Filtering method and equipment for rapid heat treatment process, medium and filter

Abstract

The invention discloses a filtering method and device for a rapid heat treatment process, a medium and a filter, and belongs to the technical field of semiconductor manufacturing, and the filtering method comprises the following steps: S1, obtaining an original temperature signal; s2, performing a band-pass filtering algorithm on the original temperature signal to obtain a low-frequency interference signal; s3, processing the original temperature signal according to the low-frequency interference signal to obtain an interference-removed signal; and S4, performing a low-pass filtering algorithm on the interference-removed signal to obtain a final temperature signal. According to the invention, the combined design of the band-pass filtering algorithm and the low-pass filtering algorithm is utilized to filter out known specific low-frequency interference signals appearing in the rapid heat treatment system, so that the control performance of the temperature control algorithm in the peak annealing process is improved.

Description

Technical Field

[0001] This invention belongs to the field of semiconductor manufacturing technology, and particularly relates to filtering methods, equipment, media and filters for rapid thermal processing. Background Technology

[0002] Rapid Thermal Processing (RTP) is an advanced monolithic wafer thermal processing technology. Compared to traditional batch thermal processing, RTP is more suitable for miniaturizing the feature size of integrated circuits and is an indispensable process in advanced semiconductor manufacturing. Temperature control of monolithic wafers is a core technology of paramount importance.

[0003] Temperature control parameters for rapid heat treatment processes generally include two types: temperature and temperature difference. Temperature parameters refer to the overall requirement that multiple temperatures must meet various customer-specified requirements, such as heating rate, overshoot, and steady-state error. Temperature difference parameters refer to the numerical difference between various temperatures, typically the difference between the highest and lowest temperatures at the same moment.

[0004] The digital filtering algorithm is a crucial software module in the temperature controller, responsible for filtering and processing the received wafer temperature measurement signal before transmitting it to the control algorithm for closed-loop control. This prevents low-frequency interference signals from reaching the control algorithm and subsequently the control voltage. The feedback signal originates from the original signal from the high-temperature thermometer and contains noise signals of various frequencies. Of particular concern is the low-frequency signal doped into the system frequency. This low-frequency signal is generated by the wafer's levitational rotation during the heat treatment process. The high-temperature thermometer actually measures the temperature of a rotating wafer.

[0005] Existing digital filtering algorithms cannot effectively filter out specific low-frequency interference signals in rapid thermal processing systems without increasing signal delay. Although increasing the filtering parameters of first-order or mean filters can improve the filtering effect, this operation also increases signal delay. Especially in the peak annealing process of rapid thermal processing, the heating rate can reach up to 250℃ / s, and the increase in signal delay directly affects the performance of system temperature control. Summary of the Invention

[0006] Based on the technical problems existing in the prior art, the present invention provides a filtering method, device, medium and filter for rapid heat treatment processes.

[0007] According to a first aspect of the technical solution of the present invention, a filtering method for a rapid heat treatment process is provided, comprising the following steps: S1: Acquire the raw temperature signal; S2: A low-frequency interference signal is obtained by applying a bandpass filtering algorithm to the original temperature signal; S3: Process the original temperature signal based on the low-frequency interference signal to obtain a de-interference signal; S4: The final temperature signal is obtained by applying a low-pass filtering algorithm to the interference removal signal.

[0008] A further improvement of the present invention is that, in S1, the following steps are included: S11: Perform continuous sampling according to the sampling period to obtain a discrete sequence; S12: Denoise the discrete sequence to obtain a denoised sequence; S13: Convert the units of the limited sequence to obtain the original temperature signal.

[0009] A further improvement of the present invention is that the transfer function expression of the bandpass filtering algorithm is: ; In the formula, s is the Laplace operator, and ζ BP ω is the damping coefficient of the bandpass filter. BP,n This is the inherent frequency of the bandpass filter.

[0010] A further improvement of the present invention is that, in S3, a de-interference signal is obtained by subtracting a low-frequency interference signal from the original temperature signal.

[0011] A further improvement of the present invention is that the transfer function expression of the low-pass filtering algorithm is: ; In the formula, ζ LP ω is the damping coefficient of the low-pass filter. LP,n This is the inherent frequency of the low-pass filter.

[0012] A further improvement of the present invention is that the transfer function expression of the final temperature signal relative to the original temperature signal is: .

[0013] A further improvement of the present invention is that step S4 includes the following steps: S41: Perform Z-transformation on the transfer function F(s) of the final temperature signal to obtain F(z); S42: Perform an inverse Z-transform on F(z) to obtain the final discrete-time expression.

[0014] According to a second aspect of the technical solution of the present invention, a filter for a rapid thermal processing process is provided, comprising: The data acquisition module is used to acquire the raw temperature signal; A bandpass filter module is used to apply a bandpass filter algorithm to the original temperature signal to obtain a low-frequency interference signal; The interference removal module is used to process the original temperature signal based on the low-frequency interference signal to obtain the interference removal signal; The low-pass filter module is used to apply a low-pass filter algorithm to the interference removal signal to obtain the final temperature signal.

[0015] According to a third aspect of the technical solution of the present invention, an electronic device is provided, which employs the above-described filtering method for rapid thermal processing, comprising: One or more processors; Storage device for storing one or more computer programs; When the one or more computer programs are executed by the one or more processors, the one or more processors implement a filtering method for a rapid thermal processing process as described above.

[0016] According to a fourth aspect of the present invention, a computer-readable storage medium is provided, on which a computer program is stored, wherein the computer program, when executed by a processor, implements a filtering method for a rapid thermal processing process as described above.

[0017] The above technical solution has the following beneficial technical effects: This invention utilizes a combination of bandpass and lowpass filtering algorithms to filter out known specific low-frequency interference signals that appear in rapid heat treatment systems, thereby improving the control performance of the temperature control algorithm in the peak annealing process. Attached Figure Description

[0018] The accompanying drawings are provided to better understand the invention and are not intended to unduly limit the scope of the invention. Wherein: Figure 1 This is a schematic flowchart of a filtering method for a rapid heat treatment process according to the present invention. Figure 2 This is a schematic block diagram of the structure of a filter for a rapid thermal processing process according to the present invention; Figure 3 This is a schematic diagram of peak tip annealing test data before and after the application of the method in Embodiment 1 of the present invention; Figure 4 This is a schematic diagram of the structure of the computer system in an embodiment of the present invention. Detailed Implementation

[0019] The following description, in conjunction with the accompanying drawings, illustrates exemplary embodiments of the present invention, including various details to aid understanding. These details should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of the invention. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0020] Example 1 like Figure 1 As shown, the present invention provides a filtering method for a rapid heat treatment process, which includes the following steps: S1: Acquire the raw temperature signal; S2: A low-frequency interference signal is obtained by applying a bandpass filtering algorithm to the original temperature signal; S3: Process the original temperature signal based on the low-frequency interference signal to obtain a de-interference signal; S4: The final temperature signal is obtained by applying a low-pass filtering algorithm to the interference removal signal.

[0021] Specifically, the original temperature signal is acquired through a temperature sensor, and this original temperature signal is the temperature signal at the wafer during the rapid thermal processing. Using the acquired original temperature data as input, a bandpass filter algorithm is employed to filter out low-frequency interference signals from the original temperature signal. Then, the low-frequency interference signals are removed to obtain a de-interference signal. This de-interference signal is then used as a new input value, and a low-pass filter algorithm is applied to remove high-frequency noise from the interference signals, resulting in the final temperature signal. The low-frequency interference signals are handled by the bandpass filter algorithm, while the high-frequency noise in the signal is handled by the low-pass filter. This eliminates the need to lower the cutoff frequency of the low-pass filter to remove low-frequency interference, thus avoiding an increase in signal delay.

[0022] Specifically, S1 includes the following steps: S11: Perform continuous sampling according to the sampling period to obtain a discrete sequence; S12: Denoise the discrete sequence to obtain a denoised sequence; S13: Convert the units of the limited sequence to obtain the original temperature signal.

[0023] By continuously sampling according to the sampling period, it is ensured that no transient temperature jumps are missed in the obtained discrete sequence, and the steep rising edge of 250 ℃ / s in the RTP peak annealing segment can also be completely captured. Then, the discrete sequence is denoised to remove glitches and occasional code skipping, so as to avoid abnormal data affecting the output of the final temperature data. Since the discrete sequence acquired by the temperature sensor is a voltage signal, it is converted into a temperature signal through a unit conversion step to obtain the original temperature signal.

[0024] Specifically, in S11, the analog voltage signal output by the temperature sensor is sampled at equal intervals with a fixed sampling period, and immediately stored in the buffer after each trigger, forming a discrete sequence with equal time intervals.

[0025] Specifically, in S12, a 3-5 point window is first used to remove spikes from the discrete sequence by applying a moving average or median filter, thus eliminating occasional code skipping.

[0026] Specifically, in S13, the denoising sequence is saturated and limited according to the preset reasonable upper and lower voltage limits, and values ​​exceeding the upper and lower limits are removed. Then, the voltage values ​​in the denoising sequence are converted into temperature values ​​through a preset conversion formula, which are used as the raw temperature data in subsequent steps.

[0027] Specifically, the transfer function expression of the bandpass filtering algorithm is as follows: ; In the formula, s is the Laplace operator, and ζ BP ω is the damping coefficient of the bandpass filter. BP,n The natural frequency of the bandpass filter. The transfer function of the bandpass filtering algorithm is given, and the frequency of the low-frequency interference signal in step S2 is based on ω. BP,n Sure, The bandwidth of the low-frequency interference signal is determined by the debugging parameters. A transfer function is a mathematical concept that represents a mathematical description of data transferred from one point to another.

[0028] Specifically, in S3, the low-frequency interference signal is subtracted from the original temperature signal to obtain the de-interference signal.

[0029] Specifically, the transfer function expression of the low-pass filtering algorithm is as follows: ; In the formula, ζ LP ω is the damping coefficient of the low-pass filter. LP,n This is the inherent frequency of the low-pass filter. This is the transfer function of the low-pass filtering algorithm. and Used for debugging and filtering out high-frequency noise.

[0030] Specifically, the transfer function expression of the final temperature signal relative to the original temperature signal is as follows: .

[0031] In the formula, Y(s) and U(s) are the Laplace transform expressions of the filtered output signal and the filtered input T (i.e., the original temperature signal), respectively.

[0032] Specifically, S4 includes the following steps: S41: Perform Z-transformation on the transfer function F(s) of the final temperature signal to obtain F(z); S42: Perform an inverse Z-transform on F(z) to obtain the final discrete-time expression.

[0033] Specifically, the transfer function of the final temperature signal is expressed as a discrete form F(z) through the Z-transform, which facilitates its application. This is achieved by employing a zero-order hold. The conversion is performed using the following formula: ; In the formula, Let be the signal acquisition period. Therefore, the formula exists: ; F(z) is a fractional polynomial consisting of the variable z: ; By performing an inverse Z-transform on F(z), the final discrete-time expression is obtained: ; In the formula, the coefficients and That is The inevitable result of the transformation is... , , , and Composition, and yes The intervals are discrete time points. Therefore, the above formula can be written into a computer program in code form.

[0034] Specifically, the temperature data obtained before and after using the method in this embodiment are as follows: Figure 3 As shown, the temperature curve on the left represents temperature data collected using known methods. Low-frequency interference signals are only slightly attenuated but are still present in the curves with high temperature change rates. The curve on the right, however, demonstrates that this invention effectively filters out low-frequency interference signals appearing in temperature curves with high temperature change rates.

[0035] Example 2 like Figure 2 As shown, the present invention provides a filter for a rapid heat treatment process, which employs the filtering method for a rapid heat treatment process described in the foregoing embodiments, and includes: The data acquisition module is used to acquire the raw temperature signal; A bandpass filter module is used to apply a bandpass filter algorithm to the original temperature signal to obtain a low-frequency interference signal; The interference removal module is used to process the original temperature signal based on the low-frequency interference signal to obtain the interference removal signal; The low-pass filter module is used to apply a low-pass filter algorithm to the interference removal signal to obtain the final temperature signal.

[0036] Specifically, the data acquisition module includes: A continuous sampling unit is used to perform continuous sampling according to a sampling period to obtain a discrete sequence; The denoising unit is used to denoise the discrete sequence to obtain a denoised sequence. The conversion unit is used to convert the limited sequence to units to obtain the original temperature signal.

[0037] By continuously sampling according to the sampling period, it is ensured that no transient temperature jumps are missed in the obtained discrete sequence, and the steep rising edge of 250 ℃ / s in the RTP peak annealing segment can also be completely captured. Then, the discrete sequence is denoised to remove glitches and occasional code skipping, so as to avoid abnormal data affecting the output of the final temperature data. Since the discrete sequence acquired by the temperature sensor is a voltage signal, it is converted into a temperature signal through a unit conversion step to obtain the original temperature signal.

[0038] Specifically, in the continuous sampling unit, the analog voltage signal output by the temperature sensor is sampled at equal intervals with a fixed sampling period, and stored in the buffer immediately after each trigger, forming a discrete sequence with equal time intervals.

[0039] Specifically, in the denoising unit, a 3-5 point window is first used to remove spikes from the discrete sequence by applying a moving average or median filter, thus eliminating occasional code skipping.

[0040] Specifically, in the conversion unit, the denoising sequence is saturated and limited according to preset reasonable upper and lower voltage limits, and values ​​exceeding the upper and lower limits are removed. Then, the voltage values ​​in the denoising sequence are converted into temperature values ​​through a preset conversion formula, which are used as the original temperature data in subsequent steps.

[0041] Specifically, the transfer function expression of the bandpass filtering algorithm is as follows: ; In the formula, s is the Laplace operator, and ζ BPω is the damping coefficient of the bandpass filter. BP,n The natural frequency of the bandpass filter. The transfer function of the bandpass filtering algorithm is given, and the frequency of the low-frequency interference signal in step S2 is based on ω. BP,n Sure, The bandwidth of the low-frequency interference signal is determined by the debugging parameters.

[0042] Specifically, the transfer function expression of the low-pass filtering algorithm is as follows: ; In the formula, ζ LP ω is the damping coefficient of the low-pass filter. LP,n This is the inherent frequency of the low-pass filter. This is the transfer function of the low-pass filtering algorithm. and Used for debugging and filtering out high-frequency noise.

[0043] Specifically, the transfer function expression for the final temperature signal is: .

[0044] In the formula, Y(s) and U(s) are the Laplace transform expressions of the filtered output signal and the filtered input T (i.e., the original temperature signal), respectively.

[0045] Specifically, the low-pass filter module includes: The transformation unit is used to perform Z-transformation on the transfer function F(s) of the final temperature signal to obtain F(z). The inverse Z-transformation unit is used to perform the inverse Z-transformation on F(z) to obtain the final discrete-time expression.

[0046] Specifically, the transfer function of the final temperature signal is expressed as a discrete form F(z) through the Z-transform, which facilitates its application. This is achieved by employing a zero-order hold. The conversion is performed using the following formula: ; In the formula, Let be the signal acquisition period. Therefore, the formula exists: ; F(z) is a fractional polynomial consisting of the variable z: ; By performing an inverse Z-transform on F(z), the final discrete-time expression is obtained: ; In the formula, the coefficients and That is The inevitable result of the transformation is... , , , and Composition, and yes The intervals are discrete time points. Therefore, the above formula can be written into a computer program in code form.

[0047] This invention also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements any of the filtering methods described above for rapid thermal processing.

[0048] The present invention also provides an electronic device on which the filtering method for a rapid thermal processing process according to the foregoing embodiments is run. The electronic device of the present invention includes: one or more processors; a storage device for storing one or more computer programs; when the one or more computer programs are executed by the one or more processors, the one or more processors implement the filtering method for a rapid thermal processing process provided by the present invention. References are made below. Figure 4 This illustrates a schematic diagram of the structure of a computer system 800 suitable for implementing embodiments of the present invention in an electronic device. For example... Figure 4 As shown, the computer system 800 includes a central processing unit (CPU) 801, which can perform various appropriate actions and processes based on a computer program stored in a read-only memory (ROM) 802 or a computer program loaded from a storage section 808 into a random access memory (RAM) 803. The RAM 803 also stores various computer programs and data required for the operation of the computer system 800. The CPU 801, ROM 802, and RAM 803 are interconnected via a bus 804. An input / output (I / O) interface 805 is also connected to the bus 804.

[0049] The following components are connected to I / O interface 805: an input section 806 including a keyboard, mouse, etc.; an output section 807 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 808 including a hard disk, etc.; and a communication section 809 including a network interface card such as a LAN card, modem, etc. The communication section 809 performs communication processing via a network such as the Internet. A drive 810 is also connected to I / O interface 805 as needed. A removable medium 811, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on drive 810 as needed so that computer programs read from it can be installed into storage section 808 as needed.

[0050] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0051] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can occur depending on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A filtering method for rapid heat treatment processes, characterized in that, Includes the following steps: S1: Acquire the raw temperature signal; S2: A low-frequency interference signal is obtained by applying a bandpass filtering algorithm to the original temperature signal; S3: Process the original temperature signal based on the low-frequency interference signal to obtain a de-interference signal; S4: The final temperature signal is obtained by applying a low-pass filtering algorithm to the interference removal signal.

2. The filtering method for a rapid heat treatment process according to claim 1, characterized in that, S1 includes the following steps: S11: Perform continuous sampling according to the sampling period to obtain a discrete sequence; S12: Denoise the discrete sequence to obtain a denoised sequence; S13: Convert the units of the limited sequence to obtain the original temperature signal.

3. The filtering method for a rapid heat treatment process according to claim 1, characterized in that, The transfer function expression of the bandpass filtering algorithm is: ； In the formula, s is the Laplace operator, and ζ BP ω is the damping coefficient of the bandpass filter. BP,n This is the inherent frequency of the bandpass filter.

4. The filtering method for a rapid heat treatment process according to claim 1, characterized in that, In S3, the low-frequency interference signal is subtracted from the original temperature signal to obtain the de-interference signal.

5. A filtering method for a rapid heat treatment process according to claim 3, characterized in that, The transfer function expression of the low-pass filtering algorithm is: ； In the formula, ζ LP ω is the damping coefficient of the low-pass filter. LP,n This is the inherent frequency of the low-pass filter.

6. A filtering method for a rapid heat treatment process according to claim 5, characterized in that, The transfer function expression of the final temperature signal relative to the original temperature signal is: 。 7. A filtering method for a rapid heat treatment process according to claim 5, characterized in that, S4 includes the following steps: S41: Perform Z-transformation on the transfer function F(s) of the final temperature signal to obtain F(z); S42: Perform an inverse Z-transform on F(z) to obtain the final discrete-time expression.

8. A filter for a rapid heat treatment process, employing the filtering method for a rapid heat treatment process according to any one of claims 1-7, characterized in that, include: The data acquisition module is used to acquire the raw temperature signal; A bandpass filter module is used to apply a bandpass filter algorithm to the original temperature signal to obtain a low-frequency interference signal; The interference removal module is used to process the original temperature signal based on the low-frequency interference signal to obtain the interference removal signal; The low-pass filter module is used to apply a low-pass filter algorithm to the interference removal signal to obtain the final temperature signal.

9. An electronic device, characterized in that, include: One or more processors; Storage device for storing one or more computer programs; When the one or more computer programs are executed by the one or more processors, the one or more processors implement a filtering method for a rapid thermal processing process as described in any one of claims 1-7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements a filtering method for a rapid thermal processing process as described in any one of claims 1-7.

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