Temperature measurement method, system, in-situ measurement device for semiconductor furnace tube and related products

Abstract

The application provides a temperature measurement method and system for a semiconductor furnace tube, an in-situ measurement device and related products, and relates to the technical field of semiconductor detection. The application synchronously samples and photoelectrically converts reflected light corresponding to two preset wave bands, and pre-weakens the influence of front-end temperature drift on temperature measurement results in the signal acquisition stage based on the feedforward compensation of the physical characteristics of semiconductor devices. The application collects the temperature at different preset positions inside the in-situ measurement device through multiple temperature sensors, predicts the target temperature parameter in combination with a pre-constructed thermal path model, identifies the current temperature change stage, and determines the current compensation amount according to the compensation coefficient library corresponding to different temperature intervals and different change stages, so as to more accurately represent the real thermal state of the key devices inside the device, dynamically compensate for temperature drift, and improve the accuracy, stability and adaptability to complex thermal environment changes of the wafer surface temperature measurement in the semiconductor furnace tube.

Description

Technical Field

[0001] This application relates to the field of semiconductor testing technology, and in particular to a method, system, in-situ measuring device, and related products for measuring the temperature of a semiconductor furnace tube. Background Technology

[0002] With the continuous development of semiconductor manufacturing processes, especially in semiconductor furnace tube processes such as diffusion, annealing, oxidation, and epitaxy, higher requirements are placed on the accuracy, real-time performance, and stability of wafer surface temperature measurement. The internal temperature of the semiconductor furnace tube directly affects the quality of thin film growth, doping uniformity, stress distribution, and device performance. Therefore, using a dual-color thermometer for in-situ, non-contact temperature measurement of the wafer surface inside the furnace tube has become an important technical method.

[0003] Dual-color thermometers are based on the principle of thermal radiation ratio measurement. They collect the radiation intensity of the same target in two independent narrow-band spectral bands, calculate the ratio, and invert the temperature. Compared to single-color thermometers, dual-color thermometers are less sensitive to changes in wafer surface emissivity (such as different film layers, roughness, and oxidation levels), and can partially eliminate signal attenuation caused by factors such as optical window deposition and atmospheric particle scattering in the optical path. Therefore, they are gradually being introduced into in-situ wafer temperature monitoring in semiconductor furnace tubes.

[0004] However, the application scenarios of semiconductor furnace tubes differ significantly from those of traditional high-temperature industrial measurements. Semiconductor furnace tubes are typically characterized by high temperatures, confined cavities, strong and continuous thermal radiation, concentrated local heat sources, and complex internal thermal coupling. During long-term operation, the thermometer is usually installed outside the furnace opening or process chamber, observing the internal wafers through a quartz or sapphire window. Thermal radiation from the furnace tube is conducted to the thermometer's interior through the window and mechanical structure. Simultaneously, significant non-uniform temperature rises occur in areas such as the equipment chassis near the heat source and in localized power devices on the circuit board. This results in critical components within the thermometer, such as optical elements, infrared detectors, and preamplifiers, being placed in a complex temperature gradient field. This thermal environment can cause detector responsivity drift, dark current variations, amplifier gain and bias point drift, and even filter center wavelength shifts, ultimately leading to systematic deviations in temperature measurements. Particularly in semiconductor furnace tube processes, significant temperature rises often occur near the furnace opening, the chassis near the heat source, and in localized areas of the circuit board, creating large temperature gradients at different locations within the temperature measuring device, thus exacerbating measurement errors.

[0005] In traditional technologies, to reduce the impact of ambient temperature changes on the measurement results of dual-color thermometers, the ambient temperature is typically acquired using a temperature sensor located at a single position inside the enclosure, and the measurement results are compensated based on this single-point temperature. This approach is simple in structure and easy to implement, and can provide some compensation when the ambient temperature changes slowly and the internal temperature distribution of the device is relatively uniform. However, in semiconductor furnace tube scenarios, single-point compensation cannot accurately reflect the true thermal state of key components such as detector junction temperature, amplifier temperature, and optical element temperature. It also struggles to characterize the differences in dynamic nonlinear drift of various components during heating, cooling, and process cycles. Consequently, it is prone to inaccurate compensation, which in turn affects the temperature measurement accuracy and stability of the semiconductor furnace tube. Summary of the Invention

[0006] The purpose of this application is to provide a method, system, in-situ measurement device and related products for measuring the temperature of semiconductor furnace tubes, so as to overcome the defects of traditional single-point compensation methods in semiconductor furnace tube scenarios, which are prone to inaccurate compensation and thus affect the temperature measurement accuracy and stability of semiconductor furnace tubes.

[0007] In a first aspect, this application proposes a method for measuring the temperature of a semiconductor furnace tube, applicable to in-situ measurement devices, the method comprising: The digital voltage signal and temperature dataset are acquired. The digital voltage signal is obtained by synchronously sampling and photoelectric conversion of two reflected lights formed by two preset wavelengths of light irradiating the wafer surface inside the furnace tube, and then performing feedforward compensation based on the physical characteristics of the semiconductor device. The temperature dataset is acquired by multiple temperature sensors at different preset locations inside the in-situ measurement device. The original measured temperature is calculated based on the digital voltage signal; Based on the temperature dataset and the pre-built thermal path model, predict the target temperature parameters and identify the current temperature change stage; Based on the target temperature parameter and the current temperature change stage, the current compensation amount is confirmed from the preset compensation coefficient library, which is established during pre-calibration for different temperature ranges and different change stages. The original measured temperature is compensated based on the current compensation amount to obtain the compensated output temperature.

[0008] In one embodiment, the in-situ measurement device includes a data acquisition module disposed within the housing. The data acquisition module includes a detector and a signal conditioning unit disposed on a circuit board. The signal conditioning unit includes a preamplifier and a reference power supply. The temperature dataset includes the detector temperature corresponding to the detector, the analog front-end temperature corresponding to the signal conditioning unit, and the ambient reference temperature corresponding to the location of the housing away from the heat source. Methods for obtaining digital voltage signals by feedforward compensation of two reflected lights that have undergone synchronous sampling and photoelectric conversion based on the physical characteristics of semiconductor devices include: The two reflected lights are converted into photoelectric signals to obtain detector output currents corresponding to two preset wavelength bands; Based on the current detector temperature and preset bias voltage, the dark current of the detector output current is compensated according to the pre-calibrated dark current and temperature characteristics to obtain the real photocurrent corresponding to the two preset bands. Based on the currently acquired detector temperature, the detector's responsivity in two preset bands is corrected according to the pre-calibrated responsivity temperature coefficient, and the actual photocurrent is corrected based on the corrected responsivity to obtain the corrected electrical signals corresponding to the two preset bands. Based on the currently acquired simulated front-end temperature, according to the pre-calibrated gain-temperature drift relationship and input bias current-temperature drift relationship, temperature drift compensation is performed on the gain and input bias current of the preamplifier to correct the voltage signal corresponding to the corrected electrical signal. The corrected voltage signal is converted from analog to digital to obtain digital voltage signals corresponding to two preset bands. In one embodiment, the temperature dataset also includes the circuit board temperature corresponding to the circuit board; Methods for pre-building heat path models include: During the pre-calibration stage, the in-situ measuring device is placed in a temperature-controlled environment test chamber, and a temperature excitation is applied to the in-situ measuring device. The temperature excitation includes at least one of step temperature change, ramp temperature change, sinusoidal temperature change, and local heating. Under the temperature excitation, temperature data output by multiple temperature sensors located at preset positions inside the in-situ measuring device are simultaneously sampled; each preset position corresponds to one or more temperature measurement points. Based on the temperature data, a dynamic relationship of thermal coupling between multiple temperature measuring points and detectors is established according to thermal network theory, and its expression is as follows:

[0009] in, For detector temperature, For the thermal time constant of the detector, For environmental reference temperature, To simulate front-end temperature, The temperature corresponding to the i-th circuit board, , and For coupling coefficients, For external heat flow input, The coupling coefficient corresponding to the external heat flow input. For bias terms; The model parameters in the thermally coupled dynamic relationship are extracted using a system identification method to obtain the thermal path model.

[0010] In one embodiment, the target temperature parameters include a predicted temperature and a temperature change slope; the temperature change phase includes a heating phase, a cooling phase, and a constant temperature phase. The step of predicting target temperature parameters and identifying the current temperature change stage based on the temperature dataset and a pre-built thermal path model includes: The temperature dataset collected at the current moment is input into the thermal path model to obtain the predicted temperature of the target object at the next moment; the target object includes at least one of the following: a detector, a signal conditioning unit, a part of the enclosure away from the heat source, and a circuit board; The predicted temperatures corresponding to the most recent multiple sampling times of each target object are obtained, and each predicted temperature is fitted to obtain the temperature change slope corresponding to each target object. If the slope of the temperature change of any target object is greater than the preset heating threshold, the temperature change stage corresponding to that target object is considered to be the heating stage. If the slope of the temperature change of any target object is less than the preset cooling threshold, the temperature change stage corresponding to that target object is considered to be the cooling stage. If the slope of the temperature change of any target object is between the preset heating threshold and the preset cooling threshold, the temperature change stage corresponding to the target object is considered to be the isothermal stage. When there are multiple target objects, a voting process is performed based on the temperature change stages corresponding to the multiple target objects, and the current temperature change stage is determined according to the voting results. In one embodiment, determining the current compensation amount from a preset compensation coefficient library based on the target temperature parameter and the current temperature change stage includes: Based on the predicted temperature, determine the two adjacent temperature nodes where the predicted temperature is located; Based on the current stage of temperature change, the corresponding set of compensation coefficients is retrieved from the preset compensation coefficient library; Obtain the compensation values ​​corresponding to the two adjacent temperature nodes from the set of compensation coefficients; The compensation values ​​corresponding to the two adjacent temperature nodes are interpolated to obtain the current compensation amount. In one embodiment, calculating the original measured temperature based on the digital voltage signal includes: Calculate the corresponding two-color ratio based on the two digital voltage signals at different sampling times; Based on the pre-stored correspondence between temperature and ratio, calculate the instantaneous temperature value corresponding to each of the two-color ratios; The instantaneous temperature values ​​are sorted according to the sampling time to obtain the original measured temperature.

[0011] In one embodiment, the temperature change phase includes a constant temperature phase; the method further includes: If the current temperature change phase is a constant temperature phase and the duration exceeds the preset time, obtain the external reference temperature; The compensation residual is determined based on the compensated output temperature and the external reference temperature; Based on the compensation residual, the compensation coefficients in the corresponding temperature range in the compensation coefficient library are corrected.

[0012] In one embodiment, the method further includes: Anomaly detection is performed on the collected temperature dataset; When the system detects that any temperature in the temperature dataset exceeds a preset upper limit, the temperature difference between any two temperature measuring points exceeds a preset threshold, the slope of the temperature change at any temperature measuring point exceeds a preset threshold, or the reading of any temperature sensor remains unchanged for a long time or deviates from the preset range, the system determines it to be abnormal and outputs an alarm message.

[0013] Secondly, this application proposes a temperature measurement system for a semiconductor furnace tube, which is installed within an in-situ measuring device. The system includes: The acquisition module is used to acquire digital voltage signals and temperature datasets; wherein, the digital voltage signals are obtained by synchronously sampling and photoelectric conversion of two reflected lights formed by two preset wavelength light signals irradiating the wafer surface inside the furnace tube, and by feedforward compensation based on the physical characteristics of semiconductor devices; the temperature datasets are acquired by multiple temperature sensors at different preset locations inside the in-situ measurement device. The processing module is used to calculate the original measured temperature based on the digital voltage signal; predict the target temperature parameter based on the temperature dataset and a pre-built thermal path model, and identify the current temperature change stage; confirm the current compensation amount from a preset compensation coefficient library based on the target temperature parameter and the current temperature change stage, the compensation coefficient library being established during pre-calibration for different temperature ranges and different change stages; and compensate the original measured temperature based on the current compensation amount to obtain the compensated output temperature.

[0014] Thirdly, this application proposes an in-situ measurement device, the device comprising: The light source module is used to generate measurement light, separate the measurement light into two preset wavelength bands, and irradiate the wafer surface inside the furnace tube. The acquisition module is used to simultaneously sample two reflected lights generated on the wafer surface based on the optical signal, perform photoelectric conversion on them, and then perform feedforward compensation based on the physical characteristics of the semiconductor device to obtain a digital voltage signal. The measurement module includes multiple temperature sensors located at different preset positions inside the in-situ measurement device, used to collect temperature data sets; The temperature measurement system for the semiconductor furnace tube as described in the second aspect is used to calculate the original measured temperature based on the digital voltage signal; predict the target temperature parameter based on the temperature dataset and a pre-built thermal path model, and identify the current temperature change stage; confirm the current compensation amount from a preset compensation coefficient library based on the target temperature parameter and the current temperature change stage, the compensation coefficient library being established during pre-calibration for different temperature ranges and different change stages; and compensate the original measured temperature based on the current compensation amount to obtain the compensated output temperature.

[0015] In one embodiment, the in-situ measuring device is partially housed within the housing; The acquisition module includes a detector and a signal conditioning unit mounted on a circuit board. The signal conditioning unit includes a preamplifier and a reference power supply. The preset location includes at least one of the following: the detector housing, near the preamplifier and the reference power supply, away from the heat source in the housing, and on the circuit board.

[0016] Fourthly, this application also provides a computer device. The computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the method steps of the first aspect.

[0017] Fifthly, this application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program thereon, which, when executed by a processor, implements the method steps of the first aspect.

[0018] The aforementioned temperature measurement methods, systems, in-situ measurement devices, and related products for semiconductor furnace tubes have at least the following advantages: This application achieves simultaneous sampling and photoelectric conversion of reflected light corresponding to two preset wavelength bands, combined with feedforward compensation based on the physical characteristics of semiconductor devices. This enables the reduction of the impact of temperature drift of the detector and front-end circuit on the temperature measurement results during the signal acquisition stage. Simultaneously, multiple temperature sensors collect the temperature at different preset locations inside the in-situ measurement device, and a pre-built thermal path model is used to predict the target temperature parameters and identify the current temperature change stage. The current compensation amount is then determined based on the compensation coefficient library corresponding to different temperature ranges and different change stages. This allows for a more accurate characterization of the true thermal state of key components inside the device and dynamic compensation for temperature drift, thereby improving the accuracy, stability, and adaptability to complex thermal environment changes in wafer surface temperature measurement within the semiconductor furnace tube. Attached Figure Description

[0019] Figure 1 This is a structural block diagram of an in-situ measurement device in one embodiment; Figure 2 This is a schematic flowchart of a temperature measurement method for a semiconductor furnace tube in one embodiment; Figure 3 This is a flowchart illustrating the steps for obtaining a digital voltage signal in one embodiment; Figure 4 This is a flowchart illustrating the steps of predicting target temperature parameters and identifying the current temperature change stage in one embodiment. Figure 5 This is a structural block diagram of a temperature measurement system for a semiconductor furnace tube in one embodiment. Detailed Implementation

[0020] The following specific examples illustrate the implementation of this application. Those skilled in the art can easily understand other advantages and effects of this application from the content disclosed in this specification. This application can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of this application. It should be noted that, unless otherwise specified, the following embodiments and features in the embodiments can be combined with each other.

[0021] Some exemplary embodiments of this application have been described for illustrative purposes. It should be understood that this application may be implemented in other ways not specifically shown in the accompanying drawings.

[0022] Please see Figure 1 In one exemplary embodiment, this application provides an in-situ measurement device, including: a light source module, a data acquisition module, a measurement module, and a temperature measurement system for a semiconductor furnace tube. The light source module is used to generate measurement light, which is then separated into two preset wavelength bands and irradiated onto the wafer surface inside the furnace tube.

[0023] Optionally, the light source module in this embodiment includes a broadband light source, a front protection window, a front lens, a beam splitter, a first narrowband filter, and a second narrowband filter.

[0024] Specifically, a broadband light source is used to generate measurement light covering a first preset wavelength band and a second preset wavelength band, which enters the furnace tube through a front protection window; a front lens is used to collimate and focus the measurement light; a beam splitter is used to separate the measurement light into two optical signals. Exemplarily, the beam splitter can be a dichroic mirror, a beam splitter prism, or a grating. A first narrowband filter and a second narrowband filter are respectively disposed on corresponding optical paths to select the first preset wavelength band and the second preset wavelength band from the two optical signals, respectively. Exemplarily, the center wavelengths of the first and second preset wavelength bands can be 0.9 μm and 1.05 μm, respectively, and the bandwidths can both be 50 nm. The separated optical signals of the two preset wavelength bands are then irradiated onto the wafer surface inside the furnace tube through a beam combining optical path and an exiting optics, or irradiated onto the same measurement area on the wafer surface along a near-coaxial optical path, so as to subsequently acquire the corresponding reflected light signals.

[0025] The acquisition module is used to simultaneously sample two reflected lights generated by optical signals on the wafer surface, perform photoelectric conversion on them, and then perform feedforward compensation based on the physical characteristics of semiconductor devices to obtain a digital voltage signal.

[0026] Optionally, the acquisition module includes two photodetectors and a signal conditioning unit. The signal conditioning unit includes a preamplifier, a compensation subunit, a programmable gain amplifier (PGA), an anti-aliasing filter, and an analog-to-digital converter (ADC) connected in sequence. It should be understood that the signal conditioning unit is mounted on a circuit board.

[0027] Specifically, two photodetectors receive two reflected lights from the wafer surface and convert the corresponding optical signals into electrical signals. The photodetectors can be InGaAs detectors (suitable for the 0.8–1.7 μm band) or Si detectors (suitable for the 0.4–1.1 μm band). Since the detector itself is one of the most temperature-sensitive components, its responsivity, dark current, and other parameters change significantly with temperature. To improve stability, this embodiment also includes a TEC temperature control component to stabilize the detector's operating temperature at a fixed level.

[0028] The signal conditioning unit is electrically connected to two photodetectors and is used to condition, compensate, and acquire the weak electrical signals output by the detectors. During operation, the preamplifier amplifies the weak current or voltage signals output by the detectors to obtain the corresponding initial voltage signal; the compensation subunit is used to acquire the currently acquired detector temperature... and known bias voltage Based on the physical characteristics of semiconductor devices, feedforward compensation is performed on the initial voltage signal to correct errors introduced by factors such as detector dark current and response rate temperature drift, resulting in a compensated voltage signal. A programmable gain amplifier is used to adaptively adjust the amplification factor of the compensated voltage signal according to the signal strength, thereby improving the dynamic range utilization under different operating conditions. An anti-aliasing filter is used to suppress high-frequency noise and out-of-band interference. An analog-to-digital converter is used to synchronously sample and convert the conditioned analog signal to digital voltage signals corresponding to two preset bands. and For example, the analog-to-digital converter has a resolution of at least 16 bits and an adjustable sampling rate, typically 100Hz.

[0029] In one example, the sampling process of the two channels is controlled by the same clock source to ensure that the reflected signals of the two bands are acquired at the same sampling time, thereby improving the accuracy of subsequent data processing.

[0030] Furthermore, the in-situ measurement device is housed within the enclosure. That is, apart from the broadband light source of the light source module and the front protection window, all other components of the in-situ measurement device are housed within the enclosure. The acquisition module includes a detector and a signal conditioning unit mounted on a circuit board. The signal conditioning unit includes a preamplifier and a reference power supply. Preset locations include the detector housing, near the preamplifier and reference power supply, away from the heat source within the enclosure, and on the circuit board.

[0031] The measurement module includes multiple temperature sensors located at different preset positions inside the in-situ measurement device, used to collect temperature datasets.

[0032] Specifically, considering the strong thermal radiation, complex local heat conduction paths, and uneven temperature distribution inside the chassis during the operation of the semiconductor furnace tube, the actual temperatures of different areas of the detector, analog front-end circuit, reference power supply, and circuit board are prone to difference. Furthermore, temperature changes at these locations are more likely to cause temperature measurement signal drift. Therefore, in this embodiment, preset positions are set at one or more locations: at the detector tube shell, near the preamplifier and reference power supply, away from the heat source in the chassis, and on the circuit board. The reference power supply provides a stable reference voltage for the preamplifier, bias circuit, and analog-to-digital converter in the signal conditioning unit, thereby reducing the impact of power supply fluctuations and temperature drift on the accuracy of temperature measurement signal processing.

[0033] Furthermore, temperature sensors located on the detector housing are used to acquire the detector's operating temperature; temperature sensors located near the preamplifier and reference power supply are used to acquire the temperature of the analog front-end area; temperature sensors located away from the heat source within the enclosure are used to acquire the ambient reference temperature; and temperature sensors located in different areas of the circuit board are used to acquire information on the circuit board's temperature distribution. By placing temperature sensors in these temperature-sensitive locations, the true thermal state of key components inside the in-situ measurement device can be more accurately characterized, providing a more reliable temperature data foundation for subsequent thermal path model construction, temperature change trend prediction, and dynamic compensation.

[0034] For example, the above-mentioned high-precision digital temperature sensor, such as TMP117 or DS18B20, has an accuracy better than ±0.1℃ and a sampling rate of not less than 1Hz, preferably 5 to 10Hz.

[0035] The temperature measurement system for the semiconductor furnace tube is used to calculate the original measured temperature based on the digital voltage signal; predict the target temperature parameters and identify the current temperature change stage based on the temperature dataset and the pre-built thermal path model; confirm the current compensation amount from the preset compensation coefficient library based on the target temperature parameters and the current temperature change stage. The compensation coefficient library is established during pre-calibration for different temperature ranges and different change stages; and compensate the original measured temperature based on the current compensation amount to obtain the compensated output temperature.

[0036] The aforementioned in-situ measurement device provides measurement light in two preset wavelengths through a light source module. The acquisition module synchronously samples, converts, and compensates for the two reflected lights based on the physical characteristics of semiconductor devices. This can reduce the impact of factors such as detector temperature drift and analog front-end drift on the measurement signal during the signal acquisition stage. At the same time, combined with the distributed acquisition of temperature data at multiple preset locations inside the enclosure by the measurement module, and the prediction and staged compensation of the target temperature parameters by the temperature measurement system based on the thermal path model, it can more accurately characterize the true thermal state of key internal components and dynamically compensate for temperature drift, thereby improving the accuracy and stability of wafer surface temperature measurement inside the semiconductor furnace tube. Please see Figure 2 In one exemplary embodiment, this application provides a method for measuring the temperature of a semiconductor furnace tube, specifically including the following steps: Step 202: Obtain the digital voltage signal and temperature dataset.

[0037] Specifically, the digital voltage signal is obtained by synchronously sampling and photoelectrically converting two reflected lights formed by two preset wavelength signals irradiating the wafer surface inside the furnace tube, and then performing feedforward compensation based on the physical characteristics of the semiconductor device. This digital voltage signal is used to characterize the radiation response intensity under the two preset wavelengths and serves as the basis for subsequent calculation of the original measured temperature. Feedforward compensation based on the physical characteristics of the semiconductor device refers to, during the formation of the digital voltage signal, combining the temperature drift characteristics, response characteristics, and bias characteristics of the detector and related signal conditioning devices to pre-correct errors in the detection signal caused by changes in the physical characteristics of the devices, thereby improving the accuracy of the digital voltage signal in characterizing the target radiation information.

[0038] A temperature dataset refers to a collection of temperature information acquired by multiple temperature sensors at different preset locations inside an in-situ measurement device. This temperature dataset is used to characterize the thermal state distribution at various key locations inside the in-situ measurement device, rather than being limited to the ambient temperature at a single location.

[0039] Different preset locations refer to pre-selected locations within the in-situ measurement device that are easily affected by temperature changes and significantly impact the accuracy of temperature measurement results. These locations are typically the location of heat-sensitive devices, critical locations on the heat transfer path, or representative locations that characterize the overall thermal state inside the device. By deploying temperature sensors at these locations, the temperature distribution characteristics inside the in-situ measurement device can be comprehensively reflected, providing data support for subsequent thermal path model construction, target temperature parameter prediction, and drift compensation. For example, the temperature dataset includes at least one of the following: the temperature at the detector location, the temperature at the simulation front-end location, the ambient reference temperature of the enclosure away from the heat source, and the temperature of different areas of the circuit board.

[0040] Step 204: Calculate the original measured temperature based on the digital voltage signal. Specifically, the original measured temperature refers to the target temperature result obtained by direct conversion from the digital voltage signal. This temperature result characterizes the initial measured temperature value of the wafer surface inside the furnace tube at the current sampling time.

[0041] Furthermore, a pre-established correspondence exists between the digital voltage signal and temperature. Since the digital voltage signal characterizes the radiation response intensity of the wafer surface at two preset wavelengths, the radiation energy distribution corresponding to the two preset wavelengths changes with different target temperatures, thus causing the corresponding digital voltage signal to change. This correspondence can be obtained by pre-collecting the corresponding digital voltage signals at multiple known temperature points and establishing a mapping relationship between each known temperature point and the corresponding digital voltage signal.

[0042] Step 206: Based on the temperature dataset and the pre-built thermal path model, predict the target temperature parameters and identify the current temperature change stage. Specifically, the target temperature parameter refers to the information parameter that can characterize the thermal state of key locations inside the enclosure, and is used to reflect the temperature state and its changing trend at the current moment or the next moment.

[0043] The stage of temperature change refers to the type of change in the current thermal state, which can be used to distinguish between different states such as rising temperature, cooling temperature, or basically stable temperature.

[0044] The thermal path model is used to characterize the heat transfer relationships and thermal state changes between key locations. Based on the temperature dataset and the thermal path model, the target temperature parameters corresponding to the current thermal state can be obtained, and it can be further determined which temperature change stage the current temperature change is in, providing a basis for determining the subsequent compensation amount.

[0045] Step 208: Based on the target temperature parameters and the current temperature change stage, confirm the current compensation amount from the preset compensation coefficient library. The compensation coefficient library is established during pre-calibration for different temperature ranges and different change stages.

[0046] Specifically, the compensation coefficient library is a pre-established and stored set of compensation parameters used to reflect the drift patterns of temperature measurement results under different temperature conditions. Since different temperature ranges correspond to different drift characteristics, and different stages of temperature change may also correspond to different compensation requirements, the compensation coefficient library is related not only to the temperature range but also to the temperature change state. Based on the target temperature parameter, the current corresponding temperature range can be determined; based on the current temperature change stage, the current corresponding change state can be determined. Based on the correspondence between these two parameters and the compensation coefficient library, the appropriate compensation amount for the current moment can ultimately be determined.

[0047] Step 210: Compensate the original measured temperature based on the current compensation amount to obtain the compensated output temperature.

[0048] Specifically, the compensated output temperature refers to the temperature result obtained after correcting the original measured temperature by incorporating the current compensation amount.

[0049] The aforementioned temperature measurement method for semiconductor furnace tubes, by synchronously sampling and photoelectric conversion of reflected light corresponding to two preset wavelength bands, and combining it with feedforward compensation based on the physical characteristics of semiconductor devices, can reduce the impact of temperature drift of the detector and front-end circuit on the temperature measurement results in advance during the signal acquisition stage. At the same time, by collecting the temperature at different preset locations inside the in-situ measurement device through multiple temperature sensors, and combining it with a pre-constructed thermal path model to predict the target temperature parameters and identify the current temperature change stage, and then determining the current compensation amount based on the compensation coefficient library corresponding to different temperature ranges and different change stages, can more accurately characterize the true thermal state of key components inside the device and dynamically compensate for temperature drift, thereby improving the accuracy, stability, and adaptability to complex thermal environment changes of wafer surface temperature measurement inside the semiconductor furnace tube.

[0050] Please see Figure 3 Optionally, in the case where the in-situ measurement device includes a data acquisition module housed within the enclosure, the data acquisition module includes a detector and a signal conditioning unit mounted on a circuit board, the signal conditioning unit includes a preamplifier and a reference power supply, and the temperature dataset includes the detector temperature corresponding to the detector, the analog front-end temperature corresponding to the signal conditioning unit, and the ambient reference temperature corresponding to the location of the enclosure away from the heat source, the method of obtaining a digital voltage signal by feedforward compensation of the two reflected lights after synchronous sampling and photoelectric conversion based on the physical characteristics of semiconductor devices includes: Step 302: Perform photoelectric conversion on the two reflected lights respectively to obtain the detector output current corresponding to the two preset wavelength bands.

[0051] Step 304: Based on the currently acquired detector temperature and preset bias voltage, perform dark current compensation on the detector output current according to the pre-calibrated dark current and temperature characteristics to obtain the real photocurrent corresponding to the two preset bands.

[0052] Step 306: Based on the currently acquired detector temperature, the detector's responsivity in two preset bands is corrected according to the pre-calibrated responsivity temperature coefficient. The actual photocurrent is then corrected based on the corrected responsivity to obtain the corrected electrical signals corresponding to the two preset bands.

[0053] Step 308: Based on the currently acquired analog front-end temperature, according to the pre-calibrated gain-temperature drift relationship and input bias current-temperature drift relationship, perform temperature drift compensation on the gain and input bias current of the preamplifier to correct the voltage signal corresponding to the correction electrical signal.

[0054] Step 310: Perform analog-to-digital conversion on the corrected voltage signal to obtain digital voltage signals corresponding to the two preset bands.

[0055] Specifically, the following description will focus on the structure of the in-situ measuring device provided in the above embodiments.

[0056] Two reflected beams are incident on their respective photodetectors. The detectors output currents based on the incident light intensity, denoted as the first detector output current. Second detector output current The current signal output by the detector is then sent to the compensation subunit for feedforward correction.

[0057] Furthermore, this application performs dark current compensation on the current signal output by the aforementioned detector.

[0058] Because the detector's dark current changes with detector temperature, this drift will directly add to the detector's output current in a high-temperature furnace tube environment. Therefore, when acquiring... and Then, firstly, the detector temperature currently collected is used. and preset bias voltage Compensation is performed on the dark current component.

[0059] During the pre-calibration phase, the relationship between dark current and temperature is established in advance through temperature variation experiments. For example, the dark current satisfies the following empirical relationship:

[0060] in, Reference temperature Dark current under, To activate energy, Here, is the Boltzmann constant. During online operation, the compensation subunit calculates the current dark current value based on the current detector temperature and subtracts the dark current component from the detector output current to obtain the actual photocurrent corresponding to the two preset wavelength bands:

[0061] Thus, the first true photocurrent was obtained. Second real photocurrent .

[0062] Furthermore, this application performs a responsivity temperature correction on the actual photocurrent.

[0063] The detector operates in two wavelength bands and The responsivity also changes with detector temperature. Without correction, even if the incident radiation energy remains constant, the proportion of photocurrent output by the detector will shift at different temperatures, thus affecting subsequent temperature calculations.

[0064] Therefore, in this embodiment, based on the currently collected detector temperature The system calls a pre-calibrated temperature coefficient of response rate to perform online correction of the response rates of the two bands. For example, the first... The response rate correction relationship for each working band is as follows:

[0065] in, Reference temperature The response rate is as follows This represents the temperature coefficient of the responsivity in this band. Using the corrected responsivity, the actual photocurrents corresponding to the two bands are normalized to obtain the corrected electrical signals. For example, the signal characteristics after responsivity correction can be obtained through the following ratio relationship:

[0066] This correction process can reduce errors caused by inconsistencies in detector band response and temperature drift in response rate.

[0067] Furthermore, this application also compensates for the temperature drift of the preamplifier.

[0068] In this embodiment, the analog voltage corresponding to the actual photocurrent or the responsivity-corrected electrical signal is also affected by the temperature drift of the analog front-end circuit before entering the analog-to-digital converter. Specifically, the gain of the preamplifier will vary with the temperature of the analog front-end. The input bias current also changes with temperature, causing additional errors in the output voltage signal.

[0069] Therefore, the compensation subunit further adjusts the current simulated front-end temperature based on the collected data. The gain-temperature drift relationship obtained by calling the calibration Relationship between input bias current and temperature drift The gain and bias drift introduced by the preamplifier are compensated for. After compensation, a corrected voltage signal that is closer to the ideal state is obtained.

[0070] The voltage signal, after undergoing the aforementioned dark current compensation, response rate temperature correction, and preamplifier temperature drift compensation, is sent to an analog-to-digital converter for analog-to-digital conversion to obtain digital voltage signals corresponding to two preset frequency bands. and .

[0071] By adopting the above scheme, based on the feedforward compensation method of the physical characteristics of semiconductor devices, dark current compensation, response rate temperature correction and analog front-end temperature drift compensation are performed on the detector output signal in sequence. This can reduce the influence of detector body temperature drift and front-end circuit temperature drift on the detection signal before analog-to-digital conversion, so that the obtained digital voltage signal can more accurately represent the real radiation information of the wafer surface. This provides a more reliable input basis for subsequent original measurement temperature calculation, thermal path model prediction and dynamic compensation, and improves the accuracy and stability of in-situ temperature measurement of semiconductor furnace tubes.

[0072] Optionally, if the temperature dataset also includes the circuit board temperature corresponding to the circuit board, the methods for pre-building the thermal path model include: During the pre-calibration stage, the in-situ measuring device is placed in a temperature-controlled environmental test chamber, and a temperature excitation is applied to the in-situ measuring device. The temperature excitation includes at least one of step temperature change, ramp temperature change, sinusoidal temperature change, and local heating.

[0073] Under temperature excitation, temperature data output by multiple temperature sensors located at preset positions inside the in-situ measuring device are simultaneously sampled; each preset position corresponds to one or more temperature measurement points.

[0074] Based on temperature data, a dynamic relationship of thermal coupling between multiple temperature measuring points and detectors is established according to thermal network theory. Its expression is as follows:

[0075] in, For detector temperature, For the thermal time constant of the detector, For environmental reference temperature, To simulate front-end temperature, The temperature corresponding to the i-th circuit board, , and For coupling coefficients, For external heat flow input, The coupling coefficient corresponding to the external heat flow input. For bias terms; The system identification method is used to extract the model parameters in the thermal coupling dynamic relationship to obtain the thermal path model.

[0076] Specifically, the temperature dataset includes not only the detector temperature corresponding to the detector, the simulation front-end temperature corresponding to the simulation front-end, and the ambient reference temperature, but also the temperatures of one or more circuit boards corresponding to different areas of the circuit board.

[0077] During the pre-calibration phase, the in-situ measuring device is first placed in a temperature-controlled environmental test chamber. The chamber applies different forms of temperature excitation to cover various thermal change conditions that may be encountered during actual use. Specifically, step temperature changes simulate sudden changes in ambient temperature; ramp temperature changes simulate slow heating or cooling; sinusoidal temperature changes simulate periodic thermal disturbances; and localized heating simulates furnace radiation, localized component heating, or uneven heating in a specific area. These different types of temperature excitation create multiple heat transfer paths and thermal response states within the in-situ measuring device, facilitating the subsequent extraction of more complete thermal coupling characteristics.

[0078] During the application of temperature excitation, multiple temperature sensors located at preset positions inside the in-situ measuring device are simultaneously sampled. Each preset position corresponds to one or more temperature measurement points, thereby obtaining the detector temperature. Simulated front-end temperature Ambient reference temperature and the temperature of one or more circuit boards , In one specific embodiment, the sampling frequency of each temperature sensor can be set to 5Hz to 10Hz to ensure that the dynamic temperature response process of each temperature measuring point inside the device can be recorded relatively completely under temperature excitation.

[0079] After acquiring temperature data from each temperature measurement point, a dynamic relationship of thermal coupling between multiple temperature measurement points and the detector is established based on thermal network theory. In this embodiment, the detector is used as the target thermal node, and the ambient reference temperature, simulated front-end temperature, circuit board temperature, and external heat flow input are used as inputs affecting the thermal state of the detector to establish the above-mentioned heat transfer relationship, wherein... Used to characterize the detector's response speed to external thermal disturbances; Used to characterize the additional heating effect from local radiation or external heat sources; Used to characterize fixed offsets in the model.

[0080] Finally, a system identification method is used to extract the model parameters in the aforementioned thermal coupling dynamic relationship. For example, in this embodiment, a least-squares fitting method is used to fit multiple sets of temperature response data collected during the pre-calibration stage to obtain the detector thermal time constant, various coupling coefficients, external heat flow input coefficients, and bias terms. Furthermore, for in-situ measurement devices with different structural arrangements or different device configurations, calibration can be performed separately to obtain the corresponding thermal path model parameters.

[0081] The obtained thermal path model and its parameters are written into a non-volatile memory and called up when the device is running online to predict the thermal state of the detector and its changing trend based on real-time temperature data.

[0082] By adopting the above scheme, by applying various types of temperature excitations to the in-situ measuring device during the pre-calibration stage and simultaneously collecting temperature data at each preset location, the dynamic relationship of thermal coupling between multiple key temperature measuring points inside the device can be obtained more completely. Furthermore, based on thermal network theory, a thermal path model is established that includes the detector thermal time constant, the coupling coefficient of each temperature measuring point, the external heat flow input term, and the bias term. By identifying and extracting the model parameters through the system, the thermal path model can more accurately characterize the heat transfer path, thermal inertia, and local heating effects inside the in-situ measuring device, thereby providing a more reliable model basis for predicting the target temperature parameters in the online stage.

[0083] Optionally, the original measured temperature is calculated based on the digital voltage signal, including: Based on the two digital voltage signals at different sampling times, the corresponding two-color ratio is calculated; based on the pre-stored correspondence between temperature and ratio, the instantaneous temperature value corresponding to each two-color ratio is calculated; the instantaneous temperature values ​​are sorted according to the sampling time order to obtain the original measured temperature.

[0084] Specifically, the basic principle of a dual-color thermometer is that the thermal radiation intensity of the same temperature measurement target at two different wavelengths is related to the target temperature. By obtaining the intensity ratio of the radiation signals in the two bands, the influence of changes in the overall transmittance of the optical path, slow fluctuations in the target emissivity, and changes in the detection gain on the temperature measurement results can be reduced, thereby improving the stability of temperature measurement.

[0085] For the wafer surface inside the furnace tube in this embodiment, the acquisition module simultaneously acquires digital voltage signals corresponding to two preset wavelength bands. and ,in, Indicates time The digital voltage signal in the first band, Indicates time The digital voltage signal in the second band.

[0086] For example, the corresponding two-color ratio value can be calculated based on two digital voltage signals at different sampling times, and can be expressed as:

[0087] in, Let be the two-color ratio at time t.

[0088] Furthermore, after obtaining the two-color ratio Then, the pre-stored temperature-ratio correspondence is invoked to calculate the corresponding instantaneous temperature value. The temperature-ratio correspondence can be pre-established through a standard blackbody calibration experiment and stored in the form of a lookup table, piecewise function, or fitted function. For example, the instantaneous temperature value can be expressed as:

[0089] in, This represents the temperature-ratio mapping function.

[0090] Based on the above process, for different sampling times The two digital voltage signals acquired synchronously can be used to calculate the corresponding two-color ratio. And further obtain the corresponding instantaneous temperature value. .

[0091] Subsequently, the instantaneous temperature values ​​are arranged according to the sampling time sequence to form the original measured temperature. .

[0092] Please see Figure 4 Optionally, when the target temperature parameters include the predicted temperature and the temperature change slope; and the temperature change stages include a heating stage, a cooling stage, and a isothermal stage, the target temperature parameters are predicted based on the temperature dataset and a pre-built thermal path model, and the current temperature change stage is identified, including: Step 402: Input the temperature dataset collected at the current moment into the thermal path model to obtain the predicted temperature of the target object at the next moment; the target object includes at least one of the following: detector, signal conditioning unit, enclosure away from the heat source, and circuit board.

[0093] Step 404: Obtain the predicted temperature corresponding to the most recent multiple sampling times of each target object, and perform fitting processing on each predicted temperature to obtain the temperature change slope corresponding to each target object.

[0094] Step 406: If the slope of the temperature change of any target object is greater than the preset heating threshold, the temperature change stage corresponding to that target object is considered to be the heating stage.

[0095] Step 408: If the slope of the temperature change of any target object is less than the preset cooling threshold, the temperature change stage corresponding to that target object is considered to be the cooling stage.

[0096] Step 410: If the slope of the temperature change of any target object is between the preset heating threshold and the preset cooling threshold, the temperature change stage corresponding to the target object is considered to be the constant temperature stage.

[0097] Step 412: When there are multiple target objects, a voting process is performed based on the temperature change stages corresponding to the multiple target objects, and the current temperature change stage is determined according to the voting results.

[0098] Specifically, after the in-situ measurement device enters online operation, a fixed sampling rate is used. Temperature data is collected by polling multiple pre-defined locations inside the enclosure, resulting in a temperature dataset that includes the detector temperatures. Simulated front-end temperature Ambient reference temperature and the temperature of one or more circuit boards .

[0099] Optionally, to reduce the impact of random noise and occasional outliers on subsequent prediction results, this application preprocesses the temperature sequences of each temperature measurement point before inputting the temperature dataset into the thermal path model. For example, a moving average filter or median filter is applied to the most recent sampling points to suppress sampling noise; for abrupt changes that significantly deviate from the continuous trend, they can be removed or corrected according to a preset threshold.

[0100] Furthermore, the preprocessed temperature dataset is input into a pre-constructed thermal path model. Based on the current temperature state and historical temperature change trends, the temperature of the target object at the next moment is predicted to obtain the predicted temperature. For example, this embodiment of the application is based on the Kalman filter concept. First, the state is predicted based on the previous moment's state estimate and the thermal path model. Then, the state is updated using the current measured temperature, ultimately obtaining the predicted temperature for the next moment. Among them, the prediction time step The time constant can be set to 0.1s to 1s based on the system thermal time constant.

[0101] Furthermore, the temperature change slope is used to characterize whether the target object is currently in a heating, cooling, or relatively stable thermal state. This application reads the predicted temperature corresponding to the most recent N sampling times for each target object, and performs linear fitting with time as the independent variable and predicted temperature as the dependent variable to obtain the temperature change slope of the target object at the current stage. For example, when the target object is a detector node, the slope of the temperature change corresponding to the detector can be obtained. When trend analysis is performed on both the simulated front-end node and the environmental baseline node simultaneously, the results can also be obtained separately. and .

[0102] Furthermore, after obtaining the temperature change slope of each target object, this application compares it with preset heating thresholds and preset cooling thresholds to identify the current temperature change stage. For example, this application uses the preset heating threshold... Set to +0.1℃ / min, preset cooling threshold. Set to -0.1℃ / min.

[0103] If the target object is a single object, the temperature change stage is determined directly based on the comparison results. If there are multiple target objects, the overall temperature change stage is determined by majority voting based on the temperature change stage of each target object. This way, even if a single temperature measurement point is affected by instantaneous disturbances, a relatively stable stage identification result can still be maintained.

[0104] By adopting the above scheme, the temperature of the target object at the next moment is predicted by inputting the currently collected multi-point temperature data into the thermal path model. Based on the predicted temperature at multiple recent sampling moments, the slope of temperature change is determined, thereby identifying the current temperature change stage. This application not only obtains the current thermal state information, but also can grasp the development trend of the thermal state in advance, thereby reducing the compensation lag caused by thermal inertia and heat transfer delay. At the same time, the comprehensive judgment based on the change rate of multiple objects can also improve the stability and accuracy of temperature change stage identification.

[0105] Optionally, based on the target temperature parameter and the current temperature change stage, the current compensation amount is determined from a preset compensation coefficient library, including: Based on the predicted temperature, determine the two adjacent temperature nodes where the predicted temperature is located; based on the current temperature change stage, call the corresponding compensation coefficient set from the preset compensation coefficient library; obtain the compensation values ​​corresponding to the two adjacent temperature nodes from the compensation coefficient set; perform interpolation calculation on the compensation values ​​corresponding to the two adjacent temperature nodes to obtain the current compensation amount.

[0106] Specifically, in order to improve the compensation accuracy of in-situ temperature measurement of semiconductor furnace tubes under complex thermal environments, this application pre-constructs a segmented nonlinear compensation coefficient library, and determines the current compensation amount based on the predicted temperature and the current temperature change stage during the online operation phase, so as to dynamically compensate for the drift of the original measured temperature.

[0107] The construction of the compensation coefficient library includes the following steps: During the pre-calibration stage, the in-situ measuring device is placed in a temperature-controlled chamber, allowing the device to operate under different ambient temperature conditions, and measurement drift data corresponding to multiple temperature ranges and multiple change stages are collected. For example, the temperature range can be divided into 5°C intervals, such as 0°C~5°C, 5°C~10°C, 10°C~15°C, etc., and the drift amount during the heating, cooling, and isothermal stages is calibrated within each temperature range.

[0108] During the calibration process, the reference temperature obtained by calibration with a standard temperature source is used as the benchmark, and the difference between the original measured temperature and the reference temperature is determined as the drift. Therefore, a correspondence between the drift and the detector temperature and the stage of change is established under different temperature ranges and different stages of change, and its expression is:

[0109] in, This indicates the temperature corresponding to the detector. This indicates the current stage of temperature change.

[0110] In this embodiment, the function The data can be stored using a lookup table, piecewise linear interpolation, or polynomial fitting. Preferably, for easy online retrieval, a two-dimensional compensation coefficient table structure combining temperature nodes and stage classification is used for storage. That is, under each temperature node, the compensation values ​​corresponding to the three change stages of heating, cooling, and constant temperature are recorded to form a compensation coefficient library, which is then stored in non-volatile memory.

[0111] Furthermore, during the online operation phase, the processor determines the current compensation amount from the compensation coefficient library based on the predicted temperature and the current temperature change phase.

[0112] Specifically, firstly based on the predicted temperature The two adjacent temperature nodes of the predicted temperature are determined. For example, when the predicted temperature is 23.2℃, if the compensation coefficient library sets nodes every 5℃, the adjacent temperature nodes can be determined to be 20℃ and 25℃.

[0113] Secondly, based on the current stage of temperature change, the corresponding set of compensation coefficients is retrieved from the compensation coefficient library. For example, if the current stage of temperature change is identified as a heating stage, the set of compensation coefficients corresponding to the heating stage is retrieved; if it is identified as a cooling stage, the set of compensation coefficients corresponding to the cooling stage is retrieved; and if it is identified as a constant temperature stage, the set of compensation coefficients corresponding to the constant temperature stage is retrieved.

[0114] Next, the compensation values ​​corresponding to the two adjacent temperature nodes are obtained from the set of compensation coefficients that are called. Taking the predicted temperature of 23.2℃ as an example, if the current stage is the heating phase, the compensation values ​​corresponding to the 20℃ node and the 25℃ node are read.

[0115] Finally, interpolation calculations are performed on the compensation values ​​corresponding to two adjacent temperature nodes to obtain the current compensation amount. In this embodiment, linear interpolation is preferably used to ensure a smooth transition of the compensation amount between adjacent temperature nodes, thereby avoiding abrupt changes in the compensation result when the temperature passes through the segment boundary.

[0116] Furthermore, this application will include the current compensation amount. Acting on the original measured temperature The output temperature after compensation is obtained. Its expression is:

[0117] in, The original measured temperature is obtained by direct conversion from the digital voltage signal. The compensation amount is determined at the current moment. This is the output temperature after dynamic compensation.

[0118] Furthermore, this application also sends the compensated output temperature to the display unit for display in real time, and also sends it to the external control system, host computer or process monitoring system for subsequent monitoring, recording or closed-loop control.

[0119] By adopting the above scheme, by establishing compensation coefficient libraries corresponding to different temperature ranges and different temperature change stages during the pre-calibration stage, and calling the corresponding compensation coefficient set according to the predicted temperature and the current temperature change stage during the online operation stage, and then determining the current compensation amount through interpolation of adjacent temperature nodes, this application can more accurately characterize the nonlinear drift characteristics under different temperature ranges and the thermal hysteresis differences during heating, cooling, and isothermal processes, avoiding the problem that a single linear temperature coefficient is difficult to adapt to complex thermal behavior. Furthermore, by applying the current compensation amount to the original measurement temperature in real time, the compensation abrupt change at the temperature node switching point can be reduced, the continuity of the compensation process can be improved, thereby improving the accuracy and stability of in-situ temperature measurement of semiconductor furnace tubes under dynamic thermal environments.

[0120] Optionally, the above-mentioned temperature measurement method for semiconductor furnace tubes further includes: If the current temperature change phase is a constant temperature phase and the duration exceeds the preset time, obtain the external reference temperature; determine the compensation residual based on the compensated output temperature and the external reference temperature; and correct the compensation coefficients for the corresponding temperature range in the compensation coefficient library based on the compensation residual.

[0121] Specifically, in order to reduce the impact of component aging, long-term temperature drift and slow changes in device parameters on compensation accuracy, this application further incorporates an adaptive correction process for the compensation coefficient library.

[0122] During the online operation of the in-situ measurement device, this application continuously monitors the current temperature change stage and the duration of that stage. When the current temperature change stage is determined to be a constant temperature stage based on the aforementioned stage identification results, and the duration of the constant temperature stage exceeds a preset duration, an adaptive correction condition is triggered. The reason for performing the correction during the constant temperature stage is that the internal thermal state of the device is relatively stable at this time, and the measurement results are less affected by transient thermal disturbances, making it more suitable for extracting long-term deviations.

[0123] Furthermore, under the condition of satisfying the adaptive correction, an external reference temperature is acquired and used as the temperature reference under the current operating conditions. This external reference temperature can be provided by periodically calibrated fixtures, such as a standard blackbody source, a standard temperature source, or a calibrated reference temperature measuring device; it can also be provided by a reference source set inside the device, such as a built-in stable reference temperature module.

[0124] Furthermore, this application reads the compensated output temperature at the current moment. And combined with the obtained external reference temperature Determine the current compensation residual. Its expression is:

[0125] in, It characterizes the magnitude and direction of the deviation of the current compensation result from the reference temperature.

[0126] After obtaining the compensation residual, this application locates the corresponding compensation coefficient in the compensation coefficient library based on the temperature range of the current predicted temperature, and corrects the compensation coefficient for that temperature range based on the compensation residual. After correction, the corrected compensation coefficient is written to non-volatile memory for subsequent temperature compensation. In this way, during subsequent operation, dynamic drift compensation can be performed based on the updated compensation coefficient library, thereby gradually adapting to parameter changes caused by device aging and long-term drift.

[0127] Optionally, the above-mentioned temperature measurement method for semiconductor furnace tubes further includes: The system performs anomaly detection on the collected temperature dataset. If any temperature in the temperature dataset exceeds the preset upper limit, the temperature difference between any two temperature measurement points exceeds the preset threshold, the slope of the temperature change at any temperature measurement point exceeds the preset threshold, or the reading of any temperature sensor remains unchanged for a long time or deviates from the preset range, the system determines it to be abnormal and outputs an alarm message.

[0128] Specifically, to improve the safety and reliability of the in-situ measurement process of semiconductor furnace tubes, a temperature anomaly diagnosis and alarm mechanism is further incorporated into the temperature measurement method to identify potential conditions such as overheating, localized thermal anomalies, abnormal temperature rise, and temperature sensor malfunctions.

[0129] This application continuously acquires temperature data sets from each temperature measurement point according to a preset sampling period and performs anomaly detection from multiple aspects. For example, embodiments of this application perform anomaly detection from four aspects: absolute temperature, temperature difference between measurement points, temperature change slope, and sensor reading validity.

[0130] In one embodiment, this application compares the temperature at each temperature measurement point with a preset upper limit to determine if there is an over-temperature anomaly. For example, the upper limit of the detector temperature can be set to 70°C. When the detector temperature exceeds this preset upper limit, an over-temperature anomaly is considered to exist, and an alarm is triggered. Optionally, to avoid false alarms caused by momentary disturbances, continuous judgment conditions can be set, for example, outputting an over-temperature alarm only when the detector temperature exceeds the preset upper limit for multiple consecutive sampling cycles.

[0131] In another embodiment, this application determines whether an abnormal temperature gradient exists based on the temperature difference between any two temperature measurement points. For example, the absolute difference between the detector temperature and the ambient reference temperature can be used as a key monitoring indicator. When the temperature difference exceeds a preset threshold, it is considered that there may be localized overheating, uneven heat dissipation, or abnormal heat accumulation inside the device. For example, the temperature difference threshold can be set to 10°C. When the temperature gradient exceeds this threshold, an abnormal temperature gradient warning is output. Furthermore, the temperature difference between the simulation front-end and the environmental reference, as well as between temperature measurement points on adjacent circuit boards, can also be detected to more comprehensively monitor internal heat distribution anomalies.

[0132] In another embodiment, this application calculates the temperature change slope based on the temperature change of each temperature measuring point over time, and determines whether there is an abnormal rapid temperature rise or fall. For example, temperature data from multiple recent sampling times can be fitted to obtain the temperature change slope for the corresponding temperature measuring point. When the temperature change slope of any temperature measuring point exceeds a preset threshold, it is considered that there is an abnormal temperature change slope. For example, the detector temperature change slope threshold can be set to 5℃ / min. When the detector temperature change slope exceeds this threshold, a corresponding warning message is output. This type of anomaly can be used to indicate situations such as a sudden increase in external heat radiation, abnormal ventilation and heat dissipation, or sudden overheating of local components.

[0133] In another embodiment, this application also performs validity checks on the reading status of each temperature sensor to determine whether a sensor malfunction exists. For example, if the reading of a temperature sensor remains unchanged for an extended period, exceeding a preset duration, the temperature sensor is considered to be malfunctioning, experiencing communication interruption, or having an output freeze. Similarly, if the reading of a temperature sensor significantly deviates from a preset reasonable range, or if its trend is significantly inconsistent with that of adjacent temperature measurement points, the temperature sensor is also considered to be malfunctioning. Upon identifying a sensor malfunction, the corresponding sensor is marked as faulty and a fault alarm message is output.

[0134] In the above embodiments, an alarm message is generated and output when any abnormal condition is met. The alarm message can be displayed on a screen for engineers to view directly; in addition, a switch alarm signal or a digital communication alarm bit can be output through the output unit to upload the abnormal status to the host computer, process control system, or equipment management system.

[0135] By adopting the above method and continuously monitoring and comprehensively judging the temperature dataset, this application can promptly identify abnormal situations such as detector overheating, local thermal anomalies inside the device, abnormal rapid temperature rise, and temperature sensor failure, and has the ability to diagnose the internal thermal state. At the same time, by outputting alarm information through the display screen and output unit, it can also facilitate engineers to discover and deal with potential faults in a timely manner, and improve the operational safety of the in-situ temperature measurement process of the semiconductor furnace tube.

[0136] The aforementioned temperature measurement method for semiconductor furnace tubes, by synchronously sampling and photoelectric conversion of reflected light corresponding to two preset wavelength bands, and combining it with feedforward compensation based on the physical characteristics of semiconductor devices, can reduce the impact of temperature drift of the detector and front-end circuit on the temperature measurement results in advance during the signal acquisition stage. At the same time, by collecting the temperature at different preset locations inside the in-situ measurement device through multiple temperature sensors, and combining it with a pre-constructed thermal path model to predict the target temperature parameters and identify the current temperature change stage, and then determining the current compensation amount based on the compensation coefficient library corresponding to different temperature ranges and different change stages, can more accurately characterize the true thermal state of key components inside the device and dynamically compensate for temperature drift, thereby improving the accuracy, stability, and adaptability to complex thermal environment changes of wafer surface temperature measurement inside the semiconductor furnace tube.

[0137] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0138] Based on the same inventive concept, this application also provides a temperature measurement system for a semiconductor furnace tube. This system is applicable to the temperature measurement method for the semiconductor furnace tube described above. The solution provided by this system is similar to the solution described in the above method. Therefore, the specific limitations in one or more system embodiments provided below can be found in the limitations of the method above, and will not be repeated here.

[0139] Please see Figure 5 In one embodiment, the temperature measurement system for the semiconductor furnace tube includes an acquisition module and a processing module.

[0140] The acquisition module is used to acquire digital voltage signals and temperature datasets. The digital voltage signals are obtained by synchronously sampling and photoelectric conversion of two reflected lights formed by two preset wavelength light signals irradiating the wafer surface inside the furnace tube, and then performing feedforward compensation based on the physical characteristics of the semiconductor device. The temperature datasets are acquired by multiple temperature sensors at different preset locations inside the in-situ measurement device.

[0141] The processing module is used to calculate the original measured temperature based on the digital voltage signal; predict the target temperature parameters based on the temperature dataset and the pre-built thermal path model, and identify the current temperature change stage; confirm the current compensation amount from the preset compensation coefficient library based on the target temperature parameters and the current temperature change stage. The compensation coefficient library is established during pre-calibration for different temperature ranges and different change stages; and compensate the original measured temperature based on the current compensation amount to obtain the compensated output temperature.

[0142] The method of obtaining digital voltage signals by feedforward compensation of two reflected lights after synchronous sampling and photoelectric conversion based on the physical characteristics of semiconductor devices includes: performing photoelectric conversion on the two reflected lights respectively to obtain detector output currents corresponding to two preset wavelength bands; performing dark current compensation on the detector output current according to the currently acquired detector temperature and preset bias voltage, and according to the pre-calibrated dark current and temperature characteristics, to obtain the real photocurrents corresponding to the two preset wavelength bands; performing temperature correction on the detector responsivity in the two preset wavelength bands according to the currently acquired detector temperature and the pre-calibrated responsivity temperature coefficient, and correcting the real photocurrent based on the corrected responsivity to obtain corrected electrical signals corresponding to the two preset wavelength bands; performing temperature drift compensation on the gain and input bias current of the preamplifier according to the currently acquired analog front-end temperature and the pre-calibrated gain-temperature drift relationship and input bias current-temperature drift relationship, to correct the voltage signal corresponding to the corrected electrical signal; and performing analog-to-digital conversion on the corrected voltage signal to obtain digital voltage signals corresponding to the two preset wavelength bands.

[0143] Optionally, the temperature measurement system for the aforementioned semiconductor furnace tube may also include a model building module.

[0144] The model building module is used in the pre-calibration stage to set up the in-situ measuring device in a temperature-controlled environment test chamber and apply temperature excitation to the in-situ measuring device. The temperature excitation includes at least one of step temperature change, ramp temperature change, sinusoidal temperature change, and local heating. Under the action of temperature excitation, temperature data output from multiple temperature sensors located at preset positions inside the in-situ measuring device are sampled simultaneously. Each preset position corresponds to one or more temperature measurement points. Based on the temperature data, the dynamic relationship of thermal coupling between multiple temperature measurement points and detectors is established according to thermal network theory, and its expression is:

[0145] in, For detector temperature, For the thermal time constant of the detector, For environmental reference temperature, To simulate front-end temperature, The temperature corresponding to the i-th circuit board, , and For coupling coefficients, For external heat flow input, The coupling coefficient corresponding to the external heat flow input. The bias term is used; the model parameters in the thermally coupled dynamic relationship are extracted using the system identification method to obtain the thermal path model.

[0146] Optionally, the processing module calculates the original measured temperature based on the digital voltage signal, including: calculating the corresponding two-color ratio based on the two digital voltage signals at different sampling times; calculating the instantaneous temperature value corresponding to each two-color ratio based on the pre-stored correspondence between temperature and ratio; and sorting each instantaneous temperature value according to the sampling time order to obtain the original measured temperature.

[0147] Optionally, the processing module predicts target temperature parameters and identifies the current temperature change stage based on the temperature dataset and a pre-built thermal path model, including: inputting the temperature dataset collected at the current moment into the thermal path model to obtain the predicted temperature of the target object at the next moment; the target object includes at least one of the following: a detector, a signal conditioning unit, a part of the enclosure away from the heat source, and a circuit board; obtaining the predicted temperatures corresponding to the most recent multiple sampling moments of each target object, and fitting each predicted temperature to obtain the temperature change slope corresponding to each target object; if the temperature change slope of any target object is greater than a preset heating threshold, the temperature change stage corresponding to that target object is considered to be a heating stage; if the temperature change slope of any target object is less than a preset cooling threshold, the temperature change stage corresponding to that target object is considered to be a cooling stage; if the temperature change slope of any target object is between the preset heating threshold and the preset cooling threshold, the temperature change stage corresponding to that target object is considered to be a constant temperature stage; if there are multiple target objects, a voting process is performed based on the temperature change stages corresponding to multiple target objects, and the current temperature change stage is determined according to the voting results.

[0148] Optionally, the processing module determines the current compensation amount from a preset compensation coefficient library based on the target temperature parameter and the current temperature change stage, including: determining two adjacent temperature nodes where the predicted temperature is located based on the predicted temperature; calling the corresponding compensation coefficient set from the preset compensation coefficient library based on the current temperature change stage; obtaining the compensation value corresponding to the two adjacent temperature nodes from the compensation coefficient set; and performing interpolation calculation on the compensation value corresponding to the two adjacent temperature nodes to obtain the current compensation amount.

[0149] Optionally, the processing module is also used to obtain an external reference temperature when the current temperature change phase is a constant temperature phase and the duration exceeds a preset time; determine the compensation residual based on the compensated output temperature and the external reference temperature; and correct the compensation coefficients of the corresponding temperature range in the compensation coefficient library based on the compensation residual.

[0150] Optionally, the processing module is also used to perform anomaly detection on the acquired temperature dataset; when it is detected that any temperature in the temperature dataset exceeds the preset upper limit, the temperature difference between any two temperature measuring points exceeds the preset threshold, the temperature change slope of any temperature measuring point exceeds the preset threshold, or the reading of any temperature sensor remains unchanged for a long time or deviates from the preset range, the system determines it as an anomaly and outputs alarm information.

[0151] The aforementioned temperature measurement system for the semiconductor furnace tube, by synchronously sampling and photoelectrically converting the reflected light corresponding to two preset wavelength bands, and combining it with feedforward compensation based on the physical characteristics of semiconductor devices, can reduce the impact of temperature drift of the detector and front-end circuit on the measurement results in advance during the signal acquisition stage. At the same time, by collecting the temperature at different preset locations inside the in-situ measurement device through multiple temperature sensors, and combining it with a pre-built thermal path model to predict the target temperature parameters and identify the current temperature change stage, and then determining the current compensation amount based on the compensation coefficient library corresponding to different temperature ranges and different change stages, can more accurately characterize the true thermal state of key components inside the device and dynamically compensate for temperature drift, thereby improving the accuracy, stability, and adaptability to complex thermal environment changes of wafer surface temperature measurement inside the semiconductor furnace tube.

[0152] Each module in the aforementioned temperature measurement system for semiconductor furnace tubes can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the computer device's memory as software, so that the processor can call and execute the corresponding operations of each module.

[0153] In one feasible embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the method steps in the above-described method for measuring the temperature of a semiconductor furnace tube.

[0154] In one feasible embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the method steps in the above-described method for measuring the temperature of a semiconductor furnace tube.

[0155] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0156] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0157] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for measuring the temperature of a semiconductor furnace tube, characterized in that, Applicable to in-situ measurement devices, the method includes: The digital voltage signal and temperature dataset are acquired. The digital voltage signal is obtained by synchronously sampling and photoelectric conversion of two reflected lights formed by two preset wavelengths of light irradiating the wafer surface inside the furnace tube, and then performing feedforward compensation based on the physical characteristics of the semiconductor device. The temperature dataset is acquired by multiple temperature sensors at different preset locations inside the in-situ measurement device. The original measured temperature is calculated based on the digital voltage signal; Based on the temperature dataset and the pre-built thermal path model, predict the target temperature parameters and identify the current temperature change stage; Based on the target temperature parameter and the current temperature change stage, the current compensation amount is confirmed from the preset compensation coefficient library, which is established during pre-calibration for different temperature ranges and different change stages. The original measured temperature is compensated based on the current compensation amount to obtain the compensated output temperature.

2. The method according to claim 1, characterized in that, The in-situ measurement device includes a data acquisition module installed inside the enclosure. The data acquisition module includes a detector and a signal conditioning unit installed on a circuit board. The signal conditioning unit includes a preamplifier and a reference power supply. The temperature dataset includes the detector temperature corresponding to the detector, the analog front-end temperature corresponding to the signal conditioning unit, and the ambient reference temperature corresponding to the location of the enclosure away from the heat source. Methods for obtaining digital voltage signals by feedforward compensation of two reflected lights that have undergone synchronous sampling and photoelectric conversion based on the physical characteristics of semiconductor devices include: The two reflected lights are converted into photoelectric signals to obtain detector output currents corresponding to two preset wavelength bands; Based on the current detector temperature and preset bias voltage, the dark current of the detector output current is compensated according to the pre-calibrated dark current and temperature characteristics to obtain the real photocurrent corresponding to the two preset bands. Based on the currently acquired detector temperature, the detector's responsivity in two preset bands is corrected according to the pre-calibrated responsivity temperature coefficient, and the actual photocurrent is corrected based on the corrected responsivity to obtain the corrected electrical signals corresponding to the two preset bands. Based on the currently acquired simulated front-end temperature, according to the pre-calibrated gain-temperature drift relationship and input bias current-temperature drift relationship, temperature drift compensation is performed on the gain and input bias current of the preamplifier to correct the voltage signal corresponding to the corrected electrical signal. The corrected voltage signal is converted from analog to digital to obtain digital voltage signals corresponding to two preset bands.

3. The method according to claim 2, characterized in that, The temperature dataset also includes the circuit board temperature corresponding to the circuit board. Methods for pre-building heat path models include: During the pre-calibration stage, the in-situ measuring device is placed in a temperature-controlled environment test chamber, and a temperature excitation is applied to the in-situ measuring device. The temperature excitation includes at least one of step temperature change, ramp temperature change, sinusoidal temperature change, and local heating. Under the temperature excitation, temperature data output by multiple temperature sensors located at preset positions inside the in-situ measuring device are simultaneously sampled; each preset position corresponds to one or more temperature measurement points. Based on the temperature data, a dynamic relationship of thermal coupling between multiple temperature measuring points and detectors is established according to thermal network theory, and its expression is as follows: in, For detector temperature, For the thermal time constant of the detector, For environmental reference temperature, To simulate front-end temperature, The temperature corresponding to the i-th circuit board, , and For coupling coefficients, For external heat flow input, The coupling coefficient corresponding to the external heat flow input. For bias terms; The model parameters in the thermally coupled dynamic relationship are extracted using a system identification method to obtain the thermal path model.

4. The method according to claim 1, characterized in that, The target temperature parameters include the predicted temperature and the temperature change slope; the temperature change stages include a heating stage, a cooling stage, and a constant temperature stage. The step of predicting target temperature parameters and identifying the current temperature change stage based on the temperature dataset and a pre-built thermal path model includes: The temperature dataset collected at the current moment is input into the thermal path model to obtain the predicted temperature of the target object at the next moment; the target object includes at least one of the following: a detector, a signal conditioning unit, a part of the enclosure away from the heat source, and a circuit board; The predicted temperatures corresponding to the most recent multiple sampling times of each target object are obtained, and each predicted temperature is fitted to obtain the temperature change slope corresponding to each target object. If the slope of the temperature change of any target object is greater than the preset heating threshold, the temperature change stage corresponding to that target object is considered to be the heating stage. If the slope of the temperature change of any target object is less than the preset cooling threshold, the temperature change stage corresponding to that target object is considered to be the cooling stage. If the slope of the temperature change of any target object is between the preset heating threshold and the preset cooling threshold, the temperature change stage corresponding to the target object is considered to be the isothermal stage. When there are multiple target objects, a voting process is performed based on the temperature change stages corresponding to the multiple target objects, and the current temperature change stage is determined according to the voting results.

5. The method according to claim 4, characterized in that, The step of determining the current compensation amount from a preset compensation coefficient library based on the target temperature parameter and the current temperature change stage includes: Based on the predicted temperature, determine the two adjacent temperature nodes where the predicted temperature is located; Based on the current stage of temperature change, the corresponding set of compensation coefficients is retrieved from the preset compensation coefficient library; Obtain the compensation values ​​corresponding to the two adjacent temperature nodes from the set of compensation coefficients; The compensation values ​​corresponding to the two adjacent temperature nodes are interpolated to obtain the current compensation amount.

6. The method according to claim 1, characterized in that, The step of calculating the original measured temperature based on the digital voltage signal includes: Calculate the corresponding two-color ratio based on the two digital voltage signals at different sampling times; Based on the pre-stored correspondence between temperature and ratio, calculate the instantaneous temperature value corresponding to each of the two-color ratios; The instantaneous temperature values ​​are sorted according to the sampling time to obtain the original measured temperature.

7. The method according to claim 1, characterized in that, The temperature change phase includes a constant temperature phase; the method further includes: If the current temperature change phase is a constant temperature phase and the duration exceeds the preset time, obtain the external reference temperature; The compensation residual is determined based on the compensated output temperature and the external reference temperature; Based on the compensation residual, the compensation coefficients in the corresponding temperature range in the compensation coefficient library are corrected.

8. The method according to claim 1, characterized in that, The method further includes: Anomaly detection is performed on the collected temperature dataset; When the system detects that any temperature in the temperature dataset exceeds a preset upper limit, the temperature difference between any two temperature measuring points exceeds a preset threshold, the slope of the temperature change at any temperature measuring point exceeds a preset threshold, or the reading of any temperature sensor remains unchanged for a long time or deviates from the preset range, the system determines it to be abnormal and outputs an alarm message.

9. A temperature measurement system for a semiconductor furnace tube, characterized in that, The system, located within an in-situ measuring device, includes: The acquisition module is used to acquire digital voltage signals and temperature datasets; wherein, the digital voltage signals are obtained by synchronously sampling and photoelectric conversion of two reflected lights formed by two preset wavelength light signals irradiating the wafer surface inside the furnace tube, and by feedforward compensation based on the physical characteristics of semiconductor devices; the temperature datasets are acquired by multiple temperature sensors at different preset locations inside the in-situ measurement device. The processing module is used to calculate the original measured temperature based on the digital voltage signal; predict the target temperature parameter based on the temperature dataset and a pre-built thermal path model, and identify the current temperature change stage; confirm the current compensation amount from a preset compensation coefficient library based on the target temperature parameter and the current temperature change stage, the compensation coefficient library being established during pre-calibration for different temperature ranges and different change stages; and compensate the original measured temperature based on the current compensation amount to obtain the compensated output temperature.

10. An in-situ measuring device, characterized in that, The device includes: The light source module is used to generate measurement light, separate the measurement light into two preset wavelength bands, and irradiate the wafer surface inside the furnace tube. The acquisition module is used to simultaneously sample two reflected lights generated on the wafer surface based on the optical signal, perform photoelectric conversion on them, and then perform feedforward compensation based on the physical characteristics of the semiconductor device to obtain a digital voltage signal. The measurement module includes multiple temperature sensors located at different preset positions inside the in-situ measurement device, used to collect temperature data sets; The temperature measurement system for a semiconductor furnace tube as described in claim 9 is configured to: calculate the original measured temperature based on the digital voltage signal; predict the target temperature parameter and identify the current temperature change stage based on the temperature dataset and a pre-built thermal path model; confirm the current compensation amount from a preset compensation coefficient library based on the target temperature parameter and the current temperature change stage, wherein the compensation coefficient library is established during pre-calibration for different temperature ranges and different change stages; and compensate the original measured temperature based on the current compensation amount to obtain the compensated output temperature.

11. The apparatus according to claim 10, characterized in that, The in-situ measuring device is partially housed inside the box. The acquisition module includes a detector and a signal conditioning unit mounted on a circuit board. The signal conditioning unit includes a preamplifier and a reference power supply. The preset location includes at least one of the following: the detector housing, near the preamplifier and the reference power supply, away from the heat source in the housing, and on the circuit board.

12. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1-8.

13. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1-8.

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