Application Method and System of Embedded System in Pressure Transmitter

Abstract

The present invention relates to the field of industrial automation control, and discloses an application method and system of an embedded system in a pressure transmitter, including: analyzing the working environment corresponding to the pressure transmitter, collecting the current pressure sensitivity information of the pressure transmitter, and setting the working mode sequence of the embedded system in the pressure transmitter; calculating the operation efficiency loss of the embedded system in the data processing process, calculating the signal conduction efficiency loss generated during the transmission of the embedded system, and determining the composite operation loss of the embedded system in the pressure transmitter; calculating the measurement distortion coefficient of the pressure transmitter, calculating the resource occupancy evolution rate of the embedded system, and evaluating the operation steady-state performance of the embedded system in the pressure transmitter; determining the performance optimization target of the embedded system, performing application control management on the embedded system in the pressure transmitter, and obtaining the application result. The present invention can improve the application efficiency of the embedded system in the pressure transmitter.

Description

Technical Field

[0001] The present invention relates to an application method and system of an embedded system in a pressure transmitter, belonging to the field of industrial automation control. Background Art

[0002] Pressure transmitters are widely used in industrial production, aerospace, medical and other fields, and are particularly crucial in industrial production. Precise pressure monitoring is related to the stability of the production process, the improvement of product quality and safe production. With the increasing demand for automation and intelligence in various industries, the market demand for pressure transmitters is on the rise, and the performance and function requirements are more stringent.

[0003] At present, most pressure transmitters adopt traditional general-purpose microprocessors with specific signal processing circuits. In actual applications, first, functions such as the measurement range, accuracy, output signal type, etc., and control requirements such as real-time processing and communication transmission are determined. Then, a microprocessor with appropriate computing speed, memory, and peripheral interfaces is selected, and a hardware circuit is built to connect the microprocessor with signal conditioning, A / D conversion, and communication interface circuits. A sensor is connected to collect pressure signals. At the software level, programs are written in C language or assembly language to implement data acquisition, processing, conversion, and communication transmission. Finally, the system is debugged, the measured values are calibrated, and the signal amplification factor is adjusted. This method uses general-purpose microprocessors that are not customized for pressure measurement, with low resource utilization efficiency, difficult to meet the requirements of real-time performance and high precision, complex software architecture, high development and maintenance costs, poor flexibility and scalability in the face of diverse application scenarios, resulting in easy interference with measurement accuracy, difficult to adapt to complex working environments, and unable to meet the high-performance requirements of modern industry for pressure monitoring. Therefore, a method that can improve the application efficiency of embedded systems in pressure transmitters is needed. Summary of the Invention

[0004] The present invention provides an application method and system of an embedded system in a pressure transmitter, and its main purpose is to improve the application efficiency of the embedded system in the pressure transmitter.

[0005] To achieve the above object, an application method of an embedded system in a pressure transmitter provided by the present invention includes:

[0006] Obtain a pressure transmitter applying the embedded system, analyze the working environment corresponding to the pressure transmitter, collect the current pressure sensitivity information of the pressure transmitter, and set the working mode sequence of the embedded system in the pressure transmitter according to the working environment and the pressure sensitivity information;

[0007] Calculate the operation efficiency loss of the embedded system during data processing, and calculate the signal conduction efficiency loss generated by the embedded system during transmission. Combine the operation efficiency loss and the conduction efficiency loss to determine the composite operation loss of the embedded system in the pressure transmitter;

[0008] Record the pressure detection data and system operation state parameters of the pressure transmitter under the control of the embedded system. Based on the pressure detection data, calculate the measurement distortion coefficient of the pressure transmitter. Based on the system operation state parameters, calculate the resource occupancy evolution rate of the embedded system. Combine the measurement distortion coefficient and the resource occupancy evolution rate to evaluate the running steady-state performance of the embedded system in the pressure transmitter;

[0009] Combine the pressure sensitivity information and the composite operation loss to determine the performance optimization target of the embedded system. According to the running steady-state performance and the performance optimization target, formulate the running optimization strategy of the embedded system in the pressure transmitter. Based on the running optimization strategy and the working mode sequence, execute the application control and management of the embedded system in the pressure transmitter to obtain the application result.

[0010] Optionally, setting the working mode sequence of the embedded system in the pressure transmitter according to the working environment and the pressure sensitivity information includes:

[0011] Collect parameters of the working environment to obtain environmental parameters;

[0012] Conduct index analysis on the pressure sensitivity information to obtain sensitivity indexes;

[0013] Based on the environmental parameters and the sensitivity indexes, identify the applicable working modes of the pressure transmitter;

[0014] Rank the applicable working modes by priority to obtain the working mode sequence of the embedded system in the pressure transmitter.

[0015] Optionally, calculating the operation efficiency loss of the embedded system in the data processing process includes:

[0016] Collect and process the operation data of the embedded system to obtain system operation data;

[0017] Preprocess the system operation data to obtain preprocessed data;

[0018] Extract features from the preprocessed data to obtain system operation features;

[0019] Based on the system operation features, calculate the operation efficiency loss of the embedded system in the data processing process.

[0020] Optionally, calculating the signal conduction efficiency loss generated by the embedded system during transmission includes:

[0021] Monitor the signals during the transmission process of the embedded system to obtain signal transmission data;

[0022] Perform filtering processing on the signal transmission data to obtain filtered signal data;

[0023] Extract features from the filtered signal data to obtain signal transmission features;

[0024] Based on the signal transmission features, calculate the signal conduction efficiency loss generated by the embedded system during the transmission process.

[0025] Optionally, the calculating the signal conduction efficiency loss generated by the embedded system during the transmission process based on the signal transmission features includes:

[0026] Extract the original signal features and output signal features from the signal transmission features;

[0027] Extract the original signal strength, original signal frequency, and original signal phase of the embedded system during the transmission process from the original signal features;

[0028] Extract the output signal strength, output signal frequency, and output signal phase of the embedded system during the transmission process from the output signal features;

[0029] Calculate the time delay value of the embedded system during the transmission process, and combine the original signal strength, the original signal frequency, the original signal phase, the output signal strength, the output signal frequency, the output signal phase, and the time delay value. Calculate the signal conduction efficiency loss generated by the embedded system during the transmission process through the following formula:

[0030] ;

[0031] Where, A represents the signal conduction efficiency loss generated by the embedded system during the transmission process, represents the original signal strength of the i-th signal, represents the output signal strength of the i-th signal, represents the original signal frequency of the i-th signal, represents the output signal frequency of the i-th signal, represents the original signal phase of the i-th signal, represents the output signal phase of the i-th signal, represents the time delay value of the i-th signal, represents the ideal transmission time of the i-th signal, i represents the signal serial number, and n represents the number of signals.

[0032] Optionally, calculating the measurement distortion coefficient of the pressure transmitter based on the pressure detection data includes:

[0033] Performing data smoothing processing on the pressure detection data to obtain smoothed pressure detection data;

[0034] Extracting the pressure detection values from the smoothed pressure detection data;

[0035] Calculating the pressure mean value and the pressure standard deviation corresponding to the pressure transmitter based on the pressure detection values;

[0036] Performing signal decomposition processing on the smoothed pressure detection data to obtain a pressure signal component and a signal noise component;

[0037] Calculating the noise level corresponding to the smoothed pressure detection data based on the pressure signal component and the signal noise component;

[0038] Combining the pressure detection values, the pressure mean value, the pressure standard deviation, and the noise level to calculate the measurement distortion coefficient of the pressure transmitter.

[0039] Optionally, combining the pressure detection values, the pressure mean value, the pressure standard deviation, and the noise level to calculate the measurement distortion coefficient of the pressure transmitter includes:

[0040] Calculating the signal distortion degree corresponding to the pressure transmitter based on the pressure detection values;

[0041] Combining the signal distortion degree, the pressure mean value, the pressure standard deviation, and the noise level, and calculating the measurement distortion coefficient of the pressure transmitter through the following formula:

[0042] ;

[0043] where F represents the measurement distortion coefficient of the pressure transmitter, represents the pressure mean value, represents the ideal pressure mean value, represents the pressure standard deviation, represents the ideal standard deviation, represents the noise level, represents the maximum allowable noise level, represents the signal distortion degree.

[0044] Optionally, calculating the resource occupancy evolution rate of the embedded system based on the system operation state parameters includes:

[0045] Performing time calibration processing on the system operation state parameters to obtain calibrated operation state parameters;

[0046] Divide the calibration operation state parameters into interval windows to obtain a set of window state parameters;

[0047] Conduct a trend analysis on the set of window state parameters to obtain the window state trend;

[0048] Based on the window state trend, calculate the derivative rate of resource occupancy of the embedded system.

[0049] Optionally, evaluating the running steady-state performance of the embedded system in the pressure transmitter by combining the measurement distortion coefficient and the derivative rate of resource occupancy includes:

[0050] Perform normalization processing on the measurement distortion coefficient and the derivative rate of resource occupancy to obtain a normalized distortion coefficient and a normalized derivative rate;

[0051] Query the system description function corresponding to the embedded system and analyze the function-sensitive factors corresponding to the system description function;

[0052] Based on the function-sensitive factors, allocate weight coefficients corresponding to the measurement distortion coefficient and the derivative rate of resource occupancy to obtain a distortion weight and a derivative weight;

[0053] Combine the distortion weight, the derivative weight, the normalized distortion coefficient, and the normalized derivative rate to calculate the running steady-state score of the embedded system in the pressure transmitter;

[0054] Evaluate the running steady-state performance of the embedded system in the pressure transmitter based on the running steady-state score.

[0055] To solve the above problems, the present invention also provides an application system of an embedded system in a pressure transmitter, and the system includes:

[0056] A working mode sequence setting module, configured to obtain a pressure transmitter applying the embedded system, analyze the working environment corresponding to the pressure transmitter, collect the current pressure sensitivity information of the pressure transmitter, and set the working mode sequence of the embedded system in the pressure transmitter according to the working environment and the pressure sensitivity information;

[0057] An operation loss calculation module, configured to calculate the operation efficiency loss of the embedded system in the data processing process, calculate the signal conduction efficiency loss generated by the embedded system in the transmission process, and combine the operation efficiency loss and the conduction efficiency loss to determine the composite operation loss of the embedded system in the pressure transmitter;

[0058] The running steady-state performance evaluation module is used to record the pressure detection data and system operation state parameters of the pressure transmitter under the control of the embedded system. Based on the pressure detection data, calculate the measurement distortion coefficient of the pressure transmitter. Based on the system operation state parameters, calculate the resource occupancy evolution rate of the embedded system. Combine the measurement distortion coefficient and the resource occupancy evolution rate to evaluate the running steady-state performance of the embedded system in the pressure transmitter;

[0059] The application control and management module is used to combine the pressure sensitivity information and the composite operation loss to determine the performance optimization goal of the embedded system. According to the running steady-state performance and the performance optimization goal, formulate the running optimization strategy of the embedded system in the pressure transmitter. Based on the running optimization strategy and the working mode sequence, execute the application control and management of the embedded system in the pressure transmitter to obtain the application result.

[0060] Compared with the problems described in the background art, according to the operating environment and the pressure sensitivity information, the present invention sets the working mode sequence of the embedded system in the pressure transmitter, and can obtain the optimized working state scheme of the pressure transmitter in different environments, thereby laying a foundation for subsequent adjustment of the working mode of the embedded system. Further, by calculating the operation efficiency loss of the embedded system in the data processing process, the present invention can accurately insight into the resource utilization efficiency of the system in the data operation link, clarify the potential loss points caused by factors such as hardware performance bottlenecks and algorithm complexity, and provide an important basis for the subsequent determination of the composite operation loss of the embedded system in the pressure transmitter. By calculating the measurement distortion coefficient of the pressure transmitter based on the pressure detection data, the present invention can quantify the deviation degree of the measurement result of the pressure transmitter, and provide a basis for the subsequent evaluation of the running steady-state performance of the embedded system in the pressure transmitter. Further, by combining the pressure sensitivity information and the composite operation loss to determine the performance optimization goal, and then according to the running steady-state performance and the performance optimization goal, formulating the running optimization strategy of the embedded system in the pressure transmitter, and finally combining the working mode sequence to execute the application control and management, this multi-step and comprehensive multi-factor method can comprehensively and accurately optimize the operation of the embedded system in the pressure transmitter, improving the overall performance and stability of the system. Therefore, the application method and system of the embedded system in the pressure transmitter provided by the embodiments of the present invention can improve the application efficiency of the embedded system in the pressure transmitter. Description of the Drawings

[0061] Figure 1 It is a schematic flowchart of the application method of the embedded system in the pressure transmitter provided by an embodiment of the present invention;

[0062] Figure 2 This is a schematic diagram of a module for implementing the application method of the embedded system in a pressure transmitter provided by an embodiment of the present invention.

[0063] The implementation, functional features, and advantages of the present invention will be further described with reference to the embodiments and the accompanying drawings. Specific embodiments

[0064] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0065] The embodiment of the present application provides an application method of an embedded system in a pressure transmitter. The execution subject of the application method of the embedded system in the pressure transmitter includes, but is not limited to, at least one of electronic devices such as a server, a terminal, etc. that can be configured to execute the method provided by the embodiment of the present application. In other words, the application method of the embedded system in the pressure transmitter can be executed by software or hardware installed on a terminal device or a server device. The server includes, but is not limited to: a single server, a server cluster, a cloud server, or a cloud server cluster, etc.

[0066] Embodiment 1

[0067] Refer to Figure 1 As shown, it is a flowchart of the application method of the embedded system in a pressure transmitter provided by an embodiment of the present invention. In this embodiment, the application method of the embedded system in the pressure transmitter includes:

[0068] S1. Obtain a pressure transmitter to which the embedded system is applied, analyze the working environment corresponding to the pressure transmitter, collect the current pressure sensitivity information of the pressure transmitter, and set the working mode sequence of the embedded system in the pressure transmitter according to the working environment and the pressure sensitivity information.

[0069] According to the working environment and the pressure sensitivity information, the present invention sets the working mode sequence of the embedded system in the pressure transmitter, and can obtain an optimized working state solution of the pressure transmitter in different environments, thereby laying a foundation for subsequent adjustment of the working mode of the embedded system.

[0070] It should be noted that the pressure transmitter is a device used to measure and transmit pressure signals. It is usually composed of a sensor, a signal processing circuit, and an embedded system, and has high-precision pressure detection and signal transmission capabilities. The operating environment refers to the working conditions where the pressure transmitter is located, such as temperature, humidity, pressure range, etc. The pressure sensitivity information refers to the pressure measurement accuracy and sensitivity data of the pressure transmitter in the current environment. The working mode sequence is a combination of working modes set by the embedded system according to environmental conditions and pressure sensitivity information, such as low-power mode, high-precision mode, fast response mode, etc. Further, the analysis of the operating environment of the pressure transmitter can be achieved through sensor data collection and environmental monitoring equipment; the collection of the pressure sensitivity information can be obtained through a pressure calibration device.

[0071] Specifically, setting the working mode sequence of the embedded system in the pressure transmitter according to the operating environment and the pressure sensitivity information includes:

[0072] Collect parameters of the operating environment to obtain environmental parameters;

[0073] Analyze the indicators of the pressure sensitivity information to obtain sensitivity indicators;

[0074] Based on the environmental parameters and the sensitivity indicators, identify the applicable working modes of the pressure transmitter;

[0075] Rank the applicable working modes by priority to obtain the working mode sequence of the embedded system in the pressure transmitter.

[0076] It should be noted that the environmental parameters are the key data in the operating environment, such as temperature value, humidity value, pressure range, etc. The sensitivity indicators are the quantitative data of the pressure measurement accuracy and sensitivity of the pressure transmitter in the current environment. The applicable working mode is the working mode that can optimize the performance of the pressure transmitter by the embedded system under specific environmental conditions.

[0077] Furthermore, the data collection of the operating environment can be achieved through multi-sensor fusion technology; the index analysis of the pressure sensitivity information can be realized through data fitting and statistical analysis; based on the environmental parameters and the sensitivity index, the applicable operating mode of the pressure transmitter is identified. For example, certain environmental parameters may indicate a relatively high current environmental temperature, and in this case, the low-power consumption mode can be preferentially selected to reduce device heating; if the pressure sensitivity information shows that the current measurement accuracy requirement is relatively high, the high-precision mode can be selected to improve measurement accuracy. The priority ranking of the applicable operating modes can be achieved through a multi-objective optimization algorithm, such as using the non-dominated sorting genetic algorithm (NSGA-II), comprehensively considering multiple objectives such as the measurement accuracy, response speed, and energy consumption of the pressure transmitter, and comprehensively evaluating and ranking different operating modes to determine the priority of each operating mode.

[0078] S2. Calculate the operation efficiency loss of the embedded system during the data processing process, and calculate the signal conduction efficiency loss generated by the embedded system during the transmission process. Combining the operation efficiency loss and the conduction efficiency loss, determine the composite operation loss of the embedded system in the pressure transmitter.

[0079] By calculating the operation efficiency loss of the embedded system during the data processing process, the present invention can accurately insight into the resource utilization efficiency of the system in the data operation link, clarify the potential loss points caused by factors such as hardware performance bottlenecks and algorithm complexity, and provide an important basis for determining the composite operation loss of the embedded system in the pressure transmitter later. It should be explained that the operation efficiency loss refers to the loss caused by the waste of computing resources and the reduction of processing efficiency due to factors such as hardware performance limitations and algorithm complexity when the embedded system executes data processing tasks.

[0080] Specifically, the calculation of the operation efficiency loss of the embedded system during the data processing process includes:

[0081] Collect and process the operation data of the embedded system to obtain the system operation data;

[0082] Preprocess the system operation data to obtain the preprocessed data;

[0083] Extract features from the preprocessed data to obtain the system operation features;

[0084] Based on the system operation features, calculate the operation efficiency loss of the embedded system during the data processing process.

[0085] It should be noted that the system operation data includes indicators such as CPU utilization rate, memory occupancy rate, and disk I / O. The preprocessed data is the system operation data after removing noise and outliers. The system operation characteristics are key indicators reflecting the system operation state, such as the change trend of CPU utilization rate, the peak value of memory occupancy, etc. Further, the collection of the system operation data can be achieved through system monitoring tools, such as the top command in the Linux system; the processing of the preprocessed data can be achieved through data cleaning algorithms, such as outlier detection based on statistical methods; the feature extraction of the system operation characteristics can be achieved through time series analysis methods, such as Fourier transform or wavelet transform; based on the system operation characteristics, calculate the operation efficiency loss of the embedded system. For example, for CPU load, within time T, if the CPU busy time is t1, the CPU load rate L = t1 / T, and the higher the load rate, the greater the operation efficiency loss. In terms of memory occupancy, record the actual occupied memory M1 and the total available memory M0, and the memory occupancy rate R = M1 / M0. A high occupancy rate will increase the operation efficiency loss. The data processing duration refers to the time from when the data enters the system to when the processing is completed. Let the theoretically shortest processing time be t0 and the actual processing time be t2. The extension coefficient E = t2 / t0. The larger the coefficient, the higher the loss. Standardize each of the above coefficients and add the results to obtain the operation efficiency loss of the embedded system.

[0086] By calculating the signal conduction efficiency loss generated by the embedded system during the transmission process, the present invention can accurately insight into the degree to which signal transmission is affected by the system, providing a key basis for optimizing the signal transmission path and improving the overall performance of the system. It should be noted that the conduction efficiency loss refers to the loss generated due to the decline in signal quality caused by signal attenuation, interference, etc. during the transmission of the pressure signal through relevant circuits, interfaces, etc. of the embedded system.

[0087] Specifically, the calculation of the signal conduction efficiency loss generated by the embedded system during the transmission process includes:

[0088] Monitor the signal during the transmission process of the embedded system to obtain signal transmission data;

[0089] Perform filtering processing on the signal transmission data to obtain filtered signal data;

[0090] Perform feature extraction on the filtered signal data to obtain signal transmission characteristics;

[0091] Based on the signal transmission characteristics, calculate the signal conduction efficiency loss generated by the embedded system during the transmission process.

[0092] It should be noted that the signal transmission data includes indicators such as signal delay time and signal strength attenuation. The filtered signal data is the signal transmission data after removing noise. The signal transmission characteristics are the key indicators reflecting the signal transmission quality, such as the fluctuation of signal delay and the attenuation degree of signal strength. Further, the monitoring of the signal transmission data can be achieved through a signal analyzer; the processing of the filtered signal data can be achieved through digital filtering algorithms such as Kalman filtering; the feature extraction of the signal transmission characteristics can be achieved through signal processing methods such as spectrum analysis.

[0093] Further, as an optional embodiment of the present invention, calculating the signal conduction efficiency loss generated by the embedded system during the transmission process based on the signal transmission characteristics includes:

[0094] Extracting the original signal characteristics and output signal characteristics in the signal transmission characteristics;

[0095] Extracting the original signal strength, original signal frequency, and original signal phase of the embedded system during the transmission process from the original signal characteristics;

[0096] Extracting the output signal strength, output signal frequency, and output signal phase of the embedded system during the transmission process from the output signal characteristics;

[0097] Calculating the time delay value of the embedded system during the transmission process, and combining the original signal strength, the original signal frequency, the original signal phase, the output signal strength, the output signal frequency, the output signal phase, and the time delay value, calculating the signal conduction efficiency loss generated by the embedded system during the transmission process through the following formula:

[0098] ;

[0099] where A represents the signal conduction efficiency loss generated by the embedded system during the transmission process, represents the original signal strength of the i-th signal, represents the output signal strength of the i-th signal, represents the original signal frequency of the i-th signal, represents the output signal frequency of the i-th signal, represents the original signal phase of the i-th signal, represents the output signal phase of the i-th signal, represents the time delay value of the i-th signal, represents the ideal transmission time of the i-th signal, i represents the signal serial number, and n represents the number of signals.

[0100] It should be explained that the original signal characteristics and the output signal characteristics are key components of the signal transmission characteristics. The original signal strength, the original signal frequency, and the original signal phase are the basic signal attribute characteristics of the original signal characteristics regarding the embedded system during the transmission process. The output signal strength, the output signal frequency, and the output signal phase are the corresponding signal attribute characteristics of the embedded system after the transmission effect during the transmission process. The time delay value is the signal transmission time change characteristic of the embedded system during the transmission process. The ideal transmission time is the time that should be consumed for the signal to complete the transmission under ideal conditions such as without interference.

[0101] Furthermore, the original signal characteristics and the output signal characteristics in the signal transmission characteristics can be extracted by collecting data at the start and end of signal transmission respectively through multimodal sensors; the original signal strength, the original signal frequency, and the original signal phase of the embedded system during the transmission process can be extracted from the original signal characteristics through technical means such as signal spectrum analysis and amplitude detection; the output signal strength, the output signal frequency, and the output signal phase of the embedded system during the transmission process can be extracted from the output signal characteristics by processing the data at the end of transmission through the same signal spectrum analysis, amplitude detection combined with signal processing algorithms; the time delay value of the embedded system during the transmission process can be calculated by comparing the sending timestamp at the start of the signal and the receiving timestamp at the end of the signal.

[0102] The present invention determines the composite operation loss of the embedded system in the pressure transmitter by combining the operation efficiency loss and the conduction efficiency loss, which can comprehensively evaluate the operation efficiency of the system, and further provide a basis for optimizing the system performance. It should be explained that the composite operation loss is a comprehensive performance measurement index of the embedded system in the pressure transmitter. It integrates the operation efficiency loss and the conduction efficiency loss, comprehensively reflects the resource consumption and efficiency reduction of the system during data processing and signal transmission, and provides a key basis for evaluating the overall operation state and optimization direction of the system. Furthermore, by combining the operation efficiency loss and the conduction efficiency loss, the composite operation loss of the embedded system in the pressure transmitter is determined. For example, a specific loss superposition algorithm is adopted to add the values of the operation efficiency loss and the conduction efficiency loss, and then the coupling influence coefficient of the two during system operation is considered for correction to determine the composite operation loss. This value can help evaluate the comprehensive energy consumption level of the system in the pressure transmitter.

[0103] S3. Record the pressure detection data and system operation state parameters of the pressure transmitter under the control of the embedded system. Based on the pressure detection data, calculate the measurement distortion coefficient of the pressure transmitter. Based on the system operation state parameters, calculate the resource occupation evolution rate of the embedded system. Combine the measurement distortion coefficient and the resource occupation evolution rate to evaluate the running steady-state performance of the embedded system in the pressure transmitter.

[0104] By calculating the measurement distortion coefficient of the pressure transmitter based on the pressure detection data, the present invention can quantify the deviation degree of the measurement result of the pressure transmitter, providing a basis for the subsequent evaluation of the running steady-state performance of the embedded system in the pressure transmitter. It should be noted that the pressure detection data is the data obtained by the pressure transmitter measuring the pressure under the control of the embedded system, reflecting the real-time condition of the pressure; the system operation state parameters are the relevant parameters describing the running state of the embedded system, such as CPU usage rate, memory occupancy rate, number of threads, etc.; the measurement distortion coefficient is an index measuring the deviation degree between the measurement result of the pressure transmitter and the true value. The recording of the pressure detection data can be realized by a data acquisition card, and the recording of the system operation state parameters can be realized by system monitoring software.

[0105] Specifically, the calculating the measurement distortion coefficient of the pressure transmitter based on the pressure detection data includes:

[0106] Perform data smoothing processing on the pressure detection data to obtain smoothed pressure detection data;

[0107] Extract the pressure detection values from the smoothed pressure detection data;

[0108] Based on the pressure detection values, calculate the corresponding pressure mean value and pressure standard deviation of the pressure transmitter;

[0109] Perform signal decomposition processing on the smoothed pressure detection data to obtain pressure signal components and signal noise components;

[0110] Based on the pressure signal components and the signal noise components, calculate the noise level corresponding to the smoothed pressure detection data;

[0111] Combine the pressure detection values, the pressure mean value, the pressure standard deviation and the noise level to calculate the measurement distortion coefficient of the pressure transmitter.

[0112] It should be explained that the smoothed pressure detection data is the data obtained by processing the pressure detection data through noise reduction, filtering, etc. to reduce fluctuations and interference. The pressure detection value is the specific value in the smoothed pressure detection data used to characterize the magnitude of the pressure. The pressure signal component and the signal noise component are respectively components of the smoothed pressure detection data. The former reflects the real pressure change, and the latter represents the interference fluctuation. The noise level is a measure of the noise intensity corresponding to the smoothed pressure detection data, reflecting the degree of noise interference of the data.

[0113] Furthermore, the pressure detection data can be smoothed through a moving average filtering algorithm to obtain the smoothed pressure detection data; the pressure detection value in the smoothed pressure detection data can be extracted by direct reading or a specific indexing method; based on the pressure detection value, the pressure mean value and the pressure standard deviation corresponding to the pressure transmitter can be calculated through an arithmetic mean formula and a standard deviation calculation formula; the smoothed pressure detection data can be decomposed through a wavelet decomposition algorithm to obtain the pressure signal component and the signal noise component; based on the pressure signal component and the signal noise component, the noise level corresponding to the smoothed pressure detection data can be calculated by calculating the power ratio of the noise component.

[0114] Furthermore, as an optional embodiment of the present invention, calculating the measurement distortion coefficient of the pressure transmitter by combining the pressure detection value, the pressure mean value, the pressure standard deviation and the noise level includes:

[0115] Based on the pressure detection value, calculate the signal distortion degree corresponding to the pressure transmitter;

[0116] Combining the signal distortion degree, the pressure mean value, the pressure standard deviation and the noise level, calculate the measurement distortion coefficient of the pressure transmitter through the following formula:

[0117] ;

[0118] where F represents the measurement distortion coefficient of the pressure transmitter, represents the pressure mean value, represents the ideal pressure mean value, represents the pressure standard deviation, represents the ideal standard deviation, represents the noise level, represents the maximum allowable noise level, represents the signal distortion degree.

[0119] It should be noted that the signal distortion degree represents the deviation degree of the measurement signal corresponding to the pressure transmitter from the true pressure signal in terms of waveform, amplitude, etc.; the ideal pressure mean value is the average pressure that the pressure transmitter should output under standard working conditions, serving as a reference standard for measuring the accuracy of the actual pressure mean value; the ideal standard deviation is the theoretical value of the degree of dispersion of pressure measurement data in an ideal stable state, used to compare with the actual pressure standard deviation to evaluate the measurement stability; the maximum allowable noise level is the upper limit of the noise intensity that can be tolerated in the measurement data on the premise of ensuring that the measurement accuracy of the pressure transmitter is not significantly affected. Further, the ideal pressure mean value and the ideal standard deviation can be obtained by conducting a large number of tests on the pressure transmitter under standard working conditions, collecting and analyzing the data; the maximum allowable noise level can be determined from the product specification of the pressure transmitter or according to the accuracy requirements of relevant industry standards and actual application scenarios.

[0120] In the present invention, by calculating the resource occupancy evolution rate of the embedded system based on the system operation situation parameters, the dynamic change trend of the system resource usage can be detected in a timely manner, potential resource bottleneck problems can be predicted in advance, providing a strong basis for reasonably optimizing the system resource configuration and ensuring the stable operation of the system, and effectively avoiding system failures such as system jamming and crashing caused by insufficient resources or excessive resource occupancy. It should be noted that the resource occupancy evolution rate represents the degree of change in the resource occupancy (such as CPU usage rate, memory occupancy, etc.) of the embedded system per unit time, and is used to measure the dynamic change trend of the system resource usage.

[0121] Specifically, calculating the resource occupancy evolution rate of the embedded system based on the system operation situation parameters includes:

[0122] Performing time calibration processing on the system operation situation parameters to obtain calibrated operation situation parameters;

[0123] Performing interval window division on the calibrated operation situation parameters to obtain a set of window situation parameters;

[0124] Performing trend analysis on the set of window situation parameters to obtain the window situation trend;

[0125] Calculating the resource occupancy evolution rate of the embedded system based on the window situation trend.

[0126] It should be noted that the calibrated operation situation parameter is the data obtained by performing time calibration processing on the system operation situation parameter to ensure that the time series is accurate and consistent. The window situation parameter set is a series of data sets containing situation parameters within different time intervals, which are obtained by dividing the calibrated operation situation parameter according to a specific interval window division method. The window situation trend is obtained by trend analysis (such as linear regression and other methods) of the window situation parameter set, and is a quantitative result reflecting the change trend of resource occupancy over time within each window.

[0127] Furthermore, the system operation situation parameter can be time-calibrated by comparing the high-precision clock inside the system or an external standard time source, and the calibrated operation situation parameter can be obtained according to the time deviation. The calibrated operation situation parameter can be divided into interval windows according to a preset fixed window duration or a dynamically adjusted window strategy to obtain the window situation parameter set. Algorithms such as least squares linear regression and moving average method can be used to perform trend analysis on the window situation parameter set to obtain the window situation trend. Based on the window situation trend, by converting and summarizing the trend values of each window according to the window time span and the expected time unit, the resource occupancy evolution rate of the embedded system can be calculated. For example, first, according to the conversion relationship between the window time span and the expected time unit, the trend values of each window are converted into change rates under a unified time scale, and then statistical means such as summation or median are used to comprehensively obtain the resource occupancy evolution rate of the embedded system.

[0128] By combining the measurement distortion coefficient and the resource occupancy evolution rate, the present invention evaluates the running steady-state performance of the embedded system in the pressure transmitter, and can comprehensively and accurately evaluate the comprehensive stability of the system in pressure measurement and its own resource management, laying an important basis for formulating the subsequent operation optimization strategy of the embedded system in the pressure transmitter. It should be noted that the running steady-state performance is the ability performance of the embedded system in the pressure transmitter to maintain accurate pressure measurement and stable utilization of its own resources during the pressure measurement process, ensuring the overall reliability, continuity, and high efficiency of the system.

[0129] Specifically, the evaluation of the running steady-state performance of the embedded system in the pressure transmitter by combining the measurement distortion coefficient and the resource occupancy evolution rate includes:

[0130] Normalize the measurement distortion coefficient and the resource occupancy evolution rate to obtain the normalized distortion coefficient and the normalized evolution rate;

[0131] Query the system description function corresponding to the embedded system and analyze the function-sensitive factors corresponding to the system description function;

[0132] Based on the function-sensitive factors, assign weight coefficients corresponding to the measurement distortion coefficient and the resource occupancy evolution rate to obtain a distortion weight and an evolution weight;

[0133] Combine the distortion weight, the evolution weight, the normalized distortion coefficient, and the normalized evolution rate to calculate the running steady-state score of the embedded system in the pressure transmitter;

[0134] Based on the running steady-state score, evaluate the running steady-state performance of the embedded system in the pressure transmitter.

[0135] It should be explained that the normalized distortion coefficient and the normalized evolution rate are respectively quantitative indicators that eliminate dimensional differences and facilitate unified comparative analysis after the measurement distortion coefficient and the resource occupancy evolution rate are normalized; the system description function is the set of functional characteristics and expected goals corresponding to the embedded system; the function-sensitive factor is the key factor corresponding to the system description function that has a significant impact on its performance and effect; the distortion weight and the evolution weight are respectively the importance ratios of the measurement distortion coefficient and the resource occupancy evolution rate in evaluating the running steady-state performance of the system; the running steady-state score represents the quantitative score of the overall running stability and reliability of the embedded system in the pressure transmitter, reflecting the comprehensive measurement distortion and resource occupancy.

[0136] Furthermore, the measurement distortion coefficient and the resource occupancy evolution rate can be normalized by the min-max normalization algorithm to obtain the normalized distortion coefficient and the normalized evolution rate; the system description function corresponding to the embedded system can be queried by referring to the system technical documentation or calling a specific system information query interface, and the function-sensitive factors corresponding to the system description function can be analyzed by methods such as expert experience judgment, correlation analysis, or fault tree analysis; based on the function-sensitive factors, the weight coefficients corresponding to the measurement distortion coefficient and the resource occupancy evolution rate can be assigned by means of the analytic hierarchy process, the entropy weight method, or machine learning algorithms to obtain the distortion weight and the evolution weight; combining the distortion weight, the evolution weight, the normalized distortion coefficient, and the normalized evolution rate, the running steady-state score of the embedded system in the pressure transmitter can be calculated by the weighted summation formula; based on the running steady-state score, the running steady-state performance of the embedded system in the pressure transmitter can be evaluated by means of a pre-set score threshold interval or comparison with historical data.

[0137] S4. Combine the pressure sensitivity information and the composite operation loss to determine the performance optimization objective of the embedded system. According to the running steady-state performance and the performance optimization objective, formulate the operation optimization strategy of the embedded system in the pressure transmitter. Based on the operation optimization strategy and the working mode sequence, execute the application control and management of the embedded system in the pressure transmitter to obtain the application result.

[0138] In the present invention, by combining the pressure sensitivity information and the composite operation loss to determine the performance optimization objective, and then according to the running steady-state performance and the performance optimization objective, formulating the operation optimization strategy of the embedded system in the pressure transmitter, and finally combining the working mode sequence to execute the application control and management. This multi-step and comprehensive multi-factor approach can comprehensively and accurately optimize the operation of the embedded system in the pressure transmitter, improve the overall performance and stability of the system. It should be noted that the performance optimization objective is a set of quantitative indicators and effects that comprehensively consider the pressure sensitivity information and the composite operation loss situation in the application scenario of the embedded system in the pressure transmitter, and are expected to achieve multi-faceted performance improvements such as improving measurement accuracy, reducing resource consumption, and enhancing operation stability. The operation optimization strategy is a specific method for optimizing the operation of the embedded system in the pressure transmitter.

[0139] Further, combine the pressure sensitivity information and the composite operation loss to determine the performance optimization objective of the embedded system. For example, when the pressure sensitivity is lower than the standard value, set improving the measurement accuracy as the primary objective, and at the same time, according to the degree of the composite operation loss, formulate a specific index of reducing the loss by X% within a certain period of time; or when the pressure sensitivity meets the requirements but the loss is too high, focus on reducing the composite operation loss, and expect that after optimization, the overall energy consumption of the system can be reduced by Y% on the premise of ensuring that the measurement accuracy does not decrease.

[0140] Further, according to the running steady-state performance and the performance optimization objective, formulate the operation optimization strategy of the embedded system in the pressure transmitter. For example, when the running steady-state performance shows that the system resource occupancy rate is relatively high but the pressure sensitivity is acceptable, focus on reducing the composite operation loss. By optimizing the system software code, reducing unnecessary processes and data processing links, and at the same time adjusting the working frequency and voltage of the hardware, energy conservation can be achieved without affecting the pressure measurement accuracy; if the pressure measurement error is relatively large and the resource occupancy is also unreasonable in the running steady-state performance, and the performance optimization objective requires double improvement, on the one hand, upgrade the pressure sensor hardware to improve the measurement accuracy, and on the other hand, redesign the software architecture, optimize the data processing and transmission process, and improve the overall operation efficiency of the system.

[0141] Finally, based on the above-mentioned operation optimization strategy and the working mode sequence, the application control and management of the embedded system in the pressure transmitter can be executed through an automated control feedback mechanism to obtain an application result.

[0142] Compared with the problems described in the background art, according to the operating environment and the pressure sensitivity information, the present invention sets the working mode sequence of the embedded system in the pressure transmitter, and can obtain an optimized working state solution of the pressure transmitter in different environments, thereby laying a foundation for subsequent adjustment of the working mode of the embedded system. Further, by calculating the operation efficiency loss of the embedded system during the data processing process, the present invention can accurately insight into the resource utilization efficiency of the system in the data operation link, clarify potential loss points caused by factors such as hardware performance bottlenecks and algorithm complexity, and provide an important basis for the determination of the composite operation loss of the embedded system in the pressure transmitter in the future. By calculating the measurement distortion coefficient of the pressure transmitter based on the pressure detection data, the present invention can quantify the deviation degree of the measurement result of the pressure transmitter, and provide a basis for the evaluation of the operation steady-state performance of the embedded system in the pressure transmitter in the future. Further, by combining the pressure sensitivity information and the composite operation loss to determine the performance optimization target, and then formulating the operation optimization strategy of the embedded system in the pressure transmitter according to the operation steady-state performance and the performance optimization target, and finally executing the application control and management in combination with the working mode sequence, this multi-step and multi-factor comprehensive method can comprehensively and accurately optimize the operation of the embedded system in the pressure transmitter, and improve the overall performance and stability of the system. Therefore, the application method and system of the embedded system in the pressure transmitter provided by the embodiments of the present invention can improve the application efficiency of the embedded system in the pressure transmitter.

[0143] Embodiment 2

[0144] As Figure 2 shown, it is a functional module diagram of an application system of an embedded system in a pressure transmitter according to the present invention.

[0145] The application system 200 of the embedded system in the pressure transmitter according to the present invention can be installed in an electronic device. According to the realized functions, the application system of the embedded system in the pressure transmitter can include a working mode sequence setting module 201, an operation loss calculation module 202, an operation steady-state performance evaluation module 203, and an application control and management module 204. The modules in the present invention can also be referred to as units, which refer to a series of computer program segments that can be executed by the processor of the electronic device and can complete fixed functions, and are stored in the memory of the electronic device.

[0146] In the embodiments of the present invention, the functions of each module / unit are as follows:

[0147] The working mode sequence setting module 201 is configured to obtain a pressure transmitter applying an embedded system, analyze the working environment corresponding to the pressure transmitter, collect the current pressure sensitivity information of the pressure transmitter, and set the working mode sequence of the embedded system in the pressure transmitter according to the working environment and the pressure sensitivity information;

[0148] The operation loss calculation module 202 is configured to calculate the operation efficiency loss of the embedded system during data processing, calculate the signal conduction efficiency loss generated during the transmission of the embedded system, and determine the composite operation loss of the embedded system in the pressure transmitter by combining the operation efficiency loss and the conduction efficiency loss;

[0149] The operation steady-state performance evaluation module 203 is configured to record the pressure detection data and system operation state parameters of the pressure transmitter under the control of the embedded system, calculate the measurement distortion coefficient of the pressure transmitter based on the pressure detection data, calculate the resource occupation evolution rate of the embedded system based on the system operation state parameters, and evaluate the operation steady-state performance of the embedded system in the pressure transmitter by combining the measurement distortion coefficient and the resource occupation evolution rate;

[0150] The application control and management module 204 is configured to determine the performance optimization target of the embedded system by combining the pressure sensitivity information and the composite operation loss, formulate an operation optimization strategy of the embedded system in the pressure transmitter according to the operation steady-state performance and the performance optimization target, perform application control and management of the embedded system in the pressure transmitter based on the operation optimization strategy and the working mode sequence, and obtain an application result.

[0151] Specifically, each module in the application system 200 of the embedded system in the pressure transmitter in the embodiment of the present invention adopts the same technical means as the Figure 1 application method of the embedded system in the pressure transmitter described above, and can produce the same technical effects, which will not be elaborated here.

[0152] For those skilled in the art, it is obvious that the present invention is not limited to the details of the above exemplary embodiments, and without departing from the spirit or basic characteristics of the present invention, the present invention can be implemented in other specific forms.

[0153] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. An application method of an embedded system in a pressure transmitter, characterized in that: The method comprises: Acquire a pressure transmitter to which an embedded system is applied, analyze the operating environment corresponding to the pressure transmitter, collect current pressure precision sensitivity information of the pressure transmitter, and set a working mode sequence of the embedded system in the pressure transmitter according to the operating environment and the pressure precision sensitivity information, wherein the working mode sequence is a combination of working modes set by the embedded system according to environmental conditions and pressure precision sensitivity information; Calculating the computing efficiency loss of the embedded system during data processing, and calculating the signal conduction efficiency loss generated by the embedded system during transmission, and combining the computing efficiency loss and the conduction efficiency loss to determine the composite operation loss of the embedded system in the pressure transmitter; Record the pressure detection data and system operation status parameters of the pressure transmitter under the control of the embedded system, wherein the system operation status parameters are related parameters describing the operating status of the embedded system; calculate the measurement distortion coefficient of the pressure transmitter based on the pressure detection data, wherein the measurement distortion coefficient is an indicator measuring the degree of deviation between the measurement result of the pressure transmitter and the true value; calculate the resource occupancy evolution rate of the embedded system based on the system operation status parameters, wherein the resource occupancy evolution rate indicates the degree of change of the resource occupancy of the embedded system in unit time, and is used to measure the dynamic change trend of system resource usage; and evaluate the operating steady-state performance of the embedded system in the pressure transmitter in combination with the measurement distortion coefficient and the resource occupancy evolution rate; In combination with the pressure sensitivity information and the composite operating loss, the performance optimization target of the embedded system is determined, and according to the operating steady-state performance and the performance optimization target, an operation optimization strategy of the embedded system in the pressure transmitter is formulated. Based on the operation optimization strategy and the working mode sequence, application control and management of the embedded system in the pressure transmitter is performed to obtain application results.

2. The method for applying the embedded system in a pressure transmitter according to claim 1, characterized in that: The step of setting a working mode sequence of the embedded system in the pressure transmitter according to the working environment and the pressure sensitivity information includes: Collecting parameters of the working environment to obtain environmental parameters; Performing index analysis on the pressure sensitivity information to obtain a sensitivity index; Based on the environmental parameter and the sensitivity index, identifying an applicable working mode of the pressure transmitter; The applicable working modes are prioritized to obtain a working mode sequence of the embedded system in the pressure transmitter.

3. The method for applying the embedded system in a pressure transmitter according to claim 1, characterized in that: The calculating the computing performance loss of the embedded system during data processing includes: Collecting and processing the operation data of the embedded system to obtain system operation data; Preprocessing the system operation data to obtain preprocessed data; Performing feature extraction on the preprocessed data to obtain system operation features; Based on the system operation characteristics, the computing performance loss of the embedded system during data processing is calculated.

4. The method for applying the embedded system in a pressure transmitter according to claim 1, characterized in that: The calculating the signal conduction efficiency loss generated by the embedded system during the transmission process includes: Monitoring the signal of the embedded system during the transmission process to obtain signal transmission data; Performing filtering on the signal transmission data to obtain filtered signal data; Performing feature extraction on the filtered signal data to obtain signal transmission features; Based on the signal transmission characteristics, the signal conduction efficiency loss generated by the embedded system during the transmission process is calculated.

5. The method for applying the embedded system in a pressure transmitter according to claim 4, characterized in that: The calculating, based on the signal transmission characteristics, the signal conduction efficiency loss generated by the embedded system during the transmission process includes: Extracting original signal features and output signal features from the signal transmission features; Extracting the original signal strength, original signal frequency, and original signal phase of the embedded system during transmission from the original signal features; Extracting the output signal strength, output signal frequency, and output signal phase of the embedded system during transmission from the output signal characteristics; The time delay value of the embedded system during the transmission process is calculated, and the signal conduction efficiency loss generated by the embedded system during the transmission process is calculated by combining the original signal strength, the original signal frequency, the original signal phase, the output signal strength, the output signal frequency, the output signal phase and the time delay value through the following formula: ； Among them, A represents the signal conduction efficiency loss generated by the embedded system during the transmission process. represents the original signal strength of the i-th signal, represents the output signal strength of the i-th signal, represents the original signal frequency of the i-th signal, represents the output signal frequency of the i-th signal, represents the original signal phase of the i-th signal, represents the output signal phase of the i-th signal, represents the time delay value of the i-th signal, represents the ideal transmission time of the i-th signal, i represents the signal sequence number, and n represents the number of signals.

6. The method for applying the embedded system in a pressure transmitter according to claim 1, characterized in that: The step of calculating the measurement distortion coefficient of the pressure transmitter based on the pressure detection data comprises: Performing data smoothing processing on the pressure detection data to obtain smoothed pressure detection data; extracting a pressure detection value from the smoothed pressure detection data; Based on the pressure detection value, calculating the pressure mean and pressure standard deviation corresponding to the pressure transmitter; Performing signal decomposition processing on the smoothed pressure detection data to obtain a pressure signal component and a signal noise component; calculating a noise level corresponding to the smoothed pressure detection data based on the pressure signal component and the signal noise component; The measurement distortion coefficient of the pressure transmitter is calculated by combining the pressure detection value, the pressure mean value, the pressure standard deviation and the noise level.

7. The method for applying the embedded system in a pressure transmitter according to claim 6, characterized in that: The calculating the measurement distortion coefficient of the pressure transmitter by combining the pressure detection value, the pressure mean value, the pressure standard deviation and the noise level includes: Based on the pressure detection value, calculating the signal distortion corresponding to the pressure transmitter; Combining the signal distortion, the pressure mean, the pressure standard deviation and the noise level, the measurement distortion coefficient of the pressure transmitter is calculated by the following formula: ； Where F represents the measurement distortion coefficient of the pressure transmitter, represents the mean pressure, represents the ideal pressure mean, represents the pressure standard deviation, represents the ideal standard deviation, represents the noise level, represents the maximum permissible noise level, Indicates signal distortion.

8. The method for applying the embedded system in a pressure transmitter according to claim 1, characterized in that: The step of calculating the resource occupancy evolution rate of the embedded system based on the system operation status parameter includes: Performing time calibration processing on the system operation status parameter to obtain a calibrated operation status parameter; Dividing the calibration operation status parameter into interval windows to obtain a window status parameter set; Performing trend analysis on the window situation parameter set to obtain a window situation trend; Based on the window situation trend, a resource occupancy evolution rate of the embedded system is calculated.

9. The method for applying the embedded system in a pressure transmitter according to claim 1, characterized in that: The step of evaluating the steady-state performance of the embedded system in the pressure transmitter by combining the measured distortion coefficient and the resource occupancy variation rate includes: Normalizing the measured distortion coefficient and the resource occupancy variation rate to obtain a normalized distortion coefficient and a normalized variation rate; Querying the system description function corresponding to the embedded system, and analyzing the function sensitive factors corresponding to the system description function; Based on the functional sensitivity factor, weight coefficients corresponding to the measured distortion coefficient and the resource occupancy evolution rate are allocated to obtain a distortion weight and an evolution weight; Calculate the running steady-state score of the embedded system in the pressure transmitter by combining the distortion weight, the derivative weight, the normalized distortion coefficient and the normalized derivative rate; Based on the steady-state operation score, the steady-state operation performance of the embedded system in the pressure transmitter is evaluated.

10. An application system of an embedded system in a pressure transmitter, characterized in that: The system comprises: A working mode sequence setting module, used to obtain a pressure transmitter to which an embedded system is applied, analyze the operating environment corresponding to the pressure transmitter, collect the current pressure precision sensitivity information of the pressure transmitter, and set the working mode sequence of the embedded system in the pressure transmitter according to the operating environment and the pressure precision sensitivity information, wherein the working mode sequence is a combination of working modes set by the embedded system according to environmental conditions and pressure precision sensitivity information; An operation loss calculation module, used to calculate the computing efficiency loss of the embedded system during data processing, and calculate the signal conduction efficiency loss generated by the embedded system during transmission, and determine the composite operation loss of the embedded system in the pressure transmitter by combining the computing efficiency loss and the conduction efficiency loss; An operation steady-state performance evaluation module is used to record the pressure detection data and system operation status parameters of the pressure transmitter under the control of the embedded system, wherein the system operation status parameters are related parameters describing the operation status of the embedded system, and based on the pressure detection data, calculate the measurement distortion coefficient of the pressure transmitter, wherein the measurement distortion coefficient is an indicator measuring the degree of deviation between the measurement result of the pressure transmitter and the true value, and based on the system operation status parameters, calculate the resource occupancy evolution rate of the embedded system, wherein the resource occupancy evolution rate represents the degree of change of the resource occupancy of the embedded system in unit time, and is used to measure the dynamic change trend of system resource usage, and evaluate the operation steady-state performance of the embedded system in the pressure transmitter in combination with the measurement distortion coefficient and the resource occupancy evolution rate; An application control management module is used to determine the performance optimization target of the embedded system in combination with the pressure sensitivity information and the composite operating loss, formulate an operation optimization strategy for the embedded system in the pressure transmitter according to the operating steady-state performance and the performance optimization target, and execute application control management of the embedded system in the pressure transmitter based on the operation optimization strategy and the working mode sequence to obtain application results.

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