JPH10282011A - Defect inspection method for surface of object - Google Patents

Abstract

PROBLEM TO BE SOLVED: To enable fast inspection of defects by determining parameters of a light source distribution function with a limited volume of calculation. SOLUTION: In a defect inspection method in which the surface of an object is irradiated with light at an observation point to inspect the presence of a defect at the observation point based on a plurality of luminance values obtained by measuring the reflected light, among parameters of the light source distribution function indicating the above mentioned luminance values, approximation functions as regression models are separately generated for the first parameter indicating peak values of the light source distribution function, the second parameter indicating an expanse of the base of the light source distribution function and the third parameter indicating a deviation of the peak values. Regression coefficients of the respective approximation functions are determined by a regression analysis using the parameters thus obtained as purpose variables and the plurality of luminance values as description variables (S4, S6 and S8). Parameters are determined by the approximation functions using the plurality of luminance values measured per arbitrary observation point and the above- mentioned regression coefficients to inspect the presence of a defect at the observation point based on the parameters.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a defect inspection method for an object surface for detecting defects such as scratches and roughness on the surface of a magnetic recording medium by obtaining parameters of a light source distribution function at observation points on the surface of a magnetic recording medium such as a hard disk. About.

[0002]

2. Description of the Related Art FIG. 3 is a diagram schematically showing a two-dimensional luminance distribution of reflected light as a light source distribution function when an observation point on a medium surface is irradiated with light from a light source. In FIG. 3, reference numeral 10 denotes a light source, reference numeral 20 denotes an inspection medium such as a hard disk, reference numeral 21 denotes an observation point, and reference numerals 31 to 35 denote cameras for imaging reflected light from the observation point 21. Here, the cameras 31 to 35
The central camera 33 is disposed at a position for receiving the specularly reflected light from the observation point 21, and the cameras 32, 3 on both sides thereof
4 and the outermost cameras 31 and 35 are symmetrically arranged at positions separated by an equal angle.

[0003] When a two-dimensional light source distribution is considered, luminance values b ₁ to b measured by the cameras 31 to 35 are considered.
₅ is represented by the light source distribution function f (θ _s ) in Equation 1.

[0004]

F (θ _s ) = Aexp {(2θ _n −θ _s ) ² / σ ² }

In the above equation 1, θ _s is the angle between the optical axis from the light source 10 and the optical axis of the regular reflected light. Next, each parameter in Equation 1 will be described with reference to FIG. In FIG. 4, f (θ _s ) is a light source distribution function serving as a reference when it is assumed that the observation point 21 is a mirror surface, and ± 1 [deg] with the position of the central camera 33 as the center.
This is an example of measuring the luminance values b _{1 to} b ₅ by arranging the cameras 34 and 32 at the positions of, and arranging the cameras 35 and 31 at the positions of ± 3 [deg].

Here, A is a parameter indicating the reflectance of the observation point 21 and indicates a peak value (peak value of luminance) of the light source distribution function, and is influenced by a flaw of the observation point 21 or the like.
Further, θ _n is a parameter indicating the inclination of the observation point 21 and indicates the amount of deviation of the peak value from the reference light source distribution function f (θ _s ), and σ is the surface roughness of the observation point 21 such as roughness. This is a parameter indicating the degree of spread of the skirt from the reference light source distribution function f (θ _s ).

[0007]

Conventionally, the above parameters A, σ, and θ _n have been calculated using, for example, the undetermined coefficient determination method. However, the amount of calculation is extremely large, and the load on the computer is enormous. And at the same time needed a lot of time. Therefore, the present invention obtains each parameter of the light source distribution function directly from a plurality of luminance values for the observation point by regression analysis,
It is an object of the present invention to provide a method for inspecting a defect on the surface of an object which can reduce the calculation load and increase the speed, and enables the surface inspection in a short time.

[0008]

In order to solve the above-mentioned problems, the invention according to claim 1 irradiates light to an observation point on the surface of an object, and measures the reflected light based on a plurality of luminance values obtained by measuring the reflected light. A defect inspection method for inspecting the presence or absence of a defect at the observation point, the first parameter A indicating a peak value of the light source distribution function among the parameters of the light source distribution function indicating the luminance value; An approximate function as a regression model is created for each of the second parameter σ indicating the spread of the skirt and the third parameter θ _n indicating the deviation of the peak value, and each parameter is used as an objective variable and a plurality of luminance values. The regression coefficient of each approximation function is obtained by regression analysis using as an explanatory variable, and each parameter is obtained by the approximation function using a plurality of luminance values measured for an arbitrary observation point and the regression coefficient. It is intended to inspect the presence or absence of a defect of the observation point on the basis of the parameters.

According to a second aspect of the present invention, in the defect inspection method for an object surface according to the first aspect, a plurality of luminance values as explanatory variables are weighted for each parameter.

[0010]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS An embodiment of the present invention will be described below with reference to the drawings. FIG. 1 is a flowchart showing the processing procedure of this embodiment, and its contents will be sequentially described below.
First, a reference light source distribution function f as shown in FIG.
Based on (θ _s ), luminance values b _{1 to} b ₅ corresponding to the imaging positions of the cameras 31 to 35 are obtained (S1).

Next, for each parameter A, σ, θ _n ,
Performing a predetermined weighting to each luminance value b ₁ ~b ₅ (S2). This weighting is not always necessary in the present invention, but is a process required to accurately grasp the state of change according to the meaning of each parameter. Incidentally, FIG. 2 shows an example of the weighting, for example the light source most emphasis on b ₃ for parameters A about the peak value of the distribution function, b ₁ for the parameters σ indicating the divergence degree of the hem of the light source distribution function , the most emphasis on b _5,
Further, b _{2 to} b ₄ are equally emphasized for the parameter θ _n indicating the shift of the peak value of the light source distribution function.

Next, while changing the parameter A as a target variable in a predetermined range (A _min ≦ A ≦ A _max ),
Approximate function for parameter A, ie, regression model f _{A
(B 1, b 2, b} 3, b 4, b 5) to create a (S3). The approximation function f _A (b ₁ , b ₂ , b ₃ , b ₄ , b ₅ ) is represented by, for example, Expression 2.

[0013]

F _A (b ₁ , b ₂ , b ₃ , b ₄ , b ₅ ) = a ₀ + a _{11
^{b 1 + a 12 b 1 2}} + a 13 b 1 3 + a 14 b 1 4 + a 15 b 1 5 + a 21
^{_{b 2 + a 22 b 2 2}} + a 23 b 2 3 + a 24 b 2 4 + a 25 b 2 5 + a 31
^{_{b 3 + a 32 b 3 2}} + a 33 b 3 3 + a 34 b 3 4 + a 35 b 3 5 + a 41
^{_{b 4 + a 42 b 4 2}} + a 43 b 4 3 + a 44 b 4 4 + a 45 b 4 5 + a 51
^{_{b 5 + a 52 b 5 2}} + a 53 b 5 3 + a 54 b 5 4 + a 55 b 5 5

Here, for each objective variable A within the above range, the values of the corresponding explanatory variables b _{1 to} b ₅ can be calculated based on the reference light source distribution function f (θ _s ).
26 regression coefficients a ₀ , a for each objective variable A
_11, a _12, ......, the approximation function f _A (b ₁ having a _54, a _55,
b ₂ , b ₃ , b ₄ , b ₅ ) can be created in large numbers. Next, these regression coefficients a ₀ , a ₁₁ , a ₁₂ ,..., A ₅₄ ,
_a55 is calculated by regression analysis (S4). In particular,
Each objective variable A = f _A (b ₁ , b ₂ , b ₃ , b ₄ ,
b ₅ ) and regression coefficients a ₀ , a ₁₁ , a
₁₂ ,..., A ₅₄ and a ₅₅ are obtained.

Similarly, the parameters σ and θ
_nWith the approximation function fσ (b₁, B_Two,
b_Three, B_Four, B_Five), Fθ_n(B₁, B_Two, B_Three, B_Four, B_Five)
And the regression coefficient h for each₀, H₁₁, H₁₂,…
…, H₅₄, H₅₅And p₀, P₁₁, P₁₂, ……, p₅₄, P
₅₅(S5 to S8). (The signs h,
p is for convenience. Here, the approximate function fσ (b₁, B_Two, B_Three, B_Four, B_Five)
And fθ_n(B₁, B_Two, B _Three, B_Four, B_Five) Is easy from Equation 1
Therefore, the description is omitted.

In the above embodiment, the brightness values b _{1 to} b ₅ of the cameras 31 to 35 arranged at five locations are used as explanatory variables. However, the number of brightness values (in other words, the number of cameras) may be arbitrary. .

As described above, the regression coefficients a ₀ , a ₁₁ , a
₁₂ ,..., A ₅₄ , a ₅₅ and h ₀ , h ₁₁ , h ₁₂ ,.
_54, h _55, and _{p 0, p 11, p 12} , ......, if p _54, p ₅₅ is calculated, the approximation function _{f A (b 1, b 2} , b 3, b 4,
_{b 5), fσ (b 1} , b 2, b 3, b 4, b 5), fθ
_{n (b 1, b 2,} b 3, b 4, b 5) the by substituting the luminance values b ₁ ~b ₅ arbitrary observation point, A at the observation point,
σ, θ _n can be obtained. Therefore, the presence or absence of a flaw, inclination, roughness, or the like at the observation point can be detected, and the presence or absence of a defect on the surface of the inspection medium 20 can be inspected.

In the above embodiment, the case where the present invention is applied to the defect inspection of the surface of a magnetic recording medium such as a hard disk has been described, but the present invention is also applicable to the defect inspection of the surface of another object.

[0019]

As described above, according to the first aspect of the present invention, an approximate function relating to a plurality of parameters is created and its regression coefficient is obtained, so that the plurality of luminance values measured for an arbitrary observation point can be obtained. Parameters can be directly obtained, and surface conditions such as scratches, inclinations, and roughness of observation points can be detected with high accuracy. Therefore, high-speed defect inspection of an inspection medium such as a hard disk can be performed. Further, by using the luminance value weighted according to the property of the parameter as described in claim 2, more accurate defect inspection can be performed.

[Brief description of the drawings]

FIG. 1 is a flowchart showing an embodiment of the present invention.

FIG. 2 is a diagram illustrating an example of a weight for each parameter according to the embodiment.

FIG. 3 is an explanatory diagram of a light source distribution function.

FIG. 4 is an explanatory diagram of each parameter.

[Explanation of symbols]

 DESCRIPTION OF SYMBOLS 10 Light source 20 Inspection medium 21 Observation point 31-35 Camera

Claims (2)

[Claims] An object surface defect inspection method for irradiating an observation point on an object surface with light and inspecting the observation point for a defect based on a plurality of luminance values obtained by measuring reflected light, Among the parameters of the light source distribution function indicating the luminance value, a first parameter indicating the peak value of the light source distribution function, a second parameter indicating the spread of the tail of the light source distribution function, and a second parameter indicating the deviation of the peak value. For each of the three parameters, an approximation function as a regression model was created, and the regression coefficient of each approximation function was obtained by regression analysis using each of the parameters as an objective variable and a plurality of luminance values as explanatory variables. A method of determining each parameter by the approximation function using a plurality of luminance values and the regression coefficient, and inspecting the observation point for a defect based on these parameters. Defect inspection method for the surface. 2. The defect inspection method for an object surface according to claim 1, wherein a plurality of luminance values as explanatory variables are weighted for each parameter.