

[Example of allowable range of the number of moving average defects in the longitudinal direction exceeding the threshold value]
(1) Grade A products (products that can be sold to customers (or applications) α, β, γ) → Number of longitudinal moving average defect count exceeding the threshold is less than 2 (2) Grade B products (customers ( (Or use) Products that can be sold for β and γ) → Number of longitudinal moving average number of defects exceeding the threshold is less than 4 (3) Grade C products (products that can be sold to customers (or uses) γ) → Longitudinal moving average number of defects exceeding the threshold is less than 6 (4) Scrap target product → Longitudinal moving average number of defects exceeding the threshold is 6 or more

[Pass / fail judgment processing]
Finally, with reference to the flowchart shown in FIG. 7, the operation of the surface defect inspection apparatus when executing the pass / fail determination process of the inspected object 10 based on the single defect rating process and the swarm defect rating process will be described.

  FIG. 7 is a flowchart showing the flow of pass / fail determination processing according to an embodiment of the present invention. The flowchart shown in FIG. 7 starts at the timing when the single defect rating process and the swarm defect rating process are completed, and the pass / fail determination process proceeds to the process of step S21.

  In the process of step S21, the determination part 17 determines whether the rating determination of the to-be-inspected object 10 is a pass based on the result of the single defect rating process. For example, in the single defect rating process, when the inspected object 10 manufactured for the customer (or application) α is rated as a rating class B product, the determination unit 17 determines that the inspected object 10 is rejected.

  On the other hand, when the inspected object 10 manufactured for the customer (or application) α is rated as a grade A grade product in the single defect rating process, the determination unit 17 determines that the inspected object 10 is acceptable. As a result of the determination, when the rating determination of the device under test 10 is acceptable, the determination unit 17 advances the pass / fail determination process to the process of step S22. On the other hand, when the rating determination of the device under test 10 fails, the determination unit 17 advances the pass / fail determination process to the process of step S24.

  In the process of step S22, the determination part 17 determines whether the rating determination of the to-be-inspected object 10 is a pass based on the result of a cluster defect rating process. For example, when the inspected object 10 manufactured for the customer (or application) β is rated as a rated C grade product in the cluster defect rating process, the determination unit 17 determines that the inspected object 10 is rejected.

On the other hand, when the inspected object 10 manufactured for the customer (or application) β is rated as a rated A grade product in the swarm defect rating process, the determination unit 17 determines that the inspected object 10 is acceptable.
As a result of the determination, when the rating determination of the device under test 10 is acceptable, the determination unit 17 advances the pass / fail determination process to the process of step S23. On the other hand, when the rating determination of the device under test 10 fails, the determination unit 17 advances the pass / fail determination process to the process of step S24.

  In the process of step S <b> 23, the determination unit 17 determines that the inspection object 10 is acceptable, and outputs information indicating that the inspection object 10 is acceptable to the result output unit 18. Thereby, the process of step S23 is completed and a series of pass / fail determination processes are completed.

  In the process of step S <b> 24, the determination unit 17 determines that the object 10 is rejected, and outputs information indicating that the object 10 is rejected to the result output unit 18. Thereby, the process of step S24 is completed and a series of pass / fail determination processes are completed.

  As is clear from the above description, in the surface inspection apparatus according to an embodiment of the present invention, the determination unit 17 divides the device under test 10 in the longitudinal direction and the width direction based on the type and degree of surface defects. In each unit region formed by this, the number of moving average defects in the longitudinal direction is calculated from the number of weighted defects in the unit region and the number of weighted defects in the front region adjacent to the longitudinal direction (region on the downstream side in the transport direction). By comparing with the number threshold, a unit region whose longitudinal moving average defect number is larger than the defect number threshold is extracted as a region exceeding the longitudinal moving average defect number threshold, and exceeds the longitudinal moving average defect number threshold in the inspection object 10. The number of areas is calculated, and the object to be inspected 10 is rated based on the calculated number of areas in the longitudinal direction moving average defect count exceeding the threshold value. According to such a surface inspection apparatus, it is possible to rank an object to be inspected based on a minute defect that becomes a problem when swarming. Moreover, swarm defect rating can be performed more accurately by freely setting the size of the unit area and the number of target areas for which a moving average is taken.

  Furthermore, in the surface inspection apparatus according to the embodiment of the present invention, the determination unit 17 performs the rating of the inspection object 10 due to a single defect in addition to the rating of the inspection object 10 due to the cluster defect, so that the defect that can be inspected As a result, the inspection can be performed in a wide range from a minute defect to a large defect, and there is no inspection omission and a highly accurate defect inspection can be performed.

  Although the embodiment to which the invention made by the present inventor is applied has been described above, the present invention is not limited by the description and the drawings that form a part of the disclosure of the present invention according to this embodiment.

DESCRIPTION OF SYMBOLS 10 To-be-inspected object 11a, 11b Image input part 12a, 12b Image processing part 13a, 13b Feature-value calculating part 14 Defect type determination part 15 Defect degree determination part 16 Storage part 17 Determination part 18 Result output part

Claims (5)

A first step of extracting a minute defect in each unit region formed by dividing the object to be inspected in the longitudinal direction and the width direction, and calculating the number of defects in the unit region;
A second step of calculating the number of moving average defects in the longitudinal direction of unit regions adjacent in the longitudinal direction;
A third step of comparing the calculated number of moving average defects in the longitudinal direction with a predetermined threshold value and, if the calculated number of moving average defects in the length direction exceeds the threshold value, extracting as a region exceeding the threshold value in the lengthwise moving average defect number;
A fourth step of calculating the number of the areas that exceed the extracted longitudinal moving average defect count threshold value, and classifying the object to be inspected based on the calculated number of areas exceeding the longitudinal moving average defect count threshold value;
A surface defect inspection method characterized by comprising: The surface defect inspection method according to claim 1,
The first step calculates the number of weighted defects by multiplying the number of defects by a predetermined weighting factor determined according to the type and degree of surface defects, and calculates the sum of the calculated number of weighted defects. A surface defect inspection method comprising the step of calculating the number of defects in a unit region. The surface defect inspection method according to claim 1 or 2,
A calculation step for determining a representative defect in each unit length region formed by dividing the object to be inspected in the longitudinal direction based on the type and degree of the surface defect, and calculating a mixing rate of the representative defect in the object to be inspected When,
A rating step that ranks the object to be inspected based on the mixing ratio of the representative defects, and performs pass / fail determination of the object to be inspected based on the rating result;
A surface defect inspection method characterized by comprising: In the surface defect inspection method according to claim 3,
The calculation step and the determination step are executed before executing the first to fourth steps, and only the first object to be inspected is determined to be acceptable by the rating based on the mixing rate of the representative defects. A surface defect inspection method characterized by executing the fourth step. A first means for extracting a minute defect in each unit region formed by dividing the object to be inspected in the longitudinal direction and the width direction, and calculating the number of defects in the unit region;
A second means for calculating the number of moving average defects in the longitudinal direction of unit regions adjacent in the longitudinal direction;
A third means for comparing the calculated number of moving average defects in the longitudinal direction with a predetermined threshold and, if the calculated number of moving average defects in the longitudinal direction exceeds the threshold value, extracting as a region exceeding the threshold value in the lengthwise moving average defect number;
A fourth means for calculating the number of the longitudinal moving average defect count exceeding the threshold value extracted, and grading the object to be inspected based on the calculated longitudinal moving average defect count threshold exceeding area number;
A surface defect inspection apparatus comprising: