An anti-interference detection method for wafer temperature measurement system

Abstract

The present invention discloses an anti-interference detection method for a wafer temperature measurement system, which belongs to the field of semiconductor rapid thermal processing technology. The anti-interference detection method includes the following steps: a temperature sensor detects the temperature of a wafer, an original sample value obtained by the temperature sensor is first subjected to noise interference filtering processing by a temperature detector, and then the processed data is sent to a temperature controller as the detected temperature of the wafer. The temperature controller compares the detected temperature with the formula set temperature, and then adjusts the output power to form a closed-loop control; the noise interference filtering processing includes: the original sample value obtained by the temperature sensor is first subjected to data verification, the verified data is subjected to de-extreme value filtering, and then a noise estimation algorithm is used to perform real-time estimation and identify steady-state noise. The steady-state noise is removed to obtain the actual temperature of the wafer. The present invention adopts de-extreme value filtering in terms of random disturbance and adopts a noise estimation method in terms of stable sinusoidal disturbance, significantly improving the accuracy of temperature measurement.

Description

Technical Field

[0001] The present invention belongs to the technical field of semiconductor rapid thermal processing technology, and in particular relates to an anti-interference detection method for a wafer temperature measurement system. Background Art

[0002] Rapid Thermal Processing (RTP) is an advanced, single-wafer heat treatment process, a key technology in semiconductor manufacturing that can alter the microstructure and properties of materials. During RTP, the wafer temperature is rapidly raised to the required process temperature and then rapidly cooled. Precise temperature control is crucial for the RTP process, and accurate wafer temperature measurement has a decisive impact on temperature control and process yield.

[0003] Rapid thermal processing typically utilizes non-contact temperature measurement technology. Given the complex system structure of RTP equipment, electromagnetic interference, such as static electricity and radio frequency, can occur in the surrounding environment. Furthermore, there are the effects of magnetic levitation rotation and other mechanical disturbances in the system. These interferences can severely impact the temperature measurement system, leading to inaccurate temperature measurements and, consequently, suboptimal temperature control. Therefore, these interferences must be shielded and filtered to ensure that the temperature measurement system has strong anti-interference capabilities. Furthermore, because rapid thermal processing requires rapid temperature increases and decreases, real-time temperature anti-interference detection is essential. Existing solutions lack anti-interference design or are ineffective. Significant noise interference is present in the temperature data, making it difficult to filter out and impacting control effectiveness. Therefore, an effective anti-interference solution is needed. Summary of the Invention

[0004] Based on the technical problems existing in the prior art, the present invention provides an anti-interference detection method for a wafer temperature measurement system to solve the problems of obvious noise in the temperature data measured in existing semiconductor equipment, which affects the control effect, and effectively filters out interference and obtains accurate temperature data, thereby improving the accuracy of temperature control in semiconductor processes.

[0005] According to the technical solution of the present invention, the present invention provides an anti-interference detection method for a wafer temperature measurement system, wherein the wafer temperature measurement system adopted includes a temperature sensor for detecting the wafer temperature, the temperature sensor is sequentially connected to a temperature detector, a temperature controller, and a power controller, the temperature controller is connected to a host computer, and the power controller is connected to a wafer heating device of a semiconductor device;

[0006] The anti-interference detection method of the wafer temperature measurement system includes the following steps:

[0007] The temperature controller receives the recipe parameters set by the host computer and adjusts the output power of the power controller to control the heating power of the wafer heating device. The temperature sensor detects the temperature of the wafer. The raw sample value obtained by the temperature sensor is first processed by the temperature detector to remove noise interference and obtain the wafer detection temperature. The wafer detection temperature is then sent to the temperature controller. The temperature controller compares the wafer detection temperature with the recipe setting temperature and then adjusts the output power to form a closed-loop control.

[0008] Among them, the noise interference filtering process includes that the original sampling value obtained by the temperature sensor is first subjected to data verification to prevent data errors, the verified data is filtered out by de-extreme value filtering to remove possible random interference, and then the noise estimation algorithm is used to perform real-time estimation and identify steady-state noise. After removing the steady-state noise through real-time filtering, the wafer detection temperature is obtained.

[0009] Furthermore, the de-extreme value filtering is to use a cache array to simulate a queue to store the temperature measurement data obtained by the temperature sensor. The queue length is N. The calculation starts only after the queue is filled. The later data always replaces the earliest data in the queue to maintain the real-time nature of the data. The values ​​in the queue are arranged in order of size, and the middle value is taken as the benchmark T mid , according to the current formula heating rate or cooling rate, determine the theoretical maximum difference between two adjacent temperature values ​​err r , define T mid ±(a×err r ) is the de-extreme value judgment condition at the current moment. If the actual sampling value at the current moment exceeds the range of the de-extreme value judgment condition at the current moment, the temperature measurement data value at the current moment is refreshed according to the de-extreme value judgment condition at the current moment.

[0010] Furthermore, the noise estimation algorithm includes the following:

[0011] Define the residual Loss:

[0012] ,

[0013] Among them, T' i is the measured value after de-extreme filtering, TN i is the sinusoidal noise value, T i is the current predicted value of the system, M is the number of iterations;

[0014] ,

[0015] in, τ is the time constant of the system, K is the transfer coefficient, T i-1 is the predicted value of the system at the previous sampling moment;

[0016] TNi =A i sin(2πfT s +φ i ),

[0017] Where f is the system noise frequency, which is determined by the magnetic levitation rotation frequency; T s is the sampling time; A i is the amplitude of the sinusoidal noise at the current sampling moment; φ i is the sinusoidal noise phase angle at the current sampling moment;

[0018] Loss to A i and φ i Calculate the partial derivatives respectively and get the following iterative formula:

[0019] A i = A i-1 – b×sin(2πfT s +φ i-1 ),

[0020] φ i = φ i-1 – b×cos(2πfT s +φ i-1 ) ;

[0021] Among them, A i is the amplitude of the sinusoidal noise at the current sampling moment; A i-1 is the amplitude of the sinusoidal noise at the previous sampling moment; φ i is the sinusoidal noise phase angle at the current sampling moment; φ i-1 is the sinusoidal noise phase angle at the previous sampling moment; b is the sinusoidal noise estimation iteration update rate;

[0022] The optimization goal is to minimize Loss, so the sinusoidal noise value TN at the current sampling moment is obtained i .

[0023] Furthermore, the noise estimation algorithm further includes:

[0024] When secondary filtering is observed or the amplitude of the second harmonic is detected to be higher than the set threshold, the second harmonic filtering is turned on; the second harmonic filtering specifically includes the following:

[0025] Define the residual Loss' of the second harmonic filtering process:

[0026] ,

[0027] Among them, T'' i TNS is the measured value after removing the sinusoidal noise. i is the second harmonic noise value, T iis the current predicted value of the system, M is the number of iterations;

[0028] TNS i =A' i sin(2πf'T s +φ' i ),

[0029] Where f' is the second harmonic noise frequency, f'=2f, f is the system noise frequency; T s is the sampling time; A' i is the second harmonic noise amplitude at the current sampling moment; φ' i is the second harmonic noise phase angle at the current sampling moment;

[0030] Loss' to A' i and φ' i Calculate the partial derivatives respectively and get the following iterative formula:

[0031] A' i = A' i-1 – b'×sin(2πf'T s +φ' i-1 ),

[0032] φ' i = φ' i-1 – b'×cos(2πf'T s +φ' i-1 ) ;

[0033] Among them, A' i-1 is the second harmonic noise amplitude at the previous sampling moment; φ' i-1 is the second harmonic noise phase angle at the previous sampling moment; b' is the second harmonic estimation iteration update rate;

[0034] The optimization goal is to minimize Loss', so the second harmonic noise value TNS at the current sampling moment is obtained i .

[0035] Furthermore, a sensor control box is connected between the temperature sensor and the temperature detector; the temperature sensor and the sensor control box are connected via an optical fiber cable, and the sensor control box and the temperature detector are connected via a shielded twisted pair cable, and the shielding layer is grounded.

[0036] Furthermore, an interference suppressor is provided at a communication interface on the temperature detector for connecting with the sensor control box.

[0037] Furthermore, the temperature detector has an isolated regulated power supply with a filter circuit inside.

[0038] Furthermore, the temperature detector is arranged in a sealed shielding shell, and the temperature detector is well grounded through the shielding shell.

[0039] Compared with the prior art, the beneficial technical effects of the present invention are as follows:

[0040] 1. In the anti-interference detection method of the wafer temperature measurement system of the present invention, the main disturbances of the semiconductor device system on the temperature measurement results are divided into random disturbances and steady-state noise through analysis and research. De-extreme value filtering is used for random disturbances, and noise estimation is used for steady-state noise (stable sinusoidal disturbances). In this way, the original sampling values ​​of the temperature sensor are filtered out of noise interference, thereby improving the accuracy of wafer temperature measurement.

[0041] 2. In the anti-interference detection method of the wafer temperature measurement system of the present invention, a closed-loop controlled wafer temperature measurement system is adopted, which can automatically analyze and adjust the heating power according to the situation in real time, and then adjust the wafer heating / cooling rate, so that the change of wafer temperature better meets expectations and ultimately more accurately reaches the recipe setting temperature set by the host computer.

[0042] 3. The anti-interference detection method of the wafer temperature measurement system of the present invention also adopts a combination of hardware anti-interference and software anti-interference. The software anti-interference is to filter out noise interference from the original sampling value, and the hardware anti-interference is achieved by optimizing and improving the hardware of each device and the entire wafer temperature measurement system, thereby effectively suppressing the interference of electromagnetic fields, pulse noise signals and other aspects on the sampling value and data transmission process.

[0043] 4. The anti-interference detection method of the wafer temperature measurement system of the present invention significantly reduces the impact of disturbances on temperature data through multi-angle research and improvement, and has better real-time performance, thereby improving the temperature control accuracy and improving the yield and process quality of semiconductor processes with rapid thermal processing processes. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 It is a structural schematic diagram of the wafer temperature measurement system provided by the present invention.

[0045] Figure 2 This is a structural block diagram of a simplified wafer temperature measurement system provided by the present invention.

[0046] Figure 3 It is a flow chart of the method provided by the invention.

[0047] Description of reference numerals in the accompanying drawings:

[0048] 1. Temperature sensor; 2. Sensor control box; 3. Interference suppressor; 4. Temperature detector; 5. Temperature controller; 6. Host computer; 7. Power controller; 8. Wafer heating device; 9. Wafer. DETAILED DESCRIPTION

[0049] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0050] It should also be noted that, for ease of description, only the parts related to the invention are shown in the drawings. In the absence of conflict, the embodiments and features of the embodiments of the present invention may be combined with each other.

[0051] It should be noted that the concepts of "first" and "second" mentioned in the present invention are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0052] It should be noted that the modifications of "one" and "multiple" mentioned in the present invention are illustrative rather than restrictive. Those skilled in the art should understand that unless otherwise clearly indicated in the context, it should be understood as "one or more".

[0053] During the rapid thermal processing process in semiconductor manufacturing, accurate measurement of wafer temperature directly affects the temperature control effect, which in turn has a decisive impact on the process yield. Existing solutions do not have anti-interference design or the effect is poor. The temperature data contains significant noise and interference, which is difficult to filter out, affecting the temperature measurement and control effect. Research has found that due to the complexity of the process equipment, interference will be generated in the temperature measurement system. That is, the original sampling value = the actual wafer temperature value + random interference value + noise value, where the noise value further = sinusoidal noise value + high-order harmonic noise value. Generally, when the system is stable, the high-order harmonic noise value does not exist or can be ignored. When it is unstable, the high-order harmonic noise value will affect the temperature detection. The most influential high-order harmonic noise value is the second harmonic noise value.

[0054] See also Figures 1 to 3The anti-interference detection method for a wafer temperature measurement system provided by the present invention includes a temperature sensor 1 for detecting the temperature of a wafer 9 within a semiconductor device. The temperature sensor 1 is sequentially connected to a temperature detector 4, a temperature controller 5, and a power controller 7. The temperature controller 5 is connected to a host computer 6, and the power controller 7 is connected to a wafer heating device 8 within the semiconductor device. There are typically multiple temperature sensors 1, each monitoring the temperature at different locations on the wafer to ensure uniform heating of the wafer. For example, there may be a total of L temperature sensors.

[0055] During operation, the temperature controller receives the recipe parameters set by the host computer and automatically adjusts the output power of the power controller through a control algorithm to control the heating power of the wafer heating device (for example, the brightness of the lamp). The lamp shines on the wafer to increase the temperature of the wafer at the designed rate (or, by reducing the heating power / turning off the heating device, the wafer cools at the designed rate). The temperature sensor detects the temperature of the wafer. The raw sample value detected by the temperature sensor is first processed by the temperature detector to remove noise interference to obtain the wafer detection temperature, which is then sent to the temperature controller. The temperature controller compares the wafer detection temperature with the recipe setting temperature and then adaptively adjusts the output power to form a closed-loop control to achieve the wafer temperature change in a set manner, so that the change in wafer temperature better meets the expected and ultimately reaches the recipe setting temperature set by the host computer (i.e., the target temperature value set in the recipe). The anti-interference detection method in the wafer temperature measurement system of the present invention preferably adopts a combination of hardware anti-interference and software anti-interference; of course, in other embodiments, for example, only some of the structures / methods may be adopted.

[0056] In terms of hardware interference resistance, the wafer temperature measurement system of the present invention includes several temperature sensors (probes), a sensor control box, transmission cables, and a temperature detector. Compared to simpler solutions, the present invention further connects a sensor control box 2 between the temperature sensor 1 and the temperature detector 4. The temperature sensor 1 (probe) and the sensor control box 2 are connected by a fiber optic cable, which is resistant to electromagnetic interference. The sensor control box 2 outputs temperature measurement data, and the data is transmitted between the sensor control box 2 and the temperature detector 4 via a shielded twisted pair cable, with the shield layer grounded, which has excellent interference resistance. The shielded twisted pair cable, more specifically a shielded differential twisted pair cable, serves as the transmission cable. The communication interface on the temperature detector 4 that connects to the sensor control box 2 includes an interference suppressor 3 to suppress pulse noise and electrostatic interference that may be coupled to the interface. The temperature detector 4 also includes an isolated regulated power supply with a filter circuit to effectively filter out noise from the switching power supply input signal and shield against line-conducted interference. The temperature detector 4 is placed in a sealed shielding shell (of course, the shielding shell can allow the corresponding cables to pass through at the temperature detector interface), and the temperature detector 4 is well grounded through the shielding shell. For example, the signal ground of the temperature detector 4 is connected to the shielding shell (that is, the ground wire of the temperature detector is connected to the shielding shell). The shielding shell is well grounded, which can effectively suppress the interference of electromagnetic field radiation in space and improve the anti-interference ability.

[0057] Digital filters are used to mitigate software interference. Temperature measurement data contains both random interference and steady-state noise, and the digital filter design must filter out both simultaneously. Because temperature sensors are installed in different locations and are subject to varying degrees of external interference, each temperature sensor requires a separate digital filter. The temperature sensor data first undergoes a data check (e.g., CRC check, cumulative sum check, etc.) to prevent data errors caused by interference. The checked data is then filtered to eliminate possible random interference. Steady-state noise primarily arises from periodic steady-state noise caused by the rotation of the magnetic levitation system. Analysis has shown that this steady-state noise is sinusoidal noise with the same frequency as the magnetic levitation system and its higher harmonics. A noise estimation algorithm based on gradient descent is used to estimate and identify the steady-state noise in real time. Real-time filtering is then performed to further remove the identified steady-state noise from the current data value, ultimately resulting in the wafer measurement temperature.

[0058] More specifically, the de-extreme value filtering uses a cache array to simulate a queue to store the temperature measurement data obtained by the temperature sensor. The queue length is N, which is a positive integer selected according to the actual situation. The calculation starts only after the queue is filled. The later data always replaces the earliest data in the queue to maintain the real-time nature of the data. The values ​​in the queue (array) are arranged in order of size (for example, from small to large), and the middle value is taken as the benchmark Tmid The theoretical maximum difference between two adjacent temperature values ​​err is determined based on the current formula's heating rate or cooling rate. r , take a times of the theoretical maximum difference as the amplitude limit (theoretically a=(N+1)÷2, in actual use a certain amplification margin is required to prevent false triggering, that is, in actual use a=(N+1)÷2×c can be taken, c is an empirical parameter determined based on actual testing, c≥1), that is, define T mid ±(a×err r ) is the de-extreme value judgment condition at the current moment. If the actual sampling value at the current moment exceeds this range, the temperature measurement data value at the current moment is refreshed according to the de-extreme value judgment condition at the current moment (the actual sampling value at the current moment is replaced by the theoretical extreme value at the current moment).

[0059] For example, in the heating process, if a newly acquired actual sampling value is greater than the T value of the previous N data, mid +(a×err r ), then the newly acquired actual sampling value is considered to be incorrect and replaced with the T of the previous N data. mid +(a×err r ); if the new actual sampling value is less than or equal to the de-extreme value judgment condition value of the previous N data, it remains unchanged; before or after the newly acquired actual sampling value enters the queue (in short, before the following de-extreme value judgment condition is calculated), delete the earliest acquired data in the queue (or replace the earliest acquired data with the new data), so that when the de-extreme value judgment condition is calculated, the cache array simulation queue always contains a total of N data of the previous N sampling moments; then calculate the T of the current N data mid +(a×err r ), as the next actual sampling value de-extreme judgment condition, and so on. The cooling process is similar, the de-extreme judgment condition is T mid -(a×err r ). In this way, the random interference value T is removed by de-extreme filtering. random As a supplementary explanation, the N temperature measurement data at the initial stage of heating / cooling are the original sampling values, and then the filtering operation process actually begins. The subsequent temperature measurement data are the sampling values ​​that are judged to meet the conditions or refreshed and replaced in the above method; the "size" in "arranging the values ​​in the queue in order of size" refers to the corresponding temperature values ​​in the temperature measurement data; the temperature measurement data also corresponds to the sampling time or sequence data of the data, and the "adjacent" in "determining the theoretical maximum difference between two adjacent temperature values" refers to the sampling times that are adjacent in sequence.

[0060] In addition, the temperature control in rapid thermal processing includes the heating process, the cooling process, and the stable or soak stage after the temperature reaches the set value. The ideal stable stage is that the temperature remains unchanged without heating or cooling. The de-extreme value judgment condition of this stable stage can adopt a fixed value obtained based on experience, or still use the above calculation method, where the theoretical maximum difference err r That is, in response to temperature fluctuations, values ​​can be taken based on experience or process requirements, and it is necessary to ensure that the de-extreme value judgment condition is within the normal range determined based on experience.

[0061] The noise estimation algorithm includes the following contents.

[0062] In this invention, the gradient descent method is used to perform noise estimation, and the residual Loss is defined (residual in mathematical statistics refers to the difference between the actual observed value and the estimated value (fitted value)). The residual is used to evaluate the prediction model. The smaller the total residual, the more accurate the prediction.

[0063] ,

[0064] The optimization goal is to minimize the error between the measured value after removing the sinusoidal noise and the system predicted value.

[0065] Among them, T' i is the measured value after de-extreme filtering, TN i is the sinusoidal noise value (the estimated value of the sinusoidal noise at the current sampling moment, or the estimated value of the steady-state noise at the current sampling moment), T i is the current predicted value of the system (the wafer temperature value at the current sampling moment estimated and determined by the equipment system, in other words, the wafer temperature predicted value), and M is the number of iterations;

[0066] ,

[0067] in, τ is the time constant of the system, which is a fixed constant and is related to the control period and the delay inertia of the entire system; K is the transfer coefficient, which is a constant and is determined by the system characteristics; T i-1 is the predicted value of the system at the previous sampling moment;

[0068] TN i =A i sin(2πfT s +φ i ),

[0069] Where f is the system noise frequency, which is determined by the magnetic levitation rotation frequency; T s is the sampling time; A i is the amplitude of the sinusoidal noise at the current sampling moment, φ iis the sinusoidal noise phase angle at the current sampling moment.

[0070] Loss to A i and φ i Calculate the partial derivatives respectively and get the following iterative formula:

[0071] A i = A i-1 – b×sin(2πfT s +φ i-1 ),

[0072] φ i = φ i-1 – b×cos(2πfT s +φ i-1 ) ;

[0073] Among them, A i is the amplitude of the sinusoidal noise at the current sampling moment; A i-1 is the amplitude of the sinusoidal noise at the previous sampling moment; φ i is the sinusoidal noise phase angle at the current sampling moment; φ i-1 is the sinusoidal noise phase angle at the previous sampling moment; b is the sinusoidal noise estimation iterative update rate, which is a constant.

[0074] The optimization goal is to minimize the Loss, that is, the obtained A i and φ i Substitute the above formula to get the expression of Loss, and the optimization goal is to minimize it. In this way, the sinusoidal noise value TN at the current sampling moment can be obtained i , which can then be removed by real-time filtering. i It changes continuously in real time. By iterating the above formula, it will gradually approach the real TN i For each point, the current TN can be estimated based on the value of the previous moment. i , each calculation is a noise estimation.

[0075] When the system is stable, there is usually only a stable sinusoidal noise with the same speed as the magnetic levitation speed, that is, the aforementioned sinusoidal noise value TN i , whose frequency is f. However, when the interference intensity is large and the system is unstable, the amplitude of this noise will be large, resulting in the generation of higher harmonics. Usually, the amplitude (intensity) of the second harmonic will be relatively high, and the other higher harmonics will have little impact. Therefore, it is optional to filter out the second harmonic, the frequency of which is 2f. Further using the same form as above (the difference is that f in the formula is replaced by f', f'=2f) to estimate the noise, we can obtain the second harmonic noise value TNS i .

[0076] More specifically, the processing method can be to set a high-order harmonic filtering switch. When the second harmonic is observed in the temperature detection data, the second harmonic filtering can be turned on; or when the amplitude of the second harmonic is detected to be higher than a certain set threshold, the second harmonic filtering can be turned on. The second harmonic filtering specifically includes the following.

[0077] The optimization goal is to minimize the error between the measured value after further removing the second harmonic noise and the system predicted value.

[0078] ,

[0079] Among them, Loss' is the residual of the second harmonic filtering process, in other words, it is the sum of the errors between the measured value after further removing the second harmonic noise and the system prediction value, T'' is the measured value after removing the sinusoidal noise, TNS i is the second harmonic noise value, T i is the current predicted value of the system; M is the number of iterations;

[0080] TNS i =A' i sin(2πf'T s +φ' i ),

[0081] Where f' is the second harmonic noise frequency, f'=2f, f is the system noise frequency; T s is the sampling time;

[0082] Loss' to A' i and φ' i Calculate the partial derivatives respectively and get the following iterative formula:

[0083] A' i = A' i-1 – b'×sin(2πf'T s +φ' i-1 ),

[0084] φ' i = φ' i-1 – b'×cos(2πf'T s +φ' i-1 ) ;

[0085] Among them, A' i is the second harmonic noise amplitude at the current sampling moment; A' i-1 is the second harmonic noise amplitude at the previous sampling moment; φ' i is the second harmonic noise phase angle at the current sampling moment; φ' i-1 is the second harmonic noise phase angle at the previous sampling moment; b' is the second harmonic estimation iteration update rate, which is a constant.

[0086] The optimization goal is to minimize Loss', so the second harmonic noise value TNS at the current sampling moment is obtained i Then, the second harmonic noise value TNS can be reduced to i Remove.

[0087] As a supplementary explanation for easier understanding, the temperature detection in the present invention undergoes the following changes: the temperature sensor measures the original acquisition value T measure , original collection value T measure After de-extreme filtering, random interference value T is removed. random , get the measured value T' after de-extreme filtering, and then remove the noise value (remove the sinusoidal noise value TN i , get T'', and then further remove the second harmonic noise value TNS according to the situation i ), after such processing, the wafer detection temperature is obtained. The wafer detection temperature is the wafer temperature measured using the anti-interference detection method of the present invention, which is closer to the actual temperature of the wafer than the existing technology.

[0088] It should be noted that in a semiconductor device, multiple temperature sensors are usually installed to measure the temperature of multiple different positions of the wafer respectively. The specific arrangement and comprehensive analysis of the data from multiple temperature sensors can follow the existing technical solutions and are not the focus of improvement of the present invention, so they will not be elaborated here.

[0089] In summary, the present invention adopts de-extreme value filtering for random disturbances and adopts noise estimation method for stable sinusoidal disturbances. After the original sampling values ​​of the temperature sensor are subjected to noise interference filtering, the influence of the disturbance on the temperature data is significantly reduced, the accuracy of temperature measurement is improved, and the temperature control accuracy is thereby improved, thereby improving the quality of semiconductor processes.

[0090] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. An anti-interference detection method for a wafer temperature measurement system, characterized in that: The wafer temperature measurement system used includes a temperature sensor for detecting the wafer temperature, the temperature sensor is connected in sequence to a temperature detector, a temperature controller and a power controller, the temperature controller is connected to a host computer, and the power controller is connected to a wafer heating device of a semiconductor device; The anti-interference detection method of the wafer temperature measurement system includes the following steps: The temperature controller receives the recipe parameters set by the host computer and adjusts the output power of the power controller to control the heating power of the wafer heating device. The temperature sensor detects the temperature of the wafer. The raw sample value obtained by the temperature sensor is first processed by the temperature detector to remove noise interference and obtain the wafer detection temperature. The wafer detection temperature is then sent to the temperature controller. The temperature controller compares the wafer detection temperature with the recipe setting temperature and then adjusts the output power to form a closed-loop control. The noise interference filtering process includes: the original sample value obtained by the temperature sensor is first subjected to data verification to prevent data errors, the verified data is filtered out by de-extreme value filtering to remove possible random interference, and then a noise estimation algorithm is used to estimate and identify steady-state noise in real time. After the steady-state noise is removed by real-time filtering, the wafer detection temperature is obtained; The noise estimation algorithm includes the following: Define the residual Loss: ， Among them, T' i is the measured value after de-extreme filtering, TN i is the sinusoidal noise value, T i is the current predicted value of the system, M is the number of iterations; ， in, τ is the time constant of the system, K is the transfer coefficient, T i-1 is the predicted value of the system at the previous sampling moment; TN i =A i sin(2πfT s +φ i ), Where f is the system noise frequency, which is determined by the magnetic levitation rotation frequency; T s is the sampling time; A i is the amplitude of the sinusoidal noise at the current sampling moment; φ i is the sinusoidal noise phase angle at the current sampling moment; Loss to A i and φ i Calculate the partial derivatives respectively and get the following iterative formula: A i = A i-1 – b×sin(2πfT s +φ i-1 ), f i = φ i-1 – b×cos(2πfT s +φ i-1 ); Among them, A i is the amplitude of the sinusoidal noise at the current sampling moment; A i-1 is the amplitude of the sinusoidal noise at the previous sampling moment; φ i is the sinusoidal noise phase angle at the current sampling moment; φ i-1 is the sinusoidal noise phase angle at the previous sampling moment; b is the sinusoidal noise estimation iteration update rate; The optimization goal is to minimize Loss, so the sinusoidal noise value TN at the current sampling moment is obtained i .

2. The anti-interference detection method of the wafer temperature measurement system according to claim 1, characterized in that: The de-extreme value filtering is to use a cache array to simulate a queue to store the temperature measurement data obtained by the temperature sensor. The queue length is N. The calculation starts after the queue is filled. The later data always replaces the earliest data in the queue to maintain the real-time nature of the data. The values ​​in the queue are arranged in order of size and the middle value is taken as the benchmark T mid , according to the current formula heating rate or cooling rate, determine the theoretical maximum difference between two adjacent temperature values ​​err r , define T mid ±(a×err r ) is the de-extreme value judgment condition at the current moment. If the actual sampling value at the current moment exceeds the range of the de-extreme value judgment condition at the current moment, the temperature measurement data value at the current moment is refreshed according to the de-extreme value judgment condition at the current moment.

3. The anti-interference detection method of the wafer temperature measurement system according to claim 1, characterized in that: The noise estimation algorithm further includes: When secondary filtering is observed or the amplitude of the second harmonic is detected to be higher than the set threshold, the second harmonic filtering is turned on; the second harmonic filtering specifically includes the following: Define the residual Loss' of the second harmonic filtering process: ， Among them, T'' i TNS is the measured value after removing the sinusoidal noise. i is the second harmonic noise value, T i is the current predicted value of the system, M is the number of iterations; TNS i =A' i sin(2πf'T s +φ' i ), Where, f' is the second harmonic noise frequency, f'=2f, f is the system noise frequency; T s is the sampling time; A' i is the second harmonic noise amplitude at the current sampling moment; φ' i is the second harmonic noise phase angle at the current sampling moment; Loss' to A' i and φ' i Calculate the partial derivatives respectively and get the following iterative formula: A' i = A' i-1 – b'×sin(2πf'T s +φ' i-1 ), f' i = φ' i-1 – b'×cos(2πf'T s +φ' i-1 ); Among them, A' i-1 is the second harmonic noise amplitude at the previous sampling moment; φ' i-1 is the second harmonic noise phase angle at the previous sampling moment; b' is the second harmonic estimation iteration update rate; The optimization goal is to minimize Loss', so the second harmonic noise value TNS at the current sampling moment is obtained i .

4. The anti-interference detection method for a wafer temperature measurement system according to any one of claims 1 to 3, characterized in that: A sensor control box is also connected between the temperature sensor and the temperature detector; the temperature sensor and the sensor control box are connected via an optical fiber cable, and the sensor control box and the temperature detector are connected via a shielded twisted pair cable, with the shielding layer being grounded.

5. The anti-interference detection method of the wafer temperature measurement system according to claim 4, characterized in that: The temperature detector is provided with an interference suppressor at the communication interface for connecting with the sensor control box.

6. The anti-interference detection method of the wafer temperature measurement system according to claim 4, characterized in that: The temperature detector has an isolated regulated power supply with a filtering circuit inside.

7. The anti-interference detection method of the wafer temperature measurement system according to claim 4, characterized in that: The temperature detector is arranged in a sealed shielding shell, and the temperature detector is well grounded through the shielding shell.

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