Equipment air pressure monitoring method based on data analysis

Abstract

The invention discloses an equipment air pressure monitoring method based on data analysis, and belongs to the technical field of data analysis, and the method comprises the following steps: S1, obtaining air pressure values in a historical time period, and constructing an air pressure analysis network for the air pressure values in the historical time period; s2, generating a matrix set based on the air pressure analysis network, and constructing an air pressure monitoring matrix by using the matrix set; and S3, generating an air pressure value at the current moment by using the air pressure monitoring matrix, and completing air pressure monitoring. By constructing the air pressure analysis network and the air pressure monitoring matrix, high-precision monitoring and prediction of the air pressure in the compressor are achieved, the monitoring accuracy and real-time performance are improved, potential safety hazards and installation complexity possibly brought by installation of a sensor in the compressor are avoided, and the probability of occurrence of equipment failures can be reduced.

Description

Technical Field

[0001] The invention belongs to the technical field of data analysis, and in particular relates to a device air pressure monitoring method based on data analysis. Background Art

[0002] Compressors are widely used in the industrial field. The stability and safety of their operating status are crucial to production efficiency and product quality. As one of the important parameters for compressor operation, air pressure monitoring and control are of great significance to ensure the normal operation of the compressor. However, traditional air pressure monitoring methods often use sensors for real-time monitoring without prediction functions, which makes it difficult to meet the modern industry's demand for efficient, accurate and reliable air pressure monitoring. Summary of the invention

[0003] In order to solve the above problems, the present invention proposes a device air pressure monitoring method based on data analysis.

[0004] The technical solution of the present invention is: a method for monitoring equipment air pressure based on data analysis comprises the following steps:

[0005] S1. Obtain the air pressure values ​​in the historical time period and build an air pressure analysis network for the air pressure values ​​in the historical time period;

[0006] S2, generating a matrix set based on the air pressure analysis network, and constructing an air pressure monitoring matrix using the matrix set;

[0007] S3. Use the air pressure monitoring matrix to generate the current air pressure value and complete air pressure monitoring.

[0008] Furthermore, S1 includes the following sub-steps:

[0009] S11, obtaining air pressure values ​​in a historical time period, and randomly dividing all air pressure values ​​into a first air pressure pool and a second air pressure pool;

[0010] S12, selecting a maximum air pressure value and a minimum air pressure value from the first air pressure pool, constructing an air pressure loss function for the second air pressure value, and selecting a maximum air pressure value and a minimum air pressure value from the second air pressure pool, constructing an air pressure loss function for the first air pressure value;

[0011] S13, taking the maximum value between the absolute value of the air pressure loss function value of the first air pressure pool and the absolute value of the air pressure loss function of the second air pressure pool as the upper limit of the air pressure analysis range, and taking the minimum value between the absolute value of the air pressure loss function value of the first air pressure pool and the absolute value of the air pressure loss function of the second air pressure pool as the lower limit of the air pressure analysis range;

[0012] S14. Construct a pressure analysis network according to the pressure values ​​within the pressure analysis range in the historical time period.

[0013] The beneficial effect of the above further scheme is that in the present invention, the air pressure values ​​within a time series are divided into two data pools, the characteristic elements of the two data pools are used to construct respective loss functions, the values ​​of the loss functions are used to determine the endpoints of the air pressure analysis range, and finally an air pressure analysis network is generated. The air pressure values ​​corresponding to the grids in the air pressure analysis network are more representative, avoiding redundant parameters from affecting the prediction results of the air pressure values.

[0014] Further, in S12, the expression of the air pressure loss function Loss1 of the first air pressure pool is: Where A 1_i represents the i-th air pressure value of the first air pressure pool, I represents the number of air pressure values ​​of the first air pressure pool, and A 2_max Indicates the maximum pressure value of the second pressure pool, A 2_min represents the minimum air pressure value of the second air pressure pool, I represents the number of air pressure values ​​of the first air pressure pool, and ln(·) represents a logarithmic function;

[0015] The expression of the pressure loss function Loss2 of the second pressure pool is: Where A 2_j represents the jth air pressure value of the second air pressure pool, J represents the number of air pressure values ​​in the second air pressure pool, A 1_max Indicates the maximum pressure value of the first pressure pool, A 1_min Indicates the minimum air pressure value of the first air pressure pool.

[0016] Furthermore, S14 includes the following sub-steps:

[0017] S141, setting a blank grid for air pressure analysis, and filling the first row of the blank grid for air pressure analysis with air pressure values ​​that fall within the air pressure analysis range within the historical time period in descending order;

[0018] S142, calculating the air pressure category ratio between each remaining air pressure value and each grid in the first row of the air pressure analysis blank grid;

[0019] S143. Fill the air pressure value corresponding to the highest air pressure category rate between each grid into the bottom of the grid to obtain an air pressure analysis network.

[0020] The number of pressure values ​​that fall within the pressure analysis range during the historical time period is the same as the number of grid columns of the pressure analysis network. The number of rows of the pressure analysis network is 2.

[0021] Further, in S142, the pressure category rate p between the remaining k-th pressure value and the h-th column grid in the first row of the pressure analysis blank grid is k_h The calculation formula is: Where A kIndicates the remaining k-th air pressure value, A h It represents the air pressure value corresponding to the hth column grid in the first row of the blank grid of the air pressure analysis, α represents the upper limit of the air pressure analysis range, and β represents the lower limit of the air pressure analysis range.

[0022] Furthermore, S2 includes the following sub-steps:

[0023] S21, extracting a number of unit matrices from the air pressure analysis network to form a matrix set;

[0024] S22, generating a first air pressure element and a second air pressure element of an air pressure monitoring matrix according to the matrix set;

[0025] S23. Generate an air pressure monitoring matrix according to the first air pressure element and the second air pressure element.

[0026] The beneficial effect of the above further scheme is: in the present invention, the air pressure values ​​of each grid in the air pressure analysis network and the number of grid columns of the air pressure analysis network are used to determine the matrix set, and the parameters of the unit matrix in the matrix set are used to generate two air pressure elements, the first air pressure element is placed in the first row and first column of the air pressure monitoring matrix, and the second air pressure element is placed in the second row and second column of the air pressure monitoring matrix, and the value of the first row and second column of the air pressure monitoring matrix and the value of the second row and first column are both 1. Then, the autoregressive model is combined with the trace prediction of the air pressure monitoring matrix to greatly improve the prediction accuracy.

[0027] Furthermore, in S21, if the number of grid columns of the air pressure analysis network is an odd number, the expression of the matrix set is: ; In the formula, x 1,1 Indicates the pressure value corresponding to the first row and first column of the pressure analysis network, x 1,2 Indicates the pressure value corresponding to the first row and second column of the pressure analysis network, x 1,3 Indicates the pressure value corresponding to the first row and third column of the grid in the pressure analysis network, x 1,4 Indicates the pressure value corresponding to the first row and fourth column of the pressure analysis network, x 1,h Indicates the pressure value corresponding to the grid in the first row and the hth column in the pressure analysis network, x 1,h+1 represents the air pressure value corresponding to the grid in the first row and the h+1th column in the air pressure analysis network, x 1,H-1 Indicates the pressure value corresponding to the grid in the first row and H-1 column in the pressure analysis network, x 1,H Indicates the pressure value corresponding to the grid in the first row and H column of the pressure analysis network, x 2,1 Indicates the air pressure value corresponding to the grid in the second row and first column of the air pressure analysis network, x 2,2 Indicates the air pressure value corresponding to the second row and second column of the air pressure analysis network, x 2,3Indicates the air pressure value corresponding to the second row and third column of the air pressure analysis network, x 2,4 Indicates the air pressure value corresponding to the second row and fourth column of the air pressure analysis network, x 2,h Indicates the air pressure value corresponding to the grid in the second row and the hth column in the air pressure analysis network, x 2,h+1 represents the air pressure value corresponding to the grid in the second row and the h+1th column in the air pressure analysis network, x 2,H-1 Indicates the air pressure value corresponding to the grid in the second row and H-1 column in the air pressure analysis network, x 2,H Indicates the air pressure value corresponding to the grid in the second row and the Hth column in the air pressure analysis network, where H represents the number of columns in the air pressure analysis network;

[0028] In S21, if the number of grid columns of the pressure analysis network is even, the expression of the matrix set is: .

[0029] Furthermore, in S22, the calculation formula of the first air pressure element q1 is: ; In the formula, ε t represents the trace of the t-th unit matrix in the matrix set, x t represents the tth unit matrix in the matrix set, and T represents the number of unit matrices in the matrix set.

[0030] Furthermore, in S22, the calculation formula of the second air pressure element q2 is: ; In the formula, x t represents the tth unit matrix in the matrix set, x t+1 represents the t+1th unit matrix in the matrix set, and T represents the number of unit matrices in the matrix set.

[0031] Furthermore, in S3, the trace of the air pressure monitoring matrix is ​​used as the autoregressive coefficient of the autoregressive model, and the air pressure value in the historical time period is input into the autoregressive model to generate the air pressure value at the current moment.

[0032] An autoregressive model is a statistical model used to analyze and predict time series data.

[0033] The beneficial effects of the present invention are as follows: the present invention discloses a method for monitoring equipment air pressure based on data analysis, which realizes high-precision monitoring and prediction of the air pressure inside the compressor by constructing an air pressure analysis network and an air pressure monitoring matrix, improves the accuracy and real-time performance of monitoring, avoids the potential safety hazards and installation complexity caused by installing sensors inside the compressor, and helps reduce the probability of equipment failure. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 The figure is a flow chart of a method for monitoring equipment air pressure based on data analysis. DETAILED DESCRIPTION

[0035] The embodiments of the present invention will be further described below in conjunction with the accompanying drawings.

[0036] like Figure 1 As shown, the present invention provides a method for monitoring equipment air pressure based on data analysis, comprising the following steps:

[0037] S1. Obtain the air pressure values ​​in the historical time period and build an air pressure analysis network for the air pressure values ​​in the historical time period;

[0038] S2, generating a matrix set based on the air pressure analysis network, and constructing an air pressure monitoring matrix using the matrix set;

[0039] S3. Use the air pressure monitoring matrix to generate the current air pressure value and complete air pressure monitoring.

[0040] In this embodiment of the present invention, S1 includes the following sub-steps:

[0041] S11, obtaining air pressure values ​​in a historical time period, and randomly dividing all air pressure values ​​into a first air pressure pool and a second air pressure pool;

[0042] S12, selecting a maximum air pressure value and a minimum air pressure value from the first air pressure pool, constructing an air pressure loss function for the second air pressure value, and selecting a maximum air pressure value and a minimum air pressure value from the second air pressure pool, constructing an air pressure loss function for the first air pressure value;

[0043] S13, taking the maximum value between the absolute value of the air pressure loss function value of the first air pressure pool and the absolute value of the air pressure loss function of the second air pressure pool as the upper limit of the air pressure analysis range, and taking the minimum value between the absolute value of the air pressure loss function value of the first air pressure pool and the absolute value of the air pressure loss function of the second air pressure pool as the lower limit of the air pressure analysis range;

[0044] S14. Construct a pressure analysis network according to the pressure values ​​within the pressure analysis range in the historical time period.

[0045] In the present invention, the air pressure values ​​in a time series are divided into two data pools, and the characteristic elements of the two data pools are used to construct their respective loss functions. The values ​​of the loss functions are used to determine the endpoints of the air pressure analysis range, and finally an air pressure analysis network is generated. The air pressure values ​​corresponding to the grids in the air pressure analysis network are more representative, avoiding redundant parameters from affecting the prediction results of the air pressure values.

[0046] In the embodiment of the present invention, in S12, the expression of the air pressure loss function Loss1 of the first air pressure pool is: Where A 1_irepresents the i-th air pressure value of the first air pressure pool, I represents the number of air pressure values ​​of the first air pressure pool, and A 2_max Indicates the maximum pressure value of the second pressure pool, A 2_min represents the minimum air pressure value of the second air pressure pool, I represents the number of air pressure values ​​of the first air pressure pool, and ln(·) represents a logarithmic function;

[0047] The expression of the pressure loss function Loss2 of the second pressure pool is: Where A 2_j represents the jth air pressure value of the second air pressure pool, J represents the number of air pressure values ​​in the second air pressure pool, A 1_max Indicates the maximum pressure value of the first pressure pool, A 1_min Indicates the minimum air pressure value of the first air pressure pool.

[0048] In this embodiment of the present invention, S14 includes the following sub-steps:

[0049] S141, setting a blank grid for air pressure analysis, and filling the first row of the blank grid for air pressure analysis with air pressure values ​​that fall within the air pressure analysis range within the historical time period in descending order;

[0050] S142, calculating the air pressure category ratio between each remaining air pressure value and each grid in the first row of the air pressure analysis blank grid;

[0051] S143. Fill the air pressure value corresponding to the highest air pressure category rate between each grid into the bottom of the grid to obtain an air pressure analysis network.

[0052] The number of pressure values ​​that fall within the pressure analysis range during the historical time period is the same as the number of grid columns of the pressure analysis network. The number of rows of the pressure analysis network is 2.

[0053] In the embodiment of the present invention, in S142, the pressure category rate p between the remaining k-th pressure value and the h-th column grid in the first row of the pressure analysis blank grid is k_h The calculation formula is: Where A k represents the remaining k-th air pressure value, A h It represents the air pressure value corresponding to the hth column grid in the first row of the blank grid of the air pressure analysis, α represents the upper limit of the air pressure analysis range, and β represents the lower limit of the air pressure analysis range.

[0054] In this embodiment of the present invention, S2 includes the following sub-steps:

[0055] S21, extracting a number of unit matrices from the air pressure analysis network to form a matrix set;

[0056] S22, generating a first air pressure element and a second air pressure element of an air pressure monitoring matrix according to the matrix set;

[0057] S23. Generate an air pressure monitoring matrix according to the first air pressure element and the second air pressure element.

[0058] In the present invention, the air pressure values ​​of each grid in the air pressure analysis network and the number of grid columns of the air pressure analysis network are used to determine the matrix set, and the parameters of the unit matrix in the matrix set are used to generate two air pressure elements, the first air pressure element is placed in the first row and first column of the air pressure monitoring matrix, and the second air pressure element is placed in the second row and second column of the air pressure monitoring matrix. The value of the first row and second column of the air pressure monitoring matrix and the value of the second row and first column are both 1. Then, the autoregressive model is combined with the trace prediction of the air pressure monitoring matrix to greatly improve the prediction accuracy.

[0059] In the embodiment of the present invention, in S21, if the number of grid columns of the air pressure analysis network is an odd number, the expression of the matrix set is: ; In the formula, x 1,1 Indicates the pressure value corresponding to the first row and first column of the pressure analysis network, x 1,2 Indicates the pressure value corresponding to the first row and second column of the pressure analysis network, x 1,3 Indicates the pressure value corresponding to the first row and third column of the grid in the pressure analysis network, x 1,4 Indicates the pressure value corresponding to the first row and fourth column of the pressure analysis network, x 1,h Indicates the pressure value corresponding to the grid in the first row and the hth column in the pressure analysis network, x 1,h+1 represents the air pressure value corresponding to the grid in the first row and the h+1th column in the air pressure analysis network, x 1,H-1 Indicates the pressure value corresponding to the grid in the first row and H-1 column in the pressure analysis network, x 1,H Indicates the pressure value corresponding to the grid in the first row and H column of the pressure analysis network, x 2,1 Indicates the air pressure value corresponding to the grid in the second row and first column of the air pressure analysis network, x 2,2 Indicates the air pressure value corresponding to the second row and second column of the air pressure analysis network, x 2,3 Indicates the air pressure value corresponding to the second row and third column of the air pressure analysis network, x 2,4 Indicates the air pressure value corresponding to the second row and fourth column of the air pressure analysis network, x 2,h Indicates the air pressure value corresponding to the grid in the second row and the hth column in the air pressure analysis network, x 2,h+1 represents the air pressure value corresponding to the grid in the second row and the h+1th column in the air pressure analysis network, x 2,H-1 Indicates the air pressure value corresponding to the grid in the second row and H-1 column in the air pressure analysis network, x 2,HIndicates the air pressure value corresponding to the grid in the second row and the Hth column in the air pressure analysis network, where H represents the number of columns in the air pressure analysis network;

[0060] In S21, if the number of grid columns of the pressure analysis network is even, the expression of the matrix set is: .

[0061] In the embodiment of the present invention, in S22, the calculation formula of the first air pressure element q1 is: ; In the formula, ε t represents the trace of the t-th unit matrix in the matrix set, x t represents the tth unit matrix in the matrix set, and T represents the number of unit matrices in the matrix set.

[0062] In the embodiment of the present invention, in S22, the calculation formula of the second air pressure element q2 is: ; In the formula, x t represents the tth unit matrix in the matrix set, x t+1 represents the t+1th unit matrix in the matrix set, and T represents the number of unit matrices in the matrix set.

[0063] In the embodiment of the present invention, in S3, the trace of the air pressure monitoring matrix is ​​used as the autoregressive coefficient of the autoregressive model, and the air pressure value in the historical time period is input into the autoregressive model to generate the air pressure value at the current moment.

[0064] An autoregressive model is a statistical model used to analyze and predict time series data.

[0065] Those skilled in the art will appreciate that the embodiments described herein are intended to help readers understand the principles of the present invention, and should be understood that the protection scope of the present invention is not limited to such specific statements and embodiments. Those skilled in the art can make various other specific variations and combinations that do not deviate from the essence of the present invention based on the technical revelations disclosed by the present invention, and these variations and combinations are still within the protection scope of the present invention.

Claims

1. A method for monitoring equipment air pressure based on data analysis, characterized in that: The following steps are involved: S1. Obtain the air pressure values ​​in the historical time period and build an air pressure analysis network for the air pressure values ​​in the historical time period; S2, generating a matrix set based on the air pressure analysis network, and constructing an air pressure monitoring matrix using the matrix set; S3. Use the air pressure monitoring matrix to generate the current air pressure value and complete air pressure monitoring.

2. The equipment air pressure monitoring method based on data analysis according to claim 1 is characterized in that: The S1 comprises the following sub-steps: S11, obtaining air pressure values ​​in a historical time period, and randomly dividing all air pressure values ​​into a first air pressure pool and a second air pressure pool; S12, selecting a maximum air pressure value and a minimum air pressure value from the first air pressure pool, constructing an air pressure loss function for the second air pressure value, and selecting a maximum air pressure value and a minimum air pressure value from the second air pressure pool, constructing an air pressure loss function for the first air pressure value; S13, taking the maximum value between the absolute value of the air pressure loss function value of the first air pressure pool and the absolute value of the air pressure loss function of the second air pressure pool as the upper limit of the air pressure analysis range, and taking the minimum value between the absolute value of the air pressure loss function value of the first air pressure pool and the absolute value of the air pressure loss function of the second air pressure pool as the lower limit of the air pressure analysis range; S14. Construct a pressure analysis network according to the pressure values ​​within the pressure analysis range in the historical time period.

3. The equipment air pressure monitoring method based on data analysis according to claim 2 is characterized in that: In S12, the expression of the air pressure loss function Loss1 of the first air pressure pool is: Where A 1_i represents the i-th air pressure value of the first air pressure pool, I represents the number of air pressure values ​​of the first air pressure pool, and A 2_max Indicates the maximum pressure value of the second pressure pool, A 2_min represents the minimum air pressure value of the second air pressure pool, I represents the number of air pressure values ​​of the first air pressure pool, and ln(·) represents a logarithmic function; The expression of the pressure loss function Loss2 of the second pressure pool is: Where A 2_j represents the jth air pressure value of the second air pressure pool, J represents the number of air pressure values ​​in the second air pressure pool, A 1_max Indicates the maximum pressure value of the first pressure pool, A 1_min Indicates the minimum air pressure value of the first air pressure pool.

4. The equipment air pressure monitoring method based on data analysis according to claim 2 is characterized in that: The S14 comprises the following sub-steps: S141, setting a blank grid for air pressure analysis, and filling the first row of the blank grid for air pressure analysis with air pressure values ​​that fall within the air pressure analysis range within the historical time period in descending order; S142, calculating the air pressure category ratio between each remaining air pressure value and each grid in the first row of the air pressure analysis blank grid; S143. Fill the air pressure value corresponding to the highest air pressure category rate between each grid into the bottom of the grid to obtain an air pressure analysis network.

5. The equipment air pressure monitoring method based on data analysis according to claim 4 is characterized in that: In S142, the pressure category rate p between the remaining k-th pressure value and the h-th column grid in the first row of the pressure analysis blank grid k_h The calculation formula is: Where A k represents the remaining k-th air pressure value, A h It represents the air pressure value corresponding to the hth column grid in the first row of the blank grid of the air pressure analysis, α represents the upper limit of the air pressure analysis range, and β represents the lower limit of the air pressure analysis range.

6. The equipment air pressure monitoring method based on data analysis according to claim 1 is characterized in that: The S2 comprises the following sub-steps: S21, extracting a number of unit matrices from the air pressure analysis network to form a matrix set; S22, generating a first air pressure element and a second air pressure element of an air pressure monitoring matrix according to the matrix set; S23. Generate an air pressure monitoring matrix according to the first air pressure element and the second air pressure element.

7. The equipment air pressure monitoring method based on data analysis according to claim 6 is characterized in that: In S21, if the number of grid columns of the air pressure analysis network is an odd number, the expression of the matrix set is: ; In the formula, x 1,1 Indicates the pressure value corresponding to the first row and first column of the pressure analysis network, x 1,2 Indicates the pressure value corresponding to the first row and second column of the pressure analysis network, x 1,3 Indicates the pressure value corresponding to the first row and third column of the grid in the pressure analysis network, x 1,4 Indicates the pressure value corresponding to the first row and fourth column of the pressure analysis network, x 1,h Indicates the pressure value corresponding to the grid in the first row and the hth column in the pressure analysis network, x 1,h+1 represents the air pressure value corresponding to the grid in the first row and the h+1th column in the air pressure analysis network, x 1,H-1 Indicates the pressure value corresponding to the grid in the first row and H-1 column in the pressure analysis network, x 1,H Indicates the pressure value corresponding to the grid in the first row and H column of the pressure analysis network, x 2,1 Indicates the air pressure value corresponding to the grid in the second row and first column of the air pressure analysis network, x 2,2 Indicates the air pressure value corresponding to the second row and second column of the air pressure analysis network, x 2,3 Indicates the air pressure value corresponding to the second row and third column of the air pressure analysis network, x 2,4 Indicates the air pressure value corresponding to the second row and fourth column of the air pressure analysis network, x 2,h Indicates the air pressure value corresponding to the grid in the second row and the hth column in the air pressure analysis network, x 2,h+1 represents the air pressure value corresponding to the grid in the second row and the h+1th column in the air pressure analysis network, x 2,H-1 Indicates the air pressure value corresponding to the grid in the second row and H-1 column in the air pressure analysis network, x 2,H Indicates the air pressure value corresponding to the grid in the second row and the Hth column in the air pressure analysis network, where H represents the number of columns in the air pressure analysis network; In S21, if the number of grid columns of the air pressure analysis network is an even number, the expression of the matrix set is: 。 8. The equipment air pressure monitoring method based on data analysis according to claim 6, characterized in that: In S22, the calculation formula of the first air pressure element q1 is: ; In the formula, ε t represents the trace of the t-th unit matrix in the matrix set, x t represents the tth unit matrix in the matrix set, and T represents the number of unit matrices in the matrix set.

9. The equipment air pressure monitoring method based on data analysis according to claim 6, characterized in that: In S22, the calculation formula of the second air pressure element q2 is: ; In the formula, x t represents the tth unit matrix in the matrix set, x t+1 represents the t+1th unit matrix in the matrix set, and T represents the number of unit matrices in the matrix set.

10. The equipment air pressure monitoring method based on data analysis according to claim 1, characterized in that: In S3, the trace of the air pressure monitoring matrix is ​​used as the autoregressive coefficient of the autoregressive model, and the air pressure value in the historical time period is input into the autoregressive model to generate the air pressure value at the current moment.

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