Intelligent sensor experiment teaching platform

Abstract

The invention discloses an intelligent sensor experiment teaching platform, which comprises an intelligent sensor experiment unit, an intelligent sensor experiment teaching development module and intelligent sensor experiment teaching software, and is characterized in that the intelligent sensor experiment unit is used for completing output, transmission and detection of set physical quantities and simulation of a temperature and humidity change working environment; the intelligent sensor experiment teaching development module is used for receiving sensor output signals and running and displaying experiment teaching software; the intelligent sensor experiment teaching software realizes multifunctional and intelligent experiment teaching according to sensor data, and the experiment teaching content comprises a sensor calibration experiment, a filtering experiment, a nonlinear correction experiment, a temperature compensation experiment and a data wireless communication experiment. The experiment teaching platform has the advantages of being powerful in function, high in universality, high in intelligent degree, rich in experiment function module and high in innovativeness, students are helped to master development and application of intelligent sensors, and the innovation ability of the students is enhanced.

Description

Technical Field

[0001] The invention belongs to the field of sensor experiment teaching equipment development, and in particular relates to an intelligent sensor experiment teaching platform. Background Art

[0002] Sensors are devices used to detect various information such as physical quantities, chemical quantities, and biomass. They convert this information into electrical signals or other forms for further processing, storage, and transmission. Sensors are an important foundation for daily life, modern industry, and scientific research, and are key components for achieving automation and intelligence. However, traditional sensors have simple structures, single functions, and are more dependent on external data processing systems. Their limitations are becoming increasingly apparent, and their applications are gradually limited in the era of industrial informatization. The intelligent sensor system integrates functions such as microprocessors, memory, and communication modules on the basis of traditional sensors. It can realize data collection, processing, analysis, and transmission, and even has certain autonomous decision-making capabilities. It has the characteristics of multi-functional integration, data processing, support for networking, and real-time communication. It is the mainstream direction of the future development of sensor technology. It will continue to integrate more functions and deeply integrate with technologies such as artificial intelligence, the Internet of Things, and 5G.

[0003] At present, the sensor experimental teaching equipment on the market is relatively old, with slow iteration and update speed, low intelligence, disconnection from actual industry applications, and lack of interaction with students. Most of its teaching course experimental projects remain on the basic application of traditional sensors, only involving the functional verification of sensors, unable to provide students with a platform for innovative thinking, and are not suitable for meeting the application needs in modern industrial and intelligent scenarios.

[0004] Therefore, in order to solve the above-mentioned problems in the application of sensor experimental teaching equipment, it is urgent to design an intelligent sensor experimental teaching platform with strong versatility, high intelligence, rich experimental function modules, high degree of innovation, strong interactive performance and compatible with modern industrial applications. Summary of the invention

[0005] Purpose of the invention: The purpose of the invention is to provide an intelligent sensor experimental teaching platform with rich experimental types and powerful functions.

[0006] Technical solution: The intelligent sensor experiment teaching platform of the present invention comprises: an intelligent sensor experiment unit, an intelligent sensor experiment teaching development module and an intelligent sensor experiment teaching software running on the intelligent sensor experiment teaching development module;

[0007] The intelligent sensor experimental unit is used to complete the output, transmission, detection of set physical quantities and the simulation of the working environment with temperature and humidity changes;

[0008] The intelligent sensor experimental teaching development module is used to realize the reception and processing of sensor output signals and the operation and display of experimental teaching software;

[0009] The intelligent sensor experiment teaching software realizes multifunctional experiment teaching according to sensor data, and its functions include: experiment background introduction and course teaching, experiment equipment operation status detection and control, measurement result real-time display and drawing, experiment teaching module display and operation, experiment process recording, system communication mode configuration, experiment result submission and evaluation, experiment teaching software update and iteration and artificial intelligence voice interaction; among them, the display and operation of the experiment teaching module includes sensor calibration experiment, sensor filtering experiment, sensor nonlinear correction experiment, sensor temperature compensation experiment and sensor data wireless communication experiment.

[0010] Optionally, the intelligent sensor experimental unit includes an intelligent sensor controller, a multi-channel signal transmission device, multiple sensors, a temperature and humidity sensitive unit, a high and low temperature humidity control box and a safety protection cover. The temperature and humidity sensitive unit is integrated in the package of each sensor. The intelligent sensor controller is used to generate set physical quantities, and realizes software-based equipment control and operation monitoring through manual operation and parameter setting, or through multiple communication methods such as RS232, USB, and WIFI. The multi-channel signal transmission device provides connection ports for at least 15 sensors. The multi-channel signal transmission device and multiple sensors are arranged in a high and low temperature humidity control box under the temperature and humidity experiment. The multi-channel signal transmission device and multiple sensors are arranged in a safety protection cover under non-temperature and humidity experiments, so as to realize isolation of the multi-channel signal transmission device and multiple sensors from the outside world.

[0011] Optionally, the multiple sensors are of the same type but of different prices and performances, and their performance differences are compared based on a teaching experiment project to achieve performance comparison of different sensors. Based on compensation type experiments in the teaching experiment project, the improvement in sensor performance after compensation and the effectiveness of the software compensation algorithm are verified.

[0012] Optionally, the intelligent sensor experiment teaching development module includes: an electronic computer, an embedded development board, a wireless communication module and an electronic display screen. The measurement signal output by the intelligent sensor experiment unit is transmitted to the electronic computer or the embedded development board. The intelligent sensor experiment teaching software runs on the electronic computer or the embedded development board to process and analyze the measurement signal to obtain experimental results. The electronic display screen serves as a display terminal for the intelligent sensor experiment teaching software.

[0013] Optionally, the embedded development board has extra-large memory and multi-core processor, and provides multiple interface options including IIC interface, SPI interface, SATA interface, USB port, HDMI port, VGA interface, MIPI interface, audio jack, microSD card slot and Ethernet interface; the embedded development board supports multiple operating systems such as Raspbian, Linux, RISC and Windows; the electronic computer and embedded development board can be connected to wireless communication modules to realize multiple wireless networking methods such as WIFI, Bluetooth and ZigBee.

[0014] Optional, the experimental background introduction and course teaching functions include experimental background introduction, experimental safety training and assessment, and experimental teaching and real-time operation guidance; the experimental equipment operation status detection and control functions include monitoring the experimental equipment operation status, equipment remote control, experimental equipment use reservation, equipment automatic protection, data monitoring and alarm, error repair guide and automatic repair, and hierarchical setting of experimental equipment control permissions; the experimental process recording function includes experimental process recording and playback and experimental log recording; the experimental result submission and evaluation function includes experimental result statistics and analysis; the experimental teaching software update and iteration function includes software operating system update, software teaching content update and software experimental module update; the artificial intelligence voice interaction function includes the experimental teaching software artificial intelligence voice assistant.

[0015] Optionally, in the sensor calibration experiment, you can choose to import existing calibration data or start a new calibration experiment. If you import existing calibration data, the calibration experiment will end; if you choose to start a new calibration experiment, you need to add calibration points. After adding the set number of calibration points, import each calibration point into the intelligent sensor controller; at each set calibration point, after the output of the intelligent sensor controller stabilizes, the calibration experiment program will record the data value of the sensor output at this time; after the sensor output data values ​​corresponding to all calibration points are recorded, the software interface will draw a calibration result graph and export the calibration data.

[0016] Optionally, in the sensor filtering experiment, you can select the filtering algorithms provided by the experimental teaching software, including first-order filtering, median filtering, weighted mean filtering, sliding average filtering and Kalman filtering, or manually enter a new filtering algorithm program. After selecting the filtering algorithm, the experimental teaching software will draw a real-time curve of the output data changing with time before and after filtering. In the filtering interface, you can start and stop the sensor output data recording function, and after the data recording is completed, calculate the standard deviation of the saved data segment after being processed by each filtering algorithm as a standard for evaluating the effect of the filtering algorithm.

[0017] Optionally, in the sensor nonlinear correction experiment, you can select the nonlinear correction algorithm provided by the experimental teaching software, including table lookup method, correction function method, algebraic interpolation method, least squares method and neural network method, or manually input a new nonlinear correction algorithm program. After completing the sensor calibration process and selecting the correction algorithm, the experimental teaching software will output the corrected sensor measurement results in real time. In the nonlinear correction experiment interface, combined with the intelligent sensor controller, select and record the measurement results of multiple test points within the sensor range, and calculate the nonlinear parameters of the sensor before and after correction by each algorithm as a standard for evaluating the effectiveness of different correction methods.

[0018] Optionally, in the sensor temperature compensation experiment, combine the intelligent sensor controller and the high and low temperature humidity control box to select and record the data of multiple temperatures and test points of the physical quantity to be measured within the sensor range and working temperature range, or import existing temperature experimental data; based on the temperature compensation experimental data, select the temperature compensation algorithm provided by the experimental teaching software, including polynomial fitting method, neural network method, support vector machine, correlation vector machine, spline interpolation method, or manually enter a new temperature compensation algorithm program. After selecting the temperature compensation algorithm, a temperature compensation model will be established based on the experimental data, and the result after sensor temperature compensation will be output in real time; reselect the temperature and test points of the physical quantity to be measured, obtain the experimental data before and after compensation, and draw the curve of the change of the physical quantity measurement value with temperature before and after compensation to compare the effects of each temperature compensation algorithm.

[0019] Optional, the sensor data wireless communication experiment includes: turning on and off the Bluetooth, WIFI, and ZigBee communication methods in the experimental teaching development module, and configuring the port numbers of the WIFI and ZigBee communication methods; during the experiment, students can use self-designed WeChat applets, mobile phone applications, and computer applications based on the smart sensor course to try to use WiFi, Bluetooth, and ZigBee communication methods to receive the operating data of the experimental teaching development module, and remotely monitor and control the progress of the experiment.

[0020] Beneficial effects: Compared with the prior art, the significant technical effects of the present invention are as follows: (1) The design concept of the present invention has the versatility of intelligent sensor experimental teaching, and its experimental teaching platform supports one-to-many teaching experiments with students, and its teaching experiment carrier also supports the selection of different types of sensors; (2) The present invention integrates many experimental teaching functions, provides a rich variety of experiments, and the experimental principles involved are basic and important. The experimental effects are clear and intuitive, which can well meet the experimental teaching objectives of intelligent sensor related courses; (3) The present invention focuses on ensuring the safety of experimental personnel, provides a safety protection cover on hardware, provides safety education and training and assessment on experimental teaching software, provides abnormal monitoring and fault diagnosis and self-processing of experimental equipment, and minimizes the occurrence of experimental accidents; (4) The present invention has a high degree of intelligence and strong innovation. On the basis of integrating a microprocessor, a memory and a communication module, it can realize the collection, processing, analysis and transmission of sensor data, and can provide extended functions related to sensor experimental teaching. The experimental teaching platform is easy to iterate and update the hardware and software, and can be updated in time to make it fit the future development direction of sensor technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 A structural block diagram of an intelligent sensor experimental teaching platform provided by an embodiment of the present invention;

[0022] Figure 2 A schematic diagram of the functional structure of the intelligent sensor experiment teaching software under the intelligent sensor experiment teaching platform provided by the embodiment of the present invention;

[0023] Figure 3 A schematic diagram of an intelligent sensor experimental teaching platform device provided by an embodiment of the present invention;

[0024] Figure 4 A schematic diagram of the workflow of the intelligent sensor experimental teaching platform provided by an embodiment of the present invention;

[0025] Figure 5 A schematic diagram of a detailed flow chart of a sensor calibration experiment of an intelligent sensor experiment teaching software provided in an embodiment of the present invention;

[0026] Figure 6 A schematic diagram of the refinement process of the sensor filtering experiment of the intelligent sensor experiment teaching software provided by the embodiment of the present invention;

[0027] Figure 7 A schematic diagram of a detailed flow chart of a sensor nonlinear correction experiment of an intelligent sensor experiment teaching software provided in an embodiment of the present invention;

[0028] Figure 8 A schematic diagram of the detailed flow of the sensor temperature compensation experiment of the intelligent sensor experiment teaching software provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0029] The technical solution of the present invention is further described below in conjunction with the accompanying drawings.

[0030] The present invention designs an intelligent sensor experimental teaching platform, and selects pressure sensors as experimental teaching carriers. Because pressure sensors have a wide range of applications, mature production technology, relatively simple working principles, and high reliability, they have important sensor experimental teaching significance. Therefore, the embodiment of the present invention will build an intelligent sensor experimental teaching platform based on pressure sensors.

[0031] Figure 1 The following is a block diagram of the structure of an intelligent sensor experimental teaching platform provided by an embodiment of the present invention. Figure 1 As shown in the figure, the intelligent sensor experimental teaching platform includes an intelligent sensor experimental unit, an intelligent sensor experimental teaching development module, and an intelligent sensor experimental teaching software running on the intelligent sensor experimental teaching development module. Among them, the intelligent pressure controller in the intelligent sensor experimental unit built based on the pressure sensor is responsible for generating the pressure signal, and the multi-channel gas connection table is used as a pressure signal transmission device. The pressure sensor detects the pressure signal, converts it into an electrical signal, and then connects it to the intelligent sensor experimental teaching development module. The intelligent sensor experimental teaching development module is the hardware foundation of the experimental teaching platform, which is mainly responsible for receiving and processing sensor signals, running the experimental teaching software, and transmitting and storing sensor data. The intelligent sensor experimental teaching software can run on an electronic computer or embedded development board. It is an important implementation carrier of this experimental teaching platform. Its functions include but are not limited to experimental background introduction and course teaching, experimental equipment operation status detection and control, real-time display and drawing of measurement results, display and operation of experimental teaching modules, experimental process recording, system communication mode configuration, submission and evaluation of experimental results, update and iteration of experimental teaching software and artificial intelligence voice interaction. It can run a variety of experiments based on intelligent sensor teaching, including but not limited to sensor calibration experiments, filtering experiments, nonlinear correction experiments, temperature compensation experiments, and data wireless communication experiments. The functional structure diagram of the above intelligent sensor experimental teaching software is shown as follows: Figure 2 In some experiments, relatively basic examples can be provided, and the experimental teaching software is also programmable, allowing students to add new experimental methods, which helps to cultivate students' innovative ability.

[0032] The experimental background introduction and principle teaching functions in the intelligent sensor experimental teaching software are specifically implemented as follows:

[0033] In the experimental background introduction and principle teaching function interface, you can choose to play videos about mature application cases and cutting-edge development directions of pressure sensors in multiple fields such as industry, automobiles, medical care, and aerospace in the software interface, and introduce the important role of pressure sensors in different fields, explaining why pressure sensors have important practical significance.

[0034] In the interface of experimental background introduction and principle teaching function, you can choose to play the experimental safety training courseware in the software interface. The teaching content of this part includes the introduction of experimental safety operating procedures, reminders of important experimental safety precautions, judgment of equipment abnormalities, and demonstration of emergency disposal methods. You can also set up experimental safety knowledge training assessment on this interface, and only allow students who pass the assessment to reserve experimental equipment and participate in experimental courses. Through experimental safety teaching and assessment, the possibility of injury to experimental personnel due to equipment failure and human operation errors can be reduced.

[0035] In the experimental background introduction and principle teaching function interface, you can turn on the real-time teaching operation guidance function. After enabling this function, the experimental teaching software will provide students with experimental operation guidance in the form of text, voice or video, and remind them of the experimental progress, safety matters and operating specifications in real time.

[0036] The experimental equipment operation status detection and control function in the intelligent sensor experimental teaching software is specifically implemented as follows:

[0037] In the experimental equipment operation status detection and control function interface, the operation status of each experimental equipment can be monitored in real time. The monitored equipment includes intelligent pressure controllers, pressure sensors, electronic computers, embedded development boards, and high and low temperature humidity control boxes. The monitored equipment project information includes usage time, operation records, operation data, and equipment failures. Due to the high cost of intelligent pressure controllers and high and low temperature humidity control boxes, this function interface can be used to make advance reservations for experimental equipment, thereby reducing the number of expensive equipment purchased, reducing experimental construction costs, and improving the utilization rate of expensive experimental equipment.

[0038] In the experimental equipment operation status detection and control function interface, the equipment automatic protection function can be turned on. After this function is turned on, the experimental teaching development module will collect data from the pressure sensor, temperature and humidity sensitive unit and intelligent pressure controller in real time, and judge and prompt the accuracy of the experimental operation and parameter setting; after this function is turned on, the experimental teaching software will also monitor the received data in real time. If the data is abnormal or exceeds the experimental safety range, it will automatically evacuate the pressure controller to restore it to atmospheric pressure, interrupt the experiment in time, and remotely notify the experimental administrator and equipment manufacturer if necessary; after this function is turned on, the experimental teaching software will analyze the received experimental data and provide possible causes of alarm errors, including intelligent pressure controller setting errors, intelligent pressure controller equipment abnormalities, pressure sensor equipment abnormalities, gas connection hose / gas connection table leakage, and abnormal working environment; after this function is turned on, the experimental teaching software will also provide repair guidance corresponding to the error type and try to start the automatic repair function to reduce the possibility of human repair errors.

[0039] In the experimental equipment operation status detection and control function interface, the experimental equipment control permissions can be managed in a hierarchical manner. Teachers, experimental administrators and equipment manufacturer users can be granted advanced permissions to manage and maintain experimental equipment; for student users, low-level permissions can be set to open the corresponding experimental equipment and experimental teaching software operation permissions as needed according to the experimental project to reduce the risk of student users' misoperation of equipment.

[0040] The display and operation functions of the experimental teaching module in the intelligent sensor experimental teaching software include sensor calibration experiment, filtering experiment, nonlinear correction experiment, temperature compensation experiment and data wireless communication experiment. The specific implementation is as follows:

[0041] In the sensor calibration experiment, the sensor calibration experiment interface can be entered from the experimental teaching software interface. By manually adding pressure calibration points, the pressure points set in the calibration experiment are set with the intelligent pressure controller and the ADC original values ​​received by the electronic computer or embedded development board at this moment are recorded. Then, the calibration pressure points and the corresponding ADC original values ​​recorded during the experiment are used as calibration experiment data. At the same time, the data can be exported for use in subsequent experiments.

[0042] In the sensor calibration experiment, the calibration experiment interface allows you to choose to import existing calibration files. You can import the calibration files in the device memory or external storage device into the experimental teaching software to complete the pressure sensor calibration process.

[0043] In the sensor filtering experiment, you can enter the sensor filtering experiment interface from the experimental teaching software interface. The interface has a variety of filtering algorithms to choose from, including first-order filtering, median filtering, weighted mean filtering, sliding average filtering, and Kalman filtering. After selecting the filtering algorithm, the received original value is calculated in real time, and the filtered result is displayed in real time or a curve chart showing the filtering result changing over time is drawn.

[0044] In the sensor filtering experiment, you can choose to add a filtering algorithm on the filtering experiment interface. This function will pop up a code box on the interface for students to enter a new filtering algorithm program. After adding a new program, the original functions of the experimental teaching software will not be affected.

[0045] In the sensor filtering experiment, the data recorded for a period of time can be saved, and the data before and after filtering in the saved period can be plotted in the time domain and the standard deviation can be calculated as a basis for comparing and evaluating the operating effect of the filtering algorithm.

[0046] In the sensor nonlinear correction experiment, the sensor nonlinear correction experiment interface can be entered from the experimental teaching software interface. After obtaining the calibration data of the pressure sensor, a variety of nonlinear correction methods including table lookup method, correction function method, algebraic interpolation method, least squares method, and neural network method can be provided to establish the input / output relationship of the pressure sensor. At the same time, the corrected measurement results can be displayed in real time or the time domain diagram of the output data can be drawn.

[0047] In the sensor nonlinear correction experiment, you can choose to add a nonlinear correction algorithm on the nonlinear correction experiment interface. This function will pop up a code box on the interface for students to enter a new nonlinear correction algorithm program. After adding a new program, the original functions of the experimental teaching software will not be affected.

[0048] In the sensor nonlinear correction experiment, the nonlinear correction effect can be verified in the experimental teaching software. By selecting and collecting multiple pressure test points within the sensor range, the nonlinear parameters of the pressure sensor before and after the nonlinear correction can be calculated and used as the basis for evaluating different nonlinear correction methods.

[0049] In the sensor temperature compensation experiment, the temperature compensation experiment interface can be entered from the experimental teaching software interface. By manually adding temperature points and pressure points, and using a high and low temperature humidity control box and an intelligent pressure controller, a sufficient number of temperature points and pressure points can be collected within the sensor range and operating temperature range. Through the temperature experimental data, a variety of algorithms including polynomial fitting, neural network, support vector machine, correlation vector machine, and spline interpolation can be provided to establish a temperature compensation model for the pressure sensor.

[0050] In the sensor temperature compensation experiment, you can choose to add a temperature compensation algorithm on the temperature compensation experiment interface. This function will pop up a code box on the interface for students to enter a new temperature compensation algorithm program. After adding a new program, the original functions of the experimental teaching software are not affected. After temperature compensation, the sensor measurement results can be displayed in real time or a curve chart showing the measurement results changing with temperature can be drawn. The effects of temperature compensation of different algorithms can be evaluated by calculating parameter drift values, such as full-scale error and sensitivity error. At the same time, the modeling data and model parameters of the temperature compensation model can be imported and exported.

[0051] In the sensor data wireless communication experiment, the system wireless communication configuration function can be entered from the experimental teaching software interface. In this interface, the Bluetooth, WIFI, and ZigBee communication methods can be turned on and off, and the port numbers of WIFI and ZigBee communication methods can be configured. After completing the system's wireless communication configuration, students can design mobile phone applications, WeChat applets, and computer applications to receive and process experimental operation data based on wireless communication.

[0052] The intelligent sensor experimental teaching software has the function of recording the experimental process. After turning on this function, the students' operating steps, experimental data and experimental results during the experiment will be recorded in real time by the software. The record can be viewed and replayed so that students can summarize their experience and discover problems. After turning on this function, the experimental teaching software will also provide an experimental log recording function. Students can enter notes, questions and thoughts during the experiment. The system will automatically associate and record the experimental progress and operating steps to generate a complete and traceable experimental learning trajectory.

[0053] The intelligent sensor experiment teaching software has the function of submitting and evaluating experimental results. This function can summarize and submit various types of experimental data in the above-mentioned sensor calibration experiment, filtering experiment, nonlinear correction experiment, and temperature compensation experiment. Student users have no right to modify the experimental data to ensure the authenticity and reliability of the experimental data. This function can pre-set the standard experimental data obtained under standardized experimental operations and use it as the basis for scoring, so that the experimental teaching software can score the experimental results submitted by students and derive the results. This function can draw a report on the students' experimental mastery based on the statistics and data analysis of the students' experimental results, and can provide feedback to the teachers on the teaching situation of each experimental project and the difficulties encountered by students during the experiment.

[0054] The intelligent sensor experiment teaching software has the function of software update iteration, which can be based on RS232, USB wired mode, or WIFI, Bluetooth, ZigBee wireless communication mode. Under this function, the optional update contents include: software operating system update, experiment background introduction and course teaching content update, and sensor teaching experiment module content update.

[0055] The intelligent sensor experimental teaching software supports the artificial intelligence voice interaction function. Under this function, students can interact with the teaching software through voice dialogue to query the experimental steps, obtain the equipment operation status and data feedback information, making the experimental teaching more convenient and intelligent. Under this function, after integrating the artificial intelligence assistant, based on voice recognition technology, it can provide real-time guidance to students in terms of experimental content and operation steps. Specifically, it can provide real-time voice prompts and suggestions, and can also generate teaching demonstration pictures in real time.

[0056] Figure 3 Schematic diagram of an intelligent sensor experimental teaching platform device provided by an embodiment of the present invention. Figure 3 As shown, the electrical signal generation link of the pressure sensor experimental unit 100 includes an intelligent pressure controller 101, a high-pressure gas connection hose 102, a multi-channel gas connection platform 103, a pressure sensor 104 and a high and low temperature humidity control box. The multi-channel gas connection platform 103 and the pressure sensor 104 will be set in the high and low temperature humidity control box under the temperature and humidity experiment. The pressure sensor experimental unit 100 can realize the output, transmission and detection of the set pressure, and can simulate the changing temperature and humidity working environment.

[0057] For the intelligent pressure controller 101, air is used as the working medium to achieve pressure output. A high-precision pressure module is built in. The pressure module includes a high-precision positive pressure source and a negative pressure source. As the reference source of the intelligent pressure controller, its device panel has a touch function, which can realize full-automatic output of the set pressure. In order to meet the experimental needs, the pressure control range of the intelligent pressure controller is greater than or equal to 0-800kPa, the pressure control accuracy is better than ±40Pa, and the response time of the intelligent pressure controller does not exceed 10 seconds. The intelligent pressure controller can be operated and parameterized through a color touch screen. It also supports the control of experimental equipment and monitoring of operating status through software using multiple communication methods including RS232, USB and Wi-Fi.

[0058] The high-pressure gas connecting hose 102 is responsible for connecting the intelligent pressure controller 101 and the multi-channel gas connecting platform 103 . The hose can withstand a high pressure of 5 MPa and can transmit the high-pressure gas to the multi-channel gas connecting platform 103 .

[0059] The multi-channel gas connection table 103 is used to connect the intelligent pressure controller and the pressure sensor. Its external end can be connected to at least 15 pressure sensors to provide pressure output for them, and is responsible for transmitting the pressure signal to the pressure sensor 104. The multi-channel design allows the connection table to be installed with enough sensors to achieve a one-to-many experimental teaching operation effect. At the same time, in non-temperature and humidity experiments, a safety protection cover is also provided to isolate the gas connection table from the outside world to ensure the safety of the experimenters. Because the intelligent pressure controller and the high and low temperature humidity control box are expensive, this connection table can reduce the cost of experimental construction, expand the number of people that can be accommodated in the experiment, improve the utilization efficiency of expensive equipment, and avoid repeated cost investment.

[0060] The various pressure sensors 104 selected in the pressure sensor experimental unit 100 are products of the same type, different prices, and different performances. The performance differences between the various sensors can be compared based on the teaching experiment project to achieve performance comparison, and can also be based on the compensation type experiment in the teaching experiment project to achieve the verification of the performance improvement of the compensated pressure sensor and the effectiveness of the software compensation algorithm. For the pressure sensor 104, it contains a piezoresistive pressure core as a pressure sensitive unit to realize the conversion of pressure signals to electrical signals. The types of pressure sensitive units used include absolute pressure and gauge pressure, both of which can convert pressure signals into electrical signals. It contains a temperature and humidity sensitive unit, which contains an analog-to-digital conversion chip as a measuring element for electrical signals, and outputs the ambient temperature and pressure signals measured by the pressure sensor 104 to achieve the collection of temperature and pressure data under the temperature compensation experiment. Its output end can be externally connected to a serial port adapter module, and the sensor's measurement signal can be output to an electronic computer or an embedded development board through the adapter module.

[0061] The high and low temperature humidity control box has an ultra-wide temperature and humidity control range. This control box can be used for the verification, calibration and testing of temperature and humidity instruments, and can also be used for high-precision temperature and humidity experiments of sensors. The temperature control range of this control box is greater than or equal to -60℃~180℃, and the humidity control range is greater than or equal to 5%RH~95%RH. After stable operation, the temperature fluctuation performance is better than ±0.001℃, and the humidity fluctuation performance is better than ±0.1%RH. After stable operation, the overall temperature uniformity performance is better than 0.1℃, and the overall humidity uniformity performance is better than 0.5%RH. The temperature and humidity chamber can be operated and parameterized through a color touch screen. It also supports the control of experimental equipment and monitoring of operating status through software using multiple communication methods including RS232, USB and Wi-Fi.

[0062] The pressure sensor experimental unit 100 is also equipped with a safety protection cover, which can be used to cover the multi-channel gas connection platform when conducting non-temperature and humidity experiments to achieve isolation from the outside world. It can protect the safety of experimenters when dangerous situations such as misoperation of the pressure controller under pressure occur.

[0063] like Figure 3 As shown, the intelligent sensor experimental teaching development module 200 is responsible for receiving and processing the output electrical signal of the sensor, wireless data communication, and running and displaying the experimental teaching software. The module includes an electronic computer, an embedded development board and a wireless communication module 201. The electronic computer and the embedded development board are connected to the pressure sensor through a cable to receive the measurement signal. These signals will be used as the data source for the operation of the intelligent sensor experimental teaching software. The embedded development board needs to have the characteristics of powerful functions, rich interfaces, and easy secondary development. After combining the wireless communication module, its overall performance can meet the requirements of various experimental teaching contents of the intelligent sensor. The embedded development board is equipped with a large memory and a multi-core processor, and has multiple types of interface options including IIC interface, SPI interface, SATA interface, USB port, HDMI port, VGA interface, MIPI interface, audio jack, microSD card slot, and Ethernet interface. The embedded development board can also run programs based on Raspbian, Linux, RISC, Windows and other operating systems. The electronic computer and the embedded development board can realize WIFI, Bluetooth, ZigBee and other wireless networking methods through an external wireless communication module. The electronic display screen 203 can be connected to an electronic computer or an embedded development board via an HDMI or Type C interface cable 202, and it has a suitable size and resolution as a display terminal for experimental teaching software.

[0064] Figure 4 A schematic diagram of the workflow of the intelligent sensor experimental teaching platform provided in an embodiment of the present invention. Figure 4 The following is the standard process of intelligent sensor experimental teaching. The standardized operation process can ensure the safety of experimental personnel and reduce the loss of experimental equipment. The specific work flow is:

[0065] (1) Before the experiment begins, connect the intelligent pressure controller to the multi-channel gas connection platform through a high-pressure gas connection hose, fix the pressure sensor to the gas connection platform, and cover the gas connection platform area with a safety cover when not conducting a temperature and humidity experiment.

[0066] (2) Connect the output cable of the pressure sensor to an electronic computer or an embedded development board, connect the electronic display screen to the interface of the electronic computer or the embedded development board through an interface cable, and connect the wireless communication module to the electronic computer or the embedded development board.

[0067] (3) Turn on the power switches of the intelligent pressure controller and the high and low temperature humidity control box, power the electronic computer, embedded development board and electronic display screen, and run the intelligent sensor experimental teaching software to conduct experiments.

[0068] (4) After the experiment, the intelligent pressure controller is vented, the power of all equipment is turned off, and the experimental equipment is sorted and classified.

[0069] Figure 5 A schematic diagram of the detailed flow of the sensor calibration experiment of the intelligent sensor experimental teaching software provided in the embodiment of the present invention. In actual use, due to factors such as manufacturing errors, environmental influences, drift caused by long-term use, etc., the pressure sensor may not always maintain accuracy. Therefore, it is necessary to calibrate the sensor before use. Calibration is to determine the input and output characteristics of the pressure sensor by comparing it with a standard pressure source. The more calibration points selected in the calibration process, the higher the reliability of the calibration data, and the more accurate the established sensor input-output relationship. Figure 5 As shown, during the calibration process, you can choose to create a new calibration experiment or import existing calibration experiment data. Click the sensor calibration experiment in the intelligent sensor experiment teaching software interface. After entering the sensor calibration interface, you can choose to import existing calibration data or start a new calibration experiment. If you import existing data, the calibration experiment will end. In a new experiment, the experiment can be started after the calibration points are added to the experimental teaching software and the intelligent pressure controller. At each set pressure calibration point, after the intelligent pressure controller shows that its output is stable, the calibration experiment program will record the ADC data value output by the pressure sensor at this time. When the ADC data of the pressure sensor corresponding to all pressure calibration points are recorded, the calibration experiment is considered to be over. The software interface will draw a calibration result graph, and you can choose to export the calibration data.

[0070] Figure 6 A schematic diagram of the detailed flow of the sensor filtering experiment in the intelligent sensor experiment teaching software provided by the embodiment of the present invention. In actual use, the data acquisition process of the sensor will be affected by multiple factors such as external environmental interference and system noise. Filtering can effectively remove the signal jitter caused by factors such as high-frequency noise, random interference and environmental fluctuations in the data, making the signal more stable, thereby retaining key useful information and improving measurement accuracy. Figure 6As shown in the figure, after the electronic computer or embedded development board can receive the output data of the pressure sensor, the filtering experiment can be started. During the experiment, you can choose some basic filtering algorithms that come with the experimental teaching software, such as first-order filtering, median filtering, weighted mean filtering, sliding average filtering, and Kalman filtering, or you can choose to add a new filtering algorithm. Enter the algorithm program to be added in the code box that pops up in the software to implement the function. After adding the new program, the original function of the experimental teaching software is not affected. After selecting the filtering algorithm, the software will draw a real-time curve of the output data before and after filtering over time. During the experiment, you can also start and stop the sensor output data recording function, selectively save the data before and after filtering, and after the data recording is completed, calculate the standard deviation of the original data of the saved segment and the data results of each filtering algorithm as a basis for evaluating the filtering effect.

[0071] Figure 7 A schematic diagram of the detailed flow of the sensor nonlinear correction experiment in the intelligent sensor experimental teaching software provided by the embodiment of the present invention. Ideally, there should be a linear relationship between the input physical quantity and the output signal of the sensor. However, in actual use, the sensor exhibits nonlinear characteristics due to factors such as the sensor's manufacturing process, environmental influences, and aging. Nonlinear correction can reduce the sensor's systematic error and make the output value closer to the true value, thereby improving the sensor's measurement accuracy. Figure 7 As shown in the figure, after completing the acquisition of the pressure sensor calibration data, the nonlinear correction experiment can be started. During the experiment, you can choose some basic nonlinear algorithms that come with the experimental teaching software, such as the table lookup method, correction function method, algebraic interpolation method, least squares method, and neural network method, or you can choose to add a new nonlinear correction algorithm. Enter the algorithm program to be added in the code box that pops up in the software to implement the function. After adding the new program, the original function of the experimental teaching software is not affected. After selecting the correction algorithm, the software will output the corrected sensor measurement results in real time. Furthermore, you can also combine the intelligent pressure controller to reselect the pressure test points and record the measurement data, and verify the effect of nonlinear correction of different algorithms by calculating the nonlinearity of the measurement data within the range.

[0072] Figure 8A schematic diagram of the detailed flow chart of the sensor temperature compensation experiment of the intelligent sensor experimental teaching software provided in the embodiment of the present invention. The working environment of the sensor usually has temperature changes, and temperature is an important external factor that causes fluctuations in sensor performance. Most sensor materials and electronic components, such as strain gauges, resistors, semiconductors, etc., will cause changes in physical or electrical properties due to temperature changes, which in turn leads to measurement errors. In order to improve the measurement accuracy of intelligent sensors, temperature compensation technology is indispensable. Software temperature compensation is a software model that establishes the correspondence between the temperature data, sensor input and output data recorded in the temperature experiment. Compared with hardware temperature compensation, its implementation is simpler and the cost is lower, so it is suitable as an experimental teaching project. Figure 8 As shown, click on the sensor temperature compensation experiment in the interface of the intelligent sensor experimental teaching software. After completing the sensor calibration experiment or importing the existing sensor calibration data, you can start the temperature compensation experiment. First, you need to complete the collection of modeling data. In this interface, you can combine the intelligent pressure controller and the high and low temperature humidity control box to record enough sensor range and temperature and pressure test point data within the working temperature range, or import existing temperature experimental data. During the experiment, according to the temperature compensation experimental data, you can choose some common temperature compensation algorithms that come with the experimental teaching software, such as polynomial fitting, neural network, support vector machine, correlation vector machine, spline interpolation, or you can choose to add a new temperature compensation algorithm. Enter the algorithm program to be added in the code box that pops up in the software to realize this function. After adding the new program, the original function of the experimental teaching software is not affected. After selecting the algorithm, the experimental teaching software will establish a temperature compensation software model and output the sensor measurement results after temperature compensation in real time. Furthermore, to verify the compensation effect, the temperature points and pressure test points can be reselected and the experimental data before and after compensation can be recorded. The software will draw a curve of the pressure test points changing with temperature before and after compensation, and evaluate the effect of temperature compensation of different algorithms by calculating parameter drift values, such as full-scale error and sensitivity error.

Claims

1. An intelligent sensor experimental teaching platform, characterized in that: include: Intelligent sensor experiment unit, intelligent sensor experiment teaching development module and intelligent sensor experiment teaching software running on the intelligent sensor experiment teaching development module; The intelligent sensor experimental unit is used to complete the output, transmission, detection of set physical quantities and the simulation of the working environment with temperature and humidity changes; The intelligent sensor experimental teaching development module is used to realize the reception and processing of sensor output signals and the operation and display of experimental teaching software; The intelligent sensor experiment teaching software realizes multifunctional experiment teaching according to sensor data, and its functions include: experiment background introduction and course teaching, experiment equipment operation status detection and control, measurement result real-time display and drawing, experiment teaching module display and operation, experiment process recording, system communication mode configuration, experiment result submission and evaluation, experiment teaching software update and iteration and artificial intelligence voice interaction; among them, the display and operation of the experiment teaching module includes sensor calibration experiment, sensor filtering experiment, sensor nonlinear correction experiment, sensor temperature compensation experiment and sensor data wireless communication experiment.

2. The intelligent sensor experimental teaching platform according to claim 1 is characterized in that: The intelligent sensor experimental unit includes an intelligent sensor controller, a multi-channel signal transmission device, multiple sensors, a temperature and humidity sensitive unit, a high and low temperature humidity control box and a safety protection cover. The temperature and humidity sensitive unit is integrated in the package of each sensor. The intelligent sensor controller is used to generate the set physical quantity, and realizes software-based equipment control and operation monitoring through manual operation and parameter setting, or through multiple communication methods such as RS232, USB, and WIFI. The multi-channel signal transmission device provides connection ports for at least 15 sensors. The multi-channel signal transmission device and multiple sensors are arranged in the high and low temperature humidity control box under the temperature and humidity experiment. The multi-channel signal transmission device and multiple sensors are arranged in the safety protection cover under the non-temperature and humidity experiment, which is used to realize the isolation of the multi-channel signal transmission device and multiple sensors from the outside world.

3. The intelligent sensor experimental teaching platform according to claim 2 is characterized in that: The multiple sensors are of the same type but of different prices and performances. The performance differences are compared based on the teaching experiment project to achieve the performance advantages and disadvantages of different sensors. Based on the compensation type experiments in the teaching experiment project, the improvement of sensor performance after compensation and the effectiveness of the software compensation algorithm are verified.

4. The intelligent sensor experimental teaching platform according to claim 1 is characterized in that: The intelligent sensor experiment teaching development module includes: an electronic computer, an embedded development board, a wireless communication module and an electronic display screen. The measurement signal output by the intelligent sensor experiment unit is transmitted to the electronic computer or the embedded development board. The intelligent sensor experiment teaching software runs on the electronic computer or the embedded development board to process and analyze the measurement signal to obtain the experimental results. The electronic display screen serves as a display terminal for the intelligent sensor experiment teaching software.

5. The intelligent sensor experimental teaching platform according to claim 4 is characterized in that: The embedded development board has large memory and multi-core processor, and provides multiple interface options including IIC interface, SPI interface, SATA interface, USB port, HDMI port, VGA interface, MIPI interface, audio jack, microSD card slot and Ethernet interface; the embedded development board supports multiple operating systems such as Raspbian, Linux, RISC and Windows; electronic computers and embedded development boards can be connected to wireless communication modules to realize multiple wireless networking methods such as WIFI, Bluetooth and ZigBee.

6. The intelligent sensor experimental teaching platform according to claim 1 is characterized in that: The experimental background introduction and course teaching functions include experimental background introduction, experimental safety training and assessment, experimental teaching and real-time operation guidance; the experimental equipment operation status detection and control functions include monitoring the experimental equipment operation status, equipment remote control, experimental equipment use reservation, equipment automatic protection, data monitoring and alarm, error repair guide and automatic repair, and hierarchical setting of experimental equipment control permissions; the experimental process recording function includes experimental process recording and playback as well as experimental log recording; the experimental result submission and evaluation function includes experimental result statistics and analysis; the experimental teaching software update and iteration function includes software operating system update, software teaching content update and software experimental module update; the artificial intelligence voice interaction function includes the experimental teaching software artificial intelligence voice assistant.

7. The intelligent sensor experimental teaching platform according to claim 1 is characterized in that: In the sensor calibration experiment, you can choose to import existing calibration data or start a new calibration experiment. If you import existing calibration data, the calibration experiment will end; if you choose to start a new calibration experiment, you need to add calibration points. After adding the set number of calibration points, import each calibration point into the intelligent sensor controller; at each set calibration point, after the output of the intelligent sensor controller is stable, the calibration experiment program will record the data value of the sensor output at this time; after the sensor output data values ​​corresponding to all calibration points are recorded, the software interface will draw a calibration result graph and export the calibration data.

8. The intelligent sensor experimental teaching platform according to claim 1 is characterized in that: In the sensor filtering experiment, you can choose the filtering algorithms provided by the experimental teaching software, including first-order filtering, median filtering, weighted mean filtering, sliding average filtering and Kalman filtering, or manually enter a new filtering algorithm program. After selecting the filtering algorithm, the experimental teaching software will draw a real-time curve of the output data before and after filtering over time. In the filtering interface, you can start and stop the sensor output data recording function, and after the data recording is completed, calculate the standard deviation of the saved data segment after being processed by each filtering algorithm as a standard for evaluating the effect of the filtering algorithm.

9. The intelligent sensor experimental teaching platform according to claim 1 is characterized in that: In the sensor nonlinear correction experiment, you can choose the nonlinear correction algorithm provided by the experimental teaching software, including the table lookup method, correction function method, algebraic interpolation method, least squares method and neural network method, or manually input a new nonlinear correction algorithm program. After completing the sensor calibration process and selecting the correction algorithm, the experimental teaching software will output the corrected sensor measurement results in real time. In the nonlinear correction experiment interface, combined with the intelligent sensor controller, select and record the measurement results of multiple test points within the sensor range, and calculate the nonlinear parameters of the sensor before and after correction by each algorithm as a standard for evaluating the effectiveness of different correction methods.

10. The intelligent sensor experimental teaching platform according to claim 1, characterized in that: In the sensor temperature compensation experiment, the intelligent sensor controller and the high and low temperature humidity control box are combined to select and record the data of multiple temperatures and test points of the physical quantity to be measured within the sensor range and working temperature range, or import existing temperature experimental data; according to the temperature compensation experimental data, select the temperature compensation algorithm provided by the experimental teaching software, including polynomial fitting method, neural network method, support vector machine, correlation vector machine, spline interpolation method, or manually input a new temperature compensation algorithm program. After selecting the temperature compensation algorithm, the temperature compensation model will be established based on the experimental data, and the results of the sensor temperature compensation will be output in real time; reselect the temperature and test points of the physical quantity to be measured, obtain the experimental data before and after compensation, and draw the curve of the change of the physical quantity measurement value with temperature before and after compensation to compare the effects of each temperature compensation algorithm.

11. The intelligent sensor experimental teaching platform according to claim 1, characterized in that: The sensor data wireless communication experiment includes: turning on and off the Bluetooth, WIFI, and ZigBee communication methods in the experimental teaching development module, and configuring the port numbers of the WIFI and ZigBee communication methods; during the experiment, students can use self-designed WeChat applets, mobile applications, and computer applications based on the smart sensor course to try to use WiFi, Bluetooth, and ZigBee communication methods to receive the operating data of the experimental teaching development module, and remotely monitor and control the progress of the experiment.

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