Differential pressure prediction method for piston pressure

Abstract

The invention relates to the field of piston pressure prediction, and discloses a differential pressure prediction method for piston pressure, and the method comprises the steps: carrying out the preprocessing of the collected piston surface temperature data, environment temperature data and pressure data during the movement of a piston, and obtaining the differential pressure of the piston pressure based on the difference analysis result of the piston surface temperature data and the environment temperature data in a period of time. The differential pressure prediction module is used for performing temperature compensation correction on a pressure change state when a piston moves so as to calculate a pressure value after temperature compensation, calculating a compensated differential pressure value through the pressure value after temperature compensation, and performing comprehensive analysis on the compensated differential pressure value and historical differential pressure data to obtain a differential pressure prediction coefficient. Therefore, the differential pressure value in a certain period of time in the future is predicted, the temperature change condition during piston movement can be reflected more accurately, the accuracy of the pressure value can be further improved, the influence of the temperature change on the differential pressure calculation result can be eliminated, and the differential pressure prediction result is more accurate.

Description

Technical Field

[0001] The present invention relates to the technical field of piston pressure prediction, and more particularly to a differential pressure prediction method for piston pressure. Background Art

[0002] In a hydraulic system, the movement of a piston is often accompanied by pressure changes. Traditional piston control methods may not be able to reflect the dynamic changes of pressure in real time and accurately, while the differential pressure prediction method can predict and compensate the differential pressure of the piston pressure by real-time monitoring and analysis of the system pressure, further improving the measurement accuracy and reliability of the piston pressure gauge. This method can not only improve the control accuracy and stability of the hydraulic system, but also optimize the energy efficiency of the system and extend the service life of the equipment;

[0003] However, the above method still has the following disadvantages:

[0004] First, the existing piston differential pressure prediction method lacks the differential analysis of the piston surface temperature and the ambient temperature, and cannot obtain more accurate temperature difference values and surface temperature change values, resulting in inaccurate temperature monitoring during the movement of the piston and being unable to reflect the actual influence degree of temperature change on the pressure value;

[0005] Second, the existing piston differential pressure prediction method lacks the temperature compensation correction for the error of the influence coefficient of temperature on the pressure value affected by temperature change, and cannot eliminate the influence of temperature change on the differential pressure calculation result, resulting in inaccurate differential pressure prediction results. Summary of the Invention

[0006] In order to overcome the above defects of the prior art, the present invention provides a differential pressure prediction method for piston pressure to solve the problems existing in the above background art.

[0007] The present invention provides the following technical solution: A differential pressure prediction method for piston pressure, comprising:

[0008] S1: Real-time monitoring and acquisition of piston surface temperature data, ambient temperature data and pressure data during piston movement, and preprocessing the acquired piston surface temperature data, ambient temperature data and pressure data respectively;

[0009] S2: Obtaining a temperature difference value and a surface temperature change value by performing a differential analysis on the piston surface temperature data and the ambient temperature data over a period of time;

[0010] S3: Analyzing the influence of temperature on the pressure change state during piston movement to obtain a temperature influence coefficient, and performing temperature compensation correction on the error of the influence of temperature change on the pressure value through the temperature influence coefficient;

[0011] S4: Based on the surface temperature change value and the temperature influence coefficient, perform a comprehensive analysis, calculate the pressure value after temperature compensation, and use the pressure value after temperature compensation for the calculation of the piston differential pressure;

[0012] S5: Based on the pressure value after temperature compensation, calculate the current differential pressure of the piston to obtain the differential pressure value after compensation;

[0013] S6: Through comprehensive analysis of the differential pressure value after compensation and historical differential pressure data, obtain the differential pressure prediction coefficient, and predict the differential pressure value within a certain period in the future through the differential pressure prediction coefficient.

[0014] Preferably, in S1, by installing a piston pressure gauge on the piston movement path, fixing the pressure gauge on the engine using a bracket, and respectively connecting the two pressure gauges to the piston top and piston bottom through a suitable pressure transmission medium, the pressure data during piston movement is monitored and recorded in real time. By installing a temperature sensor in a position adjacent to the piston, the piston surface temperature data during piston movement is measured; by installing multiple temperature sensors at different positions in the external test environment simultaneously, the average temperature at different positions in the external test environment is obtained as the ambient temperature data; then, data cleaning, data conversion, standardization, and data integration are performed on the surface temperature data, ambient temperature data, and pressure data respectively.

[0015] Preferably, in S2, by respectively measuring and recording the piston surface temperature data within a period of time as T 表，1 , T 表，2 , …, T 表，i , …, T 表，n , and the ambient temperature data as T 环，1 , T 环，2 , …, T 环，i , …, T 环，n , perform a difference analysis on the piston surface temperature data and the ambient temperature data within a period of time, calculate the temperature difference value as ΔT i = T 表，i - T 环，i , and through the analysis of the average value of the piston surface temperature data and the average value of the ambient temperature data within a period of time, calculate the surface temperature change value as where n represents the number of temperature measurements.

[0016] Preferably, in S3, by analyzing the linear relationship between the temperature difference value and the piston pressure, the change situation of the temperature affecting the piston pressure error is monitored, and the temperature influence coefficient is calculated, which is used to represent the sensitivity of the temperature change to the pressure change. The specific calculation formula of the temperature influence coefficient is where P i represents the original pressure measurement value at the i-th time point, and ΔT iThe temperature difference value at the i-th time point is denoted as, and β represents the constant term.

[0017] Preferably, in S4, the error caused by temperature change is subtracted from the original pressure value, and the specific calculation formula for the temperature-compensated pressure value is where P i represents the original pressure measurement value at the i-th time point, α represents the temperature influence coefficient, R represents the surface temperature change value, ΔT i represents the temperature difference value at the i-th time point, and n represents the number of temperature measurements.

[0018] Preferably, in S5, the two pressure values measured by two piston pressure gauges at the same time point i are respectively read as P 顶，i and P 底，i , and then the two pressure values are respectively calculated as P 顶 ′ ，i and P 底 ′ ，i by using the calculation formula for the temperature-compensated pressure value. By calculating P 顶 ′ ，i and P 底 ′ ，i , the calculation formula for the compensated differential pressure value is obtained as ΔP′ = P 顶 ′ ，i -P 底 ′ ，i , and the calculated compensated differential pressure value is classified and stored in the database according to the data acquisition time.

[0019] Preferably, in S6, the historical compensated differential pressure values within a certain historical time period are collected, and the historical differential pressure data is cleaned and preprocessed, including removing outliers, filling in missing values, and data standardization. By analyzing the preprocessed historical compensated differential pressure values and the current compensated differential pressure value, and comprehensively calculating the differential pressure prediction coefficient;

[0020] The specific analysis method for the differential pressure prediction coefficient is as follows:

[0021] Step S611: By respectively calculating the historical differential pressure average value μ ΔP′ and the historical differential pressure standard deviation σ ΔP′ within a certain historical time period, the specific calculation formula for the historical differential pressure average value is The specific calculation formula for the historical differential pressure standard deviation is ΔP′ represents the compensated differential pressure value analyzed currently, and m represents the number of historical data points;

[0022] Step S612: By analyzing the influence of the time series on the differential pressure prediction, the differential pressure prediction coefficient is comprehensively calculated as a t represents the differential pressure prediction coefficient at the t-th time point, λ represents the time weight coefficient, and a t-1 represents the differential pressure prediction coefficient at the (t - 1)-th time point; and the differential pressure prediction coefficient is output as the prediction output result.

[0023] Technical effects and advantages of the present invention:

[0024] The present invention monitors and collects the piston surface temperature data, ambient temperature data, and pressure data during piston movement in real time, and preprocesses them. By analyzing the difference between the piston surface temperature data and the ambient temperature data over a period of time, the temperature difference value and the surface temperature change value are obtained. By analyzing the influence of temperature on the pressure change state during piston movement, the temperature influence coefficient is obtained, and the error of the temperature change affecting the pressure value is compensated and corrected. Through comprehensive analysis of the surface temperature change value and the temperature influence coefficient, the pressure value after temperature compensation is calculated for calculating the piston differential pressure. By calculating the current differential pressure of the piston using the pressure value after temperature compensation, the compensated differential pressure value is obtained. By comprehensively analyzing the compensated differential pressure value and the historical differential pressure data, the differential pressure prediction coefficient is obtained. By using the differential pressure prediction coefficient to predict the differential pressure value within a certain period in the future, through analyzing the difference between the piston surface temperature and the ambient temperature, more accurate temperature difference value and surface temperature change value can be obtained, which helps to more accurately reflect the temperature change situation during piston movement. Using the temperature influence coefficient to compensate and correct the error of the temperature change affecting the pressure value can further improve the accuracy of the pressure value, which is beneficial to eliminating the influence of temperature change on the differential pressure calculation result, thus making the result of differential pressure prediction more accurate. Description of the Drawings

[0025] Figure 1 is the method step diagram of the present invention.

[0026] Figure 2 is the system structure block diagram of the present invention. Detailed Embodiment

[0027] The following will clearly and completely describe the technical solutions in the present invention with reference to the drawings in the present invention. In addition, the forms of each structure described in the following embodiments are merely examples, and a differential pressure prediction method for piston pressure involved in the present invention is not limited to the structures described in the following embodiments. All other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0028] As Figure 1 shown, this embodiment provides a differential pressure prediction method for piston pressure, including:

[0029] S1: For real-time monitoring and acquisition of piston surface temperature data, ambient temperature data, and pressure data during piston movement, and separately preprocessing the acquired piston surface temperature data, ambient temperature data, and pressure data.

[0030] In this embodiment, S1 installs piston pressure gauges on the piston movement path, fixes the pressure gauges on the engine using brackets, and separately connects the two pressure gauges to the piston top and piston bottom through appropriate pressure transmission media to real-time monitor and record the pressure data during piston movement. By installing temperature sensors in positions adjacent to the piston to measure the piston surface temperature data during piston movement; by installing multiple temperature sensors at different positions in the external test environment simultaneously to obtain the average temperature at different positions in the external test environment as the ambient temperature data; and then separately performing data cleaning, data conversion, standardization, and data integration on the surface temperature data, ambient temperature data, and pressure data.

[0031] Specifically, by installing temperature sensors in positions adjacent to the piston, real-time monitoring and recording the changes in piston surface temperature during piston movement, and setting a sufficiently high data acquisition frequency to capture rapid temperature changes. By collecting ambient temperature data simultaneously with multiple temperature sensors, calculating the average temperature at different positions in the environment collected by the multiple temperature sensors at the same time point, and recording the changes in ambient temperature at different time points. Since the ambient temperature changes relatively slowly, a lower data acquisition frequency can be set. By using two piston pressure gauges connected to the piston top and piston bottom to real-time monitor and record pressure changes, the data acquisition frequency of the piston pressure gauges should match that of the temperature sensors in positions adjacent to the piston to ensure data synchronization.

[0032] S2: By performing differential analysis on the piston surface temperature data and ambient temperature data over a period of time, obtaining the temperature difference value and the surface temperature change value.

[0033] In this embodiment, S2 measures and records the piston surface temperature data over a period of time as T 表，1 , T 表，2 , …, T 表，i , …, T 表，n , and the ambient temperature data as T 环，1 , T 环，2 , …, T 环，i , …, T 环，n , performs differential analysis on the piston surface temperature data and ambient temperature data over a period of time, and calculates the temperature difference value as ΔT i = T 表，i - T 环，i, by analyzing the average value of the piston surface temperature data and the average value of the ambient temperature data over a period of time, the surface temperature change value is calculated as where n represents the number of temperature measurements.

[0034] S3: It is used to analyze the pressure change state during the piston movement due to temperature, obtain the temperature influence coefficient, and perform temperature compensation and correction on the error of the pressure value affected by the temperature change through the temperature influence coefficient.

[0035] In this embodiment, S3 monitors the change of the error of the piston pressure affected by temperature by analyzing the linear relationship between the temperature difference value and the piston pressure, and calculates the temperature influence coefficient, which is used to represent the sensitivity of the pressure change to the temperature change. The specific calculation formula of the temperature influence coefficient is where P i represents the original pressure measurement value at the i-th time point, ΔT i represents the temperature difference value at the i-th time point, and β represents the constant term.

[0036] S4: Based on the surface temperature change value and the temperature influence coefficient, a comprehensive analysis is performed to calculate the pressure value after temperature compensation, and the pressure value after temperature compensation is used for calculating the piston differential pressure.

[0037] In this embodiment, S4 subtracts the error caused by the temperature change from the original pressure value. The specific calculation formula of the pressure value after temperature compensation is where P i represents the original pressure measurement value at the i-th time point, α represents the temperature influence coefficient, R represents the surface temperature change value, ΔT i represents the temperature difference value at the i-th time point, and n represents the number of temperature measurements.

[0038] S5: Based on the pressure value after temperature compensation, the current differential pressure of the piston is calculated to obtain the compensated differential pressure value.

[0039] In this embodiment, S5 reads the two pressure values measured by two piston pressure gauges at the same time point i, which are P 顶，i and P 底，i , and then calculates the two pressure values as P 顶 ′ ，i and P 底 ′ ，i respectively by using the calculation formula of the pressure value after temperature compensation. By calculating P 顶 ′ ，i and P 底 ′ ，i , the calculation formula for obtaining the compensated differential pressure value is ΔP′ = P 顶 ′ ，i-P 底 ′ ，i , and classify and store the calculated compensated differential pressure values in the database according to the data acquisition time.

[0040] S6: By comprehensively analyzing the compensated differential pressure value and the historical differential pressure data, obtain the differential pressure prediction coefficient, and predict the differential pressure value within a certain period in the future through the differential pressure prediction coefficient.

[0041] In this embodiment, S6 collects the historical compensated differential pressure values within a certain historical time period, and cleans and preprocesses the historical differential pressure data, including removing outliers, filling missing values, and data standardization. By analyzing the preprocessed historical compensated differential pressure values and the current compensated differential pressure values, and comprehensively calculating the differential pressure prediction coefficient;

[0042] The specific analysis method of the differential pressure prediction coefficient is as follows:

[0043] Step S611: By respectively calculating the historical differential pressure average value μ ΔP′ and the historical differential pressure standard deviation σ ΔP′ , the specific calculation formula for the historical differential pressure average value is The specific calculation formula for the historical differential pressure standard deviation is ΔP′ represents the compensated differential pressure value analyzed currently, and m represents the number of historical data points;

[0044] Step S612: By analyzing the influence of the time series on the differential pressure prediction, comprehensively calculate the differential pressure prediction coefficient as a t represents the differential pressure prediction coefficient at the t-th time point, λ represents the time weight coefficient, a t-1 represents the differential pressure prediction coefficient at the (t - 1)-th time point; and output the differential pressure prediction coefficient as the prediction output result.

[0045] As Figure 2 shown, this embodiment provides an implementation system corresponding to a differential pressure prediction method for piston pressure, including a data acquisition module, a difference analysis module, a temperature influence coefficient calculation module, a temperature compensation analysis module, a differential pressure analysis module, and a differential pressure prediction module. The data acquisition module is connected to the difference analysis module, the temperature influence coefficient calculation module is connected to the temperature compensation analysis module, the difference analysis module is connected to the temperature compensation analysis module, the temperature compensation analysis module is connected to the differential pressure analysis module, and the differential pressure analysis module is connected to the differential pressure prediction module.

[0046] The data acquisition module is used to monitor and collect the piston surface temperature data, ambient temperature data, and pressure data in real time during piston movement, and preprocess the collected piston surface temperature data, ambient temperature data, and pressure data respectively;

[0047] The difference analysis module obtains the temperature difference value and the surface temperature change value by analyzing the difference between the piston surface temperature data and the ambient temperature data over a period of time;

[0048] The temperature influence coefficient calculation module is used to analyze the influence of temperature on the pressure change state during piston movement, obtain the temperature influence coefficient, and perform temperature compensation and correction on the error of the pressure value affected by temperature change through the temperature influence coefficient;

[0049] The temperature compensation analysis module performs comprehensive analysis based on the surface temperature change value and the temperature influence coefficient, calculates the pressure value after temperature compensation, and uses the pressure value after temperature compensation for the calculation of the piston differential pressure;

[0050] The differential pressure analysis module calculates the current differential pressure of the piston based on the pressure value after temperature compensation to obtain the differential pressure value after compensation;

[0051] The differential pressure prediction module obtains the differential pressure prediction coefficient by comprehensively analyzing the differential pressure value after compensation and the historical differential pressure data, and predicts the differential pressure value within a certain period in the future through the differential pressure prediction coefficient.

[0052] Finally: The above are only the preferred embodiments of the present invention and are not used to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

[0053] The above is only the specific implementation manner of this application, but the protection scope of this application is not limited thereto. Any person skilled in the art can easily think of changes or replacements within the technical scope disclosed in this application, and all should be covered by the protection scope of this application. Therefore, the protection scope of this application should be subject to the protection scope of the claims.

Claims

1. A differential pressure prediction method for piston pressure, characterized in that: include: S1: used for real-time monitoring and collecting piston surface temperature data, ambient temperature data and pressure data during piston movement, and pre-processing the collected piston surface temperature data, ambient temperature data and pressure data respectively; S2: by performing difference analysis on piston surface temperature data and ambient temperature data within a period of time, a temperature difference value and a surface temperature change value are obtained; S3: used to analyze the effect of temperature on the pressure change during piston movement, obtain the temperature influence coefficient, and use the temperature influence coefficient to perform temperature compensation correction on the error of the pressure value affected by temperature change; S4: Based on the surface temperature change value and the temperature influence coefficient, a comprehensive analysis is performed to calculate the pressure value after temperature compensation, and the pressure value after temperature compensation is used to calculate the piston differential pressure; S5: Calculate the current differential pressure of the piston based on the pressure value after temperature compensation to obtain the differential pressure value after compensation; S6: The differential pressure value after compensation is comprehensively analyzed with the historical differential pressure data to obtain a differential pressure prediction coefficient, and the differential pressure value within a certain period of time in the future is predicted by the differential pressure prediction coefficient.

2. A differential pressure prediction method for piston pressure according to claim 1, characterized in that: The S1 installs a piston pressure gauge on the piston movement path, fixes the pressure gauge on the engine with a bracket, and connects the two pressure gauges to the top and bottom of the piston through a suitable pressure transmission medium, so as to monitor and record the pressure data of the piston during movement in real time, and installs a temperature sensor in a position close to the piston to measure the surface temperature data of the piston during movement; installs multiple temperature sensors at different positions in the external test environment at the same time to simultaneously obtain the average temperature of different positions in the external test environment as the ambient temperature data; and then performs data cleaning, data conversion, standardization and data integration on the surface temperature data, ambient temperature data and pressure data respectively.

3. A differential pressure prediction method for piston pressure according to claim 1, characterized in that: S2 measures and records the piston surface temperature data for a period of time as T 表，1 , T 表，2 ,…,T 表，i ,…,T 表，n , the ambient temperature data is T 环，1 , T 环，2 ,…,T 环，i ,…,T 环，n , analyze the difference between the piston surface temperature data and the ambient temperature data over a period of time, and calculate the temperature difference value ΔT i =T 表，i -T 环，i By analyzing the average piston surface temperature data and the average ambient temperature data over a period of time, the surface temperature change value is calculated. Where n represents the number of temperature measurements.

4. A differential pressure prediction method for piston pressure according to claim 1, characterized in that: The S3 analyzes the linear relationship between the temperature difference and the piston pressure to monitor the change in the piston pressure error due to temperature, and calculates the temperature influence coefficient to indicate the sensitivity of the temperature change to the pressure change. The specific calculation formula of the temperature influence coefficient is: Among them, P i represents the original pressure measurement value at the i-th time point, ΔT i represents the temperature difference value at the i-th time point, and β represents the constant term.

5. A differential pressure prediction method for piston pressure according to claim 1, characterized in that: The S4 is calculated by subtracting the error caused by temperature change from the original pressure value. The specific calculation formula of the temperature compensated pressure value is: Among them, P i represents the original pressure measurement value at the i-th time point, α represents the temperature influence coefficient, R represents the surface temperature change value, ΔT i represents the temperature difference value at the i-th time point, and n represents the number of temperature measurements.

6. A differential pressure prediction method for piston pressure according to claim 1, characterized in that: S5 reads two pressure values ​​measured by two piston pressure gauges at the same time point i, respectively, and the two pressure values ​​are P 顶，i and P 底，i Then, the two pressure values ​​are calculated by using the temperature-compensated pressure value calculation formula: P 顶 ' ，i and P 底 ' ，i , through P 顶 ' ，i and P 底 ' ，i Calculate and get the differential pressure value after compensation as ΔP′=P 顶 ' ，i -P 底 ' ，i The calculated compensated differential pressure values ​​are stored in the database according to the data acquisition time.

7. A differential pressure prediction method for piston pressure according to claim 1, characterized in that: The S6 collects historical compensated differential pressure values ​​within a historical period of time, cleans and preprocesses the historical differential pressure data, including removing outliers, filling missing values, and standardizing data, analyzes the preprocessed historical compensated differential pressure values ​​with the current compensated differential pressure values, and comprehensively calculates the differential pressure prediction coefficient; The specific analysis method of the differential pressure prediction coefficient is: Step S611: Calculate the historical differential pressure average μ over a period of time ΔP′ and the historical differential pressure standard deviation σ ΔP′ , the specific calculation formula for the historical differential pressure average is: The specific calculation formula for the historical differential pressure standard deviation is: ΔP′ represents the compensated differential pressure value currently analyzed, and m represents the number of historical data points; Step S612: By analyzing the influence of time series on differential pressure prediction, the differential pressure prediction coefficient is comprehensively calculated as a t represents the differential pressure prediction coefficient at the tth time point, λ represents the time weight coefficient, a t-1 represents the differential pressure prediction coefficient at the t-1th time point; and outputs the differential pressure prediction coefficient as the prediction output result.

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