Wafer defect detection method and device

Abstract

The invention discloses a wafer defect detection method and device, and relates to the technical field of semiconductor manufacturing, and the method mainly comprises the steps: transmitting an ultrasonic signal and a surface wave signal to a to-be-detected wafer based on a detection parameter of the to-be-detected wafer, and collecting a reflection signal of the ultrasonic signal and a propagation signal of the surface wave signal; the reflection characteristic of the reflection signal and the propagation characteristic of the propagation signal are extracted, and first defect information of the wafer to be detected is identified based on the reflection characteristic and the propagation characteristic; fusing the reflection characteristics and the propagation characteristics to obtain characteristic parameters of the to-be-detected wafer, and identifying second defect information of the to-be-detected wafer based on the characteristic parameters; and identifying target defect information of the wafer to be detected based on the first defect information and the second defect information. Defect detection is completed based on nondestructive ultrasonic waves, surface waves and fusion processing of the nondestructive ultrasonic waves and the surface waves, and detection is more accurate.

Description

Technical Field

[0001] This application relates to the field of semiconductor manufacturing technology, and particularly to a wafer defect detection method and device based on non-destructive ultrasonic and surface wave technologies. Background Art

[0002] The semiconductor manufacturing industry is one of the important pillars of modern technology. As the basic material for manufacturing chips, the quality and performance of wafers directly affect the performance and reliability of the final products. With the continuous progress of semiconductor technology, the size of wafers has gradually increased from 2 inches in the early days to 12 inches or even larger today. This not only improves production efficiency but also poses higher requirements for wafer quality. Early wafer manufacturing technologies were relatively simple, mainly focusing on basic physical and chemical properties. However, with the continuous increase in integration, minute defects on the surface and inside of wafers have become key factors affecting chip performance. Therefore, wafer defect detection technologies have also been continuously developed, evolving from initial visual inspections and simple optical microscope inspections to today's high-precision non-destructive detection technologies.

[0003] Currently, wafer defect detection mainly uses a variety of non-destructive detection technologies. Among them, the most commonly used are ultrasonic detection technology and X-ray detection technology. The ultrasonic detection technology uses a high-frequency ultrasonic scanning microscope (such as the Hiwave ultrasonic scanning microscope S600) to scan the wafer. This device can emit high-frequency ultrasonic signals and detect the ultrasonic signals with defect information reflected from the wafer. By analyzing these signals, high-resolution images can be generated to achieve non-destructive detection of wafer defects. The X-ray detection technology, on the other hand, penetrates the wafer by emitting X-rays to form a spatial distribution image of the internal structure of the wafer. The X-ray detection technology can provide detailed information about the internal structure of the wafer, especially being highly sensitive to density and composition changes inside the material.

[0004] Although the existing wafer defect detection technologies have made significant progress, there are still problems of false detection and missed detection, especially for some minute defects, new defects, non-internal defects, etc. That is to say, although the existing wafer defect detection technologies can provide a certain detection ability, there are still deficiencies in terms of detection accuracy, etc., and further improvement and optimization are needed. Summary of the Invention

[0005] The main purpose of this application is to provide a wafer defect detection method and device, aiming to solve the problem of insufficient defect detection accuracy of existing single-acoustic-wave detection.

[0006] To achieve the above object, this application proposes a wafer defect detection method, and the method includes:

[0007] Based on the detection parameters of the wafer to be tested, an ultrasonic signal and a surface wave signal are emitted to the wafer to be tested, and the reflection signal of the ultrasonic signal and the propagation signal of the surface wave signal are collected;

[0008] Extract the reflection characteristics of the reflection signal and the propagation characteristics of the propagation signal, and based on the reflection characteristics and the propagation characteristics, identify the first defect information of the wafer to be tested;

[0009] Fuse the reflection characteristics and the propagation characteristics to obtain the characteristic parameters of the wafer to be tested, and based on the characteristic parameters, identify the second defect information of the wafer to be tested;

[0010] Based on the first defect information and the second defect information, identify the target defect information of the wafer to be tested.

[0011] In one embodiment, the step of fusing the reflection characteristics and the propagation characteristics to obtain the characteristic parameters of the wafer to be tested includes:

[0012] Based on the first sampling point of the reflection signal and the second sampling point of the propagation signal, match the reflection characteristics and the propagation characteristics to obtain first fusion data;

[0013] Based on the first timestamp of the reflection signal and the second timestamp of the propagation signal, correct the first fusion data to obtain second fusion data;

[0014] Calculate the similarity between the reflection characteristics and the propagation characteristics, and based on the similarity, verify the second fusion data;

[0015] According to the verification result, screen out the characteristic parameters of the wafer to be tested from the second fusion data.

[0016] In one embodiment, select the reflection parameters of the reflection characteristics and the propagation parameters of the propagation characteristics, and based on the reflection parameters and the propagation parameters, construct corresponding feature vectors and reference feature vectors;

[0017] Based on the feature vector and the reference feature vector, calculate the corresponding column vector, and transpose the column vector to obtain the corresponding row vector;

[0018] Based on the reflection parameters and the propagation parameters, calculate the corresponding covariance matrix, and calculate the inverse of the covariance matrix;

[0019] Substitute the column vector, the row vector and the inverse of the covariance matrix into the Mahalanobis distance formula to calculate the similarity between the reflection characteristics and the propagation characteristics.

[0020] In one embodiment, the step of identifying the first defect information of the wafer to be measured based on the reflection characteristics and the propagation characteristics includes:

[0021] The reflection characteristics include reflection intensity and transmission time, and the propagation characteristics include attenuation characteristics and phase change;

[0022] Based on the reflection intensity and the transmission time at different positions of the reflection signal on the wafer to be measured, locate the internal defect information of the wafer to be measured;

[0023] Based on the attenuation characteristics and the phase change of the propagation signal on the surface of the wafer to be measured, locate the surface defect information of the wafer to be measured;

[0024] Generate the first defect information of the wafer to be measured from the internal defect information and the surface defect information.

[0025] In one embodiment, before the step of transmitting ultrasonic signals and surface wave signals to the wafer to be measured based on the detection parameters of the wafer to be measured, the method further includes:

[0026] Obtain the wafer information of the wafer to be measured, where the wafer information includes the wafer type and the historical defect information corresponding to the wafer type;

[0027] Based on the wafer information, determine the detection parameters of the wafer to be detected, where the detection parameters include probe parameters, detection environment parameters, and acoustic wave frequency parameters.

[0028] In one embodiment, the step of transmitting ultrasonic signals and surface wave signals to the wafer to be measured based on the detection parameters of the wafer to be measured, and collecting the reflection signal of the ultrasonic signal and the propagation signal of the surface wave signal includes:

[0029] Based on the detection parameters of the wafer to be measured, determine the corresponding emission mode, where the emission mode includes emission interval;

[0030] Based on the emission mode, sequentially transmit ultrasonic signals and surface wave signals to the wafer to be measured, and respectively collect the reflection signal of the ultrasonic signal and the propagation signal of the surface wave signal based on the emission interval.

[0031] In one embodiment, the step of extracting the reflection characteristics of the reflection signal and the propagation characteristics of the propagation signal includes:

[0032] Respectively obtain the first emission time of the ultrasonic signal and the second emission time of the surface wave signal;

[0033] Based on the first emission time and the second emission time, perform data preprocessing on the reflected signal and the propagated signal, where the data preprocessing includes noise filtering, signal enhancement, and normalization;

[0034] Extract the reflection characteristics of the reflected signal and the propagation characteristics of the propagated signal after data preprocessing.

[0035] In addition, to achieve the above object, the present application also proposes a wafer defect detection device, where the wafer defect detection device includes:

[0036] A detection module, configured to emit an ultrasonic signal and a surface wave signal to the wafer to be tested based on the detection parameters of the wafer to be tested, and collect the reflected signal of the ultrasonic signal and the propagated signal of the surface wave signal;

[0037] A data processing module, configured to extract the reflection characteristics of the reflected signal and the propagation characteristics of the propagated signal, and identify the first defect information of the wafer to be tested based on the reflection characteristics and the propagation characteristics;

[0038] The data processing module is further configured to fuse the reflection characteristics and the propagation characteristics to obtain the characteristic parameters of the wafer to be tested, and identify the second defect information of the wafer to be tested based on the characteristic parameters;

[0039] The data processing module is further configured to identify the target defect information of the wafer to be tested based on the first defect information and the second defect information.

[0040] In an embodiment, the device further includes:

[0041] A pre-scanning lens, configured to obtain the wafer information of the wafer to be tested, where the wafer information includes the wafer type and the historical defect information corresponding to the wafer type;

[0042] The pre-scanning lens is further configured to determine the detection parameters of the wafer to be detected based on the wafer information, where the detection parameters include probe parameters, detection environment parameters, and acoustic wave frequency parameters.

[0043] In addition, to achieve the above object, the present application also proposes a wafer defect detection system, where the system includes: a memory, a processor, and a computer program stored on the memory and executable on the processor, and the computer program is configured to implement the steps of the wafer defect detection method as described above.

[0044] In addition, to achieve the above object, the present application also proposes a storage medium, where the storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium, and when the computer program is executed by a processor, it implements the steps of the wafer defect detection method as described above.

[0045] In addition, to achieve the above object, the present application further provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the steps of the wafer defect detection method described above are implemented.

[0046] One or more technical solutions proposed by the present application have at least the following technical effects:

[0047] Based on the detection parameters of the wafer to be tested, an ultrasonic signal and a surface wave signal are emitted to the wafer to be tested, and the reflection signal of the ultrasonic signal and the propagation signal of the surface wave signal are collected; the reflection characteristics of the reflection signal and the propagation characteristics of the propagation signal are extracted, and based on the reflection characteristics and the propagation characteristics, the first defect information of the wafer to be tested is identified; the reflection characteristics and the propagation characteristics are fused to obtain the characteristic parameters of the wafer to be tested, and based on the characteristic parameters, the second defect information of the wafer to be tested is identified; based on the first defect information and the second defect information, the target defect information of the wafer to be tested is identified. That is, when detecting, the method of combining ultrasonic waves and surface waves is selected. Compared with the single acoustic wave in the prior art, more data can be collected, and all defects of the wafer to be tested can be more comprehensively reflected. In addition, the feedback signals of the two acoustic waves are fused and processed, so that the defects are fused and verified with each other, so as to obtain a defect result with higher recognition accuracy. Through the comparison of the defect recognition before and after, a better defect recognition effect is obtained, and the recognition accuracy is better than that of the single acoustic wave. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] To more clearly illustrate the embodiments of the present application, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, for those of ordinary skill in the art, other drawings can also be obtained based on these drawings without creative efforts.

[0049] Figure 1 It is a schematic diagram of the main product structure of the wafer defect detection device of the present application;

[0050] Figure 2 It is a schematic flowchart provided by an embodiment of the wafer defect detection method of the present application;

[0051] Figure 3 It is a schematic diagram of the module structure of the wafer defect detection device in the embodiment of the present application;

[0052] Figure 4 It is a schematic diagram of the hardware architecture of the hardware operating environment involved in the wafer defect detection method in the embodiment of the present application.

[0053] The realization of the purpose, functional features, and advantages of this application will be further described in conjunction with the embodiments with reference to the accompanying drawings. Specific Embodiments

[0054] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of this application and are not used to limit this application.

[0055] To better understand the technical solutions of this application, the following will be described in detail in conjunction with the drawings of the specification and specific embodiments.

[0056] The purpose of the embodiment of this application is to provide a better wafer defect detection method, aiming to improve the accuracy of wafer defect detection. The main solution is: on the basis of the existing single ultrasonic detection, surface wave technology is added. The reflection and transmission characteristics of ultrasonic waves are used to detect the defects inside the wafer, and the propagation characteristics of surface waves are used to detect the defects on the surface of the wafer, making the detection more comprehensive. At the same time, in order to further improve the detection accuracy, ultrasonic waves and surface waves are also fused, making the positioning of defects more accurate and reliable. Finally, the defect results of the previous and subsequent times are jointly analyzed before and after, taking into account the comprehensiveness and accuracy of the detection.

[0057] In this embodiment, the wafer defect detection device is used as the execution subject for elaboration. It should be noted first that, referring to Figure 1 , the wafer defect detection device in this embodiment includes a pre-scanning lens (not shown), which is used to scan the wafer information of the wafer to be tested, including the size information of the wafer, the type of the wafer, etc., and select a suitable probe, detection environment, acoustic wave frequency, etc. according to the scanned information; a wafer carrying platform 1, which is used to carry the wafer to be tested; a robotic arm 2, which is used to accurately move the wafer to be tested to different detection positions; a probe 3, which is used to emit ultrasonic waves and surface waves. In particular, this probe can be a composite probe, that is, a combination of an ultrasonic probe and a surface wave probe, so as to realize that one probe can emit two kinds of waves; a signal processor (not shown), which includes a signal generator and a signal receiver, and is used to emit acoustic wave signals and collect the feedback of the acoustic wave signals; the probe and the signal processor form a detection module; a data processing module 4, which is used to analyze the data according to the feedback signal, so as to identify the defects of the wafer to be tested; a display module (not shown), which is used to display the detection results, including the position and type of the defects, etc.

[0058] Specifically, when a wafer (the wafer to be tested) needs to be detected, the wafer defect detection device first scans through a pre-scanning lens to determine the wafer information of the current wafer to be tested, such as 8 inches, unprocessed wafer, and the common historical defect problems are cracks, etc. Then, according to the wafer information, a suitable probe is selected, such as an ultrasonic probe plus a surface wave composite probe; the detection environment is selected, such as a water or oil environment; the acoustic wave frequency is selected, such as 5MHZ. Then, the robotic arm is controlled to position the wafer to be tested on the wafer carrying platform. Next, the signal generator on the probe is controlled to emit ultrasonic waves and surface waves to impact the wafer to be tested on the wafer carrying platform. Then, the reflected wave and the propagated wave that are fed back are received by the signal receiver, and the reflected wave and the propagated wave are transmitted to the data processing module. The data processing module analyzes and identifies the reflected wave and the propagated wave to obtain preliminary defect information, that is, the first defect information. Then, the reflected wave and the propagated wave are fused, and the fused data is analyzed and identified to obtain more accurate defect information, that is, the second defect information. Then, the first defect information and the second defect information are compared and analyzed before and after, so as to comprehensively identify the more accurate defect information of the wafer to be tested. In terms of the balance between comprehensiveness and accuracy, it has achieved the ultimate.

[0059] The technical solution of the present application will be described in detail below.

[0060] An embodiment of the present application provides a wafer defect detection method. Refer to Figure 2 , Figure 2 which is a schematic flowchart of an embodiment of the wafer defect detection method of the present application.

[0061] In this embodiment, the wafer defect detection method includes steps S10 to S40:

[0062] Step S10, based on the detection parameters of the wafer to be tested, emit ultrasonic wave signals and surface wave signals to the wafer to be tested, and collect the reflected signals of the ultrasonic wave signals and the propagated signals of the surface wave signals;

[0063] In order to solve the problem that when the prior art uses a single ultrasonic wave for wafer defect detection, although it has a certain effect, there is still a certain misjudgment rate, especially for the surface defects of wafers, such as tiny scratches, particle contamination, etc. In this embodiment, when performing detection, surface waves are introduced to solve the problem of incomplete defect detection.

[0064] Specifically, when the wafer defect detection system detects the wafer to be tested, it first emits corresponding ultrasonic wave signals and surface wave signals according to the detection parameters of the wafer to be tested, and then collects the emitted signals of the ultrasonic wave signals and the propagated signals of the surface waves according to the propagation behavior characteristics of the acoustic waves. Using the two signals as the basis for subsequent data analysis, compared with the prior art using a single ultrasonic wave, more basic data can be obtained.

[0065] It is understandable that the wafer to be tested is the wafer to be inspected, which is generally a sampling inspection sample of wafers produced in a certain batch; ultrasonic waves are sound waves with a frequency higher than the upper limit of human hearing (usually above 20 kHz) and can propagate in solids, liquids, and gases. It should be explained that by emitting ultrasonic waves into the wafer and receiving and analyzing the reflected signals, defects inside the wafer can be detected. If there are defects inside the wafer, such as cracks, bubbles, or inclusions, the ultrasonic waves will be reflected or scattered at these defects, thus forming different signal characteristics. Surface waves refer to ultrasonic waves propagating along the surface of the wafer. By emitting surface waves onto the wafer surface, surface defects can be detected. Surface waves are very sensitive to surface defects and can detect tiny scratches, particle contamination, etc. Therefore, ultrasonic waves and surface waves can complement each other, so as to collect more comprehensive reflected signals of ultrasonic waves and propagation signals of surface waves.

[0066] An exemplary implementation scenario is as follows: Assume that the wafer to be tested is a 12-inch silicon wafer, and the possible defect types include cracks, voids, and surface scratches. The wafer defect detection device selects an ultrasonic probe with a frequency of 10 MHz and a surface wave probe with a frequency of 5 MHz. The device controls the probe to move uniformly on the wafer surface, emits ultrasonic signals and surface wave signals, and respectively collects the reflected signals and propagation signals.

[0067] In a feasible implementation manner, before the step of emitting ultrasonic signals and surface wave signals to the wafer to be tested based on the detection parameters of the wafer to be tested, the method further includes:

[0068] Step a, obtaining the wafer information of the wafer to be tested, where the wafer information includes the wafer type and the historical defect information corresponding to the wafer type;

[0069] That is, in another embodiment, in order to obtain more appropriate detection results, the wafer defect detection device is set to first obtain the wafer information of the wafer to be tested, so as to select appropriate parameters to detect the wafer to be tested. Among them, the wafer information includes the wafer size, wafer type, and the historical defect information corresponding to the wafer type.

[0070] It should be noted that different wafers are manufactured by different production processes, their quality qualification standards are slightly different, and the historical defect information that has occurred is also different. In order to ensure efficient and matching detection, a pre-judgment will be made on the wafer to be tested.

[0071] Step b, based on the wafer information, determining the detection parameters of the wafer to be tested, where the detection parameters include probe parameters, detection environment parameters, and acoustic wave frequency parameters.

[0072] After obtaining the wafer information of the wafer to be measured, appropriate probe parameters, environmental detection parameters, and acoustic wave frequency parameters can be selected. Then, according to the probe parameters, a suitable probe can be selected. In one embodiment, the probe is a multi-functional integrated probe, which has both an ultrasonic probe and a surface acoustic wave probe, or it can be a combined probe of an ultrasonic probe and a surface acoustic wave probe; the environmental detection parameters are the transmission environment of the acoustic wave, which can be air. Of course, in order to ensure the continuity of the acoustic wave transmission, water or oil can be used; the acoustic wave frequency parameter is the frequency of the acoustic wave. In specific implementation, the past historical defects will be statistically analyzed to obtain the frequencies required for different wafers. For example, for a 12-inch wafer, the ultrasonic wave used is 10 MHz, and the surface acoustic wave is 5 MHz, etc. These parameters are collectively referred to as detection parameters, providing a standard basis for subsequent detection.

[0073] It should be particularly noted that when the probe is a composite probe, that is, the probe can emit both ultrasonic signals and surface acoustic wave signals. Then, when emitting ultrasonic signals and surface acoustic wave signals to the wafer to be measured, it can be either simultaneous emission or interval emission.

[0074] It can be understood that if simultaneous emission is selected, then it is necessary to separate the reflected signals of the ultrasonic signals and the propagation signals of the surface acoustic wave signals collected subsequently. Otherwise, there will be interference between the two waves, resulting in a slightly insufficient final detection accuracy. Therefore, in one embodiment, interval emission is preferably used.

[0075] Specifically, the step of emitting ultrasonic signals and surface acoustic wave signals to the wafer to be measured based on the detection parameters of the wafer to be measured and collecting the reflected signals of the ultrasonic signals and the propagation signals of the surface acoustic wave signals includes:

[0076] Based on the detection parameters of the wafer to be measured, determine the corresponding emission mode, and the emission mode includes an emission interval;

[0077] Based on the emission mode, sequentially emit ultrasonic signals and surface acoustic wave signals to the wafer to be measured, and based on the emission interval, respectively collect the reflected signals of the ultrasonic signals and the propagation signals of the surface acoustic wave signals.

[0078] That is, in order to avoid interference between the two acoustic waves, an emission interval can be set. First, emit ultrasonic signals or surface acoustic wave signals, and then emit surface acoustic wave signals or ultrasonic signals, so that relatively clean reflected signals and propagation signals can be collected respectively.

[0079] In specific implementation, if a too long emission interval is set, it will undoubtedly prolong the entire detection duration. However, if the emission interval is too short, the sound waves emitted for the first time may still have echo interference. Therefore, it is very necessary to set an appropriate emission interval to balance the detection duration and detection accuracy. In specific implementation, the empirical value method can be adopted. For example, for the comprehensive and accurate detection of a 2-inch wafer with a thickness of 1 mm, the emission interval is 0.4 ms, etc. Of course, the machine simulation learning method can also be used to obtain a more optimal emission interval.

[0080] Step S20: Extract the reflection characteristics of the reflection signal and the propagation characteristics of the propagation signal, and based on the reflection characteristics and the propagation characteristics, identify the first defect information of the wafer to be measured.

[0081] In this step, the wafer defect detection device preprocesses the collected reflection signal and propagation signal, and extracts the reflection characteristics and propagation characteristics. The reflection characteristics include reflection intensity, transmission time, and frequency response, etc., which are used to describe the reflection characteristics of ultrasonic waves; the propagation characteristics include propagation speed, attenuation characteristics, and phase change, etc., which are used to express the propagation characteristics of surface waves. Then, based on these characteristic parameters, the device identifies the first defect information of the wafer to be measured.

[0082] Specifically, the step of identifying the first defect information of the wafer to be measured based on the reflection characteristics and the propagation characteristics includes:

[0083] Step c: Based on the reflection intensity of the reflection signal at different positions of the wafer to be measured and the transmission time at different positions, locate the internal defect information of the wafer to be measured.

[0084] Step d: Based on the attenuation characteristics and phase change of the propagation signal on the surface of the wafer to be measured, locate the surface defect information of the wafer to be measured.

[0085] Step e: Generate the first defect information of the wafer to be measured from the internal defect information and the surface defect information.

[0086] It should be noted that the reflection intensity of the reflection characteristics refers to measuring the reflection intensity of the ultrasonic signal at different positions to reflect the size and shape of the defect; the projection time refers to recording the time from the emission to the reception of the ultrasonic signal for calculating the depth of the defect; the frequency response refers to analyzing the frequency components of the ultrasonic signal to identify different types and properties of defects. And the propagation speed of the propagation signal refers to measuring the propagation speed of the surface wave signal on the surface of the wafer to reflect the physical properties and surface state of the wafer to be measured; the attenuation characteristics refer to analyzing the attenuation of the surface wave signal to identify the existence and degree of surface defects; the phase change refers to measuring the phase change of the surface wave signal for accurately locating the position of the defect.

[0087] Therefore, it can be understood that the internal defect information of the wafer to be measured can be located by ultrasonic waves, and the surface defect information of the wafer to be measured can be located by surface waves. By combining the two, the comprehensive defect information of the wafer to be measured can be obtained.

[0088] An exemplary implementation scenario is as follows: Assume that the reflection characteristics of the ultrasonic signal collected are:

[0089] Reflection intensity: 100

[0090] Transmission time: 10 μs

[0091] Frequency response: [100, 200, 300]

[0092] Assume that the propagation characteristics of the surface wave signal collected are:

[0093] Propagation speed: 5000 m / s

[0094] Attenuation characteristic: 0.5 dB / cm

[0095] Phase change: π / 4 rad

[0096] Based on these characteristic parameters, the wafer defect detection device preliminarily identifies that there is a crack on the wafer surface at (x, y) = (10 mm, 10 mm).

[0097] In a feasible implementation manner, the step of extracting the reflection characteristics of the reflection signal and the propagation characteristics of the propagation signal includes:

[0098] Obtain the first emission time of the ultrasonic signal and the second emission time of the surface wave signal respectively;

[0099] According to the first emission time and the second emission time, perform data preprocessing on the reflection signal and the propagation signal. The data preprocessing includes noise filtering, signal enhancement, and normalization;

[0100] Extract the reflection characteristics of the reflection signal and the propagation characteristics of the propagation signal after data preprocessing.

[0101] That is, when extracting the reflection characteristics of the reflection signal and the propagation characteristics of the propagation signal, first perform preprocessing on the signal. This is to further avoid the mutual interference of the two sound waves, obtain the first emission time of the ultrasonic signal and the second emission time of the surface wave signal respectively, and perform staggered processing according to the interval between the first emission time and the second emission time, so as to increase the difference between the two sound waves.

[0102] It is understandable that the purpose of data preprocessing is to remove noise in the signal, improve signal quality, enhance weak signals, ensure the reliability and accuracy of the signals, and perform normalization processing to make signals from different sources comparable.

[0103] In specific implementation, digital filters (such as low-pass filters and band-pass filters) can be used to remove noise in the signal. Among them, the low-pass filter can remove high-frequency noise; the band-pass filter can retain signals within a specific frequency range and remove unwanted frequency components.

[0104] Signal amplification technology can be used to enhance weak signals to ensure the reliability and accuracy of the signals. For example, gain adjustment can dynamically adjust the gain according to the signal strength to ensure that the signal is not distorted.

[0105] Signals from different sources can be normalized to make them comparable, facilitating subsequent feature extraction and matching. For example, min-max normalization: scale the signal values to the range [0, 1]; Z-score normalization: convert the signal values to a standard normal distribution with a mean of 0 and a standard deviation of 1, etc.

[0106] An exemplary implementation scenario is (code implementation example):

[0107]

[0108]

[0109] Step S30: Fuse the reflection characteristics and the propagation characteristics to obtain the characteristic parameters of the wafer to be measured, and based on the characteristic parameters, identify the second defect information of the wafer to be measured.

[0110] In this step, the wafer defect detection device fuses the reflection characteristics representing the internal defects of the wafer to be measured and the propagation characteristics representing the surface defects of the wafer to be measured, and more accurate characteristic parameters reflecting the defects of the wafer to be measured can be obtained. This is because whether it is an ultrasonic signal or a surface wave signal, a single acoustic signal has detection deficiencies. Moreover, for cross-defects, that is, defects that belong to both internal defects and surface defects, there are two feedbacks obtained using ultrasonic signals plus surface wave signals, and there is a suspicion of redefining defects. For example, for a defect where a surface crack extends into the interior, there is a defect mark in the reflection characteristics and also a defect mark in the propagation characteristics, but the two marks may not be accurate. For example, the surface wave identifies it as a pit, while the ultrasonic wave identifies it as a cavity, etc. Therefore, data fusion is required. On the one hand, it can supplement the defect information, and on the other hand, it can also correct each other's incorrect defect information.

[0111] Specifically, the step of fusing the reflection characteristics and the propagation characteristics to obtain the characteristic parameters of the wafer to be measured includes:

[0112] Step f, based on the first sampling point of the reflected signal and the second sampling point of the propagated signal, match the reflection characteristics and the propagation characteristics to obtain first fusion data;

[0113] In one embodiment, preliminary fusion can be completed from the spatial dimension. Specifically, it can be achieved through coordinate system alignment, such as matching the reflection characteristics and the propagation characteristics in the same spatial coordinate system. This means that each sampling point of the ultrasonic signal and the surface wave signal needs to have a corresponding coordinate position. For example, if an ultrasonic probe collects a reflection intensity value at position (x,y), and the surface wave probe also collects a propagation speed value at the same position (x,y). If the sampling points of the two probes do not completely coincide, the data can be aligned to the same grid through spatial interpolation methods (such as linear interpolation or spline interpolation) to obtain the first fusion data.

[0114] Step g, based on the first timestamp of the reflected signal and the second timestamp of the propagated signal, correct the first fusion data to obtain second fusion data;

[0115] Next, further data fusion can be completed from the time dimension. In specific implementation, to ensure that the acquisition times of the ultrasonic signal and the surface wave signal are consistent. This can be achieved by adding timestamps during the data acquisition process. For example, each signal acquisition point has a timestamp to ensure that the sampling data of the two signals at the same time point can correspond. Therefore, based on the first timestamp of the reflected signal and the second timestamp of the propagated signal, the first fusion data can be corrected to avoid the problem of misalignment of acquisition points caused by inconsistent acquisition times. Of course, if there is a time delay in the acquisition of the reflected signal and the propagated signal, such as sequential acquisition, then this time deviation can also be corrected through time delay compensation technology to ensure data consistency.

[0116] Step h, calculate the similarity between the reflection characteristics and the propagation characteristics, and verify the second fusion data based on the similarity;

[0117] After that, use similarity measurement methods (such as Mahalanobis distance, cosine similarity, etc.) to compare the extracted reflection characteristics and propagation characteristics to identify defect information at the same position. For example, the similarity between the reflection intensity and the propagation speed can be calculated. If the similarity is high, it is considered that there is a defect at that position. Conversely, there may be an identification error, and in this way, the verification of the second fusion data is completed.

[0118] Furthermore, in a feasible implementation manner, the step of calculating the similarity between the reflection characteristics and the propagation characteristics includes:

[0119] Step h1, select the reflection parameters of the reflection characteristics and the propagation parameters of the propagation characteristics, and determine the similarity formula corresponding to the reflection parameters and the propagation parameters;

[0120] Step h2, substitute the reflection parameters and the propagation parameters into the similarity formula to obtain the similarity.

[0121] That is, the calculation of similarity can adopt various methods, as well as the reflection parameters and propagation parameters corresponding to different methods.

[0122] In the specific implementation process, since there may be correlations between different characteristic parameters. For example, there may be a certain association between the reflection intensity and the propagation speed. This association will affect the accuracy of similarity measurement. For example, certain types of defects may affect both the reflection intensity and the propagation speed simultaneously, resulting in the simultaneous change of these two parameters in certain areas. If traditional distance measurement methods (such as Euclidean distance) are used, these correlations may lead to the distortion of the similarity measurement results. For example, the co-variation of two characteristic parameters may be over-amplified or reduced, thus affecting the final similarity judgment.

[0123] Therefore, in a feasible implementation manner, a distance measurement method considering the correlations between variables is proposed. Specifically, the covariance matrix is used to measure the correlations between different characteristics, so as to eliminate the interference of correlations between characteristics.

[0124] Specifically, select the reflection parameters of the reflection characteristics and the propagation parameters of the propagation characteristics, and based on the reflection parameters and the propagation parameters, construct the corresponding feature vector and reference feature vector;

[0125] Based on the feature vector and the reference feature vector, calculate the corresponding column vector, and transpose the column vector to obtain the corresponding row vector;

[0126] Based on the reflection parameters and the propagation parameters, calculate the corresponding covariance matrix, and calculate the inverse of the covariance matrix;

[0127] Substitute the column vector, the row vector and the inverse of the covariance matrix into the Mahalanobis distance formula to calculate the similarity between the reflection characteristics and the propagation characteristics.

[0128] For easy understanding, taking the reflection parameter as the reflection intensity and the propagation parameter as the propagation speed as an example for detailed elaboration:

[0129] Suppose at the position (10mm, 10mm), the reflection intensity is 100 and the propagation speed is 5000m / s.

[0130] The first step, construct the feature vector:

[0131]

[0132] Among them, the feature vector x includes the reflection intensity and the propagation speed;

[0133] In the second step, construct a reference feature vector:

[0134] Assume that under normal circumstances, the average values of the reflection intensity and the propagation speed are μ 反射强度 = 50, μ 传播速度 = 4500, and construct the reference feature vector μ

[0135]

[0136] In the third step, calculate the covariance matrix:

[0137] Assume that the covariance matrix of the reflection intensity and the propagation speed is known:

[0138]

[0139] Among them, δ 11 is the variance of the reflection intensity, δ 22 is the variance of the propagation speed, δ 12 and δ 21 are the covariance of the reflection intensity and the propagation speed. Assume the specific values are:

[0140]

[0141] In the fourth step, substitute the above parameters into the Mahalanobis distance formula:

[0142]

[0143] First, calculate

[0144]

[0145] Then, calculate the inverse S of the covariance matrix -1

[0146]

[0147] Among them, det(S) = δ 11 δ 22 -δ 12 δ 21 = 25×10000 - 100×100 = 250000 - 10000 = 240000

[0148]

[0149] Therefore:

[0150]

[0151] Therefore:

[0152]

[0153] If the similarity exceeds a certain threshold, such as 10, it is considered that there is a defect at that position.

[0154] It should be noted that in the above calculation, (x - μ) is a column vector representing the difference between the obtained eigenvector and the reference eigenvector;

[0155] (x - μ) T is the transpose of (x - μ), which converts the column vector into a row vector;

[0156] S -1 is the inverse matrix of the covariance matrix.

[0157] The above method can eliminate the correlation interference between the reflection intensity and the propagation speed, making the similarity measurement more accurate. Specifically, through the inverse matrix of the covariance matrix, the correlation between features is adjusted, thereby improving the accuracy and reliability of defect detection.

[0158] In addition, other parameters and formulas can be selected for calculation, such as calculating the similarity of the transmission time and the attenuation characteristics. For example, the cosine similarity formula can be used:

[0159]

[0160] where A and B are the vectors of the transmission time and the attenuation characteristics respectively.

[0161] For example, calculate the similarity of the frequency response and the phase change. For example, the correlation coefficient formula can be used:

[0162]

[0163] where Ai and Bi are the values of the frequency response and the phase change respectively, and are their average values, etc.

[0164] If the similarity exceeds a certain threshold, it is considered that there is a defect at that position.

[0165] Step i, according to the verification result, screen out the characteristic parameters of the wafer to be tested from the second fusion data.

[0166] In this step, based on the similarity calculation of each acquisition point or sampling point, the credibility of each acquisition point or sampling point is identified. For the acquisition points or sampling points with similarity higher than the threshold, they are screened out, so as to screen out the characteristic parameters of the wafer to be measured. These characteristic parameters can better characterize the defect information of the wafer to be measured, that is, the credibility of the defect information corresponding to the characteristic parameters is relatively high, and this defect is given priority consideration.

[0167] An exemplary implementation scenario is as follows:

[0168] Suppose we have collected the following data at the position (x, y):

[0169] Ultrasonic signal:

[0170] Reflection intensity: 100

[0171] Transmission time: 10 μs

[0172] Frequency response: [100, 200, 300]

[0173] Surface wave signal:

[0174] Propagation speed: 5000 m / s

[0175] Attenuation characteristic: 0.5 dB / cm

[0176] Phase change: π / 4 rad

[0177] Spatial matching:

[0178] Ensure that the data collected by the ultrasonic signal and the surface wave signal at the same position (x, y) can be corresponding.

[0179] Time synchronization:

[0180] Ensure that the sampling data of the ultrasonic signal and the surface wave signal at the same time point can be corresponding. For example, if the ultrasonic signal collects data at t = 0 s, the surface wave signal also collects data at t = 0 s.

[0181] Feature comparison:

[0182] Compare the reflection intensity 100 with the propagation speed 5000 m / s to determine whether there is a defect at this position.

[0183] Calculate the similarity of the reflection intensity and the propagation speed. If the similarity is high, it is considered that there is a defect at this position.

[0184] In addition, other characteristic parameters (such as transmission time, frequency response, attenuation characteristic, phase change) can be comprehensively considered to further confirm the type and severity of the defect.

[0185] Exemplary description of similarity calculation:

[0186] Assume that at the position (10 mm, 10 mm), the reflection intensity is 100 and the propagation speed is 5000 m / s. The wafer defect detection device matches these two characteristic parameters in the same spatial coordinate system and ensures the consistency of the acquisition time through time synchronization technology. Then, the similarity of these two characteristic parameters is calculated using a similarity measurement method (such as Mahalanobis distance):

[0187]

[0188] Assume μ 反射强度 = 50, μ 传播速度 = 4500, which are the average values of the reflection intensity and propagation speed under normal conditions respectively. Then:

[0189]

[0190] If the set threshold is 10 and the similarity exceeds the threshold, the wafer defect detection device determines that there is a defect at this position.

[0191] Step S40: Based on the first defect information and the second defect information, identify the target defect information of the wafer to be measured.

[0192] In this embodiment, the first defect information includes the internal defect information and surface defect information of the wafer to be measured, that is, the first defect information provides more comprehensive defect information; while the second defect information contains the most definite (high similarity) defect information, that is, it provides more accurate defect information. Therefore, by combining the two, the target defect information of the wafer to be measured can be obtained. This target defect information takes into account both the comprehensiveness and authenticity of the defects, and thus can better characterize the defects of the wafer to be measured.

[0193] Finally, the wafer defect detection device combines the first defect information (the initially identified crack position) and the second defect information (the crack position confirmed by feature parameter fusion) to generate a detailed defect detection report.

[0194] An exemplary implementation scenario is as follows:

[0195] Defect position: (10 mm, 10 mm)

[0196] Defect type: crack

[0197] Defect size: 20 μm

[0198] Defect depth: 5 μm

[0199] Defect distribution: local

[0200] This embodiment provides a method for detecting wafer defects. When detecting a wafer to be measured, an acoustic wave combination method of ultrasonic signals plus surface wave signals is used to obtain both the internal defect information of the wafer to be measured and the surface defect information of the wafer to be measured, making the identification of defects more comprehensive. At the same time, the reflection characteristics corresponding to the ultrasonic signals and the propagation characteristics corresponding to the surface waves are fused and processed. By obtaining characteristic parameters that can better represent the defects of the wafer to be measured, more accurate defect information can be identified. Finally, the two identifications before and after are integrated, making the final detection result both comprehensive and reliable, and improving the accuracy of wafer defect detection.

[0201] It should be noted that the above examples are only for understanding this application and do not constitute a limitation to the wafer defect detection method of this application. Based on this technical concept, more forms of simple transformations are within the protection scope of this application.

[0202] This application also provides a wafer defect detection device. Please refer to Figure 3 , and the wafer defect detection device includes:

[0203] A detection module 20, configured to emit ultrasonic signals and surface wave signals to the wafer to be measured based on the detection parameters of the wafer to be measured, and collect the reflection signals of the ultrasonic signals and the propagation signals of the surface wave signals;

[0204] A data processing module 30, configured to extract the reflection characteristics of the reflection signals and the propagation characteristics of the propagation signals, and identify the first defect information of the wafer to be measured based on the reflection characteristics and the propagation characteristics;

[0205] The data processing module is further configured to fuse the reflection characteristics and the propagation characteristics to obtain characteristic parameters of the wafer to be measured, and identify the second defect information of the wafer to be measured based on the characteristic parameters;

[0206] The data processing module is further configured to identify the target defect information of the wafer to be measured based on the first defect information and the second defect information.

[0207] In addition, the wafer defect detection device further includes:

[0208] A pre-scanning lens 10, configured to obtain the wafer information of the wafer to be measured, where the wafer information includes the wafer type and the historical defect information corresponding to the wafer type;

[0209] The pre-scanning lens is further configured to determine the detection parameters of the wafer to be detected based on the wafer information, where the detection parameters include probe parameters, detection environment parameters, and acoustic wave frequency parameters.

[0210] And a display module 40, configured to display the target defect information.

[0211] The wafer defect detection device provided by the present application adopts the wafer defect detection method in the above embodiment, and can solve the technical problem of insufficient detection accuracy of single acoustic wave. Compared with the prior art, the beneficial effects of the wafer defect detection device provided by the present application are the same as those of the wafer defect detection method provided by the above embodiment, and other technical features in the wafer defect detection device are the same as those disclosed in the method of the above embodiment, and will not be elaborated herein.

[0212] The present application provides a wafer defect detection system. The wafer defect detection system includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the wafer defect detection method in the above embodiment.

[0213] The following refers to Figure 4 , which shows a schematic diagram of a hardware architecture suitable for implementing the wafer defect detection system of the embodiments of the present application. The wafer defect detection system in the embodiments of the present application may include, but is not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions: tablet computers), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 4 The wafer defect detection system shown is only an example, and should not impose any limitations on the functions and usage scopes of the embodiments of the present application.

[0214] As Figure 4As shown, the wafer defect detection system may include a processing device 1001 (such as a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM: Read Only Memory) 1002 or the program loaded from the storage device 1003 into the random access memory (RAM: Random Access Memory) 1004. In the RAM 1004, various programs and data required for the operation of the wafer defect detection system are also stored. The processing device 1001, the ROM 1002, and the RAM 1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems can be connected to the I / O interface 1006: an input device 1007 including, for example, a touch screen, a touch pad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD: Liquid Crystal Display), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow the wafer defect detection system to communicate with other devices wirelessly or wiredly to exchange data.

[0215] Specifically, according to the embodiments disclosed in the present application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program contains program codes for executing the methods shown in the flowcharts. In such an embodiment, the computer program can be downloaded and installed from the network through the communication device, or installed from the storage device 1003, or installed from the ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the methods of the embodiments disclosed in the present application are executed.

[0216] The wafer defect detection system provided by the present application adopts the wafer defect detection method in the above-mentioned embodiment, and can solve the technical problem of insufficient detection accuracy of single acoustic wave. Compared with the prior art, the beneficial effects of the wafer defect detection system provided by the present application are the same as those of the wafer defect detection method provided by the above-mentioned embodiment, and other technical features in the wafer defect detection system are the same as those disclosed in the method of the previous embodiment, which will not be elaborated here.

[0217] It should be understood that each part disclosed in the present application can be implemented by hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in a suitable manner in any one or more embodiments or examples.

[0218] As described above, it is only the specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present application can easily think of changes or substitutions, which should all be covered within the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims described above.

[0219] The present application provides a computer-readable storage medium having computer-readable program instructions (i.e., computer programs) stored thereon, and the computer-readable program instructions are used to execute the wafer defect detection method in the above embodiments.

[0220] The computer-readable storage medium provided by the present application can be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems or devices, or any combination of the above. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM) or a flash memory, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium can be any tangible medium that contains or stores a program, and the program can be used by or in combination with an instruction execution system or device. The program code contained on the computer-readable storage medium can be transmitted by any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination of the above.

[0221] The above computer-readable storage medium can be included in the wafer defect detection system; or it can exist alone without being assembled into the wafer defect detection system.

[0222] The above computer-readable storage medium carries one or more programs, and when the one or more programs are executed by the wafer defect detection system, the wafer defect detection system is caused to execute the steps of the above wafer defect detection method.

[0223] Computer program code for performing the operations of this application can be written in one or more programming languages or combinations thereof. The above-mentioned programming languages include object-oriented programming languages such as Java, Smalltalk, C++, and also include conventional procedural programming languages such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, executed as an independent software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any kind of network, including a local area network (LAN: Local Area Network) or a wide area network (WAN: Wide Area Network), or it can be connected to an external computer (for example, by using an Internet service provider to connect through the Internet).

[0224] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in the flowchart or block diagram can represent a module, a program segment, or a part of the code, and this module, program segment, or part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks can also occur in a different order from that marked in the accompanying drawings. For example, two consecutively represented blocks can actually be executed substantially in parallel, and they can sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, and the combination of blocks in the block diagram and / or flowchart, can be implemented by a dedicated hardware-based system for performing the specified functions or operations, or can be implemented by a combination of dedicated hardware and computer instructions.

[0225] The modules described in the embodiments of this application can be implemented in software or in hardware. Among them, the name of the module does not constitute a limitation on the unit itself in some cases.

[0226] The readable storage medium provided by this application is a computer-readable storage medium. The computer-readable storage medium stores computer-readable program instructions (i.e., computer programs) for performing the above-mentioned wafer defect detection method, and can solve the technical problem of insufficient single acoustic wave detection accuracy. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided by this application are the same as those of the wafer defect detection method provided by the above embodiments, and will not be elaborated here.

[0227] The present application also provides a computer program product, including a computer program which, when executed by a processor, implements the steps of the wafer defect detection method as described above.

[0228] The computer program product provided by the present application can solve the technical problem of insufficient single acoustic wave detection accuracy. Compared with the prior art, the beneficial effects of the computer program product provided by the present application are the same as those of the wafer defect detection method provided by the above embodiment, and will not be elaborated here.

[0229] The above are only partial embodiments of the present application, and thus do not limit the patent scope of the present application. Any equivalent structural transformation made under the technical concept of the present application by using the content of the specification and drawings of the present application, or direct / indirect application in other related technical fields, is included in the patent protection scope of the present application.

Claims

1. A wafer defect detection method, characterized in that, The described wafer defect detection method includes: Based on the detection parameters of the wafer to be measured, an ultrasonic signal and a surface wave signal are emitted to the wafer to be measured, and the reflection signal of the ultrasonic signal and the propagation signal of the surface wave signal are collected; Extract the reflection characteristics of the reflection signal and the propagation characteristics of the propagation signal, and based on the reflection characteristics and the propagation characteristics, identify the first defect information of the wafer to be measured; Fuse the reflection characteristics and the propagation characteristics to obtain the characteristic parameters of the wafer to be measured, and based on the characteristic parameters, identify the second defect information of the wafer to be measured; Based on the first defect information and the second defect information, identify the target defect information of the wafer to be measured.

2. The wafer defect detection method according to claim 1, wherein The step of fusing the reflection characteristics and the propagation characteristics to obtain the characteristic parameters of the wafer to be measured includes: Based on the first sampling point of the reflection signal and the second sampling point of the propagation signal, match the reflection characteristics and the propagation characteristics to obtain first fusion data; Based on the first timestamp of the reflection signal and the second timestamp of the propagation signal, correct the first fusion data to obtain second fusion data; Calculate the similarity between the reflection characteristics and the propagation characteristics, and verify the second fusion data based on the similarity; According to the verification result, screen out the characteristic parameters of the wafer to be measured from the second fusion data.

3. The wafer defect detection method according to claim 2, wherein, The step of calculating the similarity between the reflection characteristics and the propagation characteristics includes: Select the reflection parameters of the reflection characteristics and the propagation parameters of the propagation characteristics, and based on the reflection parameters and the propagation parameters, construct corresponding feature vectors and reference feature vectors; Based on the feature vector and the reference feature vector, calculate the corresponding column vector, and transpose the column vector to obtain the corresponding row vector; Based on the reflection parameters and the propagation parameters, calculate the corresponding covariance matrix, and calculate the inverse of the covariance matrix; Substitute the column vector, the row vector, and the inverse of the covariance matrix into the Mahalanobis distance formula to calculate the similarity between the reflection characteristics and the propagation characteristics.

4. The wafer defect detection method according to claim 1, wherein The step of identifying the first defect information of the wafer to be measured based on the reflection characteristics and the propagation characteristics includes: The reflection characteristics include reflection intensity and transmission time, and the propagation characteristics include attenuation characteristics and phase change; Based on the reflection intensity at different positions of the reflection signal on the wafer to be measured and the transmission time at different positions, locate the internal defect information of the wafer to be measured; Based on the attenuation characteristics and phase change of the propagation signal on the surface of the wafer to be measured, locate the surface defect information of the wafer to be measured; Generate the first defect information of the wafer to be measured from the internal defect information and the surface defect information.

5. The wafer defect detection method according to any one of claims 1-4, characterized in that Before the step of emitting an ultrasonic signal and a surface wave signal to the wafer to be measured based on the detection parameters of the wafer to be measured, the method further includes: Obtain the wafer information of the wafer to be measured, where the wafer information includes the wafer type and the historical defect information corresponding to the wafer type; Based on the wafer information, determine the detection parameters of the wafer to be detected, where the detection parameters include probe parameters, detection environment parameters, and acoustic wave frequency parameters.

6. The wafer defect detection method according to any one of claims 1-4, characterized in that, The step of emitting ultrasonic signals and surface wave signals to the wafer to be detected based on the detection parameters of the wafer to be detected and collecting the reflected signals of the ultrasonic signals and the propagation signals of the surface wave signals includes: Based on the detection parameters of the wafer to be detected, determine the corresponding emission mode, where the emission mode includes an emission interval; Based on the emission mode, sequentially emit ultrasonic signals and surface wave signals to the wafer to be detected, and based on the emission interval, collect the reflected signals of the ultrasonic signals and the propagation signals of the surface wave signals respectively.

7. The wafer defect detection method according to claim 6, characterized in that, The step of extracting the reflection characteristics of the reflected signal and the propagation characteristics of the propagation signal includes: Obtain the first emission time of the ultrasonic signal and the second emission time of the surface wave signal respectively; According to the first emission time and the second emission time, perform data preprocessing on the reflected signal and the propagation signal, where the data preprocessing includes noise filtering, signal enhancement, and normalization; Extract the reflection characteristics of the reflected signal after data preprocessing and the propagation characteristics of the propagation signal.

8. A wafer defect detection device, characterized in that, The device includes: A detection module, configured to emit ultrasonic signals and surface wave signals to the wafer to be detected based on the detection parameters of the wafer to be detected, and collect the reflected signals of the ultrasonic signals and the propagation signals of the surface wave signals; A data processing module, configured to extract the reflection characteristics of the reflected signal and the propagation characteristics of the propagation signal, and identify the first defect information of the wafer to be detected based on the reflection characteristics and the propagation characteristics; The data processing module is further configured to fuse the reflection characteristics and the propagation characteristics to obtain the characteristic parameters of the wafer to be detected, and identify the second defect information of the wafer to be detected based on the characteristic parameters; The data processing module is further configured to identify the target defect information of the wafer to be detected based on the first defect information and the second defect information.

9. The wafer defect detection device according to claim 8, wherein, The device further includes: A pre-scanning lens, configured to obtain the wafer information of the wafer to be detected, where the wafer information includes the wafer type and the historical defect information corresponding to the wafer type; The pre-scanning lens is further configured to determine the detection parameters of the wafer to be detected based on the wafer information, where the detection parameters include probe parameters, detection environment parameters, and acoustic wave frequency parameters.

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