Pick system reliability analysis method

Abstract

The invention provides a method for analyzing the reliability of a cutting pick system, which respectively constructs a cutting pick system reliability model under the independent influence of the environment, the area and the aggregation degree and the comprehensive influence of the environment, the area and the aggregation degree by considering the influence of the environment, the area and the aggregation degree on the reliability of the cutting pick system. The cutting pick system reliability model considering the influence of the environment, the area and the aggregation degree conforms to engineering practice, effective guidance is provided for design optimization and reliability improvement of the cutting pick system, and meanwhile a theoretical basis and a scientific basis are provided for maintenance and spare part management of the cutting pick system.

Description

Technical Field

[0001] The invention relates to the technical field of coal and rock cutting machinery, and in particular to a reliability analysis method for a pick system. Background Art

[0002] As the most critical actuator of the cantilever roadheader, the pick system is responsible for rock breaking. Its reliability directly determines the working performance and service life of the roadheader, and has a direct impact on the tunneling efficiency of the coal mine and the resulting economic benefits. Generally, there are two ways to improve the reliability of the pick system. One is to improve the reliability of the pick in the pick system; the other is to study a more reasonable internal structure of the pick system. Restricted by the technical level of raw material properties, heat treatment methods, welding quality, etc., the reliability improvement of the pick has encountered a bottleneck. Therefore, scientific evaluation of the reliability of the pick system is an important basis for guiding the optimization design, maintenance decision-making and spare parts management of the pick system. Although the evaluation methods of the reliability of the pick system have been widely studied at this stage, there is no technical solution that simultaneously considers the impact of the environment, region and concentration on the reliability of the pick system. Summary of the invention

[0003] In order to solve the above technical problem or at least partially solve the above technical problem, the present application provides a pick reliability analysis method.

[0004] According to a first aspect, a reliability analysis method for a pick system is provided, the method comprising:

[0005] S1: Obtaining the coal rock hardness, determining the allowable number of pick failures corresponding to different coal rock hardnesses according to the coal rock hardness, and establishing a pick system environmental reliability model based on the coal rock hardness and the allowable number of pick failures corresponding to different coal rock hardnesses;

[0006] S2: Divide the pick system into different areas according to preset division conditions, determine the allowable number of pick failures in each area after division and the allowable number of pick failures of the overall pick system, and establish a regional reliability model of the pick system based on the number of failed picks, the allowable number of pick failures in each area and the allowable number of pick failures of the overall pick system;

[0007] S3: acquiring the real-time position information of the pick, determining the allowable number of failures under the clustering effect according to the real-time position information of the pick and the distance threshold, and establishing a clustering reliability model of the pick system based on the number of failed picks and the maximum allowable number of failures of the picks under the clustering effect;

[0008] S4: Establishing a pick system reliability analysis model by combining the pick system environmental reliability model, the pick system regional reliability model and the pick system aggregation reliability model.

[0009] Preferably, in step S1, different coal rock environments are divided according to coal rock hardness, the allowable failure number of picks corresponding to different coal rock hardnesses in any coal rock environment and the reliability of a single component are defined, and a pick system environmental reliability model is established according to the total probability formula. The reliability formula of the pick system environmental reliability model is:

[0010]

[0011] In the formula, E j is the jth environment in which the system is located, is the allowable number of failures of the system’s picks under the jth environment, is the reliability of a single component under the jth environment, P(E j ) is the total probability formula, e is the maximum number of different environments included, is the number of combinations of i components selected from n components, where n is the total number of components.

[0012] Preferably, in step S2, according to the order in which the pick system drills into the coal and rock, the pick system is divided into different areas according to preset division conditions, and the reliability probability formula of the pick system regional reliability model is:

[0013]

[0014] Where n f is the number of failed components; S is the number of areas divided by the pick system according to the preset division conditions; is the number of components allowed to fail in the lth area; S l is the lth region of the system; is the total number of components in the lth region; k is the number of allowable failures of the overall pick system; g is the number of any components in the lth region of the system;

[0015] Based on the reliable probability formula of the pick system regional reliability model, the reliability of the pick system regional reliability model is obtained as follows:

[0016]

[0017] Preferably, the sum of the allowable failure numbers of picks in each area after division is greater than the allowable failure number of picks in the overall pick system, and the allowable failure number of picks in each area after division is less than the allowable failure number of picks in the overall pick system.

[0018] Preferably, in step S3, a clustering effect is formed when the distance between any two of a certain number of failed picks is less than a distance threshold, and the certain number refers to the allowable number of failures under the clustering effect.

[0019] Preferably, the reliable probability formula of the pick system aggregation reliability model is:

[0020]

[0021] In the formula, is the total number of cases where failed components form clusters, n f is the number of failed components; R is the reliability of a single component, n is the total number of system components, n a The minimum number of failed components that may cause system failure due to aggregation;

[0022] Based on the reliable probability formula of the pick system aggregation reliability model, the reliability of the pick system aggregation reliability model is obtained as follows:

[0023]

[0024] Preferably, the pick coordinates are obtained based on the real-time position information of the pick and the spatial coordinate system; a distance model between any two picks is constructed based on the pick coordinates; a relative distance matrix of all components of the pick system is constructed based on the distance model between any two picks; and the total number of cases where failed components form clusters is determined based on the distance threshold and the relative distance matrix.

[0025] Preferably, the reliability formula of the pick system reliability model is:

[0026]

[0027] The probability formula of the reliability model of the pick system is:

[0028]

[0029] In the formula, E j is the jth environment in which the system is located, is the reliability of a single component under the jth environment, n f is the number of failed parts, S is the number of areas divided by the pick system according to the preset division conditions, is the number of components allowed to fail in the lth region, S l is the lth region of the system, n a is the minimum number of failed components that may cause system failure due to aggregation.

[0030] Compared with the prior art, the technical solution provided by the embodiments of the present disclosure has the following advantages:

[0031] The embodiment of the present invention considers the influence of environment, region and concentration on the reliability of the pick system, and constructs the pick system reliability model under the influence of environment, region and concentration alone and the combined influence of the above three factors. The pick system reliability model considering the influence of environment, region and concentration of the present invention conforms to engineering practice, provides effective guidance for the design optimization and reliability improvement of the pick system, and provides a theoretical basis and scientific basis for the maintenance and spare parts management of the pick system. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0033] Figure 1 is a flow chart of a reliability analysis method for a pick system according to an embodiment of the present invention;

[0034] Figure 2 is a schematic diagram of a reliability block diagram of a k / n(F) system according to an embodiment of the present invention;

[0035] Figure 3.1 is a schematic diagram of a drilling condition of a pick system in coal rock according to an embodiment of the present invention;

[0036] Figure 3.2 is a schematic diagram of the regional division of the pick system in coal rock according to an embodiment of the present invention;

[0037] Figure 4.1 is a schematic diagram of pick coordinates of a pick system according to an embodiment of the present invention;

[0038] Figure 4.2 is a schematic diagram of the arrangement of picks of a pick system according to an embodiment of the present invention;

[0039] Figure 5 is a schematic diagram of a reliability curve of a single pick under different coal and rock hardness conditions according to a verification experiment of the present invention;

[0040] Figure 6 is a schematic diagram of a reliability curve of a pick system according to a verification experiment of the present invention;

[0041] Figure 7 It is a schematic diagram of sensitivity analysis of the reliability of the pick system under different n values ​​according to the verification experiment of the present invention;

[0042] Figure 8It is a schematic diagram of sensitivity analysis of the reliability of the pick system under different k values ​​according to the verification experiment of the present invention;

[0043] Fig. 9 According to the verification experiment of the present invention, a Sensitivity analysis diagram of the reliability of the pick system under the value;

[0044] Fig.10 According to the verification experiment of the present invention, H Schematic diagram of sensitivity analysis of the reliability of the pick system under different values. DETAILED DESCRIPTION

[0045] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0046] The pick system is composed of n picks arranged in a spiral line. The pick system rotates with the power provided by the cutting motor, and the picks distributed on it rotate accordingly to achieve the purpose of cutting coal and rock. Under specific coal and rock conditions, when the number of failed picks is less than k, the roadheader can maintain a certain cutting efficiency and complete the rock breaking work. At this time, the pick system is in the normal working range; when the number of failed picks is greater than or equal to k, the roadheader loses its cutting ability and cannot complete the rock breaking work because the number of picks involved in the cutting is too small. In reliability theory, if k or more of the n components that make up the system fail, the system cannot work normally and is recorded as a k / n(F) redundant system. The k / n(F) reliability block diagram of the pick system is shown as follows: Figure 2 As shown. The failure of the pick system is affected by the environment, region and concentration, as shown below:

[0047] (1) The failure of the pick system is affected by the hardness of coal and rock. In different environments, the hardness of coal and rock is different, the reliability of a single pick is different, and the number of picks that the pick system allows to fail is different, that is, the k value of the system is different in different environments, and the reliability of the system is affected by the environment.

[0048] (2) The failure of the pick system is affected by the working area. The pick system can be divided into different working areas, each of which is an independent k / n(F) system, so the entire pick system forms a multi-level k / n(F) system. Due to different positions and different work responsibilities, the number of picks allowed to fail in different areas is also different, that is, the k value in different areas is different. If any area fails, the entire pick system fails, and the system reliability is affected by the area.

[0049] (3) The failure of the pick system is affected by the degree of clustering of failed picks. When the distance between any two failed picks in the pick system is less than the distance threshold, that is, when the failed picks form a clustering effect, the entire pick system fails and the reliability of the system is affected by the degree of clustering.

[0050] The above situation is consistent with the actual application of the pick system of the tunnel boring machine. If these processes are simplified, it will lead to inaccurate reliability evaluation of the pick system. Therefore, the present invention provides a reliability analysis method for the pick system, which comprehensively considers the influence of the environment, region and concentration on the pick system.

[0051] For a brand new pick system, each pick is independently and identically distributed in R(t), and the pick is new at the initial moment, so the reliability of the pick system in the brand new state is R S (t) is:

[0052]

[0053] Among them, R S (t) is the reliability of the pick system, R(t) is the pick reliability, n is the total number of picks in the pick system, and k is the number of picks that are allowed to fail in the pick system.

[0054] According to an embodiment of the present invention, an embodiment of a reliability analysis method for a pick system is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0055] In this embodiment, a reliability analysis method for a pick system is provided, which can be used in the above-mentioned mobile terminals, such as mobile phones, tablet computers, etc. Figure 1 is a flow chart of a method for analyzing the reliability of a pick system according to an embodiment of the present invention. Figure 1 As shown, the process includes the following steps:

[0056] S1: Obtain the coal rock hardness, determine the allowable number of pick failures corresponding to different coal rock hardnesses according to the coal rock hardness, and establish a pick system environmental reliability model based on the coal rock hardness and the allowable number of pick failures corresponding to different coal rock hardnesses.

[0057] In this embodiment, when the cantilever tunneling machine performs cutting operations, the cutting efficiency of the pick system is closely related to the environment in which it is located, and the most important factor that determines the working environment of the pick system is the firmness of the coal rock cut by the pick system. Coal rock firmness refers to the comprehensive concept of the difficulty of coal rock crushing under the conditions of various coal rock crushing methods. Under different coal rock crushing methods, the firmness of the same type of coal rock is basically the same, and has the same proportional coefficient, that is, the Pusch hardness coefficient. According to the Pusch hardness coefficient f of coal rock, coal rock can be divided into coal (f<4), semi-coal rock (4≤f≤8) and rock (f>8).

[0058] When the pick system is cutting coal and rock of different hardness, it bears different loads, the natural wear degradation rate of a single pick in the system is different, the probability of random load impact is different, and the amplitude is different, so the reliability of a single pick is different, and then the reliability of the entire pick system is different. At the same time, in order to ensure the cutting performance of the pick system and the continuity of the tunneling operation, the number of picks allowed to fail in the pick system is different under different coal and rock hardness. The higher the coal and rock hardness, the greater the load, and the fewer the number of picks allowed to fail in the pick system; the lower the coal and rock hardness, the smaller the load, and the more the number of picks allowed to fail in the pick system, so the coal and rock hardness and the number of picks allowed to fail in the pick system are inversely correlated. The k value and component reliability of the k / n(F) system under different environments are shown in Table 1.

[0059] Table 1

[0060]

[0061] In the table, E j is the jth environment in which the system is located, is the allowable number of failed picks in the system under the jth environment,

[0062] is the reliability of a single component under the jth environment, where

[0063] Optionally, in step S1, different coal rock environments are divided according to coal rock hardness, and the allowable failure number and single component reliability of pick corresponding to different coal rock hardness in any coal rock environment are defined. According to the total probability formula, a pick system environmental reliability model is established. The reliability formula of the pick system environmental reliability model is:

[0064]

[0065] In the formula, E j is the jth environment in which the system is located, is the allowable number of failed picks in the system under the jth environment,

[0066] is the reliability of a single component under the jth environment, P(E j ) is the total probability formula, e is the maximum number of different environments included, is the number of combinations of i components selected from n components, where n is the total number of components.

[0067] S2: Divide the pick system into different areas according to preset division conditions, determine the allowable number of pick failures in each area after division and the allowable number of pick failures in the overall pick system, and establish a regional reliability model of the pick system based on the number of failed picks, the allowable number of pick failures in each area and the allowable number of pick failures in the overall pick system.

[0068] Optionally, after the division, the sum of the allowable failure numbers of picks in each area is greater than the allowable failure number of picks in the overall pick system, and after the division, the allowable failure number of picks in each area is less than the allowable failure number of picks in the overall pick system.

[0069] In this embodiment, the drilling conditions and area divisions of the cantilever roadheader pick system in coal rock are as follows: Figure 3.1 and Figure 3.2 As shown. According to the order in which the pick system drills into the coal and rock, the pick system is divided into three working areas: front, middle and rear. During the cutting process, if a certain number of picks fail in any area, this area will fail, and then the entire pick system will fail. That is, through regional division, the pick system is converted into a hierarchical k / n (F) system, and the number of components and the allowable number of pick failures contained in different areas are different. At the same time, when the number of failed picks in each area does not reach the allowable number of pick failures in their respective areas, but the total number of failed picks reaches the allowable number of pick failures of the overall pick system, the pick system still fails.

[0070] During the drilling process of the pick system, the front area first cuts the coal rock. Since the coal rock has well-developed stratification and joints before being broken, and the structure is relatively complete, the front area is subjected to the greatest impact, the most violent vibration, and the greatest rock breaking effect during drilling. The requirements for the integrity of the pick are the highest, so the number of pick failures allowed in this area is the smallest. After the front area is completed, the middle area begins to break the rock. Since the integrity of the coal rock structure has been destroyed, and the picks in the front area are also involved in the cutting, the impact on the middle area is reduced and the vibration is weakened. Therefore, the number of pick failures allowed in this area is in the middle. As the drilling of the middle area is completed, the integrity of the coal rock structure is further destroyed, and the number of picks involved in the cutting is further increased. Therefore, the rear area has the smallest impact, the weakest vibration, the smallest rock breaking effect, and the lowest requirements for the integrity of the pick. Therefore, the number of pick failures allowed in this area is the largest. The number of components and the number of pick failures allowed in different areas of the k / n(F) system are shown in Table 2.

[0071] Table 2

[0072]

[0073] Among them, area S l is the lth region of the system, is the total number of components in the lth region, is the allowable number of failures of picks in the lth region,

[0074] The reliability of the k / n(F) system affected by the area can be calculated according to the following steps:

[0075] (1) When the number of failed parts The system will not fail.

[0076] (2) When the number of failed parts When , the system can only fail due to the failure of area S1. In this case, the probability of system reliability is:

[0077]

[0078] The expression in the square brackets means that when the system has n f When a component fails, there is a probability that region S1 has no failure.

[0079] (3) When the number of failed parts When , the system may fail not only due to the failure of area S1, but also due to the failure of area S2. In this case, the probability of system reliability is:

[0080]

[0081] The expression in the square brackets means that when the system has n f The probability that both area S1 and area S2 do not fail when a component fails.

[0082] (4) Similarly, when the number of failed parts When , all regions may fail, and the system may fail due to the failure of any region. In this case, the probability of system reliability is:

[0083]

[0084] The expression in the square brackets means that when the system has n f When a component fails, there is a probability that no area will fail.

[0085] Optionally, different regions are divided according to the order in which the pick system drills into the coal and rock. The reliability probability formula of the pick system regional reliability model is:

[0086]

[0087] Where n f is the number of failed components; S is the number of areas divided by the pick system according to the preset division conditions; is the number of components allowed to fail in the lth area; S l is the lth region of the system; is the total number of components in the lth region; k is the number of allowable failures of the overall pick system; g is the number of any components in the lth region of the system;

[0088] Based on the reliable probability formula of the pick system regional reliability model, the reliability of the pick system regional reliability model is obtained as follows:

[0089]

[0090] S3: Acquire the real-time position information of the pick, determine the allowable number of failures under the clustering effect according to the real-time position information of the pick and the distance threshold, and establish a clustering reliability model of the pick system based on the number of failed picks and the maximum allowable number of failures of the picks under the clustering effect.

[0091] Optionally, in step S3, a clustering effect is formed when the distance between any two of a certain number of failed picks is less than a distance threshold, and the certain number refers to the allowable number of failures under the clustering effect.

[0092] Optionally, the pick coordinates are obtained based on the real-time position information of the pick and the spatial coordinate system; a distance model between any two picks is constructed based on the pick coordinates; a relative distance matrix of all components of the pick system is constructed based on the distance model between any two picks; and the total number of cases where failed components form clusters is determined based on the distance threshold and the relative distance matrix.

[0093] In this embodiment, the cantilever type roadheader pick system is composed of n picks arranged in a spiral line, and the relative positions of the picks in the system are determined. a The distance between any two picks is less than a certain distance threshold D. H , then the failed picks form a clustering effect in the local area of ​​the pick system. The vacuum area formed by the failed picks will cause the pick system to be in a discontinuous cutting state, the pick system is unevenly stressed, the load fluctuation increases, the vibration intensifies, and then the pick system loses its cutting performance, causing the entire system to fail. The coordinates of a single pick and the position of the pick in the pick system are shown in the figure below: Figure 4.1 and Figure 4.2 shown.

[0094] The spatial position coordinates of the components in the k / n(F) system are shown in Table 3. i,y i 、z i They are the horizontal, vertical and vertical coordinates of the component respectively.

[0095] Table 3

[0096]

[0097] According to the data shown in Table 2, the distance D between any two components i,j for:

[0098]

[0099] The relative distance matrix D of all components in the system can be expressed as:

[0100]

[0101] In this embodiment, let S i The relative distance between the i-th component and the subsequent components is less than the distance threshold D H For example, S1 represents the number of components whose relative distance to component 1 is less than the distance threshold. If the relative distance between two components in the system is less than the distance threshold D H There are a total of kind.

[0102] In this embodiment, the reliability of the k / n(F) system affected by the concentration of failed components can be calculated according to the following steps:

[0103] (1) When the number of failed parts n f <n a The system will not fail when

[0104] (2) When the number of failed parts n f ≥n a When , the system may fail due to the aggregation of failed components. In this case, the probability of system reliability is:

[0105]

[0106] in, is the total number of cases where failed components form clusters. The expression in square brackets means that when there are n f When a component fails, there is no probability of clustering between components.

[0107] In this embodiment, when there are n f When a component fails, the probability that the k / n(F) system is reliable due to the concentration of failed components is:

[0108]

[0109] Where n f is the number of failed components, R is the reliability of a single component, n is the total number of system components, a is the minimum number of failed components that may cause system failure due to aggregation.

[0110] Based on the reliable probability formula of the pick system aggregation reliability model, the reliability of the pick system aggregation reliability model is obtained as follows:

[0111]

[0112] S4: Establishing a pick system reliability analysis model by combining the pick system environmental reliability model, the pick system regional reliability model and the pick system aggregation reliability model.

[0113] In this embodiment, considering the impact of environment, region and concentration, when there are n f When k / n(F) components fail, the probability that the system is reliable is:

[0114]

[0115] In the formula, E j is the jth environment in which the system is located, is the reliability of a single component under the jth environment, n f is the number of failed parts, S is the number of areas divided by the pick system according to the preset division conditions, is the number of components allowed to fail in the lth region, S l is the lth region of the system, n a is the minimum number of failed components that may cause system failure due to aggregation.

[0116] The reliability formula of the pick system reliability model is:

[0117]

[0118] The embodiment of the present invention describes the structural characteristics and failure modes of the pick system and models it as a k / n(F) system. Secondly, by describing the effects of coal rock hardness, working area and the degree of clustering of failed picks on the failure of the pick system, reliability models of the pick system under the individual effects of environment, region and clustering as well as the combined effects of the three are constructed. The reliability model of the pick system that takes into account the effects of environment, region and clustering is in line with engineering practice, provides effective guidance for the design optimization and reliability improvement of the pick system, and provides a theoretical basis and scientific basis for the maintenance and spare parts management of the pick system.

[0119] The present invention is based on n a=3 as an example The solution method is that when the relative distance between any two of the three failed components is less than the distance threshold, the k / n(F) system fails due to the clustering effect of the failed components. First, select a component in the system, which can be any one of the n components; secondly, select the second component in the system, and the selection condition is that the relative distance with the first component is less than the distance threshold. After the selection is completed, n new relative distance matrices D are formed. i , each matrix is ​​composed of the relative distances of each component whose relative distance to component No. i is less than the distance threshold. For example, there are three components whose relative distance to component No. 1 is less than the distance threshold, namely, component No. 5, component No. 8, and component No. 10. The new relative distance matrix D1 composed of the relative distances of these three components is:

[0120]

[0121] Let S 1j The jth component whose relative distance to component 1 is less than the distance threshold, and the relative distance to the subsequent components is less than the distance threshold D H For example, S 15 represents the number of components whose relative distances to components 1 and 5 are both less than the distance threshold. If the relative distances between any two of the three components in the system are less than the distance threshold D H There are a total of species, that is Among them, i min is the component with the smallest number whose relative distance to the i-th component is less than the distance threshold, i max The largest numbered component whose relative distance to the i-th component is less than the distance threshold. a >3 o'clock, The above method can be used for recursive calculation.

[0122] In order to further verify the effectiveness and feasibility of the method of the present invention, the present invention conducts a cutting test by taking a small-section rock tunnel boring machine with a cutting power of 260 kW produced by a certain tunnel boring machine manufacturing company as an example.

[0123] The longitudinal pick system consists of 51 picks arranged in 3 spiral lines. If 12 picks fail in the system, the entire system fails. The coal rock in the working environment of the pick system is mainly gray-white medium-grained sandstone and gray-black sandy mudstone, with an average Pugh hardness system of f6.8, accompanied by high-hardness gangue and faults. The pick system is divided into three regions: front, middle and back, thus forming a multi-level k / n (F) system. At the same time, if the distance between any two of the three failed picks is less than 10 mm, the pick system fails due to the aggregation effect of the failed picks. The spatial coordinates, regional n value and regional k value of the pick in the pick system are shown in Table 4.

[0124] Table 4

[0125]

[0126] According to the coal and rock hardness, the working environment of the pick system is divided into coal (f<4), semi-coal and rock (4≤f≤8) and rock (f>8). According to the engineering data, the reliability model parameters of the pick system can be obtained by fitting, as shown in Table 5. Then, the reliability curves of a single pick under different coal and rock hardness conditions are plotted on Figure 5 middle.

[0127] Table 5

[0128]

[0129] Depend on Figure 5 It can be seen that when the nature of the coal rock cut by the pick system is full coal, the natural degradation rate of the pick is the lowest due to the lowest hardness of the coal. At the same time, there is no high-hardness gangue and fault in the full coal. The degradation of the pick is not affected by the impact of random loads, and only soft failure caused by natural wear will occur, so its reliability level is the highest. When the nature of the coal rock cut by the pick system is semi-coal rock, as the hardness of the coal rock increases, the natural degradation rate of the pick also increases. At the same time, due to the appearance of high-hardness gangue and faults, the degradation of the pick also includes instantaneous degradation caused by random load impact and accelerated degradation of the variable rate during the impact duration. The pick is more likely to have soft failure, so its reliability level is reduced. When the nature of the coal rock cut by the pick system is whole rock, due to the highest hardness of the rock, there is no natural degradation process for the pick, and the pick is always in a variable rate accelerated degradation process within the impact duration caused by high-hardness gangue and faults. At the same time, when the gangue and faults reach a certain hardness, the pick may also suffer hard failure caused by random load impact. Therefore, in the competitive failure mode of soft failure and hard failure, its reliability level is the lowest.

[0130] In order to consider the influence of environment, region and aggregation on the failure of the pick system and verify the universality of the model, the established pick system reliability model is transformed into a pick system reliability model considering different factors by setting different parameter values. The main factors considered by these models are compared in Table 6.

[0131] Table 6

[0132]

[0133] In order to illustrate the influence of environment, region and aggregation on the reliability of the pick system, the reliability curves of the four models listed in Table 5 are plotted on the Figure 6 From this, we can draw the following conclusions:

[0134] (1) The impact of the environment on the reliability of the pick system can be obtained by comparing the reliability curves of model 1 and model 2. As can be seen from the figure, the pick system without considering the environmental impact has a high stable reliability stage of 7 days, that is, the pick system will not fail within 7 days, which is quite different from the actual application of the pick system. The pick system considering the environmental impact has a high stable reliability stage of 5 days, and the reliability is 0.52 at 8 days, that is, the probability that the pick system will not fail within 8 days is 52%, which is in line with the actual degradation trend of the pick system. This is because when the environmental impact is not considered, the working environment of the pick system is only for the full coal working condition, there is no high-hardness gangue and fault in the coal seam, the pick wears the slowest naturally, and is not affected by random load impact, the reliability is the highest, and the system k value of the pick system under the full coal working condition is the largest. However, in actual engineering, it is impossible for the pick system to be in a static working environment. Under different coal and rock hardness conditions, the reliability of a single pick and the allowable number of pick failures of the pick system will change accordingly. If the impact of environmental changes on system failure is ignored, the system reliability calculation will be inaccurate. Therefore, the model that considers environmental impact always has a more accurate reliability level than the model that does not consider environmental impact.

[0135] (2) The influence of the region on the reliability of the pick system can be obtained by comparing the reliability curves of Model 2 and Model 3. As can be seen from the figure, the pick system without considering the regional influence has a high stable reliability stage of 5 days, and the reliability is 0.52 at 8 days. The pick system considering the regional influence has a high stable reliability stage of 4.5 days, and the reliability is 0.3 at 8 days. The probability of failure of the pick system increases by 22%. This is because the various regions of the pick system have different responsibilities and functions under specific working conditions. The failure of a certain number of picks in any region will cause the loss of function of the region, thereby causing the failure of the region and eventually causing the failure of the entire pick system. That is, the pick system and its various regions form a hierarchical k / n (F) system. If the influence of regional failure on system failure is ignored, the reliability of the system will be overestimated. Therefore, the model considering regional influence always has a lower reliability level than the model without considering regional influence.

[0136] (3) The effect of aggregation on the reliability of the pick system can be obtained by comparing the reliability curves of Model 3 and Model 4. As can be seen from the figure, the pick system without considering the effect of aggregation has a high stable reliability stage of 4.5 days, and the reliability is 0.3 at 8 days. The pick system considering the effect of aggregation only has a high stable reliability stage of 4 days, and the reliability is 0.22 at 8 days. The probability of failure of the pick system has increased by 8%. This is because although the pick system as a whole and in each region has not failed, the failed picks are locally aggregated to form a vacuum area, causing the pick system to be unevenly stressed during the cutting process, increasing load fluctuations and intensifying vibrations, which leads to the loss of cutting performance of the system and ultimately causes the failure of the entire system. If the effect of the aggregation of failed picks on system failure is ignored, the reliability of the system will be overestimated. Therefore, the model considering the effect of aggregation always has a lower reliability level than the model not considering the effect of aggregation.

[0137] (4) The reliability curve of the pick system affected by the environment, region and concentration is shown in Model 4. As can be seen from the figure, unlike the pick, which does not have a high stable reliability stage in its entire life cycle, the pick system has a high stable reliability stage of 4 days in its entire life cycle, and then enters the rapid degradation stage, and the reliability that can be used for 7 days is 0.5. At this reliability level, it still cannot meet the needs of safe and efficient production, which is the important reason why the pick system needs to adopt a reasonable maintenance and spare parts inventory strategy.

[0138] In order to verify the reliability model of the pick system and guide the optimization design of the pick system to improve reliability, it is necessary to analyze the sensitivity of the model parameters and study their influence on reliability. a and D H It is the key parameter that determines the reliability of the system. Therefore, based on the engineering data, the sensitivity of the above parameters is analyzed, and the specific parameter range is shown in Table 7.

[0139] Table 7

[0140]

[0141] The sensitivity analysis of the total number of picks n and the system failure threshold k is as follows: Figure 7 and Figure 8 As shown. When the value of n decreases from 57 to 45, the reliability of the pick system in 7 days increases by 0.48. When the value of k increases from 10 to 14, the reliability of the pick system in 7 days increases by 0.39. Therefore, by reducing the system n value or increasing the system k value, the reliability of the system is improved. In practice, n and k reflect the redundant structure of the pick system. Therefore, under the premise of meeting the overall design requirements of the tunnel boring machine, the cutting capacity of the pick system can be improved, thereby reducing the total number of picks in the system n or increasing the system failure threshold k, that is, reducing the redundancy of the system, and ultimately improving the reliability of the entire pick system.

[0142] The number of failed picks that form a clustering effect on the pick system n a and distance threshold D H The sensitivity analysis of Fig. 9 , Fig.10 As shown. a When the value of increases from 3 to 5, the reliability of the pick system in 7 days increases by 0.32; H When the value of increases from 8 to 12, the reliability of the pick system in 7 days increases by 0.33. a or D H The value of n is higher, and the reliability of the system is improved. a and D H It reflects the arrangement design of the picks in the pick system. Therefore, the pick arrangement design such as the pick system contour line, number of spiral lines, spiral rise angle, and cutter line distance should be continuously optimized to improve the cutting ability of the pick system, thereby increasing the number of failed picks that form the clustering effect. a and distance threshold D H , ultimately improving the reliability of the entire pick system.

[0143] Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present invention, and such modifications and variations are all within the scope defined by the appended claims.

Claims

1. A reliability analysis method for a pick system, characterized in that: The method comprises: S1: Obtaining the coal rock hardness, determining the allowable number of pick failures corresponding to different coal rock hardnesses according to the coal rock hardness, and establishing a pick system environmental reliability model based on the coal rock hardness and the allowable number of pick failures corresponding to different coal rock hardnesses; S2: Divide the pick system into different areas according to preset division conditions, determine the allowable number of pick failures in each area after division and the allowable number of pick failures of the overall pick system, and establish a regional reliability model of the pick system based on the number of failed picks, the allowable number of pick failures in each area and the allowable number of pick failures of the overall pick system; S3: acquiring the real-time position information of the pick, determining the allowable number of pick failures under the clustering effect according to the real-time position information of the pick and the distance threshold, and establishing a clustering reliability model of the pick system based on the number of failed picks and the allowable number of pick failures under the clustering effect; S4: Establishing a pick system reliability analysis model by combining the pick system environmental reliability model, the pick system regional reliability model and the pick system aggregation reliability model.

2. A pick system reliability analysis method according to claim 1, characterized in that: In step S1, different coal rock environments are divided according to coal rock hardness, and the allowable failure number and single component reliability of pick corresponding to different coal rock hardness in any coal rock environment are defined. According to the total probability formula, the pick system environmental reliability model is established. The reliability formula of the pick system environmental reliability model is: In the formula, E j is the jth environment in which the system is located, is the allowable number of failures of the system’s picks under the jth environment, is the reliability of a single component under the jth environment, P(E j ) is the total probability formula, e is the maximum number of different environments included, is the number of combinations of i components selected from n components, where n is the total number of components.

3. A pick system reliability analysis method according to claim 2, characterized in that: In step S2, according to the order in which the pick system drills into the coal and rock, the pick system is divided into different areas according to preset division conditions. The reliability probability formula of the pick system regional reliability model is: Where n f is the number of failed components; S is the number of areas divided by the pick system according to the preset division conditions; is the number of components allowed to fail in the lth area; S l is the lth region of the system; is the total number of components in the lth region; k is the number of allowable failures of the overall pick system; g is the number of any components in the lth region of the system; Based on the reliable probability formula of the regional reliability model of the pick system, the reliability of the regional reliability model of the pick system is obtained as follows:

4. A pick system reliability analysis method according to claim 3, characterized in that: The sum of the allowable failure numbers of picks in each area after division is greater than the allowable failure number of the overall pick system, and the allowable failure number of picks in each area after division is less than the allowable failure number of the overall pick system.

5. A pick system reliability analysis method according to claim 1, characterized in that: In step S3, a clustering effect is formed when the distance between any two of a certain number of failed picks is less than a distance threshold, and the certain number refers to the number of failed picks allowed under the clustering effect.

6. A pick system reliability analysis method according to claim 5, characterized in that: The reliable probability formula of the pick system aggregation reliability model is: In the formula, is the total number of cases where failed components form clusters, n f is the number of failed components, R is the reliability of a single component, n is the total number of system components, a The minimum number of failed components that may cause system failure due to aggregation; Based on the reliable probability formula of the pick system aggregation reliability model, the reliability of the pick system aggregation reliability model is obtained as follows:

7. A pick system reliability analysis method according to claim 5, characterized in that: Acquire the coordinates of the pick according to the real-time position information of the pick and the spatial coordinate system; Building a distance model between any two picks based on the pick coordinates; Constructing a relative distance matrix of all components of the pick system based on the distance model between any two picks; The total number of instances where failed components form clusters is determined based on the distance threshold and the relative distance matrix.

8. A pick system reliability analysis method according to claim 1, characterized in that: The reliability formula of the pick system reliability model is: The probability formula of the reliability model of the pick system is: In the formula, E j is the jth environment in which the system is located, is the reliability of a single component under the jth environment, n f is the number of failed parts, S is the number of areas divided by the pick system according to the preset division conditions, is the number of components allowed to fail in the lth region, S l is the lth region of the system, n a is the minimum number of failed components that may cause system failure due to aggregation.

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