Method for directly evaluating residual life of filter based on data modeling

Abstract

The invention relates to a method for directly evaluating the residual life of a filter based on data modeling, which is characterized in that on the basis of a function relationship between blockage time and blockage pressure difference, a mathematical model is established by utilizing a mathematical method to directly evaluate the residual service life or residual test life under subsequent rising pressure difference. And directly evaluating the residual test life or residual service life of the filter under the follow-up pressure rising difference and the limit pressure difference by adopting a mathematical method according to the established function relationship between the filter test time and the blocking pressure difference as well as between the service time and the working pressure difference and limited test data or use data. The method has practical guiding significance for researching the service life and reliability technology of the filter and developing timing, active and accurate maintenance of a hydraulic system.

Description

Technical Field

[0001] The invention relates to the technical field of hydraulic system pollution control filters, and in particular to a method for directly evaluating the remaining life of a filter based on data modeling. Background Art

[0002] The life of the filter is the core indicator of the product. The life indicator not only directly affects the pollution control level of the hydraulic system, but also serves as the basis for correct maintenance during use. At present, the "pollution capacity" is often used to indirectly represent the life of the filter at the "manufacturing end" of the filter. Strictly speaking, this is unscientific. Life is a concept of time, while "pollution capacity" is weight. Although both have a functional relationship with the blocking pressure difference, their units of measurement are not unified, which can easily give people a confused understanding and does not help the guiding role of the filter at the "use end".

[0003] Under relatively stable conditions, the filter's working flow, pressure, oil contamination, temperature, and mechanical environment will determine how fast the filter element's pressure difference increases when it is blocked. The longer the pressure difference increases to the limit, the longer the life span. Conversely, the shorter the life span. In actual use, the filter will filter, intercept, and purify pollutants in the hydraulic system, resulting in the filter element being blocked. Of course, the filter element blockage can also be achieved in the laboratory by adding dust. That is to say, there must be a mathematical functional relationship between the filter's life and the pressure difference when the filter element is blocked.

[0004] Therefore, a method based on data modeling to directly evaluate the remaining life of the filter with a wide range of applications, easy operation, and convenient comparison is needed to solve the above problems. Summary of the invention

[0005] The purpose of the present invention is to provide a method for directly evaluating the remaining life of a filter based on data modeling. It is based on the functional relationship between the clogging time and the clogging pressure difference, and uses mathematical methods to establish a mathematical model to directly evaluate the remaining service life or remaining test life under subsequent elevated pressure differences.

[0006] In order to achieve the above object, the present invention adopts such a technical solution: a method for directly evaluating the remaining life of a filter based on data modeling, wherein the specific steps of the method for directly evaluating the remaining life of a filter based on data modeling include:

[0007] Step 1: Select a brand new, unused filter, refer to the relevant test method, add test dust to the test system, and measure the test time ti (i = 1, 2, 3 ... n) when the blocking pressure difference is △Pi (i = 1, 2, 3 ... n) under normal temperature and set flow conditions, as shown in the following table:

[0008] <![CDATA[△P i ]]> <![CDATA[△P1]]> <![CDATA[△P2]]> <![CDATA[△P3]]> … <![CDATA[△P n ]]> <![CDATA[t i ]]> <![CDATA[t1]]> <![CDATA[t2]]> <![CDATA[t3]]> … <![CDATA[t n ]]>

[0009] Step 2: Use mathematical methods to fit the curve based on the data measured in step 1, such as Figure 1 As shown:

[0010] Step 3: Use mathematical curve regression method to establish a mathematical model of test time t and filter element blockage pressure difference ΔP;

[0011] Step 4: For the filters actually in use, the pressure difference increase and the corresponding use time T during use can be collected and recorded as needed, and a fitting curve of the blockage pressure difference and the use time during the working process can be drawn according to step 2 of the technical solution. Then, a mathematical model of the blockage time T and the filter element working pressure difference ΔP can be established according to step 3 of the technical solution.

[0012] Compared with the prior art, the present invention has the following beneficial effects:

[0013] Utilizing the established functional relationships between filter test time and plugging pressure differential, and between usage time and working pressure differential, and limited test data or usage data, a mathematical method is used to directly evaluate the remaining test life or remaining service life of the filter under subsequent elevated pressure differential and ultimate pressure differential under the same test or usage conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 This is the fitting curve of the plugging pressure difference and the test time DETAILED DESCRIPTION

[0015] In order to further explain the technical solution of the present invention, a method for directly evaluating the remaining life of a filter based on data modeling is described in detail below through a specific embodiment. The specific implementation steps are as follows:

[0016] Step 1: Select a brand new filter with an unused filtration ratio (filtration ratio β5 ≥ 100 for 5μm (c)). Refer to the multiple-pass test method of international standards, national standards or industry standards, add ISO-FTD fine test dust or ISO-MTD medium fine test dust to the test system, with a dust concentration of 3mg / L to 30mg / L, and measure the blockage pressure difference of △P under normal temperature and set flow rate (40L / min to 120L / min) respectively. i (i=1, 2, 3…n, n≥6) The test time is t i (i=1, 2, 3…n, n≥6), as shown in the following table:

[0017] <![CDATA[△P i (kP)]]> <![CDATA[△P1]]> <![CDATA[△P2]]> <![CDATA[△P3]]> … <![CDATA[△P n ]]> <![CDATA[t i (min)]]> <![CDATA[t1]]> <![CDATA[t2]]> <![CDATA[t3]]> … <![CDATA[t n ]]>

[0018] The termination pressure difference of the test is generally 200kP~400kP, and at least 3-N pressure difference points can be selected in equal parts to test the corresponding test time.

[0019] Step 2: Use mathematical methods to fit the curve based on the data measured in step 1, such as Figure 1 As shown:

[0020] Step 3: Use the mathematical curve regression method to establish a mathematical model of the test time t and the filter element plugging pressure difference ΔP. The closer the regression correlation coefficient R is to 1, the better the curve regression effect is, and the more realistic the mathematical model is. The established model of the test time t and the plugging pressure difference ΔP is shown in formula (1):

[0021] t=a ln m (ΔP)+b (1)

[0022] In the formula: t: test time (min);

[0023] ΔP: test blockage pressure difference (kP);

[0024] a, b: fitting constants (constants depending on the correlation coefficient R);

[0025] m: fitting index, when m = 0, it is a linear function, as shown in formula (1.1); when m = 1, it is a logarithmic function, as shown in formula (1.2); when m = 2, it is a double logarithmic function, as shown in formula (1.3);

[0026] t=a(ΔP)+b··················(1.1)

[0027] t=a ln(ΔP)+b··················(1.2)

[0028] t=a ln(ln(ΔP))+b······(1.3)

[0029] Step 4: For the filters actually in use, a differential pressure meter and a timer are installed in the system to collect and record a limited number of sets of differential pressure increases and corresponding usage time T during use. Generally, at least 3 sets of T-ΔP data are collected, namely, N sets. According to step 2 of the implementation method, a fitting curve of the working differential pressure and the usage time is drawn. Then, according to step 3 of the implementation method, a mathematical model of the usage time T and the working differential pressure ΔP is established, as shown in formula (2):

[0030] T=Aln m (ΔP)+B (2)

[0031] In the formula: T: service life (min), or converted to hours (h);

[0032] ΔP: Use blocking pressure difference (kP);

[0033] A, B: fitting constants (constants depending on the correlation coefficient R);

[0034] m: fitting index, when m = 0, it is a linear function, as shown in formula (2.1); when m = 1, it is a logarithmic function, as shown in formula (2.2); when m = 2, it is a double logarithmic function, as shown in formula (2.3);

[0035] T=A(ΔP)+B····················(2.1)

[0036] T=Aln(ΔP)+B······················(2.2)

[0037] T=Aln(ln(ΔP))+B·············(2.3)

[0038] Step 5: Substituting the subsequent elevated pressure difference or limit pressure difference into formula (1.1), formula (1.2), or formula (1.3), the corresponding remaining test life or limit test life under the same test conditions can be directly evaluated and calculated.

[0039] Step 6: Substituting the remaining working pressure difference or the limiting working pressure difference into formula (2.1), formula (2.2), or formula (2.3), the corresponding remaining service life or limiting service life under the same use conditions can be directly evaluated and calculated.

[0040] The implementation steps of the present invention are not limited to the embodiments of this case. Any appropriate changes or modifications made by anyone with similar ideas should be deemed to be within the scope of protection of the present invention.

Claims

1. A method for directly estimating the remaining life of a filter based on data modeling, comprising: Set the contamination level of the oil passing through the filter under test conditions; Under the test conditions, the experimental temperature was set to normal temperature; Set the experimental flow rate under the test conditions; Obtain the plugging pressure difference across the filter and the test time under test conditions; The model formula (1) is created based on the fitting curve of the plugging pressure difference and the test time: t=a ln m (ΔP)+b (1) Where: t: is the test time; ΔP: test blockage pressure difference; a, b: fitting constants; m: fitting index; Install a differential pressure gauge and timer or other method to record the pressure difference and the corresponding time in the system under actual working conditions; Under actual working conditions, the test temperature is set to normal temperature; The pressure difference increase and the corresponding usage time during use were measured under actual working conditions; The model formula (2) is created based on the fitting curve of the plugging pressure difference and the test time: T=A ln m (ΔP)+B (2) Where: T: service life; ΔP: Use blocking pressure difference; A, B: fitting constants; m: fitting index; The above-mentioned model formulas (1) and (2) for directly evaluating the remaining life of the filter are used, and the contamination level of the oil passing through the filter is set under the test conditions, the test temperature is set to normal temperature under the test conditions, the test flow rate is set under the test conditions, and the plugging pressure difference and test time through the filter are obtained under the test conditions; under the actual working conditions, a differential pressure gauge and a timer or other method for recording the pressure difference and the corresponding time is installed in the system, the test temperature is set to normal temperature under the actual working conditions, and the pressure difference increase during use and the corresponding use time are measured under the actual working conditions, and the above-mentioned model formula is used to directly calculate the corresponding remaining test life and limit test life under the same test conditions or the remaining service life and limit service life under the same use conditions.

2. According to the method for directly evaluating the remaining life of the filter based on data modeling according to claim 1, the contamination level of the oil passing through the filter under the test conditions is set to fine test dust or medium fine test dust, the dust concentration is 3mg / L to 30mg / L, and the set flow rate is 40L / min to 120L / min.

3. The method for directly evaluating the remaining life of a filter based on data modeling according to claim 1, wherein when the fitting index m=0 obtained under the test condition, it is substituted into formula (1) as follows: t=a(ΔP)+b.

4. The method for directly evaluating the remaining life of a filter based on data modeling according to claim 1, wherein when the fitting index m=1 obtained under the test condition, it is substituted into formula (1) as follows: t=a ln(ΔP)+b.

5. The method for directly evaluating the remaining life of a filter based on data modeling according to claim 1, wherein when the fitting index m=2 obtained under the test condition, it is substituted into formula (1) as follows: t=a ln(ln(ΔP))+b.

6. The method for directly evaluating the remaining life of a filter based on data modeling according to claim 1, wherein when m=0, the fitting index obtained from the actual filter test is substituted into formula (2) as: T=A(ΔP)+B.

7. The method for directly evaluating the remaining life of a filter based on data modeling according to claim 1, wherein when m=1, the fitting index obtained from the actual filter test is substituted into formula (2): T=A ln(ΔP)+B.

8. The method for directly estimating the remaining life of a filter based on data modeling according to claim 1, wherein the fitting index obtained from the actual filter test is m=2, and is substituted into formula (2) as follows: T=A ln(ln(ΔP))+B.

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