Unstable filtering efficiency prediction method for dry type filtering dust removal system

Abstract

A method for predicting the unsteady filtering efficiency of a dry-type filtering dust removal system comprises the following steps: calculating the filtering efficiency of single particles according to the particle capturing efficiency caused by the free diffusion effect, the direct interception effect and the inertial collision effect of dust; constructing a relation model between the dust layer filtering efficiency and the unit layer filtering efficiency; constructing a relation model among the unsteady filtering efficiency, the fiber layer filtering efficiency and the dust layer filtering efficiency of the dry type filtering dust removal system; according to the law of conservation of materials, constructing a relation model between the unsteady filtering efficiency and the filtering time when the dust layer thickness is specific; according to the particle size distribution percentage, constructing a relation model between the unsteady-state filtering efficiency of the single-particle-size dust particles and the unsteady-state filtering efficiency of the multi-dispersed-phase dust; and based on the obtained relation model, obtaining an unsteady-state filtering efficiency prediction formula of the dry-type filtering dust removal system. According to the method, the universality and accuracy of the method for predicting the unsteady filtering efficiency of the dry-type filtering dust removal system can be improved.

Description

Technical Field

[0001] The invention relates to a method for predicting the filtration efficiency of a dust removal system, in particular to a method for predicting the non-steady-state filtration efficiency of a dry filtration dust removal system, and belongs to the technical field of coal mine dust particle filtration efficiency prediction. Background Art

[0002] Particulate pollution occurs in the process of human production and life, which has a serious impact on human life and health and industrial production safety. Dry filtration dust removal technology has been increasingly widely used in the field of industrial dust prevention and control due to its advantages such as high filtration efficiency, zero water consumption, and no secondary pollution. Filtration efficiency is one of the key indicators to measure the quality of dust removal technology, which directly affects the performance and effect of the dust removal system. However, in conventional industrial applications, dry filtration dust removal systems are usually in a non-steady-state stage, and complex particle capture phenomena will occur in both the fiber layer and the dust layer. Dust-laden airflow loading conditions (such as filtration wind speed, dust concentration, etc.) will also affect the operation of the dry filtration dust removal system, greatly increasing the difficulty of predicting filtration efficiency.

[0003] At present, traditional non-steady-state filtration efficiency prediction methods are mostly based on predecessors' semi-empirical formulas and make extremely harsh assumptions about gas flow. They have high accuracy in predicting the filtration efficiency of small fiber filter materials, but are difficult to apply to the prediction of filtration efficiency of dry filtration and dust removal systems in large-scale industrial production. On the other hand, traditional non-steady-state filtration efficiency prediction methods also use simplified empirical models fitted from data under certain specific experimental conditions. They have good prediction effects when they are close to the preset experimental conditions, but cannot predict the filtration efficiency when they deviate greatly from the preset experimental conditions. The universality of the prediction methods is greatly restricted. In addition, some prediction methods only consider a single particle capture mechanism, such as only considering one of the inertial collision mechanism, direct interception mechanism or free diffusion mechanism. It is difficult to fully reflect the non-steady-state filtration characteristics of dry filtration and dust removal systems, and thus it is difficult to achieve accurate prediction of filtration efficiency. Summary of the invention

[0004] The purpose of the present invention is to provide a method for predicting the non-steady-state filtration efficiency of a dry filtration dust removal system. The method is based on the single particle filtration theory and can improve the universality and accuracy of the filtration efficiency prediction method by constructing a new filtration efficiency prediction model that takes into account the filtration wind speed, loaded dust concentration, dust layer thickness, filtration time, and particle size distribution.

[0005] In order to achieve the above object, the present invention provides a method for predicting the non-steady-state filtration efficiency of a dry filtration dust removal system, comprising the following steps:

[0006] S1: Select a single particle that makes up the dust layer as the research object, and calculate the single particle filtration efficiency based on the particle capture efficiency caused by the free diffusion of dust, direct interception, and inertial collision.

[0007] S2: The dust layer is equivalent to several unit layers stacked in series, and according to the isolated sphere theory, a relationship model between the dust layer filtration efficiency and the unit layer filtration efficiency is constructed;

[0008] S3: Considering the dust layer filtration and fiber layer filtration as relatively independent individuals, a relationship model between the non-steady-state filtration efficiency of the dry filtration dust removal system and the fiber layer filtration efficiency and dust layer filtration efficiency is constructed;

[0009] S4: According to the law of conservation of matter, the relationship between the volume of the deposited dust layer and the volume of dust captured by the filter material is used to construct a relationship model between the non-steady-state filtration efficiency and the filtration time at a specific dust layer thickness;

[0010] S5: Based on the particle size distribution percentage, a relationship model between the non-steady-state filtration efficiency of single-size dust particles and the non-steady-state filtration efficiency of multi-dispersed phase dust is constructed;

[0011] S6: Based on the relationship model obtained from steps S2 to S5, the dust-laden airflow filtration is solved by integration, high-order infinitesimal terms, and power series expansion to obtain a non-steady-state filtration efficiency prediction formula for the dry filtration dust removal system, and the non-steady-state filtration efficiency of the dry filtration dust removal system is obtained according to the non-steady-state filtration efficiency prediction formula for the dry filtration dust removal system.

[0012] Furthermore, in step S1, the calculation formula for calculating the single particle filtration efficiency is as shown in formula (1):

[0013] η s =1-(1-η It )(1-η Ip )(1-η D )(1);

[0014] In formula (1): s is the single particle filtration efficiency, %;

[0015] η It is the particle capture efficiency caused by direct interception, and its calculation formula is shown in formula (2):

[0016] η It =1.5A s R 2 (2);

[0017] η Ip is the particle capture efficiency caused by inertial collision, and its calculation formula is shown in formula (3):

[0018]

[0019] η D is the particle capture efficiency caused by free diffusion, and its calculation formula is shown in formula (4):

[0020]

[0021] In formulas (2)-(4): Pe is the Peclet number, dimensionless;

[0022] Re is the Reynolds number, dimensionless;

[0023] A s is an implicit function of porosity, dimensionless;

[0024] R is the intercept parameter, dimensionless;

[0025] Stk is the Stokes number, dimensionless.

[0026] Furthermore, step S2 specifically includes:

[0027] S2.1: Consider a dust layer with a thickness of h and a porosity of ε as N unit layers stacked in series. Assuming that the particles that make up the dust layer are uniformly and randomly distributed, the cubic volume calculation formula can be obtained:

[0028]

[0029] In formula (5): l is the thickness of the unit layer, m;

[0030] d g is the average particle diameter of the dust layer, m;

[0031] ε is the porosity of the dust layer;

[0032] By transforming formula (5), we can get the expression of unit layer thickness l as formula (6):

[0033]

[0034] S2.2: The dust particle is regarded as a sphere, and the dust layer is regarded as a collection of dust particles. Each dust particle in the dust layer is completely independent of each other. According to the isolated sphere model, the unit layer filtration efficiency η is constructed according to formula (5) and formula (6): l The difference between the single particle filtration efficiency and s The relationship model is as described in formula (7):

[0035]

[0036] In formula (7):l is the unit layer filtration efficiency of the dust layer, %;

[0037] S2.3: Consider the dust layer as a series of evenly distributed unit layers, and construct the dust layer filtration efficiency η c and unit layer filtration efficiency η l The relationship model between is shown in formula (8):

[0038]

[0039] In formula (8): c is the dust layer filtration efficiency, %;

[0040] h is the dust layer thickness, m.

[0041] Furthermore, step S3 specifically includes:

[0042] The dust layer filtration and fiber layer filtration are considered as relatively independent individuals. The fiber layer filtration efficiency η0 and the dust layer filtration efficiency η c A relationship model of the non-steady-state filtration efficiency of the dry filtration dust removal system is constructed, and the fiber layer filtration efficiency η0 is obtained through experimental testing; the relationship model is shown in formula (9):

[0043] η i =1-(1-η0)(1-η c ) (9);

[0044] In formula (9): i It is the non-steady-state filtration efficiency of the dry filtration dust removal system when loaded with dust particles of a certain particle size;

[0045] η0 is the filtration efficiency of the fiber layer;

[0046] The formula (8) and (9) are used to construct the fiber layer filtration efficiency η0 and the unit layer filtration efficiency η l The relationship model of the non-steady-state filtration efficiency of dry dust removal when a certain dust particle size is loaded is shown in formula (10):

[0047]

[0048] Furthermore, step S4 specifically includes:

[0049] By constructing an equivalent relationship between the volume of the dust layer deposited per unit time and the volume of dust captured by the filter material per unit time, a relationship model between the non-steady-state filtration efficiency and filtration time of the dry filtration dust removal system when dust particles of a certain particle size are loaded is obtained. The relationship model is shown in formula (11):

[0050] A(1-ε)ρp dh=AU0n0η i dt (11);

[0051] In formula (11): A is the projected area of ​​the fiber filter material along the filtering airflow direction;

[0052] ρ p The particle size of the loaded dust particles;

[0053] dh is the microelement along the dust thickness direction;

[0054] U0 is the filtering wind speed;

[0055] n0 is the mass concentration of particles in the dust-laden airflow;

[0056] η i It is the non-steady-state filtration efficiency of the dry filtration dust removal system when loaded with dust particles of a certain particle size;

[0057] dt is the unit filtering time.

[0058] Furthermore, step S5 specifically includes:

[0059] Considering the case where the loaded dust is multi-dispersed phase particles, based on the loaded dust particle size distribution, the non-steady-state filtration efficiency of the dry filtration dust removal system when loading multi-dispersed phase dust particles is obtained by accumulating the product of the non-steady-state filtration efficiency of single-size dust particles and the particle size distribution percentage, which is expressed as:

[0060] η=∑η i ·x i (12);

[0061] In formula (12): η is the non-steady-state filtration efficiency of the dry filtration dust removal system when loaded with multi-dispersed phase dust particles;

[0062] x i is a specific particle size d in the multi-dispersed phase particles pi The corresponding particle size distribution percentage.

[0063] Further, step S6 specifically includes: taking the relationship model obtained in steps S2 to S5 as the basic condition, and solving it by means of integration, power series expansion, and high-order infinitesimal terms. The specific process is:

[0064] The initial conditions of dh and dt in formula (11) are both 0. By integrating dh and dt in formula (11) in the dust layer thickness range of 0 to h and the time range of 0 to t, we can obtain the relationship between the filtration efficiency and the filtration time t when the dust layer thickness is h (13),

[0065]

[0066] By performing power series expansion on formula (10), we can obtain formula (14);

[0067]

[0068] Since the unit layer filtration efficiency η l <<1, then η l The infinitesimal terms of higher order terms are approximately equal to zero, and formula (10) is simplified to:

[0069]

[0070] Combining the above formulas (12)-(15), integrating and solving formula (13) in the dust layer thickness range of 0~h and the time range of 0~t, the prediction formula for the non-steady-state filtration efficiency of the dry filtration dust removal system when loaded with multi-dispersed phase dust particles can be obtained:

[0071]

[0072] In formula (16): k1 and k2 are intermediate variables;

[0073] The calculation method of the intermediate variables k1 and k2 is:

[0074]

[0075] Compared with the prior art, the prediction method of the present invention comprehensively considers various particle capture mechanisms such as inertial collision mechanism, direct interception mechanism and free diffusion mechanism, relaxes the assumption of dust-laden gas flow, and improves the universality and accuracy of filtration efficiency prediction. The prediction method of the present invention can be used to quickly and conveniently determine the theoretical dust removal efficiency of the dry dust removal system in the non-steady-state filtration stage, thereby guiding the operation of the dry filtration dust removal system, determining the influence of factors such as filtration wind speed, dust concentration, and particle size on the filtration efficiency, and then determining a reasonable and efficient operation plan for the dry filtration dust removal system. BRIEF DESCRIPTION OF THE DRAWINGS

[0076] Figure 1 is a prediction flow chart of the present invention;

[0077] Figure 2 A schematic diagram of the relationship model between the non-steady-state filtration efficiency and the filtration time established by the present invention;

[0078] Figure 3 This is a comparison chart of the predicted results and the measured results in the embodiment of the present invention. DETAILED DESCRIPTION

[0079] The present invention will be further described below in conjunction with the accompanying drawings.

[0080] like Figure 1As shown, a method for predicting the non-steady-state filtration efficiency of a dry filtration dust removal system comprises the following steps:

[0081] S1: Select a single dust particle that makes up the dust layer as the research object, and calculate the single particle filtration efficiency based on the particle capture efficiency caused by the free diffusion of dust, direct interception, and inertial collision. Among them, the particle capture efficiency caused by direct interception is η It , particle capture efficiency η caused by inertial collision Ip and the particle capture efficiency η caused by free diffusion D Respectively expressed as:

[0082] η It =1.5A s R 2 (2);

[0083]

[0084] Where: Pe is the Peclet number, dimensionless;

[0085] Re is the Reynolds number, dimensionless;

[0086] A s is an implicit function of porosity, dimensionless;

[0087] R is the intercept parameter, dimensionless;

[0088] Stk is the Stokes number, dimensionless;

[0089] In the non-steady-state filtration process of dry dust removal, since the filtration airflow and the dust layer are perpendicular to each other in most cases and the particle size range of the loaded particles is relatively large, the gravity sedimentation and electrostatic attraction of the particles can usually be ignored. The single particle filtration efficiency expression using the product of different particle capture efficiencies is:

[0090] η s =1-(1-η It )(1-η Ip )(1-η D )(1);

[0091] Where: η s is the single particle filtration efficiency, %;

[0092] S2: The dust layer is equivalent to several unit layers stacked in series, and according to the isolated ball theory, a relationship model between the dust layer filtration efficiency and the single particle filtration efficiency is constructed;

[0093] Specifically, a dust layer with a thickness of h and a porosity of ε is considered to be composed of N unit layers with a thickness of l connected in series. Assuming that the particles constituting the dust layer are uniformly and randomly distributed, the cubic volume calculation formula can be obtained:

[0094]

[0095] Where: l is the thickness of the unit layer, m;

[0096] d g is the average particle diameter of the dust layer, m;

[0097] ε is the porosity of the dust layer;

[0098] The expression of unit layer thickness l can be solved by transforming the cube volume calculation formula:

[0099]

[0100] According to the isolated ball model, the dust particle is approximated as a sphere, and the dust layer is regarded as a collection of spherical collection groups. It is believed that each spherical collection group in the dust layer is completely independent of each other. With the approximate relationship between the flow field on the surface of the isolated ball model and the flow field of the isolated ball model in the unbounded fluid, the relationship between the unit layer filtration efficiency and the single particle filtration efficiency can be obtained:

[0101]

[0102] Where: η l is the unit layer filtration efficiency of the dust layer, %;

[0103] The dust layer is regarded as a series of evenly distributed unit layers, and the filtration efficiency of the dust layer is described in the form of the product of the filtration efficiencies of the unit layers:

[0104]

[0105] Where: η c is the dust layer filtration efficiency, %;

[0106] h is the dust layer thickness, m.

[0107] S3: Based on the relationship model between the dust layer filtration efficiency and the single particle filtration efficiency constructed in step S2, a relationship model between the non-steady-state filtration efficiency of the dry filtration dust removal system and the fiber layer filtration efficiency and the dust layer filtration efficiency is constructed;

[0108] Specifically, the dust layer filtration and the fiber layer filtration are regarded as two relatively independent filtration processes. Assuming that the loaded dust particles do not affect the original structure of the fiber layer, the non-steady-state filtration efficiency of dry dust removal is expressed as the product of the dust layer filtration efficiency and the fiber layer filtration efficiency:

[0109] η i =1-(1-η0)(1-η c ) (9);

[0110] Where: η i is the non-steady-state filtration efficiency of the dry filtration dust removal system when loaded with dust particles of a certain particle size, %;

[0111] η0 is the filtration efficiency of the fiber layer, %;

[0112] Combining equations (8) and (9), we construct the non-steady-state filtration efficiency expression of dry dust removal, which includes the fiber layer filtration efficiency and the unit layer filtration efficiency:

[0113]

[0114] S4: According to the law of conservation of matter, the relationship between the volume of the deposited dust layer and the volume of dust captured by the filter material is used to construct a relationship model between the non-steady-state filtration efficiency and the filtration time at a specific dust layer thickness;

[0115] Specifically, Figure 2 As shown, according to the law of conservation of matter, the volume of the dust layer with a thickness of dh deposited along the x-axis in unit time dt should be equal to the volume of dust captured by the fiber filter material in unit time dt, and the following equation can be obtained:

[0116] A(1-ε)ρ p dh=AU0n0η i dt (11)

[0117] Where: A is the projected area of ​​the fiber filter material along the filtering airflow direction, m 2 ;

[0118] ρ p is the particle size of the loaded dust, kg / m 3 ;

[0119] dh is the microelement taken on the dust layer along the x-axis direction, dimensionless;

[0120] U0 is the filtration wind speed, m / s;

[0121] n0 is the mass concentration of particles in the dust-laden airflow, kg / m 3 ;

[0122] η i It is the non-steady-state filtration efficiency of the dry filtration dust removal system when loaded with dust particles of a certain particle size;

[0123] dt is the unit filtering time, dimensionless.

[0124] S5: Based on the particle size distribution percentage, a relationship model between the non-steady-state filtration efficiency of single-size dust particles and the non-steady-state filtration efficiency of multi-dispersed phase dust is constructed;

[0125] Specifically, according to the particle size distribution relationship of the multi-dispersed phase particles, based on the volume percentage of a certain fixed particle size particle, the filtration efficiency of the fixed particle size particles is calculated. By accumulating the product of the non-steady-state filtration efficiency of the fixed particle size dust particles and the particle size distribution percentage, the non-steady-state filtration efficiency expression of the dry dust removal system when loaded with multi-dispersed phase dust can be obtained:

[0126] η=Ση i ·x i (12)

[0127] Where: η is the non-steady-state filtration efficiency of the dry filtration dust removal system when loaded with multi-dispersed phase dust particles, %;

[0128] x i is a particle size d in the multi-dispersed phase pi The corresponding particle size distribution percentage, %.

[0129] S6: Based on the relationship model obtained in steps S2 to S5, the dust-laden airflow filtration is solved by integration, power series expansion, high-order infinitesimal terms, etc., to obtain a prediction formula for the non-steady-state filtration efficiency of the dry filtration dust removal system.

[0130] Specifically, the initial conditions of dh and dt in formula (11) are both 0. By integrating dh and dt in formula (11) in the dust layer thickness range of 0 to h and the time range of 0 to t, the relationship between the filtration efficiency and the filtration time t when the dust layer thickness is h can be obtained:

[0131]

[0132] By performing power series expansion on formula (10), we can obtain formula (14);

[0133]

[0134] Since the unit layer filtration efficiency η l <<1, then η l The infinitesimal terms of higher order terms are approximately equal to zero, and formula (10) can be simplified to:

[0135]

[0136] Combining the above formulas (12)-(15), integrating and solving formula (13) in the dust layer thickness range of 0~h and the time range of 0~t, the prediction formula for the non-steady-state filtration efficiency of the dry filtration dust removal system when loaded with multi-dispersed phase dust particles can be obtained:

[0137]

[0138] Where: k1 and k2 are intermediate variables;

[0139] The calculation method of the intermediate variables k1 and k2 in the prediction formula is:

[0140]

[0141] In one embodiment of the present invention, the filtration efficiency data of a dry dust removal system in a coal mine heading face in Changzhi City, Shanxi Province, China was selected, and the non-steady-state filtration efficiency prediction method was verified by field measured data.

[0142] In this embodiment, the median particle size of the multi-dispersed phase dust particles loaded by the dry dust removal system is 3.74×10 -6 m, the porosity of the dust layer is 0.65, and other physical parameters can be calculated by referring to the literature. The filtration efficiency is calculated by the dust concentration at the inlet and outlet of the dust collector. The two measuring points are arranged at the connection between the dust collector and the fan (measuring point A) and the connection between the dust collector and the wind tube (measuring point B). The time-weighted dust concentration within 15 minutes after the dust removal system is stably operated is used as the calculation basis. The dust concentration measurement results and the filtration efficiency calculation results are shown in Table 1.

[0143] Table 1 Dust concentration measurement results and filtration efficiency calculation results

[0144]

[0145] The basic filtering parameters such as dust concentration, dust layer porosity, median particle size, etc. are substituted into the present invention for calculation and solution, and the calculation results of the non-steady-state filtration efficiency are compared with the actual test results of the dry dust removal system to verify the accuracy of the non-steady-state filtration efficiency prediction method for the dry filtration dust removal system provided by the present invention.

[0146] The actual test results of the non-steady-state filtration efficiency of the dry dust removal system and the non-steady-state filtration efficiency results calculated by the present invention are as follows: Figure 3 As shown by Figure 3 It can be seen that the relative error between the non-steady-state filtration efficiency calculated by the present invention and the filtration efficiency actually measured on-site in the dry dust removal system in a coal mine is controlled within 15%, and the relative error is small. Therefore, the non-steady-state filtration efficiency prediction method for the dry filtration dust removal system provided by the present invention has a good prediction effect.

Claims

1. A method for predicting the non-steady-state filtration efficiency of a dry filtration dust removal system, characterized in that: The following steps are involved: S1: Select a single particle that makes up the dust layer as the research object, and construct a relationship model for the single particle filtration efficiency based on the particle capture efficiency caused by the free diffusion of dust, direct interception, and inertial collision. S2: The dust layer is equivalent to several unit layers stacked in series, and according to the isolated sphere theory, a relationship model between the dust layer filtration efficiency and the unit layer filtration efficiency is constructed; S3: Considering the dust layer filtration and fiber layer filtration as relatively independent individuals, a relationship model between the non-steady-state filtration efficiency of the dry filtration dust removal system and the fiber layer filtration efficiency and dust layer filtration efficiency is constructed; S4: According to the law of conservation of matter, the relationship between the volume of the deposited dust layer and the volume of dust captured by the filter material is used to construct a relationship model between the non-steady-state filtration efficiency and the filtration time at a specific dust layer thickness; S5: Based on the particle size distribution percentage, a relationship model between the non-steady-state filtration efficiency of single-size dust particles and the non-steady-state filtration efficiency of multi-dispersed phase dust is constructed; S6: Based on the relationship model obtained in steps S1 to S5, the dust-laden airflow filtration is solved by integration, high-order infinitesimal terms, and power series expansion to obtain a non-steady-state filtration efficiency prediction formula for the dry filtration dust removal system, and the non-steady-state filtration efficiency of the dry filtration dust removal system is obtained according to the non-steady-state filtration efficiency prediction formula for the dry filtration dust removal system.

2. The method for predicting the non-steady-state filtration efficiency of a dry filtration dust removal system according to claim 1 is characterized in that: In step S1, the calculation formula for calculating the single particle filtration efficiency is shown in formula (1): or s =1-(1-th It (1st) Ip (1st) D ) (1); In formula (1): s is the single particle filtration efficiency, %; η It is the particle capture efficiency caused by direct interception, and its calculation formula is shown in formula (2): η It =1.5A s R 2 (2); η Ip is the particle capture efficiency caused by inertial collision, and its calculation formula is shown in formula (3): η D is the particle capture efficiency caused by free diffusion, and its calculation formula is shown in formula (4): In formulas (2)-(4): Pe is the Peclet number, dimensionless; Re is the Reynolds number, dimensionless; A s is an implicit function of porosity, dimensionless; R is the intercept parameter, dimensionless; Stk is the Stokes number, dimensionless.

3. The method for predicting the non-steady-state filtration efficiency of a dry filtration dust removal system according to claim 2 is characterized in that: Step S2 specifically includes: S2.1: Consider a dust layer with a thickness of h and a porosity of ε as N unit layers stacked in series. Assuming that the particles that make up the dust layer are uniformly and randomly distributed, the cubic volume calculation formula can be obtained: In formula (5): l is the thickness of the unit layer, m; d g is the average particle diameter of the dust layer, m; ε is the porosity of the dust layer; By transforming formula (5), we can get the expression of unit layer thickness l as formula (6): S2.2: The dust particle is regarded as a sphere, and the dust layer is regarded as a collection of dust particles. Each dust particle in the dust layer is completely independent of each other. According to the isolated sphere model, the unit layer filtration efficiency η is constructed according to formula (5) and formula (6): l The difference between the single particle filtration efficiency and s The relationship model is as described in formula (7): In formula (7): l is the unit layer filtration efficiency of the dust layer, %; S2.3: Consider the dust layer as a series of evenly distributed unit layers, and construct the dust layer filtration efficiency η c and unit layer filtration efficiency η l The relationship model between is shown in formula (8): In formula (8): c is the dust layer filtration efficiency, %; h is the dust layer thickness, m.

4. A method for predicting the non-steady-state filtration efficiency of a dry filtration dust removal system according to claim 3, characterized in that: Step S3 specifically includes: The dust layer filtration and fiber layer filtration are considered as relatively independent individuals. The fiber layer filtration efficiency η0 and the dust layer filtration efficiency η c A relationship model of the non-steady-state filtration efficiency of the dry filtration dust removal system is constructed, and the fiber layer filtration efficiency η0 is obtained through experimental testing; the relationship model is shown in formula (9): or i =1-(1-η0)(1-η c ) (9); In formula (9): i It is the non-steady-state filtration efficiency of the dry filtration dust removal system when loaded with dust particles of a certain particle size; η0 is the filtration efficiency of the fiber layer; The formula (8) and (9) are used to construct the fiber layer filtration efficiency η0 and the unit layer filtration efficiency η l The relationship model of the non-steady-state filtration efficiency of dry dust removal when a certain dust particle size is loaded is shown in formula (10):

5. A method for predicting the non-steady-state filtration efficiency of a dry filtration dust removal system according to claim 4, characterized in that: Step S4 specifically includes: By constructing an equivalent relationship between the volume of the dust layer deposited per unit time and the volume of dust captured by the filter material per unit time, a relationship model between the non-steady-state filtration efficiency and filtration time of the dry filtration dust removal system when dust particles of a certain particle size are loaded is obtained. The relationship model is shown in formula (11): A(1-e)r p dh=AU0n0η i dt (11); In formula (11): A is the projected area of ​​the fiber filter material along the filtering airflow direction; ρ p The particle size of the loaded dust particles; dh is the microelement along the dust thickness direction; U0 is the filtering wind speed; n0 is the mass concentration of particles in the dust-laden airflow; η i It is the non-steady-state filtration efficiency of the dry filtration dust removal system when loaded with dust particles of a certain particle size; dt is the unit filtering time.

6. A method for predicting the non-steady-state filtration efficiency of a dry filtration dust removal system according to claim 5, characterized in that: Step S5 specifically includes: Considering the case where the loaded dust is multi-dispersed phase particles, based on the loaded dust particle size distribution, the non-steady-state filtration efficiency of the dry filtration dust removal system when loading multi-dispersed phase dust particles is obtained by accumulating the product of the non-steady-state filtration efficiency of single-size dust particles and the particle size distribution percentage, which is expressed as: the=You i ·x i (12); In formula (12): η is the non-steady-state filtration efficiency of the dry filtration dust removal system when loaded with multi-dispersed phase dust particles; x i is a specific particle size d in the multi-dispersed phase particles pi The corresponding particle size distribution percentage.

7. A method for predicting the non-steady-state filtration efficiency of a dry filtration dust removal system according to claim 6, characterized in that: Step S6 specifically includes: using the relationship model obtained in steps S2 to S5 as a basic condition, and solving it through integration, power series expansion, and high-order infinitesimal mathematical means. The specific process is: The initial conditions of dh and dt in formula (11) are both 0. By integrating dh and dt in formula (11) in the dust layer thickness range of 0 to h and the time range of 0 to t, we can obtain the relationship between the filtration efficiency and the filtration time t when the dust layer thickness is h (13), By performing power series expansion on formula (10), we can obtain formula (14); Since the unit layer filtration efficiency η l <<1, then η l The infinitesimal terms of higher order terms are approximately equal to zero, and formula (10) is simplified to: Combining the above formulas (12)-(15), integrating and solving formula (13) in the dust layer thickness range of 0~h and the time range of 0~t, the prediction formula for the non-steady-state filtration efficiency of the dry filtration dust removal system when loaded with multi-dispersed phase dust particles can be obtained: In formula (16): k1 and k2 are intermediate variables; The calculation method of the intermediate variables k1 and k2 is:

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