Differential pressure detection device, semiconductor device and pressure control method thereof

Abstract

The embodiment of the invention provides a pressure difference detection device, semiconductor equipment and a pressure control method thereof. The differential pressure detection device comprises a main pipeline, a motion module, a light source module and a detection module, the main pipeline is connected between the first input interface and the second input interface of the pressure difference detection device; the movement module is arranged on the main pipeline and is used for moving according to the pressure change of the first chamber and the second chamber; the light source module is arranged on the first input interface and is used for generating a light source emitted to the motion module and receiving reflected light of the light source reflected by the motion module; the detection module is used for calculating the pressure difference between the first chamber and the second chamber according to the reflection position of the reflected light. The pressure difference detection device has the characteristics of corrosion resistance and particle resistance, is more suitable for the silicon carbide epitaxial equipment process cavity, can detect the pressure change condition of the process cavity in real time, and improves the detection precision of the pressure difference.

Description

Technical Field

[0001] This disclosure relates to the field of semiconductor technology, and in particular to a differential pressure detection device, semiconductor equipment, and pressure control method thereof. Background Technology

[0002] Silicon carbide epitaxial equipment typically grows a high-quality silicon carbide epitaxial layer on a silicon carbide substrate, and the quality of this epitaxial layer has a significant impact on the performance of power semiconductors. Chamber pressure, as a critical element in the process, plays a vital role in the process results and consistency.

[0003] The substrate for epitaxial growth is placed on a tray and transferred from the wafer loading area to the process chamber via a robotic arm through the transfer chamber. Generally, the process chamber pressure is initially controlled at the process pressure (e.g., 100 mbar), and the transfer chamber pressure is controlled at the wafer transfer pressure (e.g., 104 mbar). After opening the valve, the tray with the substrate is fed into the process chamber for processing. After the process is completed, the tray with the substrate is transferred out of the process chamber. During the silicon carbide epitaxial growth process, the transfer chamber pressure is maintained at 104 mbar, and the process chamber pressure is maintained at 100 mbar. Current technologies primarily rely on pressure gauges to monitor the pressure in the transfer chamber and process chamber in real time. However, the accuracy and speed of pressure control in the process chamber are inextricably linked to the quality of the process results. Traditional chamber pressure control systems based on PID (proportional-integral-derivative) often rely on the skills and experience of the commissioning personnel to obtain the control system parameters through trial and error or empirical tuning. The control system parameters obtained in this way are often only applicable to a certain pressure range, and readjustment is still required when the pressure control range deviates from the set range. Summary of the Invention

[0004] This disclosure provides a differential pressure detection device, a semiconductor device, and a pressure control method thereof.

[0005] In a first aspect, embodiments of this disclosure provide a differential pressure detection device, including: a main pipeline, a motion module, a light source module, and a detection module;

[0006] The main pipeline is connected between the first input interface and the second input interface of the differential pressure detection device;

[0007] The motion module is disposed on the main pipeline and is used to move according to the pressure changes of the first chamber and the second chamber;

[0008] The light source module is disposed on the first input interface and is used to generate a light source that is directed toward the motion module, and to receive the reflected light from the light source after it has been reflected by the motion module.

[0009] The detection module is used to calculate the pressure difference between the first chamber and the second chamber based on the reflection position of the reflected light.

[0010] In a second aspect, embodiments of this disclosure provide a semiconductor device, including a transmission cavity, a process cavity, and the aforementioned differential pressure detection device;

[0011] The differential pressure detection device is disposed between the transmission chamber and the process chamber, and is used to detect the pressure difference between the transmission chamber and the process chamber.

[0012] Thirdly, embodiments of this disclosure provide a pressure control method for a semiconductor device, wherein the semiconductor device is the semiconductor device described in the second aspect; the method includes:

[0013] Obtain the pressure feedback value of the process chamber of the semiconductor device;

[0014] Obtain the pressure feedback value of the transmission cavity of the semiconductor device;

[0015] The differential pressure detection device of the semiconductor device detects the pressure difference between the process cavity and the transmission cavity based on the pressure feedback value of the process cavity and the pressure feedback value of the transmission cavity, and uses it as the differential pressure feedback value;

[0016] The actual pressure value of the process chamber is calculated based on the differential pressure feedback value and the pressure feedback value of the transmission chamber.

[0017] The pressure in the process chamber is controlled based on the actual pressure value.

[0018] The differential pressure detection device of this disclosure utilizes the pressure difference between the first and second chambers to drive a motion module on the main pipeline, and uses a light source module to reflect the motion of the motion module. The detection module calculates the pressure difference between the first and second chambers by detecting the emitted light. This differential pressure detection device is corrosion-resistant and particle-resistant, making it more suitable for the process chambers of silicon carbide epitaxial equipment. It can detect pressure changes in the process chamber in real time, improving the accuracy of differential pressure detection. Attached Figure Description

[0019] In the accompanying drawings of the embodiments disclosed herein:

[0020] Figure 1 This is a schematic diagram of the differential pressure detection device provided in the embodiments of this disclosure;

[0021] Figure 2 A schematic diagram of a sealing ring provided in an embodiment of this disclosure;

[0022] Figure 3 This is a schematic diagram of a motion guide rail provided in an embodiment of this disclosure;

[0023] Figure 4 A schematic diagram of a chamber pressure detection structure for a semiconductor device provided in an embodiment of this disclosure;

[0024] Figure 5 This is a schematic diagram of the structure of a semiconductor device in related technologies;

[0025] Figure 6 A flowchart of a pressure control method for a semiconductor device provided in an embodiment of this disclosure;

[0026] Figure 7 A schematic diagram of a pressure control method for a semiconductor device provided in an embodiment of this disclosure;

[0027] Figure 8 A block diagram of a process chamber adaptive pressure control system based on Logistic-SSA-PID provided in an embodiment of this disclosure;

[0028] Figure 9 A flowchart illustrating a method for adjusting PID parameters of a process cavity based on a logical chaotic mapping algorithm and a sparrow search algorithm, provided in this embodiment of the disclosure.

[0029] Figure 10 The flowchart below illustrates a method for evaluating adjusted PID parameters based on a pressure setpoint and actual pressure value of a process chamber, and determining target PID parameters based on the evaluation results, as provided in this embodiment of the disclosure.

[0030] Figure 11 A flowchart illustrating a method for calculating the fitness value of PID parameters based on the pressure setpoint and actual pressure value of the process chamber, as provided in this embodiment of the disclosure. Detailed Implementation

[0031] To enable those skilled in the art to better understand the technical solutions of this disclosure, the communication-sensing data processing method and computer-readable storage medium provided in the embodiments of this disclosure will be described in detail below with reference to the accompanying drawings.

[0032] The accompanying drawings of the embodiments disclosed herein are provided to further illustrate the embodiments of this disclosure and form part of the specification. They are used together with the detailed embodiments to explain this disclosure and do not constitute a limitation thereof. The above and other features and advantages will become more apparent to those skilled in the art from the description of the detailed embodiments with reference to the accompanying drawings.

[0033] Where there is no conflict, the various embodiments of this disclosure and the features thereof in the embodiments may be combined with each other.

[0034] The terminology used in this disclosure is for the purpose of describing particular embodiments only and is not intended to limit the disclosure. The term "and / or" as used in this disclosure includes any and all combinations of one or more of the associated enumerated entries. The singular forms "a" and "the" as used in this disclosure are also intended to include the plural forms, unless the context clearly indicates otherwise. The terms "comprising," "made of," etc., as used in this disclosure specify the presence of the stated feature, integral, step, operation, element, and / or component, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components, and / or groups thereof.

[0035] Unless otherwise specified, all terms used in this disclosure (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art. It will also be understood that terms such as those defined in commonly used dictionaries should be interpreted as having a meaning consistent with their meaning in the context of the relevant art and this disclosure, and will not be interpreted as having an idealized or overly formal meaning, unless expressly so defined in this disclosure.

[0036] Silicon carbide epitaxial equipment typically grows a high-quality silicon carbide epitaxial layer on a silicon carbide substrate, and the quality of this epitaxial layer has a significant impact on the performance of power semiconductors. Chamber pressure, as a critical element in the process, plays a vital role in the process results and consistency.

[0037] The substrate for epitaxial growth is placed on a tray and transferred from the wafer loading area to the process chamber via a robotic arm through the transfer chamber. Generally, the process chamber pressure is initially controlled at the process pressure (e.g., 100 mbar), and the transfer chamber pressure is controlled at the transfer pressure (e.g., 104 mbar). After opening the gate valve, the tray with the substrate is fed into the process chamber for processing. After the process is completed, the tray with the substrate is transferred out of the process chamber. During the silicon carbide epitaxial growth process, the transfer chamber pressure is maintained at 104 mbar, and the process chamber pressure is maintained at 100 mbar.

[0038] Current technologies primarily rely on pressure gauges to monitor the pressure in the transmission and process chambers in real time. However, the accuracy and speed of pressure control in the process chamber are inextricably linked to the quality of the process results. Using pressure gauges to detect and control the pressure in these chambers is susceptible to gauge drift, making accurate pressure detection impossible. The uncertainty of the gauge drift direction prevents a precise reflection of the actual chamber pressure. There is a certain deviation between the process chamber pressure and the target pressure. For example, if the desired control pressure is 100 mbar, the actual chamber pressure may be 90 mbar or even 110 mbar due to gauge drift. In such cases, special gases and particulate matter may enter the transmission chamber, contaminating it and damaging the equipment. Current technologies cannot effectively monitor the status of pressure gauges or provide rapid and accurate control of chamber pressure. While some solutions incorporate differential pressure detection devices, these devices only monitor the differential pressure and do not participate in the actual chamber pressure control.

[0039] Another existing technical solution involves obtaining the relationship between the current pressure value of the process chamber, a preset target value, and the pressure deviation value. When the pressure deviation value is less than a preset threshold, the current pressure gauge value is read, and the process gauge is automatically calibrated via software. This approach accurately controls the chamber pressure while avoiding gauge wear. The pressure deviation value is determined by calculating the pressure deviation of the process chamber using the test pressure value and a preset standard pressure value. A fitting function is constructed to calculate the predicted pressure value when the preset standard pressure value is the characteristic value. Simultaneously, when the pressure deviation value is less than the preset threshold, the current pressure measurement value is obtained. When the pressure deviation is greater than or equal to the preset threshold, an alarm is triggered.

[0040] The pressure deviation value in this scheme is calculated through a fitting relationship. Its accuracy largely depends on the accuracy of the standard pressure value and the fitting precision. The fitted value cannot truly represent the actual pressure in the chamber. Furthermore, this technology cannot monitor chamber pressure changes in real time and lacks real-time measurement and monitoring capabilities. When establishing the fitting function, it is necessary to fit test pressure values ​​obtained at different times and pressures, along with preset standard pressure values. Parameters cannot be adjusted online during the process. When the actual chamber pressure changes or the measured value drifts, it is impossible to determine which factor caused the pressure change. Secondly, when there is a large pressure deviation between the measured and predicted values, the chamber pressure cannot be automatically adjusted; it only alerts maintenance personnel to perform repairs via an alarm.

[0041] This disclosure addresses issues such as inaccurate process chamber pressure and untimely response of the pressure control system by providing a method for chamber pressure detection and control in a silicon carbide epitaxial growth apparatus. This method avoids problems such as unqualified process results or backflow of process gases caused by inaccurate process pressure or untimely control system response. While ensuring pressure control accuracy, it improves the response speed and dynamic performance of the control system.

[0042] The differential pressure detection device of this disclosure utilizes the pressure difference between the first and second chambers to drive a motion module on the main pipeline, and uses a light source module to reflect the motion of the motion module. The detection module calculates the pressure difference between the first and second chambers by detecting the emitted light. This differential pressure detection device is corrosion-resistant and particle-resistant, making it more suitable for the process chambers of silicon carbide epitaxial equipment. It can detect pressure changes in the process chamber in real time, improving the accuracy of differential pressure detection.

[0043] In this embodiment of the disclosure, the differential pressure detection device can be applied to, but is not limited to, the pressure control of the chamber of a silicon carbide epitaxial device, and can be applied to any feasible chamber pressure control scheme.

[0044] The embodiments of this disclosure will be described in detail below.

[0045] This disclosure provides a differential pressure detection device, such as... Figure 1 As shown, the differential pressure detection device 14 may include, but is not limited to: main pipeline 141, motion module 142, light source module 143 and detection module 144;

[0046] The main pipeline 141 is connected between the first input interface 145 and the second input interface 146 of the differential pressure detection device 14.

[0047] The motion module 142 is mounted on the main pipeline 141 and is used to move according to the pressure changes of the first chamber and the second chamber.

[0048] The light source module 143 is disposed on the first input interface 145 and is used to generate a light source that is directed toward the motion module 142 and to receive the reflected light after the light source is reflected by the motion module 142.

[0049] The detection module 144 is used to calculate the pressure difference between the first chamber and the second chamber based on the reflection position of the reflected light.

[0050] Traditional differential pressure detection devices detect the pressure difference between two chambers by deforming a diaphragm connected to the two chambers and combining it with an operational amplifier circuit. However, such devices suffer from low detection accuracy and poor linearity. To address these shortcomings, this disclosure provides a differential pressure detection device 14, as follows: Figure 1As shown, the pressure difference is used to drive the moving structure in the pipeline, and the force of the interaction between the magnetic poles drives the measured structure to move, thereby measuring the air pressure difference (or pressure difference) in the chamber. The pressure difference detection method of the embodiment of this disclosure is a non-contact measurement method, which has the characteristics of corrosion resistance and particle resistance, and is more suitable for the air pressure difference detection of the process chamber of silicon carbide epitaxial equipment.

[0051] In this embodiment of the disclosure, the first chamber and the second chamber can be connected to the first input interface 145 and the second input interface 146 of the differential pressure detection device via transfer pipes, respectively.

[0052] In the embodiments disclosed herein, such as Figure 1 As shown, the motion module 142 may include, but is not limited to: a magnetic motion structure 1421, an elastic damping device 1422, and a magnetic induction structure 1423.

[0053] A magnetic motion structure 1421 is disposed within the main pipeline 141 and is used to move within the main pipeline according to the pressure difference between the first chamber and the second chamber.

[0054] The elastic damping device 1422 is fixed to the first input interface 145 and rigidly connected to the magnetic motion structure 1421. It is used to drive the magnetic motion structure 1421 to move when the pressure difference between the first chamber and the second chamber is greater than the elastic damping of the elastic damping device 1422.

[0055] The magnetic induction structure 1423 is located outside the main circuit and is used to follow the movement of the magnetic motion structure, receive the light source emitted by the light source module, and reflect the reflected light back to the light source module.

[0056] In this embodiment, the pressure change between the two chambers drives the magnetic motion structure 1421 in the main pipeline 141 to move, and the magnetic motion structure 1421 can in turn drive the magnetic induction structure 1423 to move in a non-contact manner. The magnetic motion structure 1421 is rigidly connected to the elastic damping device 1422. When the pressure difference formed by the pressure change at both ends of the main pipeline 141 is greater than the elastic damping of the elastic damping device 1422, it pushes the magnetic motion structure 1421 in the main pipeline 141 to move, thereby driving the compression or extension of the elastic damping device 1422. When the pressure difference force and the magnetoelastic damping force reach a dynamic balance, the magnetic motion structure 1421 stops moving.

[0057] In the embodiments disclosed herein, such as Figure 1 As shown, the light source module 143 may include, but is not limited to, a light source emitting device 1431 and a light source detection device 1432;

[0058] A light source emitting device 1431 is disposed on the first input interface 145 and is used to generate a light source directed toward the magnetic induction structure 1423.

[0059] The magnetic induction structure 1423 is also used to project the reflected light onto the light source detection device 1432 when the light source is reflected.

[0060] The light source detection device 1432 is located on the same side as the light source emitting device 1431. When the magnetic motion structure 1421 is located in the physical middle area of ​​the main pipeline 141, the reflected light can illuminate the preset origin of the light source detection device 1432, and the air pressure of the first chamber and the second chamber are equal. The reflection position of the reflected light on the light source detection device 1432 moves with the movement of the magnetic motion structure 1421.

[0061] The detection module 144 is used to calculate the pressure difference between the first chamber and the second chamber based on the displacement of the reflection position relative to the origin.

[0062] In this embodiment, during the movement of the magnetic induction structure 1423 according to the change in pressure difference, the light emitted by the light source emitting device 1431 is reflected by the magnetic induction structure 1423 and projected onto the light source detection device 1432. The origin of the light source detection device 1432 corresponds to the physical intermediate area of ​​the magnetic motion structure 1421 and the magnetic induction structure 1423 in the main pipeline 141. At this time, the pressure difference at both ends of the pressure difference detection device 14 is equal, and the change in the position of the reflected light point can directly reflect the change in the current pressure difference.

[0063] In this embodiment, the light source detection device 1432 includes a grating ruler with a light detection structure and a photoelectric sensor. The grating ruler includes a scale grating and a reading head. Light diffracts on the scale grating, thereby producing alternating bright and dark moiré fringes. The photoelectric sensor detects the width change of the moiré fringes and converts this width change into a distance change, i.e., displacement. At this time, the change in pressure difference is converted into the displacement of the reflected light point through the movement of the magnetic motion structure 1421 and the magnetic induction structure 1423.

[0064] In this embodiment, the detection module 144 mainly includes a microprocessor and a data processing unit. The microprocessor has established a univariate polynomial function Y = Ax³ + Bx² + Cx + D based on the mapping relationship between the standard pressure difference and the displacement of the reflected light spot. X represents the distance the reflected light spot moves on the light source detection device 1432, and Y represents the calculated pressure difference value. In practical applications, when the pressure at the first input interface 145 of the pressure difference detection device 14 is greater than the pressure at the second input interface 146, it will drive the magnetic motion structure 1421 to move to the right. The magnetic induction structure 1423 follows the movement of the magnetic motion structure 1421, causing the position of the reflected light spot received by the structure 7 to move downward. At this time, the change in pressure difference can be calculated based on the downward displacement of the reflected light spot. Conversely, when the structure 5 follows the movement of the structure 2 to move to the left, the position of the reflected light spot received by the light source detection device 1432 moves upward. At this time, the change in pressure difference can be calculated based on the upward displacement of the reflected light spot. The differential pressure value measured by this differential pressure detection device 14 is divided by the origin. When the reflected light point is lower than the origin, the differential pressure measurement value can be positive, indicating that the pressure of the first input interface 145 is higher than the pressure of the second input interface 146. When the reflected light point is higher than the origin, the differential pressure measurement value can be negative, indicating that the pressure of the first input interface 145 is lower than the pressure of the second input interface 146.

[0065] In the embodiments disclosed herein, such as Figure 2 As shown, the magnetic motion structure 1421 is provided with a magnetic metal partition with a sealing ring 1421-1 to prevent the two ends of the main pipeline 141 from being connected.

[0066] In this embodiment, a guide device is provided in the main pipeline 141, and the magnetic motion structure 1421 can move in a directional manner along the guide device to avoid situations such as the magnetic motion structure 1421 tilting.

[0067] In the embodiments disclosed herein, such as Figure 3 As shown, a motion guide rail 147 is provided between the first input interface 145 and the second input interface 146, and the motion guide rail 147 is located above the main pipeline 141.

[0068] The magnetic induction structure 1423 is disposed on the motion guide rail 147 and moves along the motion guide rail 147 during the motion of following the magnetic motion structure 1421.

[0069] In this embodiment, the motion guide rail 147 can be a horizontal guide rail for laser drawing. The magnetic induction structure 1423 moves along the smooth horizontal guide rail with the movement of the magnetic motion structure 1421. The contact position between the magnetic induction structure 1423 and the motion guide rail 147 is as smooth as possible to ensure minimal friction. Furthermore, the gap between them is as small as possible to ensure minimal positional offset. The above structure ensures better cooperation with the guide rail while maintaining the directional movement of the magnetic induction structure 1423.

[0070] This disclosure also provides a semiconductor device, such as... Figure 4 As shown, it includes a transmission cavity 12, a process cavity 13, and the aforementioned differential pressure detection device 14;

[0071] The differential pressure detection device 14 is installed between the transmission chamber 12 and the process chamber 13. The differential pressure detection device 14 is used to detect the pressure difference between the transmission chamber 12 and the process chamber 13.

[0072] In this embodiment of the disclosure, the semiconductor device may refer to a silicon carbide epitaxial device.

[0073] In this embodiment of the disclosure, the semiconductor device may further include a controller; the process chamber 13 is provided with a first pressure gauge and a first butterfly valve, and the transfer chamber 12 is provided with a second pressure gauge;

[0074] The first pressure gauge is used to detect the pressure value of the process chamber 13 and serve as the pressure feedback value of the process chamber 13.

[0075] The second pressure gauge is used to detect the pressure value of the transmission cavity 12 and serve as the pressure feedback value of the transmission cavity 12.

[0076] The first butterfly valve is used to control the pressure in the process chamber;

[0077] The controller is used to control the opening degree of the first butterfly valve based on the pressure feedback value of the first pressure gauge, the pressure feedback value of the second pressure gauge, and the pressure difference detected by the differential pressure detection device 14.

[0078] In this embodiment, the semiconductor device mainly comprises three parts: a loading chamber 11, a transfer chamber 12, and a process chamber 13. Valves exist between each chamber to isolate them. Its basic structure is as follows: Figure 5 As shown.

[0079] In this embodiment of the disclosure, the aforementioned first chamber may include, but is not limited to, the process chamber 13, and the second chamber may include, but is not limited to, the transmission chamber 12.

[0080] In this embodiment of the disclosure, the chamber pressure detection device for a semiconductor device (such as a silicon carbide epitaxial device) mainly includes: a pressure gauge 12-1 (i.e., a second pressure gauge) for detecting the pressure of the transmission chamber 12, a pressure gauge 13-1 (i.e., a first pressure gauge) for detecting the pressure of the process chamber, and a differential pressure detection device 14 for detecting the pressure difference between the chambers, such as... Figure 4 As shown, the pressure gauge is responsible for real-time detection of changes in chamber pressure, and the differential pressure detection device is responsible for real-time monitoring of the pressure difference between the two chambers.

[0081] In the embodiments disclosed herein, such as Figure 4 As shown, the differential pressure detection device 14 of this embodiment can be set up by building hardware pipelines. For example, pipelines are led out from the transmission chamber 12 and the process chamber 13 respectively, and a differential pressure detection device 14 is added between the two connecting pipelines to detect the gas pressure difference between the transmission chamber 12 and the process chamber 13.

[0082] In this embodiment of the disclosure, the differential pressure detection device 14, combined with the valve body (such as the first butterfly valve) of the first chamber and the vacuum pipeline of the first chamber, can constitute a chamber pressure control system for the first chamber; the differential pressure detection device 14, combined with the valve body (such as the first butterfly valve) of the second chamber and the vacuum pipeline of the second chamber, can constitute a chamber pressure control system for the second chamber.

[0083] In this embodiment, for example, the differential pressure detection device 14, combined with the valve body (such as the first butterfly valve) of the process chamber and the vacuum pipeline of the process chamber, can constitute a chamber pressure control system for the process chamber; the differential pressure detection device 14, combined with the valve body (such as the first butterfly valve) of the transmission chamber and the vacuum pipeline of the transmission chamber, can constitute a chamber pressure control system for the transmission chamber. The chamber pressure control of the transmission chamber and the process chamber mainly relies on the real-time detection of chamber pressure by a pressure gauge, and the chamber pressure is controlled by the opening degree of the pumping air path and the first butterfly valve. The detailed pressure control scheme includes: the host computer sets a target control pressure value as the setpoint for the control system, compares it with the pressure gauge detection value, and outputs an error amount; the controller calculates the opening degree of the first butterfly valve based on this error amount. By controlling the opening degree of the first butterfly valve, the pumping speed of the vacuum pipeline is adjusted, thereby regulating the chamber pressure.

[0084] This disclosure provides a pressure control method for a semiconductor device, such as... Figure 6 , Figure 7 As shown, the method may include steps S101-S105:

[0085] S101. Obtain the pressure feedback value of the process cavity of the semiconductor equipment.

[0086] S102. Obtain the pressure feedback value of the transmission cavity of the semiconductor device.

[0087] S103. The differential pressure detection device of the semiconductor equipment detects the pressure difference between the process cavity and the transmission cavity based on the pressure feedback value of the process cavity and the pressure feedback value of the transmission cavity, and uses it as the differential pressure feedback value.

[0088] S104. Determine the actual pressure value of the process chamber based on the differential pressure feedback value and the pressure feedback value of the transmission chamber.

[0089] S105. Control the pressure in the process chamber based on the actual pressure value.

[0090] In this embodiment of the disclosure, obtaining the pressure feedback value of the process cavity of the semiconductor device may include:

[0091] The PID parameters of the process chamber are adjusted based on the logical chaotic mapping algorithm and the sparrow search algorithm;

[0092] The pressure in the process chamber is controlled based on the adjusted PID parameters to obtain the pressure feedback value of the process chamber.

[0093] Traditional chamber pressure control systems based on PID parameter tuning lack adaptive capability. They often rely on trial and error or empirical tuning to obtain the PID parameters for a specific scenario. This method heavily depends on the skill and experience of the tuning personnel, and the trial-and-error pressure control parameters are often only applicable to a certain pressure range. Deviating from this range leads to deterioration in the dynamic performance of the control system, even to the point of failure. Therefore, this disclosure proposes a chamber pressure adaptive control system based on the Logistic-SSA-PID (Logical-Sparrow Search-Proportional, Integral, Derivative) algorithm. This solves the shortcomings of traditional pressure control systems, such as large human error, difficulty in parameter tuning, and poor dynamic performance, thereby improving the control capability of the pressure control system for different process gas flow rates and pressure ranges.

[0094] Currently, chamber pressure control mainly employs PID controllers, requiring online measurement and manual tuning of PID parameters for the controlled object. The tuning of these PID parameters significantly impacts the performance of the control system. In practical applications, the controlled objects, such as online measurement systems like TM (magnetic particle detection) pressure gauges and differential pressure detection devices, as well as valve bodies (e.g., butterfly valves) and vacuum exhaust systems, exhibit highly nonlinear, time-varying uncertainties, and pure time delays. This makes adjusting the control parameters for chamber pressure difficult, and the influence of noise and disturbances prevents pressure control from achieving the desired effect. Therefore, this disclosure proposes an adaptive PID pressure control method that allows PID parameter tuning to be independent of the object's mathematical model and enables self-tuning of the PID parameters to meet real-time control requirements.

[0095] The Sparrow Search Algorithm (SSA) is a novel intelligent optimization algorithm with high search accuracy and fast convergence speed. Optimizing the PID parameters of a PID control system using this algorithm can effectively improve the dynamic characteristics and response speed of the control system, while also enhancing its disturbance resistance. Current Sparrow Search Algorithms generate the initial positions of the sparrow population randomly, leading to uneven spatial distribution and low ergodicity, directly impacting the algorithm's optimization performance and search efficiency. Therefore, this embodiment combines a Logistic chaotic mapping algorithm to initialize the initial positions of the sparrow population, enhancing the quality and uniformity of the initial positions and facilitating a more comprehensive search within the search space. The block diagram of the process chamber adaptive pressure control system based on Logistic-SSA-PID is shown below. Figure 8 As shown.

[0096] In the embodiments disclosed herein, such as Figure 9 As shown, adjusting the PID parameters of the process chamber based on the logical chaotic mapping algorithm and the sparrow search algorithm may include steps S201-S203:

[0097] S201. Correspond the sparrow population in the sparrow search algorithm to the PID parameters; the PID parameters include: proportional parameters, integral parameters, and derivative parameters.

[0098] In this embodiment of the disclosure, the sparrow population in the sparrow search algorithm is correlated with the PID parameters, including:

[0099] In the sparrow search algorithm, each sparrow population corresponds to a set of PID parameters; the number of sparrow populations is equal to the number of sets of PID parameters.

[0100] The three sparrow species in each sparrow population are mapped to the proportional, integral, and derivative parameters of the corresponding PID parameters; the three sparrow species can include: discoverer, joiner, and scout.

[0101] In this embodiment, the population size of the sparrows and the dimension of the variable to be optimized can be initialized first. The population size corresponds to the number of combinations of PID parameters in the control system (i.e., the number of combinations of proportional, integral, and derivative parameters), i.e., the number of PID parameter sets. Let the population size of the sparrows be Num, and the position of the i-th sparrow be:

[0102] R i =[R 1i R 2i R 3i ]; (1)

[0103] Where 1i, 2i, and 3i represent the dimensions of the variables to be optimized, i = 1, ..., Num, which is the number of individual sparrows in the sparrow population. Here, R... 1i The corresponding Kp parameter (i.e., proportional parameter) in the PID parameters of a PID control system, R 2i The Ki parameter (i.e., integral parameter) in the PID parameters of a PID control system corresponds to R. 3i This corresponds to the Kd parameter (i.e., the derivative parameter) in the PID parameters of a PID control system. Assuming the initial sparrow population size is 30, this corresponds to 30 combinations of Kp, Ki, and Kd parameters.

[0104] S202. The position of each sparrow in the sparrow population is initialized using a logical chaotic mapping algorithm.

[0105] In this embodiment of the disclosure, the initialization of the position of each sparrow in the sparrow population using a logical chaotic mapping algorithm may include: initializing the position of each sparrow based on the following second calculation formula:

[0106] R j(i+1) =ρR ji (1-R ji );

[0107] Where ρ is the control parameter of the logical chaotic mapping, j represents the j-th sparrow population, j = 1, 2, 3, and R 1i The proportional parameter R corresponds to the PID parameters. 2i The integral parameter R corresponds to the integral parameter in the PID parameters. 3i The derivative parameter in the corresponding PID parameters, i represents the i-th sparrow in the sparrow population, and i is a positive integer.

[0108] In this embodiment, the default value range of ρ is [0,4]. When ρ = 4, the chaotic sequence generated by the logical chaotic mapping is in a completely chaotic state, that is, the data is distributed according to a specific pattern. j = 1,…,Num, which corresponds to the number of sparrows in the population, that is, the number of possible combinations of PID parameters.

[0109] In this embodiment, a logical chaotic mapping algorithm is used to initialize the initial position of each individual sparrow, which can enhance the initial position distribution of the entire sparrow population and increase global search capability. The initial position of each sparrow population corresponds to a set of Kp (proportional parameter), Ki (integral parameter), and Kd (derivative parameter) parameters in the PID control system. After initialization by the logical chaotic mapping algorithm, the positions of each individual sparrow can be distributed in a relatively uniform manner.

[0110] In this embodiment of the disclosure, after obtaining the location of individual sparrows according to the above scheme, the location of each individual sparrow can be output to assign the location of each individual sparrow in each sparrow population to the PID parameter.

[0111] S203. Assign the position of the individual sparrow to the PID parameter.

[0112] In this embodiment of the disclosure, each of the three types of sparrows described above may include one sparrow;

[0113] Assigning the position of an individual sparrow to the PID parameter can include:

[0114] For each sparrow population, the positions of the three sparrows in the population are assigned to the proportional, integral, and derivative parameters of the PID parameters corresponding to the sparrow population.

[0115] In this embodiment of the disclosure, when a sparrow population contains only three sparrows, each sparrow represents a sparrow species, or a sparrow role, namely: discoverer, joiner, and scout. These three roles can be mapped to the three parameters in the PID parameters.

[0116] In this embodiment of the disclosure, when there are multiple sparrow populations, it is necessary to map the three sparrow species in each population to the three parameters in the PID parameters.

[0117] In this embodiment of the disclosure, the differential pressure feedback value can be obtained through the differential pressure detection device 14 described above.

[0118] In this embodiment of the disclosure, determining the actual pressure value of the process chamber based on the differential pressure feedback value and the pressure feedback value of the transmission chamber may include:

[0119] The difference between the pressure feedback value and the differential pressure feedback value of the transmission cavity is calculated and used as the true pressure value of the process cavity.

[0120] In this embodiment, to determine the magnitude and direction of the error in the chamber pressure measurement, the control system can detect the pressure PV1 of the transmission chamber, the pressure PV2 of the process chamber, and the chamber pressure difference (i.e., the pressure difference feedback value) PV3 in real time after normal operation. The chamber pressure difference value is directional; in this embodiment, the pressure difference value is the difference between the pressure in the transmission chamber and the pressure in the process chamber. Based on the real-time measurement value, the true pressure of the process chamber can be calculated as P2, as shown in the following formula: P2 = PV1 - PV3.

[0121] In this embodiment of the disclosure, for example, the measured value PV1 of the transmission cavity is 104 mbar and the pressure difference value PV3 between the two chambers is 3 mbar. At this time, the actual pressure P2 of the process cavity can be considered to be 101 mbar, but the reading of the pressure gauge PV2 of the process cavity may be 100 mbar.

[0122] In this embodiment of the disclosure, controlling the pressure in the process chamber based on the actual pressure value includes:

[0123] Based on the pressure setpoint and actual pressure value of the process chamber, the adjusted PID parameters of the process chamber are evaluated, and the target PID parameters are determined according to the evaluation results.

[0124] The pressure in the process chamber is controlled using target PID parameters.

[0125] In this embodiment of the disclosure, before evaluating the adjusted PID parameters of the process chamber based on the pressure setpoint and the actual pressure value of the process chamber, and determining the target PID parameters based on the evaluation results, the method may further include:

[0126] The pressure in the process chamber is controlled based on the adjusted PID parameters to obtain the pressure feedback values ​​of the process chamber and the transmission chamber.

[0127] Obtain the pressure difference setting value between the process chamber and the transmission chamber, as well as the pressure setting value of the transmission chamber;

[0128] The pressure setting value of the process chamber is calculated based on the pressure feedback value of the process chamber, the pressure feedback value of the transmission chamber, the differential pressure setting value, and the pressure setting value of the transmission chamber.

[0129] In this embodiment, to ensure the accuracy of pressure detection in the process chamber, the pressure gauge of the process chamber needs to be evaluated before each use. Specifically, the pressure setting value for the transmission chamber is SP1, the pressure difference setting value between the process chamber and the transmission chamber is SP3, and the pressure setting value for the transmission chamber is SP2; the pressure feedback value for the transmission chamber is PV1, the pressure difference feedback value between the process chamber and the transmission chamber is PV3, and the pressure feedback value for the process chamber is PV2. The pressure setting value of the process chamber can be adjusted in real time according to the pressure in the process chamber. This avoids process problems caused by the pressure gauge.

[0130] In this embodiment of the disclosure, the pressure setting value of the process chamber is calculated based on the pressure feedback value of the process chamber, the pressure feedback value of the transmission chamber, the differential pressure setting value, and the pressure setting value of the transmission chamber, including: calculating the pressure setting value of the process chamber based on the following first calculation formula:

[0131] SP2=SP1-SP3-((PV1-PV2)-PV3);

[0132] Among them, SP2 is the pressure setting value of the process chamber, SP1 is the pressure setting value of the transmission chamber, SP3 is the differential pressure setting value, PV1 is the pressure feedback value of the transmission chamber, PV2 is the pressure feedback value of the process chamber, and PV3 is the differential pressure feedback value.

[0133] In the embodiments disclosed herein, such as Figure 10 As shown, based on the pressure setpoint and actual pressure value of the process chamber, the adjusted PID parameters are evaluated, and the target PID parameters are determined according to the evaluation results, including steps S301-S303:

[0134] S301. Calculate the fitness value of PID parameters based on the pressure setpoint and actual pressure value of the process chamber.

[0135] In the embodiments disclosed herein, such as Figure 11 As shown, calculating the fitness values ​​of the PID parameters based on the pressure setpoint and actual pressure value of the process chamber may include steps S401-S403:

[0136] S401. Determine the fitness function; this fitness function is used to measure the quality of the location of each sparrow population and the quality of the PID parameters.

[0137] In this embodiment, a fitness function `fit` is determined. This fitness function measures the quality of a sparrow's position, specifically the impact of each set of control system parameters (Kp (proportional parameter), Ki (integral parameter), and Kd (derivative parameter)) on the performance of the control system. Furthermore, the fitness function also determines the sparrow's identity and position update rules. In this embodiment, the fitness function can be, but is not limited to, the mean absolute error (MAE) function, where MAE is the average absolute error between the measured value and the set value.

[0138] S402. Input the pressure setpoint and actual pressure value of the process chamber obtained based on each set of PID parameters into the fitness function to calculate the fitness value of each sparrow population and its corresponding PID parameters.

[0139] In this embodiment of the disclosure, when the fitness function includes a mean absolute error function and the fitness value includes the mean absolute error, the pressure setpoint and actual pressure value of the process chamber obtained based on each set of PID parameters are input into the fitness function to calculate the fitness value of each sparrow population and its corresponding PID parameters, including: calculating the mean absolute error function value based on the following third calculation formula:

[0140]

[0141] Where MAE is the mean absolute error, t is the sampling time, tol is the total sampling period, SP2 is the pressure setpoint of the process chamber, and P2 is the actual pressure value of the process chamber.

[0142] In this embodiment, the initial sparrow individual positions can be sequentially assigned to the KP, KI, and KD values ​​of the PID parameters. The mean absolute error (MAE) corresponding to the sparrow individual positions in each sparrow population is calculated based on the system's dynamic response performance. Comparing the MAEs yields the position of the sparrow individual with the smallest mean absolute error, as well as the corresponding KP, KI, and KD parameter values.

[0143] S403. Obtain a fitness value that meets the second preset requirement from multiple fitness values.

[0144] In this embodiment of the disclosure, when the fitness function includes the mean absolute error function and the fitness value includes the mean absolute error, the fitness value that meets the second preset requirement may include, but is not limited to, the mean absolute error with the smallest value.

[0145] S302. If the fitness value meets the first preset requirement, the assigned PID parameter is used as the target PID parameter to control the pressure of the process chamber.

[0146] In this embodiment of the disclosure, when the fitness function includes the mean absolute error function and the fitness value includes the mean absolute error, the first preset requirement may include, but is not limited to: the minimum mean absolute error is less than a preset expected value.

[0147] In this embodiment of the disclosure, when the mean absolute error with the smallest value is less than the preset expected value, the performance of the control system under the PID parameters can be considered acceptable. At this time, the KP, KI, and KD parameter values ​​corresponding to the sparrow population with the smallest mean absolute error can be used as the global optimal solution, that is, as the target PID parameters, and input into the PID controller.

[0148] S303. If the fitness value does not meet the first preset requirement, update the position of the sparrow population and assign the updated position of the sparrow individuals to the PID parameter. Control the pressure of the process chamber based on the reassigned PID parameter to obtain the pressure setpoint and actual pressure value of the process chamber. Then return to the step of calculating the fitness value of the PID parameter based on the pressure setpoint and actual pressure value of the process chamber until the fitness value meets the first preset requirement or reaches the preset maximum number of iterations.

[0149] In an embodiment of the present disclosure, when the average absolute error with the smallest value is greater than or equal to a preset expected value, the sparrow individuals update their own positions according to a certain rule, that is, update the values of the KP, KI, and KD parameters, and control the pressure of the process chamber based on the updated values of the KP, KI, and KD parameters. Based on this control, the pressure set value and the true pressure value of the process chamber are obtained again, the fitness value of the PID parameters is calculated, and the fitness value is judged, so as to enter the iterative process until the average absolute error with the smallest value is less than the preset expected value or the maximum number of iterations is reached, and the target PID parameters are obtained.

[0150] In an embodiment of the present disclosure, the above update of the positions of the sparrow population may include: updating the positions of each sparrow of the corresponding type in the sparrow population according to the position update rules of the discoverers, the position update rules of the joiners, and the position update rules of the scouts in the sparrow search algorithm respectively.

[0151] In each iteration process, the individuals in each sparrow population can be divided into discoverers, joiners, and scouts. The discoverers are responsible for finding food and leading the movement of the group, and the proportion in the group is about 10% - 20%. In each iteration process, the position update rule of the discoverers is shown as the following calculation formula:

[0152]

[0153] where, T is the maximum number of iterations, and tt is the current number of iterations. R tt i represents the position of the i-th sparrow when the number of iterations is tt, that is, the values of the KP, KI, and KD parameters corresponding to the i-th sparrow at the tt-th iteration. λ is a random number with a value range between (0, 1], and J is a random number that follows a normal distribution. P represents a 1×3-dimensional matrix, and the value of each element in the matrix is 1. A is the warning average absolute error value, that is, the average absolute error value corresponding to the oscillation and divergence of the control system; ST is the safety average absolute error value, that is, the control system parameter value corresponding to the convergence of the control system. When A < ST, it means that the environment around the sparrow population is safe, and the search range can be expanded to help the population obtain the optimal solution. The controller parameters can meet the requirements for the stability of the control system, and adjusting the controller parameters within the vicinity of this parameter will not cause problems to the system. If A ≥ ST, it means that there is danger in the environment around the sparrow population. At this time, the population stops foraging activities and transfers to a safe environment. That is, the controller parameters may affect the stability of the control system, causing the system to enter a control state such as oscillation and divergence, and ultimately leading to system maladjustment. Therefore, the controller parameters are not adjusted within the vicinity of this parameter, and the optimization is transferred to the vicinity of the relatively safe controller parameters.

[0154] The joiner follows the discoverer's activities, moving towards the discoverer's location corresponding to the optimal fitness value during position iteration and updates. That is, during parameter optimization, the KP, KI, and KD parameter values ​​corresponding to the sparrow individuals who are joiners are optimized towards the KP, KI, and KD parameter values ​​corresponding to the sparrow individuals with the lowest fitness value among the discoverer sparrow individuals.

[0155] If the fitness of the control system parameters corresponding to the location of the newcomer is higher than that corresponding to the location of the discoverer, the newcomer will replace the discoverer's position. If the newcomer is extremely hungry, it will move to another area to forage. The newcomer's position update rule is calculated as follows:

[0156]

[0157] Among them, R tt+1 find-best The optimal location for the discoverer, i.e., the control system parameter value corresponding to the individual sparrow that discovered it; R t tworst Let be the position of the worst individual in the sparrow population after t iterations, i.e., the control system parameter value corresponding to the sparrow with the worst fitness value in the population; A represents a 1×3 matrix, where the elements are randomly assigned to either 1 or -1. + =AT(AAT)-1. P represents a 1×3 matrix, where each element has a value of 1. When i>Num / 2, it indicates that the i-th participant is in a state of hunger and will go to other places to continue hunting. That is, the controller parameters corresponding to the participant cannot find better control system parameters near the current parameter values. At this time, the control system parameters are increased or decreased in other directions to find other optimal combinations of KP, KI, and KD parameters; otherwise, the controller parameters search for better control system parameter combinations near the current optimal solution.

[0158] Sparrow populations randomly select individuals as scouts. When a scout senses danger, sparrows on the periphery move to a safer area, while sparrows in the center move randomly. Similarly, a set of PID parameters is randomly selected from all possible controller parameter combinations (i.e., PID parameter combinations), sent to the control system, and its mean absolute error is calculated. If the mean absolute error of the control system parameters at this point is greater than the mean absolute error of the current optimal control system parameters, then the control system parameters move towards the direction corresponding to the optimal absolute error; otherwise, they move randomly near the control system parameters corresponding to the optimal absolute error. The scout position update rule is shown in the following formula:

[0159]

[0160] Among them, Rtt best R represents the current globally optimal position of the individual sparrow, i.e., the optimal combination of control system parameters KP, KI, and KD. tt worst The current position of the worst-case sparrow individual is represented by the worst combination of parameters KP, KI, and KD in the control system; τ and κ are both random numbers, where τ is the step-size control vector following a normal distribution, and κ is a random number ranging from [-1, 1]; f i t i f i t best f i t worst These represent the fitness value of the current sparrow individual, the global best fitness value, and the global worst fitness value, respectively; ψ is a very small positive constant. The fitness value here is the mean absolute error value.

[0161] In this embodiment of the disclosure, after multiple iterations, if the fitness value is less than the preset expected value (e.g., the error value) or the maximum number of iterations is reached, the global optimal solution is output as the target PID parameter to achieve optimal control performance.

[0162] In this embodiment of the disclosure, the Logistic-SSA-PID (or simply Logistic-SSA) control method uses the process chamber pressure setpoint SP2 as the control system input value and the actual chamber pressure P2 as the real-time measurement value of the system. A closed-loop PID control system is established based on the deviation between the two, and the Logistic optimization sparrow search algorithm is applied to find the optimal control system parameter values.

[0163] In this embodiment of the disclosure, after obtaining the target PID parameters through the above scheme, the pressure of the process chamber can be controlled by PID based on the target PID parameters.

[0164] The embodiments disclosed herein include at least the following beneficial effects:

[0165] 1. A non-contact differential pressure detection device is proposed, which can effectively avoid the deposition of particulate matter or corrosive gas, thereby changing the deformation capacity of the diaphragm and improving the measurement accuracy of the differential pressure detection device.

[0166] 2. A calculation scheme for automatically setting the pressure setpoint of the process chamber is proposed, which avoids the problem of gas entering the transmission chamber due to excessive pressure in the process chamber, avoids equipment alarms, shutdowns and special gas backflow caused by process chamber pressure detection errors, and effectively increases equipment safety.

[0167] 3. It can monitor the pressure gauge status of the process chamber in real time, providing a reliable reference for the full life cycle management of the pressure gauge's life and reliability.

[0168] 4. The Logistic-SSA-PID control method initializes the initial position of each sparrow individual through Logistic chaotic mapping, and uses the sparrow search algorithm to iterate and optimize multiple times to find the most suitable PID parameters. This effectively solves the shortcomings of traditional pressure control systems, such as large human error, difficulty in parameter tuning, and poor dynamic performance during parameter tuning. It also effectively solves the problems of unreasonable parameter settings and low robustness of traditional PID controllers, and improves the control capability of pressure control systems for different process gas flow and pressure ranges.

[0169] 5. Adjusting PID parameters based on the sparrow search algorithm can effectively improve the dynamic characteristics and response speed of the control system, while also enhancing its disturbance rejection capability. Adjusting PID parameters based on the logical chaotic mapping algorithm enhances the initial population quality and distribution uniformity in the sparrow search algorithm, facilitating a more comprehensive search within the search space. Furthermore, it enables the tuning of PID parameters used for chamber pressure regulation to be independent of the object's mathematical model and manual adjustment, achieving self-tuning of PID parameters and meeting the requirements of real-time chamber pressure control, thus improving pressure control accuracy.

[0170] Those skilled in the art will understand that all or some of the functional modules / units disclosed above can be implemented as software, firmware, hardware, or suitable combinations thereof.

[0171] In hardware implementations, the division between functional modules / units mentioned in the above description does not necessarily correspond to the division of physical components; for example, a physical component may have multiple functions, or a function or step may be executed by several physical components working together.

[0172] Some or all of the physical components may be implemented as software executed by a processor, such as a central processing unit (CPU), digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit (ASIC). Such software may be distributed on a computer-readable medium, which may include computer storage media (or non-transitory media) and communication media (or transient media). As is known to those skilled in the art, the term computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technique for storing information (such as computer-readable instructions, data structures, program modules, or other data). Computer storage media include, but are not limited to, random access memory (RAM, more specifically SDRAM, DDR, etc.), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory (FLASH) or other disk storage; read-only optical disc (CD-ROM), digital versatile disc (DVD) or other optical disc storage; magnetic cartridges, magnetic tapes, disk storage or other magnetic storage; and any other media that can be used to store desired information and can be accessed by a computer. Furthermore, as is known to those skilled in the art, communication media typically contain computer-readable instructions, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information delivery medium.

[0173] This disclosure has disclosed exemplary embodiments, and although specific terminology has been used, it is for general illustrative purposes only and should not be construed as limiting. In some instances, it will be apparent to those skilled in the art that features, characteristics, and / or elements described in conjunction with particular embodiments may be used alone, or in combination with features, characteristics, and / or elements described in conjunction with other embodiments, unless otherwise expressly indicated. Therefore, those skilled in the art will understand that various changes in form and detail may be made without departing from the scope of this disclosure as set forth by the appended claims.

Claims

1. A differential pressure detection device, characterized in that, include: Main circuit, motion module, light source module, and detection module; The main pipeline is connected between the first input interface and the second input interface of the differential pressure detection device; The motion module is disposed on the main pipeline and is used to move according to the pressure changes of the first chamber and the second chamber; The light source module is disposed on the first input interface and is used to generate a light source that is directed toward the motion module, and to receive the reflected light from the light source after it has been reflected by the motion module. The detection module is used to calculate the pressure difference between the first chamber and the second chamber based on the reflection position of the reflected light.

2. The differential pressure detection device according to claim 1, characterized in that, The motion module includes: a magnetic motion structure, an elastic damping device, and a magnetic induction structure; The magnetic motion structure is disposed within the main pipeline and is used to move within the main pipeline according to the pressure difference between the first chamber and the second chamber. The elastic damping device is disposed in the main pipeline and fixed to the first input interface, and is rigidly connected to the magnetic motion structure. It is used to drive the magnetic motion structure to move when the pressure difference between the first chamber and the second chamber is greater than the elastic damping of the elastic damping device. The magnetic induction structure is disposed outside the main circuit and is used to follow the movement of the magnetic motion structure, receive the light source emitted by the light source module, and reflect the reflected light back to the light source module.

3. The differential pressure detection device according to claim 2, characterized in that, The light source module includes: a light source emitting device and a light source detection device; The light source emitting device is disposed on the first input interface and is used to generate a light source directed toward the magnetic induction structure; The magnetic sensing structure is also used to ensure that the reflected light is projected onto the light source detection device when the light source is reflected. The light source detection device is located on the same side as the light source emitting device. When the magnetic motion structure is located in the physical middle area of ​​the main pipeline, the reflected light can illuminate the preset origin of the light source detection device, and the air pressure of the first chamber and the second chamber are equal. The reflection position of the reflected light on the light source detection device moves with the movement of the magnetic motion structure. The detection module is used to calculate the pressure difference between the first chamber and the second chamber based on the displacement of the reflection position relative to the origin.

4. The differential pressure detection device according to claim 2, characterized in that, The main pipeline is provided with a guide structure, and the magnetic motion structure can move in a directional manner along the guide structure.

5. The differential pressure detection device according to claim 2, characterized in that, A motion guide rail is provided between the first input interface and the second input interface, and the motion guide rail is located above the main pipeline; The magnetic induction structure is disposed on the motion guide rail and moves along the motion guide rail during the movement of following the magnetic motion structure.

6. A semiconductor device, characterized in that, Includes a transmission cavity, a process cavity, and a differential pressure detection device as described in any one of claims 1-5; The differential pressure detection device is disposed between the transmission chamber and the process chamber, and is used to detect the pressure difference between the transmission chamber and the process chamber.

7. The semiconductor device according to claim 6, characterized in that, It also includes a controller; the process chamber is equipped with a first pressure gauge and a first butterfly valve, and the transmission chamber is equipped with a second pressure gauge; The first pressure gauge is used to detect the pressure value of the process chamber and serve as the pressure feedback value of the process chamber. The second pressure gauge is used to detect the pressure value of the transmission cavity and serve as the pressure feedback value of the transmission cavity; The first butterfly valve is used to control the pressure in the process chamber; The controller is used to control the opening degree of the first butterfly valve based on the pressure feedback value of the first pressure gauge, the pressure feedback value of the second pressure gauge, and the pressure difference detected by the differential pressure detection device.

8. A pressure control method for a semiconductor device, characterized in that, The semiconductor device is the semiconductor device according to claim 7; the method includes: Obtain the pressure feedback value of the process chamber of the semiconductor device; Obtain the pressure feedback value of the transmission cavity of the semiconductor device; The differential pressure detection device of the semiconductor device detects the pressure difference between the process cavity and the transmission cavity based on the pressure feedback value of the process cavity and the pressure feedback value of the transmission cavity, and uses it as the differential pressure feedback value; The actual pressure value of the process chamber is determined based on the differential pressure feedback value and the pressure feedback value of the transmission chamber. The pressure in the process chamber is controlled based on the actual pressure value.

9. The pressure control method for a semiconductor device according to claim 8, characterized in that, The control of the pressure in the process chamber based on the actual pressure value includes: Based on the pressure setpoint of the process chamber and the actual pressure value, the adjusted PID parameters of the process chamber are evaluated, and the target PID parameters are determined according to the evaluation results. The pressure in the process chamber is controlled using the target PID parameters.

10. The pressure control method for a semiconductor device according to claim 9, characterized in that, Before evaluating the adjusted PID parameters of the process chamber based on the pressure setpoint and the actual pressure value, and determining the target PID parameters based on the evaluation results, the method further includes: The pressure of the process chamber is controlled based on the adjusted PID parameters to obtain the pressure feedback value of the process chamber and the pressure feedback value of the transmission chamber. Obtain the pressure difference setting value between the process chamber and the transmission chamber, as well as the pressure setting value of the transmission chamber; The pressure setting value of the process chamber is calculated based on the pressure feedback value of the process chamber, the pressure feedback value of the transmission chamber, the differential pressure setting value, and the pressure setting value of the transmission chamber.

11. The pressure control method for a semiconductor device according to claim 10, characterized in that, The step of calculating the pressure setting value of the process chamber based on the pressure feedback value of the process chamber, the pressure feedback value of the transmission chamber, the differential pressure setting value, and the pressure setting value of the transmission chamber includes: calculating the pressure setting value of the process chamber based on the following first calculation formula: SP2=SP1-SP3-((PV1-PV2)-PV3); Wherein, SP2 is the pressure setting value of the process chamber, SP1 is the pressure setting value of the transmission chamber, SP3 is the differential pressure setting value, PV1 is the pressure feedback value of the transmission chamber, PV2 is the pressure feedback value of the transmission chamber, and PV3 is the differential pressure feedback value.

12. The pressure control method for a semiconductor device according to claim 8, characterized in that, Determining the true pressure value of the process chamber based on the differential pressure feedback value and the pressure feedback value of the transmission chamber includes: The difference between the pressure feedback value of the transmission cavity and the differential pressure feedback value is calculated and used as the true pressure value of the process cavity.

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