A method and apparatus for processing and analyzing pressure sensor data

Abstract

A pressure sensing data processing and analysis method and device, comprising: obtaining pressure sensing data, the pressure sensing data comprising varying pressure values and corresponding times; performing smoothing preprocessing on the pressure sensing data to obtain smoothed pressure sensing data; calculating the smoothed pressure sensing data to estimate the first derivative and the second derivative of the pressure change curve at each time point; and analyzing the pressure change data and the first derivative and the second derivative at each time point to mark several feature points in the pressure change curve. The present application can determine the feature points at different times in the pressure change curve through a fast and accurate analysis method, and can be applied to the processing and analysis of pressure sensing data in membrane separation and membrane treatment technology.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of pressure sensing data analysis, in particular to a pressure sensing data processing and analysis method and device. BACKGROUND

[0002] In the field of industry and scientific research, pressure sensing data plays a crucial role, especially in membrane separation and membrane processing technology. The importance of this data is self-evident. Membrane separation technology is widely used in water treatment, food industry, biotechnology and chemical processes. In these applications, pressure is one of the key parameters that affect the performance of membrane separation, which directly determines the filtration efficiency and processing capacity. Through accurate pressure measurement, it can ensure that the membrane system operates under optimal pressure conditions, thereby optimizing separation efficiency, prolonging the service life of the membrane, and reducing energy consumption. In addition, pressure sensing data also provides important information for researchers to study the permeability and selectivity of membrane materials. By systematically changing the operating pressure and observing the impact on separation performance, researchers can optimize the design of membrane materials and develop more efficient and economical membrane separation solutions.

[0003] However, the existing analysis method of pressure sensing data has the following problems: First, the pressurization module of the pressure threshold detection instrument is affected by various factors during pressurization, such as uneven pressurization caused by equipment aging or the pressurization method of the pressurization module itself. This influence may cause the pressure change data to present a periodic fluctuation state, and such fluctuating pressure curve will affect the accuracy of the judgment of the pressure threshold of the membrane; secondly, when judging the pressure threshold of the membrane, it is usually necessary to select a stable pressure value according to the pressure change, and the existing method of observing the curve with the naked eye to judge the stable position in the change curve cannot accurately and efficiently judge the position and number of stable points; finally, when the pressure is close to the pressure threshold, the state of the membrane may gradually change, and there is a lack of a fast and accurate analysis method to judge the state of the membrane at different times in the pressure change curve. SUMMARY

[0004] The main purpose of the present application is to overcome the above-mentioned defects in the prior art, and to provide a pressure sensing data processing and analysis method and device, which can mark the feature points in the pressure change curve by analyzing the change trend of the pressure sensing data, so as to facilitate researchers to further analyze the performance of the membrane.

[0005] The present application adopts the following technical solutions:

[0006] A pressure sensing data processing and analysis method, characterized in that it comprises:

[0007] acquiring pressure sensing data, the pressure sensing data including varying pressure values and their corresponding times;

[0008] smooth the pressure sensing data to obtain smoothed pressure sensing data;

[0009] calculate the first derivative and the second derivative of the pressure change curve of the smoothed pressure sensing data at each time point;

[0010] analyze the pressure change data and the first derivative and the second derivative at each time point to mark a plurality of feature points in the pressure change curve.

[0011] The smoothing preprocessing includes median smoothing based on a sliding window and mean smoothing based on a sliding window.

[0012] The first derivative of the pressure change curve of the smoothed pressure sensing data at each time point is estimated, specifically, the first derivative of the smoothed pressure sensing data at time points other than the head and tail of the data is calculated using the central difference method, and the first derivative of the head and tail of the smoothed pressure sensor data at two time points is calculated using the backward difference method and the forward difference method, respectively.

[0013] The first derivative of the pressure change curve of the smoothed pressure sensing data at each time point is estimated, specifically, the first derivative of the point group near each time point of the pressure change curve is estimated using the least squares method.

[0014] The second derivative of the pressure change curve of the smoothed pressure sensing data at each time point is estimated, specifically, the first derivative of the pressure change curve at each time point calculated is calculated again to obtain the second derivative at each time point.

[0015] Marking a plurality of feature points in the pressure change curve includes traversing all pressure values in the pressure sensing data or sorting the pressure values corresponding to all time points, and marking the data point with the largest pressure value as the pressure maximum point.

[0016] Marking a plurality of feature points in the pressure change curve includes marking the time t0 of the maximum point of the first derivative of the pressure change curve, traversing the data points with time t > t0, comparing the first derivative of the pressure change at each data point with the stable threshold k, and if the absolute value of the first derivative of the data point is less than the stable threshold k, marking the data point as a pressure stable point.

[0017] Marking several feature points in the pressure change curve, including marking the time of the maximum point of the first derivative of the pressure change curve as t0, traversing the data points in the pressure change curve with time t>t0, and marking the data point with the minimum second derivative of the pressure change as the opening point of the membrane hole detected by the pressure sensor.

[0018] A pressure sensing data processing and analysis device, comprising

[0019] A data acquisition module acquires pressure sensing data, including varying pressure values and their corresponding times;

[0020] A data processing module performs smoothing preprocessing on the pressure sensing data to obtain smoothed pressure sensing data;

[0021] A data calculation module calculates the smoothed pressure sensing data to estimate the first and second derivatives of the pressure change curve at each time point;

[0022] A data analysis module analyzes the pressure change data and the first and second derivatives at each time point to mark several feature points in the pressure change curve.

[0023] From the above description of the present application, compared with the prior art, the present application has the following beneficial effects:

[0024] 1. The present application can reduce the error influence of periodic fluctuations of pressure in instrument measurement through preprocessing of pressure sensing data, which is beneficial to more accurately judge the change of pressure.

[0025] 2. The present application can be applied to sensor data processing of membrane separation and membrane treatment technology, and through analyzing the trend of data change, marking the numerical point after pressure stabilization, it is convenient to more efficiently and accurately obtain the pressure threshold of the membrane.

[0026] 3. The present application can mark the feature points in the pressure change curve which can describe the opening state of the membrane hole by analyzing the trend of data change, which is convenient for researchers to further analyze the performance of the membrane in membrane separation and membrane treatment technology. BRIEF DESCRIPTION OF DRAWINGS

[0027] Figure 1 A flowchart of a pressure sensing data processing and analysis method provided by the present application;

[0028] Figure 2 A schematic diagram of smoothing preprocessing of pressure change data described in the embodiment;

[0029] Figure 3 A result schematic diagram of smoothing processing of a complete set of pressure change data described in the embodiment;

[0030] Figure 4 This is a schematic diagram showing the results of calculating the first and second derivatives of the pressure change data in the embodiment, and the positions of the pressure stabilization point and the membrane pore opening point are marked according to the first and second derivatives.

[0031] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. Detailed Implementation

[0032] The present invention will be further described below through specific embodiments.

[0033] See Figure 1 A method for processing and analyzing pressure sensing data, comprising the following steps:

[0034] S1 acquires pressure sensing data, which includes the changing pressure value and its corresponding time. That is, the pressure value changes with time, and there is a one-to-one correspondence between time and pressure value.

[0035] S2 performs smoothing preprocessing on the pressure sensing data to obtain smoothed pressure sensing data.

[0036] In this invention, the smoothing preprocessing includes median smoothing based on a sliding window and mean smoothing based on a sliding window.

[0037] Specifically, median smoothing includes: assuming the pressure sensing data is a pressure value sequence P = {p1, p2, ..., p...} of length N. i …,p N}, p i Representing the i-th pressure value, the window size is set to W. When the window moves to p... i At that time, the sequence within the window is The `median(·)` function finds the median of a set of numbers. If W is even, then... The window is located at the boundary of the pressure value sequence, i.e. or When filling points outside the boundary using reflection, for example, if there is a pressure value sequence {1,2,3,4,5} and the window size is 3, when processing the first and last pressure values, a value needs to be filled out, and the filled sequence becomes {1,1,2,3,4,5,5}.

[0038] The mean smoothing method is similar to the median smoothing method. It is assumed that the pressure sensing data is a pressure value sequence P = {p1, p2, ..., p...} of length N. i ,…,p N}, p n Representing the i-th pressure value, the window size is set to W. When the window moves to p... iThe sequence in the window is The mean(·) represents the mean value of a set of numbers. When performing mean smoothing, a suitable window sliding step can be selected according to the specific pressure fluctuation. When the sliding step is set to k (k > 1), the window advances by k points each time, and the sequence processed in turn is The pressure values at positions other than 1 + jk (j = 1, 2,...) are skipped. The skipped values can be omitted or filled in using linear interpolation.

[0039] For example:

[0040] Reference Figure 2 When performing smoothing preprocessing on a set of pressure data, the window size is set to 3, and the window slides in the direction of increasing time, advancing by one time unit each time. For the sequence {4, 4.2, 4.6, 4.9, 5.2, 5.6, 6.0, 6.2} on the graph, the results after median smoothing and mean smoothing of the sliding window are {4, 4.3, 4.6, 4.9, 5.2, 5.6, 6.0, 6.2}. The overall data smoothing effect is shown in reference Figure 3 .

[0041] S3 calculates the first and second derivatives of the smoothed pressure sensor data at each time point.

[0042] In this step, the first derivative of the smoothed pressure sensor data at each time point is estimated. Specifically, the central difference method is used to calculate the first derivative of the smoothed pressure sensor data at time points other than the head and tail of the data, and the backward difference method and the forward difference method are used to calculate the first derivative of the head and tail of the data, respectively.

[0043] The first derivative of the pressure change data at each time point is estimated. For time point t i , the sampling interval between each data point is t step , and the first derivative at this point is estimated using the following central difference method:

[0044] Two points are used to estimate:

[0045] To improve accuracy, four points can also be used to estimate:

[0046] Where d i represents the first derivative at time point i, i.e., the slope.

[0047] In practical applications, the first derivative of the pressure change curve of the smoothed pressure sensing data at each time point is estimated, and the first derivative of a group of points near each time point of the pressure change curve is also estimated by using the least square method, which uses the data points in a fitting window to obtain the slope of the fitted straight line as the first derivative of the center point in the window.

[0048] In this step, the second derivative of the pressure change curve of the smoothed pressure sensing data at each time point is estimated, specifically: the first derivative of the calculated pressure change curve at each time point is calculated again to obtain the second derivative at each time point. The method for calculating the second derivative is to calculate the derivative of the obtained first derivative again to obtain the second derivative at each time point.

[0049] As shown in Figure 4 the left graph is the smoothed pressure data (solid line) and the calculated first derivative of the pressure change (short dashed line), Figure 4 and the right graph is the smoothed pressure data (solid line) and the calculated second derivative of the pressure change (long dashed line).

[0050] S4 analyzes according to the pressure change data and the first derivative and the second derivative at each time point, and marks a plurality of feature points in the pressure change curve.

[0051] The plurality of feature points in the pressure change curve are marked, including traversing all pressure values in the pressure sensing data or sorting the pressure values corresponding to all time points, and marking the data point with the largest pressure value as the maximum pressure point.

[0052] The plurality of feature points in the pressure change curve are marked, including marking the time of the maximum point of the first derivative of the pressure change curve as t0, traversing the data points with time t > t0, comparing the first derivative of the pressure change at each data point with the stable threshold k, and if the absolute value of the first derivative of the data point is less than the stable threshold k, marking the data point as a pressure stable point.

[0053] The plurality of feature points in the pressure change curve are marked, including marking the time of the maximum point of the first derivative of the pressure change curve as t0, traversing the data points with time t > t0 in the pressure change curve, and marking the data point with the minimum second derivative of the pressure change as the preliminary opening point of the membrane hole detected by the pressure sensor.

[0054] For example, the pressure stable point and the preliminary opening point of the membrane hole are marked according to the first derivative of the smoothed pressure change and the second derivative of the pressure change in the present application, as shown in Figure 4 the left graph, the shaded part is the marked pressure stable point, and the set stable threshold is 0.015 at this time; Figure 4The minimum value of the second derivative of the pressure change in the right graph is marked as the preliminary opening point of the membrane holes. Since the holes on a piece of porous membrane are not all the same size, the pressure required for the opening of large holes is smaller than that of small holes, and the preliminary opening point is the opening point of the larger holes among these holes, which can be used to measure the uniformity of the membrane holes.

[0055] Based on this, the application further provides a pressure sensing data processing and analysis device, comprising:

[0056] A data acquisition module acquires pressure sensing data, the pressure sensing data including varying pressure values and corresponding times.

[0057] A data processing module performs smoothing preprocessing on the pressure sensing data to obtain smoothed pressure sensing data.

[0058] A data calculation module calculates the smoothed pressure sensing data to estimate the first derivative and the second derivative of the pressure change curve at each time point.

[0059] A data analysis module analyzes the pressure change data and the first derivative and the second derivative at each time point to mark a plurality of feature points in the pressure change curve.

[0060] In the application, the data acquisition module, the data processing module, the data calculation module, and the data analysis module are respectively used to perform steps S1-S4 in a pressure sensing data processing and analysis method.

[0061] In the application, the terms "first", "second", "third", etc. are only used to distinguish similar objects, and do not have to be used to describe a specific order or sequence, nor can they be understood as indicating or implying relative importance. In the description, the directions or positions indicated by "up", "down", "left", "right", "front" and "back" are based on the directions or positions shown in the drawings, and are only used to facilitate the description of the application, and do not indicate or imply that the devices must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the scope of protection of the application. For those skilled in the art, the specific meaning of the above terms in this application can be understood according to the specific circumstances.

[0062] In addition, in the description of the present application, "a plurality of" means two or more, unless otherwise specified. The association between the associated objects described by "and / or" indicates that there can be three relationships, for example, A and / or B can represent the three cases of A alone, A and B together, and B alone. The character " / " generally represents an "or" relationship between the associated objects before and after it.

[0063] The above merely illustrates the specific embodiments of the present application, but the design concept of the present application is not limited thereto, and any non-essential modification of the present application by using the concept shall be deemed as the infringement of the protection scope of the present application.

Claims

1. A method for processing and analyzing pressure sensing data, applied to sensor data processing in membrane separation and membrane treatment technologies, characterized in that, include: Acquire pressure sensing data, which includes changing pressure values ​​and their corresponding times; The pressure sensing data is preprocessed by smoothing to obtain smoothed pressure sensing data. The smoothed pressure sensing data is calculated to estimate the first and second derivatives of the pressure change curve at each time point; Based on the pressure change data and the first and second derivatives at each time point, several characteristic points in the pressure change curve are marked.

2. The method for processing and analyzing pressure sensing data as described in claim 1, characterized in that, The smoothing preprocessing includes median smoothing based on a sliding window and mean smoothing based on a sliding window.

3. The method for processing and analyzing pressure sensing data as described in claim 1, characterized in that, The first derivative of the pressure change curve of the smoothed pressure sensing data at each time point is estimated by: using the central difference method to calculate the first derivative of the smoothed pressure sensing data at time points other than the head and tail of the data, and using the backward difference method and the forward difference method to calculate the first derivative of the smoothed pressure sensing data at two time points at the head and tail of the data, respectively.

4. The method for processing and analyzing pressure sensing data as described in claim 1, characterized in that, The first derivative of the pressure change curve of the smoothed pressure sensing data at each time point is estimated by using the least squares method piecewise to estimate the first derivative of the pressure change curve around each time point.

5. The method for processing and analyzing pressure sensing data as described in claim 1, characterized in that, The second derivative of the pressure change curve of the smoothed pressure sensing data at each time point is estimated by: recalculating the derivative of the first derivative of the calculated pressure change curve at each time point to obtain the second derivative at each time point.

6. The method for processing and analyzing pressure sensing data as described in claim 1, characterized in that, Marking several feature points in the pressure change curve includes traversing all pressure values ​​in the pressure sensing data or sorting the pressure values ​​corresponding to all time points, and marking the data point with the largest pressure value as the maximum pressure point.

7. The method for processing and analyzing pressure sensing data as described in claim 1, characterized in that, Marking several characteristic points in the pressure change curve, including marking the time of the point where the first derivative of the pressure change curve is maximized, and the time interval is... The data points are iterated through, and the first derivative of the pressure change at each data point is compared with the stability threshold. The comparison is performed; if the absolute value of the first derivative of the data point is less than the stability threshold... If so, then mark the data point as the pressure stabilization point.

8. The method for processing and analyzing pressure sensing data as described in claim 1, characterized in that, The time for marking several characteristic points in the pressure change curve, including the time for marking the point where the first derivative of the pressure change curve is maximized, is as follows: The time points in the pressure change curve are: The data points with the smallest second derivative of the pressure change are marked as the opening points of the membrane pores detected by the pressure sensor.

9. A pressure sensing data processing and analysis device, used for sensor data processing in membrane separation and membrane treatment technologies, characterized in that, include The data acquisition module acquires pressure sensing data, which includes changing pressure values ​​and their corresponding times. The data processing module performs smoothing preprocessing on the pressure sensing data to obtain smoothed pressure sensing data. The data calculation module calculates the smoothed pressure sensing data and estimates the first and second derivatives of the pressure change curve at each time point. The data analysis module analyzes the pressure change data and the first and second derivatives at each time point, marking several feature points in the pressure change curve.

Images