A smart sensor development verification system and signal acquisition and processing method

Abstract

The present application provides an intelligent sensor development verification system and a signal acquisition and processing method, which belongs to the technical field of aviation electromechanical and engine control. The intelligent sensor development verification system specifically includes: a sensor; a signal conditioning circuit for conditioning the sensor signal, and performing A / D acquisition and conversion into a digital signal; a SoC processing system for realizing functions such as signal acquisition, temperature sensor, signal calibration, signal interface and processing system BIT, feature data extraction and fault monitoring; a communication network interface distributed network interface, composed of a network protocol and a network transceiver, transmits the data of the intelligent sensor to the control system or receives the system configuration. The intelligent sensor development verification system is based on a general architecture. As a flexibly configurable and expandable platform, it can be used for the core function development of intelligent sensors and for the system architecture design of intelligent sensors.

Description

Technical Field

[0001] The present application relates to the field of aviation electromechanical and engine control, and in particular to an intelligent sensor development and verification system and a signal acquisition and processing method. Background Art

[0002] Smart sensors are a trend in the current development of sensors. Smart sensors are equipped with microprocessors, and have both signal detection and signal processing. They have the advantages of good reliability and stability, high sensing accuracy, and strong adaptive capabilities. Therefore, smart sensors have become one of the main development directions of sensors.

[0003] Especially in the field of aviation electromechanical and engine control, the accuracy of sensor signals is required to be high, and sensors are greatly affected by environmental stress, installation and sensor technology; the suppliers of sensors and signal acquisition and processing are often not one company and have technical barriers, which often results in the signal not being processed well; at the same time, the transmission distance of sensors and signal acquisition and processing is long, the signal attenuation and noise introduction are large, and more failure modes are brought; various sensors generally have special calibration methods, and it is difficult to effectively calibrate the signal through a unified architecture, or due to process limitations, they do not have calibration functions. Therefore, it is necessary to develop intelligent sensors to solve problems such as poor signal processing accuracy, difficulty in calibration, complex wiring and susceptibility to interference. The current intelligent sensor architecture and variety are various, but they are often specific to specific sensors and buses and are not conducive to promotion. At the same time, their processor functions are single and have poor scalability, which is not conducive to the development and verification of advanced intelligent signal processing algorithms, and it is difficult to form a universal and efficient IP. Many intelligent sensors do not have efficient calibration functions for environmental stresses such as temperature and based on installation and manufacturing processes, which greatly increases the manufacturing cost and process implementation difficulty, and cannot meet the requirements of high-precision, anti-interference, and strong real-time airborne environments. Summary of the invention

[0004] In view of this, the present application provides an intelligent sensor development and verification system and a signal acquisition and processing method, which solve the problems in the prior art. Based on a general hardware platform, it can be used as a flexibly configurable and expandable platform for the core function development and verification of intelligent sensors.

[0005] On the one hand, the present application provides a smart sensor development and verification system that adopts the following technical solutions:

[0006] An intelligent sensor development and verification system, including a sensor, a signal conditioning circuit, a SoC processing system, and a distributed communication network interface;

[0007] The sensors are installed at relevant monitoring points of the control system;

[0008] The signal conditioning circuit is used to condition the sensor signal and perform A / D acquisition and conversion into a digital signal;

[0009] The SoC processing system is an SoC processing system that integrates a microprocessor and a programmable logic unit, and realizes functions such as signal acquisition, temperature sensor, signal calibration, signal interface and processing system BIT, feature data extraction and fault monitoring. It is used to complete the calibration of signal acquisition data, extract the signal feature data required by the system, send it to the communication protocol layer through the host communication interface when the fault monitoring is normal, and report the fault in abnormal conditions;

[0010] The communication network interface is a distributed network interface, which consists of a network protocol and a network transceiver. It is configured for redundant communication and connected to a distributed or general communication network according to the system networking requirements to transmit data of the intelligent sensor to the control system or receive system configuration.

[0011] Optionally, the sensor, signal conditioning circuit, SoC processing system and distributed communication network interface can be used as independent components to form a system, or integrated to form a board, smart sensor or chip.

[0012] Optionally, the sensor, signal conditioning circuit, SoC processing system and distributed communication network interface are integrated into an intelligent sensor as required; or the function is developed and verified by composing a system through independent component boards, and then the function is transplanted and integrated into an independent intelligent sensor.

[0013] On the other hand, the present application provides a smart sensor development verification method using the following technical solution:

[0014] A smart sensor development and verification method is based on the smart sensor development and verification system, and includes the following steps:

[0015] Step 1, obtaining the temperature, displacement and pressure signals of the control system through temperature, displacement and pressure sensors, and converting them into corresponding electrical signals;

[0016] Step 2: The sensor signal conditioning circuit of the intelligent sensor system applies corresponding excitation to the sensor, and the sensor signal conditioning circuit conditions the electrical signal of the sensor and converts it into a digital signal that can be directly collected by the SoC processing system or further converts it into a digital signal through A / D conversion and is collected by the SoC processing system;

[0017] Step 3: The signal acquisition timing is controlled by the SoC processing system, and the acquisition results are stored in the programmable logic FIFO or on-chip RAM for digital filtering;

[0018] Step 4: The SoC processing system collects temperature information from an on-chip temperature sensor or an external temperature sensor, and calibrates the collected data using algorithms such as temperature compensation and nonlinear calibration;

[0019] Step 5, BIT acquisition hardware logic or software algorithm can perform BIT detection on the conditioning circuit and SoC processing system and communication system;

[0020] Step 6: According to the control system requirements, the calibrated signal acquisition data can be further extracted in the SoC processing system, and the BIT detection results can be further processed to determine whether the system is faulty and analyze the cause of the fault;

[0021] Step 7, implementing the host communication interface in the SoC processing system to complete the host control of the distributed network protocol chip or controller;

[0022] Step 8, implement the distributed network protocol and transceiver functions through the distributed network in the smart sensor system, output the data of the smart sensor system, and accept the network configuration of the control system.

[0023] Optionally, the signal conditioning method of step 2 is: perform corresponding signal conversion, amplification, hardware filtering processing on the signals of Pt200, thermocouple, and silicon piezoresistive pressure sensor, and then send them to A / D acquisition; the LVDT signal conditioning method is to amplify, filter, rectify, convert to DC effective value voltage and perform A / D acquisition; the frequency signal conditioning method is to filter, shape, convert to square wave, and perform frequency capture.

[0024] Optionally, the signal acquisition timing of step 3 is implemented by the SoC processing system through programmable logic or by the SoC processing system through software-controlled GPIO.

[0025] Optionally, the temperature sensor in step 4 uses an on-chip temperature sensor of the SoC when the SoC processing system and the control system sensor are at the same location; when the SoC processing system and the smart sensor are at different locations, an external temperature sensor near the smart sensor is used.

[0026] Optionally, the temperature compensation and nonlinear calibration algorithm in step 4 is implemented by using multivariate linear regression and neural network. By training the collected data under different standard input temperatures of the sensor, the calibration parameters are embedded into the SoC system to complete the calibration of the sensor signal collection data in real time.

[0027] Optionally, the time domain and frequency domain analysis in step 6 is implemented by performing FFT and correlation algorithms on the signal to obtain characteristics such as amplitude, frequency, effective value, and spectrum of the signal.

[0028] Optionally, in step 7, the host communication interface is implemented through a peripheral interface of the SoC processing system or through a local bus implemented by programmable logic.

[0029] In summary, this application includes the following beneficial technical effects:

[0030] The intelligent sensor development and verification system is based on a general architecture and includes the core elements of intelligent sensors. As a flexibly configurable and expandable platform, it can be used for the core function development of intelligent sensors, such as various signal processing algorithms and calibration algorithms, various distributed network networking transmissions, etc., and for the system architecture design of intelligent sensors.

[0031] The SoC system can collect the ambient temperature related to the sensor and conditioning channel through the on-chip temperature sensor or external sensor, perform temperature compensation on the signal acquisition results in the full temperature range, and realize nonlinear calibration of the full range of signal acquisition through algorithms such as neural network and multivariate linear regression. The calibrated parameters are embedded in the SoC system, and the sensor signal acquisition data can be calibrated in real time in actual signal acquisition, eliminating the acquisition error caused by temperature changes and the acquisition error caused by system nonlinearity.

[0032] The intelligent sensor system can perform time domain and frequency domain analysis on the signal acquisition data, and obtain the signal's amplitude, frequency, effective value, spectrum and other characteristics by performing FFT, correlation and other algorithms on the signal.

[0033] The intelligent sensor signal acquisition and processing method can effectively perform full-scale and full-temperature signal acquisition, temperature compensation and nonlinear calibration of sensor signals, and perform efficient digital signal processing and fault monitoring, greatly improving the anti-interference ability, accuracy, scalability and reliability of signal acquisition. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0035] Figure 1 Developed and validated a system architecture for a smart sensor;

[0036] Figure 2 This is the sensor signal conditioning circuit architecture diagram;

[0037] Figure 3 Processing system architecture diagram for SoC;

[0038] Figure 4 This is a signal acquisition architecture diagram;

[0039] Figure 5 This is the calibration architecture diagram for signal temperature compensation and nonlinear calibration;

[0040] Figure 6 This is the architecture diagram for signal time domain and frequency domain analysis;

[0041] Figure 7 This is a diagram of the distributed network architecture. DETAILED DESCRIPTION

[0042] The embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0043] The following describes the implementation methods of the present application through specific examples, and those skilled in the art can easily understand other advantages and effects of the present application from the contents disclosed in this specification. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. The present application can also be implemented or applied through other different specific implementation methods, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present application. It should be noted that, in the absence of conflict, the following embodiments and the features in the embodiments can be combined with each other. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without making creative work belong to the scope of protection of the present application.

[0044] It should be noted that various aspects of the embodiments within the scope of the appended claims are described below. It should be apparent that the aspects described herein can be embodied in a wide variety of forms, and any specific structure and / or function described herein is merely illustrative. Based on the present application, it should be understood by those skilled in the art that an aspect described herein can be implemented independently of any other aspect, and two or more of these aspects can be combined in various ways. For example, any number of aspects described herein can be used to implement the device and / or practice the method. In addition, other structures and / or functionalities other than one or more of the aspects described herein can be used to implement this device and / or practice this method.

[0045] It should also be noted that the illustrations provided in the following embodiments are only schematic illustrations of the basic concept of the present application. The drawings only show components related to the present application rather than being drawn according to the number, shape and size of components in actual implementation. In actual implementation, the type, quantity and proportion of each component may be changed arbitrarily, and the component layout may also be more complicated.

[0046] Additionally, in the following description, specific details are provided to facilitate a thorough understanding of the examples. However, it will be understood by those skilled in the art that the aspects described may be practiced without these specific details.

[0047] The embodiment of the present application provides an intelligent sensor development and verification system adopts the following technical solution:.

[0048] like Figure 1 As shown, an intelligent sensor development and verification system includes a sensor, a signal conditioning circuit, a system on chip (SOC) processing system and a distributed communication network interface.

[0049] The sensors are installed at relevant monitoring points of the control system, and the sensors include thermocouples, silicon piezoresistive pressure sensors, Pt200 temperature sensors, LVDT displacement sensors (Linear Variable Differential Transformer, linear variable differential transformer), etc.

[0050] like Figure 2 As shown, the signal conditioning circuit is used to condition the sensor signal and perform A / D acquisition and convert it into a digital signal; the signal conditioning circuit can be installed in a signal conditioning box or integrated in an intelligent sensor.

[0051] In one embodiment, the signal conditioning circuit excites the silicon piezoresistive pressure sensor, LVDT, Pt200 bridge, obtains the sensor signal for corresponding conditioning, or directly obtains the thermocouple signal for conditioning; the conditioning includes amplification, filtering, rectification, etc., converting the signal into an analog voltage that can be used for A / D conversion, and the SoC processing system performs A / D acquisition.

[0052] like Figure 3 and Figure 4 As shown, the SoC processing system is a SoC processing system that integrates a microprocessor and a programmable logic unit, and realizes functions such as signal acquisition, temperature sensor, signal calibration, signal interface and processing system BIT, feature data extraction and fault monitoring. It is used to complete the calibration of signal acquisition data, extract the signal feature data required by the system, send it to the communication protocol layer through the host communication interface when fault monitoring is normal, and report a fault under abnormal circumstances.

[0053] The SoC processing system can be a system on chip with a processor and programmable logic resources, or it can be integrated into the sensor by the SoC bare chip. The SoC system can realize signal A / D acquisition control, construct a local bus to realize the host communication interface of distributed buses such as FlexRay. At the same time, the SoC processor realizes signal acquisition storage, signal calibration and calibration, digital signal processing, BIT and other functions and algorithms. See the SoC processing system architecture diagram Figure 3 .

[0054] The SoC system can realize the signal A / D acquisition control timing through the on-chip PL or GPIO (General Purpose Input Output), can realize accurate and equal time interval high-speed A / D sampling, and store the results in FIFO memory or SoC on-chip RAM, and can perform FIR digital filtering or median filtering, average filtering, etc. as needed to eliminate signal noise, interference, etc.

[0055] The communication network interface is generally a distributed network interface, which consists of a network protocol and a network transceiver. It is configured for redundant communication and connected to a distributed or general communication network according to the system networking requirements to transmit data of smart sensors to the control system or receive system configuration.

[0056] The smart sensor development and verification system of this application is based on a general architecture and includes the core elements of smart sensors. As a flexibly configurable and expandable platform, it can be used for the core function development of smart sensors, such as various signal processing algorithms and calibration algorithms, various distributed network networking transmissions, etc., and for the system architecture design of smart sensors.

[0057] In one embodiment, the sensor, signal conditioning circuit, SoC processing system and distributed communication network interface can be used as independent components to form a system, or integrated to form a board, smart sensor or chip.

[0058] In one embodiment, the sensor, signal conditioning circuit, SoC processing system and distributed communication network interface are integrated into a smart sensor as required.

[0059] In one embodiment, the function is developed and verified by assembling a system of independent component boards, and then the functions are transplanted and integrated into an independent smart sensor.

[0060] The application also discloses a method for collecting and processing intelligent sensor signals.

[0061] A method for collecting and processing intelligent sensor signals comprises the following steps:

[0062] Step 1: Obtain temperature, displacement, pressure and other signals of the control system through temperature, displacement, pressure and other sensors, and convert them into corresponding electrical signals.

[0063] Step 2: The sensor signal conditioning circuit of the intelligent sensor system applies corresponding excitation to the sensor, such as the supply voltage of the silicon piezoresistive sensor, the primary excitation of the LVDT sensor, etc.; the sensor signal conditioning circuit conditions the electrical signal of the sensor and converts it into a digital signal that can be directly collected by the SoC processing system or performs A / D conversion to convert it into a digital signal and collect it by the SoC processing system.

[0064] Step 3: The signal acquisition timing is controlled by the SoC processing system, and the acquisition results are stored in the programmable logic FIFO or on-chip RAM for digital filtering.

[0065] Step 4: The SoC processing system collects temperature information through the on-chip temperature sensor or external temperature sensor, and calibrates the collected data through algorithms such as temperature compensation and nonlinear calibration. The calibration can be processed in real time with the real-time collected temperature, effectively improving the signal accuracy.

[0066] Step 5: BIT acquisition hardware logic or software algorithm can perform BIT detection on the conditioning circuit, SoC processing system, and communication system.

[0067] Step 6: According to the needs of the control system, the calibrated signal acquisition data can be further extracted from the SoC processing system, such as frequency domain and time domain analysis of the signal, and the BIT detection results can be further processed to determine whether the system is faulty and analyze the cause of the fault.

[0068] Step 7: Implement the host communication interface in the SoC processing system to complete the host control of the distributed network protocol chip or controller.

[0069] Step 8, implement the distributed network protocol and transceiver functions through the distributed network in the smart sensor system, output the data of the smart sensor system, and accept the network configuration of the control system.

[0070] In one embodiment,

[0071] The signal conditioning method of step 2 is: perform corresponding signal conversion, amplification, hardware filtering processing on the signals of Pt200, thermocouple, and silicon piezoresistive pressure sensor, and then send them to A / D acquisition. The signal conditioning method for LVDT is to amplify, filter, rectify, convert to DC effective value voltage and perform A / D acquisition. The frequency signal conditioning method is to filter, shape, convert to square wave, and perform frequency capture.

[0072] The signal acquisition timing of step 3 is implemented by the SoC processing system through its programmable logic or by the SoC processing system through software control of its GPIO, etc.

[0073] Among them, the temperature sensor in step 4 can use the SoC on-chip temperature sensor when the SoC processing system and the control system sensor are in the same location (such as integrated together); when the SoC processing system and the smart sensor are in different locations and their temperatures are not correlated, an external temperature sensor near the smart sensor can be used.

[0074] The temperature compensation and nonlinear calibration algorithms in step 4 are implemented using multivariate linear regression and neural networks. By training the collected data under different standard input temperatures of the sensor, the calibration parameters are embedded into the SoC system. This can complete the calibration of the sensor signal acquisition data in real time, eliminating the acquisition error caused by temperature changes and the acquisition error caused by system nonlinearity.

[0075] The time domain and frequency domain analysis in step 6 is achieved by performing FFT, correlation and other algorithms on the signal to obtain the signal's amplitude, frequency, effective value, spectrum and other characteristics.

[0076] In step 7, the host communication interface is implemented through the peripheral interface of the SoC processing system or through the programmable logic to realize the local bus. For example, the RS-485, CAN and other interfaces are implemented through the SoC peripheral interface, while the FlexRAY protocol chip interface is controlled by the programmable logic to realize the local bus. The TTP protocol chip interface can be controlled by the PCI bus through programmable logic or SoC peripherals.

[0077] In step 8, the distributed network communication protocol is implemented using a dedicated communication protocol chip, or using a peripheral integrated in the SoC processing system. Generally, a redundant design is used to ensure data transmission reliability.

[0078] The SoC system can collect the ambient temperature related to the sensor and conditioning circuit through the on-chip temperature sensor or external sensor, perform temperature compensation on the signal acquisition results in the full temperature range, and realize nonlinear calibration of the full range of signal acquisition through algorithms such as neural networks and multivariate linear regression. The calibrated parameters are embedded in the SoC system, and in the actual signal acquisition, the sensor signal acquisition data can be calibrated in real time to eliminate the acquisition error caused by temperature changes and the acquisition error caused by system nonlinearity. The architecture of the signal calibration design is shown in Figure 5. In the figure, the SoC collects the results of the sensor signal conditioning under the full range and temperature range to form a training data set, and then preprocesses the data set to eliminate redundant data and establish a data element mapping relationship; start neural network modeling, including defining the input and output data of the model, setting the number of input layer nodes, the number of output layer nodes, the number of hidden layers, the number of hidden layer nodes, the number of iterations, the learning rate, the training target accuracy and other neural network structure parameters and training parameters; start data training and obtain neural network parameters; test the obtained neural network, and use another part of the data that does not participate in the training to test whether the accuracy target is achieved, or test calibration through experiments; based on whether the test results meet the system's required accuracy as a criterion, decide whether the neural network parameters need to be adjusted. If the target has been achieved, solidify the model parameters as the calibration parameters of the smart sensor. If the target has not been achieved, continue to adjust the model parameters and re-train and test. The multivariate linear regression algorithm is similar, and the algorithm processing speed can be improved in some cases, which will not be repeated here.

[0079] The intelligent sensor system can perform time domain and frequency domain analysis on the signal acquisition data, and obtain the signal's amplitude, frequency, effective value, spectrum and other characteristics by performing FFT, correlation and other algorithms on the signal. Figure 6 In the process of collecting data for a certain signal, the collected data can be processed by selecting the data length or windowing according to the sampling rate and the accuracy required for processing, and then the fast Fourier transform (FFT) is performed to obtain the signal spectrum, and a specific spectrum or the entire spectrum is output as required; in order to obtain the precise amplitude of the signal at a certain frequency, relevant calculations can be performed at the frequency to obtain the signal amplitude. According to the selected SoC computing power, signal processing algorithms such as wavelet transform and Kalman filtering can also be used for signal processing development and verification.

[0080] In the SoC system, local bus, PCI bus, etc. can be constructed as the host communication interface. External local bus protocol chip can establish distributed network nodes to connect intelligent sensors to the control system. According to the system bandwidth requirements, fault tolerance and reliability, FlexRay, TTP, TTCAN and other buses can be selected. General CAN, RS-485 and other bus protocols can be directly implemented in the SoC system using SoC peripherals or IP. Figure 7 This is the FlexRay distributed network architecture diagram. A local bus is built in the SoC system as the host interface of the FlexRay bus protocol. Through the external FlexRay protocol chip and transceiver as the communication layer, redundant FlexRay nodes can be realized. The communication rate can reach 10Mbps, and time triggering is supported to ensure the high reliability and strong real-time control requirements of the system.

[0081] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed in the present application should be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be based on the protection scope of the claims.

Claims

1. An intelligent sensor development and verification system, characterized in that: Includes sensors, signal conditioning circuits, SoC processing systems, and distributed communication network interfaces; The sensors are installed at relevant monitoring points of the control system; The signal conditioning circuit applies corresponding excitation to the sensor and obtains the sensor signal. The signal conditioning circuit is used to condition the electrical signal of the sensor and perform A / D acquisition and conversion into a digital signal; The SoC processing system is an SoC processing system that integrates a microprocessor and a programmable logic unit, and realizes signal acquisition, temperature sensor, signal calibration, signal interface and processing system BIT, feature data extraction and fault monitoring functions. It is used to complete the calibration of signal acquisition data, extract the signal feature data required by the system, and send it to the communication protocol layer through the host communication interface under normal fault monitoring. In abnormal situations, it reports a fault. The SoC processing system calibrates the collected data through temperature compensation and nonlinear calibration algorithms based on the temperature information of the on-chip temperature sensor. The temperature compensation and nonlinear calibration algorithms are implemented using multivariate linear regression and neural networks. By training the collected data under various standard inputs of the sensor at different temperatures, the calibration parameters are embedded in the SoC system, and the calibration of the sensor signal acquisition data is completed in real time. The communication network interface is a distributed network interface, which consists of a network protocol and a network transceiver. It is configured for redundant communication according to the system networking requirements and connected to a distributed or general communication network to transmit data of smart sensors to the control system or receive system configuration; The sensor, signal conditioning circuit, SoC processing system and distributed communication network interface are integrated into an intelligent sensor as required; or the function is developed and verified by forming a system through independent component boards, and then the function is transplanted and integrated into an independent intelligent sensor.

2. The intelligent sensor development verification system according to claim 1, characterized in that: The sensor, signal conditioning circuit, SoC processing system and distributed communication network interface can be used as independent components to form a system, or integrated to form a board, smart sensor or chip.

3. A method for collecting and processing signals from an intelligent sensor, using the intelligent sensor development and verification system as claimed in claim 1 or 2, characterized in that: The steps include: Step 1, obtaining the temperature, displacement and pressure signals of the control system through temperature, displacement and pressure sensors, and converting them into corresponding electrical signals; Step 2: The sensor signal conditioning circuit of the intelligent sensor system applies corresponding excitation to the sensor, and the sensor signal conditioning circuit conditions the electrical signal of the sensor and converts it into a digital signal that can be directly collected by the SoC processing system or further converts it into a digital signal through A / D conversion and is collected by the SoC processing system; Step 3: The signal acquisition timing is controlled by the SoC processing system, and the acquisition results are stored in the programmable logic FIFO or on-chip RAM for digital filtering; Step 4, the SoC processing system collects temperature information through an on-chip temperature sensor or an external temperature sensor, and calibrates the collected data through temperature compensation and nonlinear calibration algorithms; Step 5, BIT acquisition hardware logic or software algorithm can perform BIT detection on the conditioning circuit and SoC processing system and communication system; Step 6: According to the control system requirements, the calibrated signal acquisition data can be further extracted in the SoC processing system, and the BIT detection results can be further processed to determine whether the system is faulty and analyze the cause of the fault; Step 7, implementing the host communication interface in the SoC processing system to complete the host control of the distributed network protocol chip or controller; Step 8, implement the distributed network protocol and transceiver functions through the distributed network in the smart sensor system, output the data of the smart sensor system, and accept the network configuration of the control system.

4. The intelligent sensor signal acquisition and processing method according to claim 3 is characterized in that: The signal conditioning method of step 2 is: perform corresponding signal conversion, amplification, hardware filtering processing on the signals of Pt200, thermocouple, and silicon piezoresistive pressure sensor, and then send them to A / D acquisition. The LVDT signal conditioning method is to amplify, filter, rectify, convert to DC effective value voltage and perform A / D acquisition. The frequency signal conditioning method is to filter, shape, convert to square wave, and perform frequency capture.

5. The intelligent sensor signal acquisition and processing method according to claim 3 is characterized in that: The signal acquisition timing of step 3 is implemented by the SoC processing system through programmable logic or by the SoC processing system through software control of GPIO.

6. The intelligent sensor signal acquisition and processing method according to claim 3 is characterized in that: The temperature sensor in step 4 uses an on-chip temperature sensor of the SoC when the SoC processing system and the control system sensor are in the same position; and uses an external temperature sensor near the smart sensor when the SoC processing system and the smart sensor are in different positions.

7. The intelligent sensor signal acquisition and processing method according to claim 3 is characterized in that: The time domain and frequency domain analysis in step 6 is achieved by performing FFT and correlation algorithms on the signal to obtain the amplitude, frequency, effective value, and spectrum characteristics of the signal.

8. The intelligent sensor signal acquisition and processing method according to claim 3 is characterized in that: In step 7, the host communication interface is implemented through a peripheral interface of the SoC processing system or through a local bus implemented by programmable logic.

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