Optical detection device, signal-to-noise ratio estimation method, and defect detection method

Abstract

The present application relates to an optical detection device and a signal-to-noise ratio estimation method and a defect detection method, wherein the optical detection device includes a turntable, a light source, a detector and a processor, the processor adapts a noise interference evaluation model according to the rotation speed signal of the turntable, determines the input parameters of the evaluation model according to the electrical signal and / or detection parameters of the detector, inputs the input parameters into the evaluation model to calculate the signal-to-noise ratio, and judges whether there is a defect in the area of ​​the surface of the object to be detected that is illuminated by the detection light according to the signal-to-noise ratio. The technical solution establishes a noise interference evaluation model that is adapted to the rotation speed of the object to be detected, and then the signal-to-noise ratio of the optical detection device can be easily calculated in combination with the acquired input parameters, which can not only improve the efficiency of signal-to-noise ratio calculation under different rotation speeds or detection modes, but also obtain the relationship between the signal-to-noise ratio and the signal acquisition conditions, thereby improving the accuracy of the signal-to-noise ratio calculation, and further facilitating the improvement of the accuracy of optical detection.

Description

Technical Field

[0001] The present application relates to the field of optical detection technology, and in particular to an optical detection device, a signal-to-noise ratio estimation method, and a defect detection method. Background Art

[0002] In the production and manufacturing of chips, advanced manufacturing processes mean processing more complex integrated circuit layouts, and complex integrated circuit layouts also require more sophisticated detection technology to determine whether the layout products are qualified. Integrated circuit detection technology has been driving the improvement of semiconductor process technology, thereby continuously improving the product yield.

[0003] In the optical inspection equipment of integrated circuits, the inspection module is an important component of the entire system. During the design process, the inspection module usually selects suitable detectors and light-collecting optical elements (such as lenses) according to the inspection requirements, and develops and designs them in combination with the overall architecture. Therefore, improving the performance of the inspection module will be very important for the inspection effect of the integrated circuit.

[0004] During the working process of the detection module, in addition to the real signal, a series of uncertain information will be introduced, such as the uncertainty of the optical signal itself, thermal motion of the material, electronic noise, etc. These noises have a negative impact on the performance of the detection module. In severe cases, it will cause optical detection failure. Therefore, it is necessary to further improve the existing integrated circuit optical detection technology. Summary of the invention

[0005] The main technical problem solved by this application is: how to improve the accuracy of optical detection of integrated circuits. In order to solve the above technical problem, this application proposes an optical detection device, a signal-to-noise ratio estimation method, and a defect detection method.

[0006] According to the first aspect, an optical detection device is provided in an embodiment, comprising: a turntable for carrying an object to be detected and driving the object to be detected to rotate; a light source for generating detection light, wherein the detection light forms reflected light after being irradiated on the surface of the object to be detected; a detector for receiving the reflected light and / or background light other than the reflected light, forming an optical signal and converting the optical signal into an electrical signal; a processor connected to the turntable, the light source and the detector, and used for controlling and analyzing optical detection of the object to be detected; wherein the processor controls the operation of the turntable, the light source and the detector, and obtains a rotation speed signal of the turntable, as well as an electrical signal and detection parameters of the detector; the processor adapts an evaluation model of noise interference according to the rotation speed signal; the processor determines the input parameters of the evaluation model according to the electrical signal and / or the detection parameters; the processor inputs the input parameters into the evaluation model to obtain a signal-to-noise ratio; the processor determines whether there is a defect in the area of ​​the surface of the object to be detected irradiated by the detection light according to the signal-to-noise ratio.

[0007] The processor adapts an evaluation model of noise interference according to the speed signal, including: the processor determines the speed level according to the speed signal; the processor determines the main noise type and the secondary noise type interfered in the optical detection according to the speed level; the processor establishes an evaluation model of noise interference according to the main noise type.

[0008] The rotation speed levels of the turntable include a low rotation speed mode, a medium rotation speed mode and a high rotation speed mode; in the low rotation speed mode, the main noise type determined by the processor includes shot noise, and the established evaluation model is

[0009]

[0010] In the medium speed mode, the main noise types determined by the processor include shot noise, dark current noise and read noise, so the established evaluation model is

[0011]

[0012] In the high speed mode, the main noise type determined by the processor includes read noise, and the established evaluation model is:

[0013]

[0014] Among them, P s is the number of photons of the reflected light entering the detector per unit time, P bis the number of photons of the background light entering the detector per unit time, QE is the quantum efficiency of the detector in photoelectric conversion, t is the exposure time of the detector, D is the dark current of the detector, and R is the readout noise of the detector.

[0015] The processor determines the input parameters of the evaluation model according to the electrical signal and / or the detection parameters, including: the processor obtains the number of photons of the background light entering the detector per unit time according to the electrical signal converted from the background light, and obtains the number of photons of the reflected light entering the detector per unit time according to the electrical signal converted from the reflected light and the background light; the processor obtains the quantum efficiency of the detector in photoelectric conversion, the exposure time of the detector, the dark current of the detector and the readout noise of the detector according to the detection parameters; the processor determines multiple parameters including the number of photons of the reflected light entering the detector per unit time, the number of photons of the background light entering the detector per unit time, the quantum efficiency of the detector in photoelectric conversion, the exposure time of the detector, the dark current of the detector and the readout noise of the detector as the input parameters of the evaluation model.

[0016] The processor determines, according to the signal-to-noise ratio, whether there is a defect in an area on the surface of the object to be detected that is illuminated by the detection light, including: the processor compares the signal-to-noise ratio with a preset threshold; when the processor determines that the signal-to-noise ratio is less than the preset threshold, determining that there is a defect in the area on the surface of the object to be detected that is illuminated by the detection light.

[0017] The detection light generated by the light source is laser, and the laser is used to irradiate the surface of the object to be detected in a point-like or line-like form, and form an area irradiated by the laser on the surface of the object to be detected.

[0018] According to the second aspect, an embodiment provides a method for estimating the signal-to-noise ratio of optical detection, including: obtaining an electrical signal generated by a detector and detection parameters of the detector; the electrical signal is obtained by the detector receiving an optical signal and converting it, and the optical signal is the reflected light on the surface of the object to be detected and / or the background light other than the reflected light; obtaining a rotation speed signal of the object to be detected, and adapting an evaluation model of noise interference according to the rotation speed signal; determining input parameters of the evaluation model according to the electrical signal and / or the detection parameters; and inputting the input parameters into the evaluation model to obtain the signal-to-noise ratio.

[0019] The evaluation model for adapting the noise interference according to the rotation speed signal includes: determining the rotation speed level according to the speed signal of the object to be detected; determining the main noise type and the secondary noise type interfered in the optical detection according to the rotation speed level; and establishing the evaluation model for noise interference according to the main noise type.

[0020] The speed levels include low speed mode, medium speed mode and high speed mode; in the low speed mode, the main noise type determined includes shot noise, and the established evaluation model is

[0021]

[0022] In the medium speed mode, the main noise types determined include shot noise, dark current noise and read noise, so the established evaluation model is:

[0023]

[0024] In the high speed mode, the main noise type determined includes read noise, so the established evaluation model is:

[0025]

[0026] Among them, P s is the number of photons of the reflected light entering the detector per unit time, P b is the number of photons of the background light entering the detector per unit time, QE is the quantum efficiency of the detector in photoelectric conversion, t is the exposure time of the detector, D is the dark current of the detector, and R is the readout noise of the detector.

[0027] The step of determining the input parameters of the evaluation model according to the electrical signal and / or the detection parameters includes: obtaining the number of photons of the background light entering the detector per unit time according to the electrical signal converted from the background light, and obtaining the number of photons of the reflected light entering the detector per unit time according to the electrical signal converted from the reflected light and the background light; obtaining the quantum efficiency of the detector in photoelectric conversion, the exposure time of the detector, the dark current of the detector, and the readout noise of the detector according to the detection parameters; and determining more than one of the number of photons of the reflected light entering the detector per unit time, the number of photons of the background light entering the detector per unit time, the quantum efficiency of the detector in photoelectric conversion, the exposure time of the detector, the dark current of the detector, and the readout noise of the detector as the input parameters of the evaluation model.

[0028] According to the third aspect, an embodiment provides a defect detection method for optical inspection, including: obtaining a rotation speed signal of a turntable carrying an object to be inspected; obtaining an electrical signal generated by a detector that converts an optical signal and a detection parameter of the detector; the electrical signal is obtained after the detector receives and converts the optical signal, and the optical signal is the reflected light on the surface of the object to be inspected and / or the background light other than the reflected light; adapting an evaluation model of noise interference according to the rotation speed signal; determining input parameters of the evaluation model according to the electrical signal and / or the detection parameters; inputting the input parameters into the evaluation model to obtain a signal-to-noise ratio; and judging whether there is a defect in the area on the surface of the object to be inspected that is illuminated by the detection light according to the signal-to-noise ratio.

[0029] The determining, based on the signal-to-noise ratio, whether there is a defect in the area on the surface of the object to be detected that is illuminated by the detection light includes: comparing the signal-to-noise ratio with a preset threshold; and determining that there is a defect in the area on the surface of the object to be detected that is illuminated by the detection light when it is determined that the signal-to-noise ratio is less than the preset threshold.

[0030] According to the fourth aspect, an embodiment provides a computer-readable storage medium having a program stored thereon, wherein the program can be executed by a processor to implement the signal-to-noise ratio estimation method described in the second aspect above, and / or to implement the defect detection method described in the third aspect above.

[0031] The beneficial effects of this application are:

[0032] According to the above embodiments, an optical detection device, a signal-to-noise ratio estimation method, and a defect detection method are provided, wherein the optical detection device includes a turntable, a light source, a detector, and a processor, the processor controls the operation of the turntable, the light source, and the detector, and obtains the rotation speed signal of the turntable, as well as the electrical signal and detection parameters of the detector; the processor adapts the evaluation model of noise interference according to the rotation speed signal; the processor determines the input parameters of the evaluation model according to the electrical signal and / or the detection parameters; the processor inputs the input parameters into the evaluation model to calculate the signal-to-noise ratio; the processor determines whether there are defects in the area on the surface of the object to be detected that is illuminated by the detection light according to the signal-to-noise ratio. On the one hand, the technical solution establishes a noise interference evaluation model that is adapted to the rotational speed of the object to be detected. Combined with the acquired input parameters, it is easy to calculate the signal-to-noise ratio of the optical detection device. This not only improves the efficiency of signal-to-noise ratio calculation under different rotational speeds or detection modes, but also obtains the relationship between the signal-to-noise ratio and the signal acquisition conditions, thereby improving the accuracy of the signal-to-noise ratio calculation. On the other hand, the technical solution uses the signal-to-noise ratio as an evaluation indicator to determine whether there are defects in the area on the surface of the object to be detected that is illuminated by the detection light. This not only uses a new method to evaluate the surface defects of integrated circuit products, but the accurate calculation result of the signal-to-noise ratio is also conducive to improving the accuracy of optical detection, thereby enhancing the feasibility of detection signal-to-noise ratio in optical detection applications. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 This is a structural diagram of an optical detection device in one embodiment of the present application;

[0034] Figure 2 This is a flow chart of a signal-to-noise ratio estimation method in one embodiment of the present application;

[0035] Figure 3 Flowchart for establishing the noise interference assessment model;

[0036] Figure 4 Flowchart for determining the input parameters of the evaluation model;

[0037] Figure 5 This is a flow chart of a defect detection method in one embodiment of the present application;

[0038] Figure 6 A flow chart for determining surface defects of an object to be inspected;

[0039] Figure 7 This is a structural diagram of an optical detection device in another embodiment of the present application. DETAILED DESCRIPTION

[0040] The present application is further described in detail below by specific embodiments in conjunction with the accompanying drawings. Wherein similar elements in different embodiments adopt associated similar element numbers. In the following embodiments, many detailed descriptions are intended to enable the present application to be better understood. However, those skilled in the art can easily recognize that some of the features can be omitted in different situations, or can be replaced by other elements, materials, and methods. In some cases, some operations related to the present application are not shown or described in the specification, in order to avoid the core part of the present application being overwhelmed by too much description, and for those skilled in the art, it is not necessary to describe these related operations in detail, and they can fully understand the related operations based on the description in the specification and the general technical knowledge in the art.

[0041] In addition, the features, operations or characteristics described in the specification can be combined in any appropriate manner to form various implementations. At the same time, the steps or actions in the method description can also be interchanged or adjusted in a manner that is obvious to those skilled in the art. Therefore, the various sequences in the specification and the drawings are only for the purpose of clearly describing a certain embodiment and are not meant to be a required sequence, unless otherwise specified that a certain sequence must be followed.

[0042] The serial numbers of the components in this document, such as "first", "second", etc., are only used to distinguish the objects described and do not have any order or technical meaning. The "connection" and "coupling" mentioned in this application, unless otherwise specified, include direct and indirect connections (couplings).

[0043] Embodiment 1

[0044] Please refer to Figure 1 In this embodiment, an optical detection device is disclosed. The optical detection device 1 mainly includes a turntable 11, a light source 12, a detector 13 and a processor 14, which are described below respectively.

[0045] The turntable 11 is a rotatable load-bearing platform for carrying the object A to be detected. The turntable 11 has the ability to rotate and can drive the carried object A to be detected to rotate. For example, the turntable 11 may include components such as a rotating table, a motor, and a speed detection sensor, wherein the rotating table is used to carry the object to be detected, the motor is used to drive the rotating table to rotate, and the speed detection sensor is used to detect the rotation speed of the rotating table and generate a speed signal. Of course, the turntable 11 should have the ability to fix the object A to be detected so that the object A to be detected will not fall off the rotating table during the rotation of the turntable 11.

[0046] It should be noted that the object A to be inspected here mainly refers to an integrated circuit, such as a chip layout layer, a wafer to be etched, etc. Of course, the object A to be inspected can also be some process parts with regular shapes, which often have high process requirements on the surface of such parts, and should have no defects or as few defects as possible, so as to meet the needs of industrial applications.

[0047] The light source 12 is a light emitting component for generating detection light, and the detection light can form reflected light after irradiating the surface of the object A to be detected. For example, the light outlet of the light source 12 can face the object A to be detected, so that the object A to be detected is directly irradiated with the detection light.

[0048] In one embodiment, the detection light generated by the light source 12 is laser, which is used to irradiate the surface of the object A to be detected in the form of points or lines, and form a laser irradiation area on the surface of the object A to be detected. It can be understood that the laser has high brightness, high directivity, high monochromaticity and high coherence, and can produce a stable and reliable irradiation effect on the surface of the detection object A, minimize the influence of ambient light, and thus improve the reliability of optical detection.

[0049] The detector 13 is an optical detection component, such as a laser camera, a CCD camera, a CMOS camera, etc. The purpose of using the detector 13 is to receive the reflected light formed by the object A to be detected under the irradiation of the detection light, and / or to receive the background light other than the reflected light, and the detector 13 can use the received light to form an optical signal and convert the optical signal into an electrical signal, thereby transmitting the electrical signal to the processor 14 for analysis and processing. It can be understood that the background light mentioned here refers to the ambient light existing in the detection space, and the background light will inevitably be received by the detector 13 together with the reflected light. At this time, the detector 13 can convert the optical signal of the combination of the reflected light and the background light into a corresponding electrical signal; of course, if the detection space is a completely dark environment, the existence of the background light can be ignored. If the background light is to be detected alone, the detector 13 can be used to receive only the background light when the light source does not generate the detection light (i.e., there is no reflected light), thereby converting the optical signal of the background light into a corresponding electrical signal.

[0050] It should be noted that, since the detection light can form an irradiation area on the surface of the object A to be detected, the reflected light can reflect the surface features of the object in the irradiation area, and the electrical signal generated by the conversion of the reflected light will also reflect the surface features of the object in the irradiation area. Under normal circumstances, if the surface features of the object in the irradiation area are defects, the reflected light will be offset or divergent, thereby weakening the electrical signal. In addition, since the object A to be detected is in a rotating state following the turntable 11, the irradiation area will also change continuously. As long as the emitting direction of the detection light of the light source 12 is properly adjusted, the irradiation area can be spread over the surface of the object A to be detected, thereby performing a complete optical detection on the surface of the object A to be detected. It can be understood that the higher the rotation speed of the object A to be detected, the more irradiation areas need to be detected per unit time, and the higher the sensitivity of the optical detection.

[0051] The processor 14 is a logic processing component such as a CPU, MCU, FPGA, or a single-chip microcomputer, which is connected to the turntable 11, the light source 12, and the detector 13 through some ports. The processor 14 is used to control and analyze the optical detection of the object A to be detected.

[0052] In this embodiment, the processor 14 serves as a logic processing component of optical detection and plays a role in work timing control and signal analysis. The functions of the processor 14 will be introduced below.

[0053] (1) During the optical detection of the object A to be detected, the processor 14 controls the operation of the turntable 11, the light source 12 and the detector 13, for example, controls the turntable 11 to drive the carried object A to be detected to rotate at a predetermined speed, controls the light source 12 to generate detection light, and controls the detector 13 to perform photoelectric conversion; at this time, the processor 14 obtains the rotation speed signal of the turntable 11, and obtains the electrical signal and detection parameters of the detector 13.

[0054] It should be noted that the rotation speed signal of the turntable 11 can be measured by a speed detection sensor, and the electrical signal and detection parameters of the detector 13 are directly output by the detector 13, wherein the electrical signal is generated by converting the optical signal, and the detection parameters are the basic parameters of the camera (such as photoelectric conversion efficiency, exposure time, dark current, read noise, etc.).

[0055] (2) The processor 14 adapts the noise interference evaluation model according to the rotation speed signal. Since the rotation speed of the object to be detected in optical detection has a great relationship with the introduced noise interference factor, it is necessary to distinguish the rotation speed levels here, so as to adapt different noise interference evaluation models according to different rotation speed levels. The evaluation model here is used to calculate the signal-to-noise ratio, and the calculation result is related to the number of photons and the basic parameters of the camera.

[0056] (3) The processor 14 determines the input parameters of the evaluation model based on the electrical signal and / or the detection parameters. Since the calculation result of the signal-to-noise ratio using the evaluation model is related to the number of photons and the basic parameters of the camera, and the number of photons can be converted using pixel values ​​(the pixel value of each pixel in each frame of the camera can be obtained by analog and digital processing of the electrical signal), the input parameters of the evaluation model can be obtained by analyzing the electrical signal and detection parameters of the detector 13.

[0057] (4) The processor 14 inputs the input parameters into the evaluation model to obtain the signal-to-noise ratio.

[0058] (5) The processor 14 determines whether there is a defect in the area on the surface of the object to be inspected that is illuminated by the inspection light based on the signal-to-noise ratio.

[0059] It should be noted that the signal-to-noise ratio refers to the ratio of the signal to the noise in an electronic device or electronic system. The signal here refers to the electronic signal from outside the device that needs to be processed by this device, and the noise refers to the irregular additional signal that does not exist in the original signal after passing through the device, and the additional signal does not change with the change of the original signal. Figure 1 For the optical detection device 1 in the figure, the signal of the device refers to the light signal received by the detector 13, and the noise refers to the shot noise caused by the light signal and the dark current noise and read noise caused by the performance of the detector 13 itself. Since the defects on the surface of the object A to be detected will cause the change of the reflected light on the surface of the object A to be detected, and cause the fluctuation of the light signal incident on the detector 13, resulting in the change of the calculation result of the signal-to-noise ratio, the defects on the surface of the object A to be detected can be judged based on this idea.

[0060] In one embodiment, the processor 14 adapts the noise interference evaluation model according to the speed signal, including:

[0061] 1) The processor 14 determines the speed level according to the speed signal. The rotation speed can be obtained by analyzing the speed signal. If a certain speed range is determined as a speed level, multiple speed levels can be obtained. For example, the rotation speed is divided into three speed levels: low, medium, and high. 50-300rpm is set as a low speed level (i.e., low speed mode), 300-600rpm is set as a medium speed level (i.e., medium speed mode), and above 600rpm is set as a high speed level (i.e., high speed mode).

[0062] 2) The processor 14 determines the main noise type and the secondary noise type that are disturbed in the optical detection according to the rotation speed level. In the optical detection, the noise interference mainly includes shot noise, dark current noise and read noise; in the low rotation speed mode, the main noise type that is disturbed is shot noise, and the secondary noise types are dark current noise and read noise; in the medium rotation speed mode, the main noise types that are disturbed are shot noise, dark current noise and read noise, and there is no secondary noise type; in the high rotation speed mode, the main noise type that is disturbed is read noise, and the secondary noise types are dark current noise and shot noise.

[0063] 3) The processor 14 establishes an evaluation model of noise interference according to the main noise type.

[0064] In order to illustrate the effects of shot noise, dark current noise and readout noise on the signal-to-noise ratio, these three noises can be combined to obtain the following formula:

[0065]

[0066] Among them, P s is the number of photons of reflected light entering the detector 13 per unit time, P b is the number of photons of background light entering the detector 13 per unit time, QE is the quantum efficiency of the detector 13 in photoelectric conversion, t is the exposure time of the detector 13, D is the dark current of the detector 13, and R is the readout noise of the detector 13.

[0067] It should be noted that the number of photons can be converted from the pixel value corresponding to the electrical signal, the quantum efficiency can be the efficiency of converting photons into charges, the exposure time can be the exposure integration time, the dark current size can be the size of the electrical signal output by the detector 13 in the absence of light, and the readout noise size can be the size of the pixel readout value corresponding to the electrical signal.

[0068] In the above formula, It represents the shot noise from the optical signal. The fundamental reason for the existence of shot noise is the particle nature of light, that is, light is composed of discrete photons. The photons of the detection light or the reflected light emitted by the light source hit the detector. There may be some factors between the light source emission and the detector reception that cause individual photons not to be received by the detector, or there are particularly many photons emitted within a certain time period. This leads to fluctuations in the gray value, which is the so-called shot noise. Shot noise generally follows the Poisson distribution. It represents the shot noise from the dark current (i.e., dark current noise). Since the chip of the camera is made of silicon, as long as it is not at absolute zero, the thermal motion of the material itself will generate electrons that are read out as "signals", thus being called dark current. It represents the read noise. Read noise is the noise introduced during the signal readout process of the camera and is a fixed value for a CCD camera. Since the above three noise sources are not correlated with each other, the total noise is equal to the square root of the sum of their squares.

[0069] In a specific embodiment, the rotation speed levels of the turntable 11 include a low rotation speed mode, a medium rotation speed mode, and a high rotation speed mode. The evaluation models established under different rotation speed levels will be described below.

[0070] Case 1, in the low rotation speed mode, the read noise and the dark current are both fixed. Therefore, the stronger the optical signal, the greater its shot noise. Coupled with the relatively large exposure time t (in the ms level), this leads to D*t + R 2 <<P*QE*t, then the shot noise becomes the main source of noise. Then the main noise types determined by the processor 14 include shot noise, and the established evaluation model is

[0071]

[0072] It can be understood that in the low rotation speed mode, if it is assumed that the rotation speed of the turntable 11 changes from v to v / n, then the exposure time will change from t to n*t. And if SNR1 corresponds to the speed v and SNR2 corresponds to the speed v / n, then there is At this time, the functional relationship between n and SNR can be characterized. The larger n is, the larger SNR is, but the change rate of SNR is getting smaller.

[0073] Case 2, in the medium rotation speed mode, shot noise, read noise, and dark current noise all exist, and no single noise dominates, that is, P*QE*t, D*t, R 2 can all play a role as components in the original formula. Then the main noise types determined by the processor 14 include shot noise, dark current noise, and read noise, and the established evaluation model is

[0074]

[0075] Case 3: In high-speed mode, the exposure time t is extremely short (at the microsecond level), the light signal to be captured is very weak, and P*QE*t< <D*t<<R 2 , then the read noise becomes the main source of the overall noise, then the main noise type determined by the processor 14 includes the read noise, and the established evaluation model is

[0076]

[0077] It can be understood that in the high-speed mode, if it is assumed that the rotation speed of the turntable 11 changes from v to n*v, the exposure time will change from t to t / n. If SNR1 corresponds to the speed v and SNR2 corresponds to the speed n*v, then SNR1 / SNR2=n is satisfied. At this time, the functional relationship between n and SNR can be characterized. n changes in a positive correlation with SNR. The larger n is, the larger the SNR is.

[0078] In one embodiment, the processor 14 determines the input parameters of the evaluation model according to the electrical signal and / or the detection parameter, including:

[0079] 1) The processor 14 obtains the number of photons of the background light entering the detector 13 per unit time according to the electrical signal converted from the background light, and obtains the number of photons of the reflected light entering the detector 13 per unit time according to the electrical signal converted from the reflected light and the background light. For example, the processor 14 obtains the number of photons of the background light entering the detector 13 per unit time P b , and the number of photons P of reflected light entering the detector 13 per unit time is obtained s .

[0080] 2) The processor 14 obtains the quantum efficiency of the detector 13 in photoelectric conversion, the exposure time of the detector 13, the dark current of the detector 13, and the readout noise of the detector 13 according to the detection parameters. For example, the processor 14 obtains the quantum efficiency QE of the detector 13 in photoelectric conversion, the exposure time t of the detector 13, the dark current D of the detector 13, and the readout noise R of the detector 13.

[0081] 3) The processor 14 determines multiple parameters including the number of photons of reflected light entering the detector 13 per unit time, the number of photons of background light entering the detector 13 per unit time, the quantum efficiency of the detector 13 in photoelectric conversion, the exposure time of the detector 13, the dark current of the detector 13, and the readout noise of the detector 13 as input parameters of the evaluation model. The input parameters of the evaluation model under different speed modes can be referred to the above formula and will not be repeated here.

[0082] In one embodiment, the processor 14 determines whether there is a defect in the area on the surface of the object A to be detected that is illuminated by the detection light based on the signal-to-noise ratio, including: 1) the processor 14 compares the signal-to-noise ratio with a preset threshold; 2) when the processor 14 determines that the signal-to-noise ratio is less than the preset threshold, it is determined that there is a defect (such as abnormal texture defect characteristics, etc.) in the area on the surface of the object A to be detected that is illuminated by the detection light.

[0083] It should be noted that, since the defects on the surface of the object A to be detected will cause the change of the reflected light on the surface of the object A to be detected, and cause the number of photons of the light signal entering the detector 13 to decrease, this will cause the calculation result of the signal-to-noise ratio to become smaller. When the signal-to-noise ratio is less than the preset threshold, it can be determined that there are defects in the area of ​​the surface of the object A to be detected that is illuminated by the detection light. It can be understood that when physical defects are detected on the surface of the object A to be detected, the number and position of the defect points can be recorded, so as to facilitate the sorting of unqualified objects to be detected from the user.

[0084] Embodiment 2

[0085] Based on the optical detection device disclosed in the first embodiment, this embodiment discloses a method for estimating the signal-to-noise ratio of optical detection. The method mainly includes: Figure 1 The processor 14 in implements the corresponding functions.

[0086] In this embodiment, please refer to Figure 1 and Figure 2 The signal-to-noise ratio estimation method includes steps 210-240, which are described below respectively.

[0087] Step 210, obtaining an electrical signal generated by a detector 13 and a detection parameter of the detector 13. Here, the electrical signal is obtained by the detector 13 receiving and converting an optical signal, and the optical signal is the reflected light of the surface of the object to be detected and / or the background light other than the reflected light.

[0088] for example Figure 1 , the light source 12 generates detection light and irradiates the surface of the object A to be detected to form reflected light, and the detector 13 receives the reflected light formed by the object A to be detected under the irradiation of the detection light, and / or receives the background light other than the reflected light. Then, the detector 13 can use the received light to form an optical signal and convert the optical signal into an electrical signal, thereby transmitting the electrical signal to the processor 14 for analysis and processing. The detection parameters of the detector 13 are basic parameters of the camera, such as photoelectric conversion efficiency, exposure time, dark current, read noise, etc.

[0089] Step 220 , obtain the rotation speed signal of the object A to be detected, and adapt the noise interference evaluation model according to the rotation speed signal. Since the processor 14 is connected to the turntable 11 , the processor 14 can obtain the rotation speed signal through the speed detection sensor of the turntable 11 .

[0090] See also Figure 1 In the optical detection device 1, since the rotation speed of the object A to be detected has a great relationship with the introduced noise interference factor, it is necessary to differentiate the rotation speed levels, so as to adapt different noise interference evaluation models according to different rotation speed levels. The evaluation model here is used to calculate the signal-to-noise ratio, and the calculation result is related to the number of photons and the basic parameters of the camera.

[0091] Step 230, determining the input parameters of the evaluation model according to the electrical signal and / or the detection parameters. It should be noted that since the calculation result of the signal-to-noise ratio using the evaluation model is related to the number of photons and the basic parameters of the camera, the input parameters of the evaluation model can be obtained by analyzing the electrical signal and detection parameters of the detector 13.

[0092] In step 240, the input parameters are input into the evaluation model to obtain the signal-to-noise ratio.

[0093] In this embodiment, the above step 220 mainly involves the process of adapting the evaluation model of noise interference, so please refer to Figure 3 , the step 220 may specifically include steps 221-223, which are described as follows respectively.

[0094] Step 221, determine the speed level according to the speed signal of the object A to be detected. Figure 1 The processor 14 can obtain the rotation speed by analyzing the rotation speed signal. If a certain speed range is determined as a rotation speed level, multiple rotation speed levels can be obtained. For example, the rotation speed is divided into three rotation speed levels of low, medium and high, which are set as low speed mode, medium speed mode and high speed mode respectively.

[0095] Step 222, determine the main noise type and the secondary noise type disturbed in the optical detection according to the rotation speed level. It can be understood that the noise interference mainly includes shot noise, dark current noise and read noise; then, in the low rotation speed mode, the main noise type disturbed is shot noise, and the secondary noise types are dark current noise and read noise; in the medium rotation speed mode, the main noise types disturbed are shot noise, dark current noise and read noise, and there is no secondary noise type; in the high rotation speed mode, the main noise type disturbed is read noise, and the secondary noise types are dark current noise and shot noise.

[0096] Step 223: Establish a noise interference evaluation model based on the main noise type. Figure 1 , and the low speed mode, medium speed mode and high speed mode are used as examples for explanation.

[0097] In the low speed mode, the main noise type determined by the processor 14 includes shot noise, and the established evaluation model is:

[0098]

[0099] In the medium speed mode, the main noise types determined by the processor 14 include shot noise, dark current noise and read noise, and the established evaluation model is:

[0100]

[0101] In the high speed mode, the main noise type determined by the processor 14 includes read noise, and the established evaluation model is:

[0102]

[0103] Among them, P s is the number of photons of reflected light entering the detector 13 per unit time, P b is the number of photons of background light entering the detector 13 per unit time, QE is the quantum efficiency of the detector 13 in photoelectric conversion, t is the exposure time of the detector 13, D is the dark current of the detector 13, and R is the readout noise of the detector 13. Of course, the principle of establishing the relevant evaluation model can also refer to the above embodiment 1, which will not be repeated here.

[0104] In this embodiment, the above step 230 mainly involves the process of determining the input parameters of the evaluation model, so please refer to Figure 4 , the step 230 may specifically include steps 231-233, which are described as follows respectively.

[0105] Step 231, obtain the number of photons of background light entering the detector 13 per unit time according to the electrical signal converted from the background light, and obtain the number of photons of reflected light entering the detector per unit time according to the electrical signal converted from the reflected light and the background light. Figure 1 The processor 14 obtains the number of photons P of the background light entering the detector 13 per unit time. b , and the number of photons P of reflected light entering the detector 13 per unit time is obtained s .

[0106] Step 232, according to the detection parameters, the quantum efficiency of the detector 13 in photoelectric conversion, the exposure time of the detector 13, the dark current of the detector 13 and the readout noise of the detector 13 are obtained. Figure 1 The processor 14 obtains the quantum efficiency QE of the detector 13 in photoelectric conversion, obtains the exposure time t of the detector 13 , obtains the dark current D of the detector 13 , and obtains the readout noise R of the detector 13 .

[0107] In step 233, the number of photons of reflected light entering the detector 13 per unit time, the number of photons of background light entering the detector 13 per unit time, the quantum efficiency of the detector 13 in photoelectric conversion, the exposure time of the detector 13, the dark current of the detector 13 and the readout noise of the detector 13 are determined as input parameters of the evaluation model.

[0108] It can be understood that the evaluation model established in the low speed mode is Then as long as we get P s , P b The signal-to-noise ratio (SNR) can be calculated by using the input parameters of QE and t. Similarly, since the evaluation model established in the medium speed mode is So we only need to get P s , P b The signal-to-noise ratio (SNR) can be calculated by using the input parameters of QE, D, R, and t. Since the evaluation model established in the high-speed mode is So we only need to get P s The signal-to-noise ratio (SNR) can be calculated by using the input parameters of QE, R, and t.

[0109] It should be noted that in this embodiment, a noise interference evaluation model adapted to the rotational speed of the object to be detected is established. Then, the signal-to-noise ratio of the optical detection device can be easily calculated in combination with the acquired input parameters. This can not only improve the efficiency of signal-to-noise ratio calculation under different rotational speeds or detection modes, but also obtain the relationship between the signal-to-noise ratio and the signal acquisition conditions, thereby improving the accuracy of the signal-to-noise ratio calculation.

[0110] Embodiment 3

[0111] Based on the optical detection device disclosed in the first embodiment, this embodiment discloses an optical detection defect detection method, which mainly includes: Figure 1 The processor 14 in implements the corresponding functions.

[0112] In this embodiment, see Figure 1 and Figure 5 , the defect detection method includes steps 310-360, which are described below respectively.

[0113] Step 310: Obtain the rotation speed signal of the turntable 11 carrying the object A to be detected. Figure 1 The processor 14 can obtain a rotation speed signal through a speed detection sensor of the turntable 11 .

[0114] Step 320, obtaining the electrical signal generated by the detector 13 that converts the optical signal and the detection parameters of the detector 13. Here, the electrical signal is obtained by the detector 13 receiving and converting the optical signal, and the optical signal is the reflected light on the surface of the object A to be detected and / or the background light other than the reflected light. For details of this step, please refer to step 210 in the second embodiment.

[0115] Step 330: adapt the noise interference evaluation model according to the speed signal. For details of this step, please refer to steps 221-223 in the second embodiment.

[0116] Step 340: Determine input parameters of the evaluation model according to the electrical signal and / or the detection parameter. For details of this step, please refer to steps 231-233 in the second embodiment.

[0117] Step 350: Input the input parameters into the evaluation model to calculate the signal-to-noise ratio.

[0118] In one embodiment, in low speed mode, P s , P b , QE, t, these input parameters are input into the evaluation model The signal-to-noise ratio SNR can be calculated in the medium speed mode. s , P b , QE, D, R, t These input parameters are input into the evaluation model The signal-to-noise ratio SNR can be calculated in the high speed mode. s , QE, R, t, these input parameters are input into the evaluation model The signal-to-noise ratio SNR can be calculated.

[0119] Step 360 , judging whether there is a defect in the area of ​​the surface of the object A to be inspected that is illuminated by the inspection light according to the signal-to-noise ratio.

[0120] In this embodiment, the above step 360 mainly involves the process of determining the defects on the surface of the object to be detected, so please refer to Figure 6 , the step 360 may specifically include steps 361-364, which are described as follows respectively.

[0121] Step 361, compare the signal-to-noise ratio with a preset threshold value. The preset threshold value here can be a value freely set by the user, such as 60 dB, and of course other values ​​can be selected without specific limitation.

[0122] Step 362, determine whether the signal-to-noise ratio is less than a preset threshold, if so, proceed to step 363, otherwise proceed to step 364.

[0123] Step 363, when the signal-to-noise ratio is less than the preset threshold, it can be determined that there is a defect in the area of ​​the surface of the object A to be detected that is illuminated by the detection light. Since the defect on the surface of the object A to be detected will cause the change of the reflected light on the surface of the object A to be detected, and cause the number of photons of the light signal entering the detector 13 to decrease, this will cause the calculation result of the signal-to-noise ratio to become smaller. When the signal-to-noise ratio is less than the preset threshold, it can be determined that there is a defect in the area of ​​the surface of the object A to be detected that is illuminated by the detection light.

[0124] Step 364: When the signal-to-noise ratio is greater than or equal to the preset threshold, it can be determined that there is no defect in the area of ​​the surface of the object A to be detected that is illuminated by the detection light. At this time, it indicates that the surface characteristics of the object in the area illuminated by the detection light are normal, and there is no need to mark the defect points.

[0125] It should be noted that in this embodiment, the signal-to-noise ratio is used as an evaluation indicator to determine whether there are defects in the area on the surface of the object to be inspected that is illuminated by the detection light. Not only does it use a new method to evaluate the surface defects of integrated circuit products, but the accurate calculation result of the signal-to-noise ratio is also conducive to improving the accuracy of optical detection, thereby enhancing the feasibility of detection signal-to-noise ratio in optical detection applications.

[0126] Embodiment 4:

[0127] Based on the signal-to-noise ratio estimation method disclosed in the second embodiment and the defect detection method disclosed in the third embodiment, an optical detection device is disclosed in this embodiment. The optical detection device 4 includes a memory 41 and a processor 42 .

[0128] In this embodiment, the memory 41 and the processor 42 are the main components of the optical detection device 4. Of course, the optical detection device may include some detection components and execution components connected to the processor 42. For details, please refer to the above embodiment 1, which will not be described in detail here.

[0129] The memory 41 can be used as a computer-readable storage medium, and is used here to store a program, which can be a program code corresponding to the signal-to-noise ratio estimation method in the second embodiment, or a program code corresponding to the defect detection method in the third embodiment.

[0130] The processor 42 is connected to the memory 41 and is used to execute the program stored in the memory 41 to implement the signal-to-noise ratio estimation method disclosed in the above embodiment 2 (see Figure 2 Steps 210-230 in the above embodiment), and the defect detection method disclosed in the third embodiment (see Figure 5 310-360 in FIG.

[0131] It should be noted that the functions implemented by the processor 42 can also refer to the processor 14 in the first embodiment, and will not be described in detail here.

[0132] Those skilled in the art will appreciate that all or part of the functions of the various methods in the above-mentioned embodiments can be implemented by hardware or by computer programs. When all or part of the functions in the above-mentioned embodiments are implemented by computer programs, the program can be stored in a computer-readable storage medium, and the storage medium can include: read-only memory, random access memory, disk, optical disk, hard disk, etc., and the program is executed by a computer to implement the above-mentioned functions. For example, the program is stored in the memory of the device, and when the program in the memory is executed by the processor, all or part of the above-mentioned functions can be implemented. In addition, when all or part of the functions in the above-mentioned embodiments are implemented by computer programs, the program can also be stored in a storage medium such as a server, another computer, disk, optical disk, flash disk or mobile hard disk, and can be downloaded or copied and saved in the memory of the local device, or the system of the local device is updated, and when the program in the memory is executed by the processor, all or part of the functions in the above-mentioned embodiments can be implemented.

[0133] The above specific examples are used to illustrate the present application, which is only used to help understand the technical solution of the present application and is not intended to limit the present application. For technicians in the relevant technical field, according to the idea of ​​the present application, several simple deductions, deformations or substitutions can also be made.

Claims

1. An optical detection device, characterized in that: include: A turntable, used to carry the object to be detected and drive the object to be detected to rotate; A light source, used to generate detection light, wherein the detection light forms reflected light after being irradiated on the surface of the object to be detected; a detector, used for receiving the reflected light and / or background light other than the reflected light, forming an optical signal and converting the optical signal into an electrical signal; A processor is connected to the turntable, the light source and the detector, and is used to control and analyze the optical detection of the object to be detected; wherein, The processor controls the operation of the turntable, the light source and the detector, and obtains the rotation speed signal of the turntable, and obtains the electrical signal and detection parameters of the detector; The processor determines a speed level according to the speed signal; The processor determines the primary noise type and the secondary noise type disturbed in the optical detection according to the rotation speed level; The processor establishes an evaluation model of noise interference according to the main noise type; The processor determines input parameters of the evaluation model according to the electrical signal and / or the detection parameter; The processor inputs the input parameters into the evaluation model to obtain a signal-to-noise ratio; The processor determines whether there is a defect in a region of the surface of the object to be detected that is illuminated by the detection light according to the signal-to-noise ratio.

2. The optical detection device according to claim 1, characterized in that: The rotation speed levels of the turntable include a low rotation speed mode, a medium rotation speed mode and a high rotation speed mode; In the low speed mode, the main noise type determined by the processor includes shot noise, and the established evaluation model is: In the medium speed mode, the main noise types determined by the processor include shot noise, dark current noise and read noise, so the established evaluation model is In the high speed mode, the main noise type determined by the processor includes read noise, and the established evaluation model is: Among them, P s is the number of photons of the reflected light entering the detector per unit time, P b is the number of photons of the background light entering the detector per unit time, QE is the quantum efficiency of the detector in photoelectric conversion, t is the exposure time of the detector, D is the dark current of the detector, and R is the readout noise of the detector.

3. The optical detection device according to claim 2, characterized in that: The processor determines the input parameters of the evaluation model according to the electrical signal and / or the detection parameter, including: The processor obtains the number of photons of the background light incident on the detector per unit time according to the electrical signal converted from the background light, and obtains the number of photons of the reflected light incident on the detector per unit time according to the electrical signal converted from the reflected light and the background light; The processor obtains the quantum efficiency of the detector in photoelectric conversion, the exposure time of the detector, the dark current of the detector and the readout noise of the detector according to the detection parameters; The processor determines multiple parameters including the number of photons of the reflected light entering the detector per unit time, the number of photons of the background light entering the detector per unit time, the quantum efficiency of the detector in photoelectric conversion, the exposure time of the detector, the dark current of the detector and the readout noise of the detector as input parameters of the evaluation model.

4. The optical detection device according to claim 1, characterized in that: The processor determines, according to the signal-to-noise ratio, whether there is a defect in an area of ​​the surface of the object to be detected that is illuminated by the detection light, including: The processor compares the signal-to-noise ratio with a preset threshold; When the processor determines that the signal-to-noise ratio is less than the preset threshold, it determines that a defect exists in the area of ​​the surface of the object to be detected that is illuminated by the detection light.

5. The optical detection device according to claim 1, characterized in that: The detection light generated by the light source is laser, and the laser is used to irradiate the surface of the object to be detected in a point-like or line-like form, and form an area irradiated by the laser on the surface of the object to be detected.

6. A method for estimating the signal-to-noise ratio of optical detection, characterized in that: include: Acquiring an electrical signal generated by a detector and a detection parameter of the detector; The electrical signal is obtained by the detector receiving and converting an optical signal, wherein the optical signal is the reflected light from the surface of the object to be detected and / or the background light other than the reflected light; Acquire a rotation speed signal of the object to be detected, determine a rotation speed level according to the rotation speed signal of the object to be detected, determine a main noise type and a secondary noise type interfered with in optical detection according to the rotation speed level, and establish an evaluation model of noise interference according to the main noise type; Determining input parameters of the evaluation model according to the electrical signal and / or the detection parameter; The input parameters are input into the evaluation model to obtain a signal-to-noise ratio.

7. The method for estimating the signal-to-noise ratio of optical detection according to claim 6, characterized in that: The speed levels include a low speed mode, a medium speed mode and a high speed mode; In the low speed mode, the main noise type determined includes shot noise, so the established evaluation model is: In the medium speed mode, the main noise types determined include shot noise, dark current noise and read noise, so the established evaluation model is: In the high speed mode, the main noise type determined includes read noise, so the established evaluation model is: Among them, P s is the number of photons of the reflected light entering the detector per unit time, P b is the number of photons of the background light entering the detector per unit time, QE is the quantum efficiency of the detector in photoelectric conversion, t is the exposure time of the detector, D is the dark current of the detector, and R is the readout noise of the detector.

8. The method for estimating the signal-to-noise ratio of optical detection according to claim 6, characterized in that: Determining the input parameters of the evaluation model according to the electrical signal and / or the detection parameter comprises: Obtaining the number of photons of the background light incident on the detector per unit time according to the electrical signal converted from the background light, and obtaining the number of photons of the reflected light incident on the detector per unit time according to the electrical signal converted from the reflected light and the background light; According to the detection parameters, the quantum efficiency of the detector in photoelectric conversion, the exposure time of the detector, the dark current of the detector and the readout noise of the detector are obtained; Determine more than one of the number of photons of the reflected light entering the detector per unit time, the number of photons of the background light entering the detector per unit time, the quantum efficiency of the detector in photoelectric conversion, the exposure time of the detector, the dark current of the detector and the readout noise of the detector as input parameters of the evaluation model.

9. A defect detection method for optical detection, characterized in that: include: Acquire a rotation speed signal of a turntable carrying an object to be detected; Acquiring an electrical signal generated by a detector and a detection parameter of the detector; The electrical signal is obtained by the detector receiving and converting an optical signal, wherein the optical signal is the reflected light from the surface of the object to be detected and / or the background light other than the reflected light; determining a speed level according to the speed signal; Determining the main noise type and the secondary noise type disturbed in the optical detection according to the rotation speed level; Establishing a noise interference assessment model according to the main noise types; Determining input parameters of the evaluation model according to the electrical signal and / or the detection parameter; Inputting the input parameters into the evaluation model to obtain a signal-to-noise ratio; It is determined whether there is a defect in the area of ​​the surface of the object to be detected that is illuminated by the detection light according to the signal-to-noise ratio.

10. The optical defect detection method according to claim 9, characterized in that: The determining, according to the signal-to-noise ratio, whether there is a defect in an area of ​​the surface of the object to be detected that is illuminated by the detection light includes: comparing the signal-to-noise ratio with a preset threshold; When it is determined that the signal-to-noise ratio is less than the preset threshold, it is determined that a defect exists in the area of ​​the surface of the object to be detected that is illuminated by the detection light.

11. A computer-readable storage medium, characterized in that: The medium stores a program, which can be executed by a processor to implement the signal-to-noise ratio estimation method for optical detection as described in any one of claims 6-8, and / or to implement the defect detection method for optical detection as described in any one of claims 9-10.

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