Semiconductor-based module high and low temperature test system

Abstract

The invention discloses a module high and low temperature test system based on a semiconductor, and the system comprises a hardware module which is used for controlling the temperature, transmitting data, and receiving an instruction; a control algorithm unit; the control algorithm module comprises a PID control module which optimizes temperature control by adjusting proportional, integral and differential parameters and improves the stability and response speed of the system by using a self-adaptive PID or fuzzy PID method. High temperature measurement precision can be realized by using a high-sensitivity sensor, errors can be reduced, control accuracy can be improved, novel technologies such as an MEMS actuator and the like are adopted, the temperature can be rapidly adjusted, the rapid change environment requirement can be met, meanwhile, through fuzzy logic and a reinforcement learning algorithm, the system can automatically adjust a control strategy according to real-time data, and the system is suitable for large-scale popularization and application. The method adapts to different working environments and conditions, combines edge calculation and deep learning technologies, can predict temperature changes, and takes measures in advance.

Description

Technical Field

[0001] The invention belongs to the technical field of semiconductor testing, and in particular relates to a semiconductor-based module high and low temperature testing system. Background Art

[0002] The semiconductor-based module high and low temperature test system refers to a system that uses semiconductor refrigeration technology to perform high and low temperature tests on modules.

[0003] The existing high and low temperature test system has the following problems:

[0004] The control software algorithm or hardware response speed may be delayed or deviated at extreme temperatures, resulting in inaccurate temperature control and inability to accurately synchronize the temperature setting with the actual temperature;

[0005] The temperature control, power supply, airflow and other subsystems of the test system may become unstable due to extreme temperature fluctuations or electrical interference, resulting in test failure or errors. Extreme temperature changes may cause the internal electronic components of the system to malfunction or the thermal management system to malfunction, especially in continuous temperature cycles. Summary of the invention

[0006] The object of the present invention is to provide a semiconductor-based module high and low temperature test system to solve the system stability problem raised in the above background technology and the problem of software control and temperature asynchronism.

[0007] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: a semiconductor-based module high and low temperature test system, which includes a hardware module for controlling temperature, transmitting data, and receiving instructions; a control algorithm unit; the control algorithm module includes a PID control module that optimizes temperature control by adjusting proportional, integral and differential parameters, and uses an adaptive PID or fuzzy PID method to improve the stability and response speed of the system, and a predictive control module that uses a model predictive control method to predict temperature based on a dynamic model of the system and adjust the control strategy in advance, and also includes a machine learning module that uses a machine learning algorithm to predict temperature and trains through historical data to improve control accuracy, and also includes a fuzzy controller that uses a control algorithm based on fuzzy logic, can handle uncertainty and nonlinear problems, has strong adaptability, and is suitable for temperature control in complex environments; a data acquisition frequency enhancement unit, which is used to collect and process temperature data at a high frequency within a specified time; an integrated optimization unit, which is used to combine multiple sensors and cooperate with edge devices to process data to achieve intelligent decision-making; an interactive interface for operators to intuitively monitor and control temperature.

[0008] As a preferred technical solution of the present invention, the hardware module is composed of a hardware module and a data acquisition and processing module, wherein the hardware module includes

[0009] Quantum dot temperature sensor: Use quantum dot-based temperature sensors, which have extremely high sensitivity and fast response time, and can detect temperature changes at the micron level;

[0010] MEMS Actuators: Tiny heaters and coolers using micro-electromechanical systems (MEMS) technology that are fast-response and highly efficient, capable of regulating temperature in a very short time.

[0011] Fiber optic temperature sensor: Utilizes fiber optic sensing technology to achieve remote temperature monitoring without being subject to electromagnetic interference, and is suitable for temperature collection in complex environments;

[0012] Self-powered module: Use thermoelectric power generation module (such as Seebeck effect) to convert ambient temperature difference into electrical energy to provide power for sensors and controllers, achieving self-powered.

[0013] As a preferred technical solution in the present invention, the data acquisition and processing module includes

[0014] Edge computing devices, such as NVIDIA Jetson Nano, are used for data processing to analyze temperature data in real time and make predictions, reducing data transmission delays;

[0015] High-frequency data acquisition card: Select a high-frequency data acquisition card that can support a sampling rate of several thousand hertz, combined with FPGA (field programmable gate array) to achieve ultra-high frequency data acquisition.

[0016] As a preferred technical solution in the present invention, the data acquisition frequency improvement unit includes a high-frequency sampling module that collects multiple temperature data in a short period of time and optimizes the data acquisition program, a data processing module that uses a fast signal processing algorithm to process the collected temperature data and reduce the impact of noise, and a real-time monitoring module that obtains temperature change information in a timely manner and performs dynamic adjustments by implementing a data monitoring system.

[0017] As a preferred technical solution in the present invention, the integrated optimization unit includes

[0018] Sensor fusion algorithm module, which is used to combine different types of sensor data and use Kalman filter or particle filter algorithm for data fusion to improve the accuracy and stability of temperature measurement;

[0019] Cloud-edge collaborative computing performs real-time data processing and control on edge devices, while uploading data to the cloud for larger-scale analysis and optimization to achieve intelligent decision-making.

[0020] As a preferred technical solution in the present invention, the interactive interface includes a virtual reality interface and an augmented reality auxiliary module.

[0021] As a preferred technical solution in the present invention, the integrated optimization unit is built with a feedback learning mechanism to continuously optimize the control algorithm through feedback and system operation data.

[0022] Compared with the prior art, the present invention has the following beneficial effects:

[0023] The use of highly sensitive sensors can achieve higher temperature measurement accuracy, reduce errors, and improve control accuracy. The use of new technologies such as MEMS actuators can quickly adjust the temperature to adapt to rapidly changing environmental requirements. At the same time, through fuzzy logic and reinforcement learning algorithms, the system can automatically adjust the control strategy according to real-time data to adapt to different working environments and conditions. Combined with edge computing and deep learning technology, temperature changes can be predicted, measures can be taken in advance, and temperature fluctuations can be reduced. Through sensor fusion technology, the stability of temperature monitoring can be improved, the impact of a single sensor failure on the system can be reduced, and redundant modules can be introduced into the system to ensure that the system can still operate normally when a part fails, thereby improving reliability. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 It is a system diagram of the present invention. DETAILED DESCRIPTION

[0025] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0026] See also Figure 1 The present invention provides a technical solution: a semiconductor-based module high and low temperature test system, the high and low temperature test system includes

[0027] Hardware module, used for temperature control, data transmission, and command reception;

[0028] Control algorithm unit; the control algorithm module includes a PID control module that optimizes temperature control by adjusting proportional, integral and differential parameters, and uses adaptive PID or fuzzy PID methods to improve the stability and response speed of the system, and a predictive control module that uses a model predictive control method to predict temperature based on the dynamic model of the system and adjust the control strategy in advance. It also includes a machine learning module that uses a machine learning algorithm to predict temperature and trains with historical data to improve control accuracy. It also includes a fuzzy controller that uses a control algorithm based on fuzzy logic, can handle uncertainty and nonlinear problems, has strong adaptability, and is suitable for temperature control in complex environments;

[0029] Data collection frequency enhancement unit, used to collect and process temperature data at a high frequency within a specified time;

[0030] Integrated optimization unit, used to combine multiple sensors and cooperate with edge devices to process data and achieve intelligent decision-making;

[0031] Interactive interface for operators to intuitively monitor and control temperature.

[0032] In this embodiment, the hardware module is composed of a hardware module and a data acquisition and processing module, wherein the hardware module includes

[0033] Quantum dot temperature sensor: Use quantum dot-based temperature sensors, which have extremely high sensitivity and fast response time, and can detect temperature changes at the micron level;

[0034] MEMS Actuators: Tiny heaters and coolers using micro-electromechanical systems (MEMS) technology that are fast-response and highly efficient, capable of regulating temperature in a very short time.

[0035] Fiber optic temperature sensor: Utilizes fiber optic sensing technology to achieve remote temperature monitoring without being subject to electromagnetic interference, and is suitable for temperature collection in complex environments;

[0036] Self-powered module: Use thermoelectric power generation module (such as Seebeck effect) to convert ambient temperature difference into electrical energy to provide power for sensors and controllers, achieving self-powered.

[0037] In this embodiment, the data acquisition and processing module includes

[0038] Edge computing devices, such as NVIDIA Jetson Nano, are used for data processing to analyze temperature data in real time and make predictions, reducing data transmission delays;

[0039] High-frequency data acquisition card: Select a high-frequency data acquisition card that can support a sampling rate of several thousand hertz, combined with FPGA (field programmable gate array) to achieve ultra-high frequency data acquisition.

[0040] In this embodiment, the data acquisition frequency improvement unit includes a high-frequency sampling module that collects multiple temperature data in a short period of time and optimizes the data acquisition program, a data processing module that uses a fast signal processing algorithm to process the collected temperature data and reduce the impact of noise, and a real-time monitoring module that obtains temperature change information in a timely manner and performs dynamic adjustments through the implementation of a data monitoring system.

[0041] In this embodiment, the integrated optimization unit includes

[0042] Sensor fusion algorithm module, which is used to combine different types of sensor data and use Kalman filter or particle filter algorithm for data fusion to improve the accuracy and stability of temperature measurement;

[0043] Cloud-edge collaborative computing performs real-time data processing and control on edge devices, while uploading data to the cloud for larger-scale analysis and optimization to achieve intelligent decision-making.

[0044] In this embodiment, the interactive interface includes a virtual reality interface and an augmented reality auxiliary module.

[0045] In this embodiment, a feedback learning mechanism is built into the integrated optimization unit to continuously optimize the control algorithm through feedback and system operation data.

[0046] Although embodiments of the present invention have been shown and described (see the above detailed description for details), it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to these embodiments without departing from the principles and spirit of the present invention, and the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A semiconductor-based module high and low temperature test system, characterized by: The high and low temperature test system includes Hardware module, used for temperature control, data transmission, and command reception; Control algorithm unit; the control algorithm module includes a PID control module that optimizes temperature control by adjusting proportional, integral and differential parameters, and uses adaptive PID or fuzzy PID methods to improve the stability and response speed of the system, and a predictive control module that uses a model predictive control method to predict temperature based on the dynamic model of the system and adjust the control strategy in advance. It also includes a machine learning module that uses a machine learning algorithm to predict temperature and trains with historical data to improve control accuracy. It also includes a fuzzy controller that uses a control algorithm based on fuzzy logic, can handle uncertainty and nonlinear problems, has strong adaptability, and is suitable for temperature control in complex environments; Data collection frequency enhancement unit, used to collect and process temperature data at a high frequency within a specified time; Integrated optimization unit, used to combine multiple sensors and cooperate with edge devices to process data and achieve intelligent decision-making; Interactive interface for operators to intuitively monitor and control temperature.

2. A semiconductor-based module high and low temperature test system according to claim 1, characterized in that: The hardware module is composed of a hardware module and a data acquisition and processing module, wherein the hardware module includes Quantum dot temperature sensor: Use quantum dot-based temperature sensors to detect temperature changes at the micron level; MEMS actuators: With fast response and high efficiency, they can adjust the temperature in a very short time. Fiber optic temperature sensor: Utilizes fiber optic sensing technology to achieve remote temperature monitoring without being affected by electromagnetic interference; Self-powered module: Use thermoelectric power generation module to convert ambient temperature difference into electrical energy to provide power for sensors and controllers, achieving self-powered.

3. A semiconductor-based module high and low temperature test system according to claim 2, characterized in that: The data acquisition and processing module includes Edge computing devices, which are used for data processing, real-time analysis of temperature data and prediction, reduce data transmission delays; High-frequency data acquisition card: Select a high-frequency data acquisition card that can support a sampling rate of several thousand Hz and combine it with FPGA to achieve ultra-high frequency data acquisition.

4. The semiconductor-based module high and low temperature test system according to claim 1, characterized in that: The data acquisition frequency improvement unit includes a high-frequency sampling module that collects multiple temperature data in a short period of time and optimizes the data acquisition program, a data processing module that uses a fast signal processing algorithm to process the collected temperature data and reduce the impact of noise, and a real-time monitoring module that obtains temperature change information in a timely manner and performs dynamic adjustments through the implementation of a data monitoring system.

5. The semiconductor-based module high and low temperature test system according to claim 1, characterized in that: The integrated optimization unit comprises Sensor fusion algorithm module, which is used to combine different types of sensor data and use Kalman filter or particle filter algorithm for data fusion to improve the accuracy and stability of temperature measurement; Cloud-edge collaborative computing performs real-time data processing and control on edge devices, while uploading data to the cloud for larger-scale analysis and optimization to achieve intelligent decision-making.

6. The semiconductor-based module high and low temperature test system according to claim 1, characterized in that: The interactive interface includes a virtual reality interface and an augmented reality auxiliary module.

7. The semiconductor-based module high and low temperature test system according to claim 1, characterized in that: The integrated optimization unit has a built-in feedback learning mechanism to continuously optimize the control algorithm through feedback and system operation data.

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