Intelligent maintenance system for coal mine conveyor belt

Abstract

The invention belongs to the technical field of coal mine conveyor belt maintenance, and particularly discloses an intelligent maintenance system for a coal mine conveyor belt. The system comprises a belt information import module, a belt operation monitoring module, a belt operation analysis module, a belt maintenance judgment module, a belt maintenance confirmation module, a database and a belt maintenance execution terminal. According to the method, when the current belt position deviates, the belt position overhaul maintenance degree is counted by combining historical belt overhaul data, overhaul confirmation of the belt position is carried out, the effectiveness of belt overhaul is guaranteed, the time regularity analysis is carried out on the temperature, the sound loudness and the vibration frequency, and the accuracy of belt overhaul is improved. The pertinence of coal mine conveyor belt environment analysis is guaranteed, predictive maintenance is facilitated, meanwhile, the coal mine adhesion degree of the target belt is analyzed by setting the position weight and combining the adhesion growth rate and the coal mine adhesion ratio, and the influence of the coal mine adhesion position on the belt is accurately evaluated.

Description

Technical Field

[0001] The invention belongs to the technical field of maintenance of coal mine conveyor belts, and relates to an intelligent maintenance system for coal mine conveyor belts. Background Art

[0002] Coal mine conveyor belt maintenance generally refers to the regular or irregular inspection, maintenance and repair of belt conveyors used in coal mines to ensure their normal operation and extend their service life.

[0003] The current maintenance of coal mine conveyor belts mainly includes the restoration of the belt position and the cleaning of the belt surface. There are still the following deficiencies: 1. When the coal mine conveyor belt position is currently inspected, only the corresponding maintenance is performed according to the current belt position deviation. No further analysis is performed on the maintenance status after the historical position deviation inspection. The targeted nature of the belt maintenance cannot be guaranteed, potential problems cannot be discovered, and the operating stability of the coal mine conveyor cannot be guaranteed.

[0004] 2. Currently, there is no regular analysis of the temperature, sound volume and vibration frequency of coal mine conveyor belts, which cannot ensure the pertinence of coal mine conveyor belt environmental analysis, cannot detect the potential failure trend of the belts, and thus cannot perform predictive maintenance, reducing the reliability of coal mine conveyor belt maintenance.

[0005] 3. Currently, the surface cleaning of the coal conveyor belt is determined only based on whether the coal is attached or not. The coal attachment position is not analyzed in detail, and the impact of the coal attachment position on the belt cannot be accurately assessed, and local problems of coal attachment cannot be discovered. This increases the complexity of subsequent coal attachment maintenance. Summary of the invention

[0006] In view of this, in order to solve the problems raised in the above background technology, an intelligent maintenance system for coal mine conveyor belts is now proposed.

[0007] The purpose of the present invention can be achieved through the following technical solutions: The present invention provides an intelligent maintenance system for coal mine conveyor belts, including: a belt information import module, used to record the coal mine conveyor belt to be inspected as a target belt, and import the benchmark operating status information and operating mark information of the target belt.

[0008] The belt operation monitoring module is used to monitor the current cumulative monitoring time of the target belt, and monitor the operating status information and monitoring video of the target belt in the current monitoring time period. The operating status information includes the temperature, sound loudness and vibration frequency of the target belt in each monitoring time period.

[0009] The belt operation analysis module is used to analyze the belt operation status according to the operation status information and monitoring video of the target belt in the current monitoring time period.

[0010] The belt maintenance judgment module is used to judge the belt maintenance demand based on the belt operation status analysis results.

[0011] The belt maintenance confirmation module is used to confirm each required maintenance item and the maintenance information of each required maintenance item when the judgment result is that the belt maintenance is required.

[0012] The database is used to store the historical maintenance log of the target belt, store the reference attachment ratio of the coal mine under each monitoring time, and store the associated triggering factors of the belt position deviation.

[0013] The belt maintenance execution terminal is used to execute corresponding maintenance according to each required maintenance item and the maintenance information of each required maintenance item.

[0014] Furthermore, the belt running status analysis includes: dividing the monitoring video of the target belt in the current monitoring time period into frames to obtain each video frame, and recording the monitoring time point of each video frame, sorting the video frames in chronological order according to the monitoring time, taking the video frame with the last sorting position as the current video frame, and extracting the current image of the target belt from the current video frame.

[0015] The reference image of the target belt is extracted from the reference running state information of the target belt, and the reference image of the target belt is overlapped and compared with the current image to obtain the overlapped image area of ​​the target belt, which is recorded as S1, and the area of ​​the target belt is recorded as S2.

[0016] Compare S1 with S2, and use the ratio as the position compliance of the target belt, denoted as

[0017] Extract the reference temperature, reference vibration frequency and reference sound loudness of the target belt at each monitoring time from the benchmark operating status information of the target belt, and then calculate the transportation environment compliance of the target belt

[0018] Extract the reference attachment area of ​​the target belt from the benchmark running status information of the target belt, and then calculate the coal mine attachment degree of the target belt and will and As the result of belt running status analysis.

[0019] Furthermore, the statistically calculating the transport environment compliance of the target belt includes: calculating the transport temperature compliance φ1 of the target belt according to the temperature in each monitoring time period.

[0020] The maximum vibration frequency is selected from the vibration frequencies in each monitoring time period and is recorded as f.

[0021] A vibration frequency variation curve is constructed with the monitoring time period as the horizontal axis and the vibration frequency as the vertical axis. The reference vibration frequency is extracted from the benchmark operating state information of the target belt, and a vibration frequency reference line is constructed in the vibration frequency variation curve.

[0022] The length of the curve located above the vibration frequency reference curve is located from the vibration frequency variation curve and is recorded as L1, and the length of the vibration frequency variation curve is recorded as L2.

[0023] Statistical target belt transport vibration compliance φ2, K1 and f' are the deviation vibration frequency ratio and vibration frequency of the setting reference respectively.

[0024] The target belt's transport sound loudness compliance is obtained by using the same statistical method as φ2, and is recorded as φ3.

[0025] Statistical target belt transportation environment compliance p1, p2 and p3 are the weights of the set transportation temperature compliance, transportation vibration compliance and transportation sound loudness compliance respectively, p1>p2>p3, p1+p2+p3=1.

[0026] Furthermore, the statistical target belt's transport temperature compliance includes: extracting the maximum temperature from the temperatures of each monitoring time period, recorded as C, constructing a temperature change curve with the monitoring time period as the horizontal coordinate and the temperature as the vertical coordinate, extracting a reference temperature change curve from the benchmark operating status information of the target belt, overlapping and comparing it with the temperature change curve, obtaining the length of the temperature overlap curve, recorded as L3, and recording the length of the temperature change curve as L4.

[0027] Statistical target belt transport temperature compliance φ1, K2 and C′ are the length ratio and temperature of the temperature coincidence curve set as the reference, respectively.

[0028] Furthermore, the statistical coal mine attachment degree of the target belt includes: extracting the area of ​​each coal mine attachment point from the current video frame, summing them up to obtain the total area of ​​the coal mine attachment point of the current video frame, and comparing it with the surface area of ​​the target belt to obtain the coal mine attachment ratio of the current video frame as the coal mine attachment ratio under the current cumulative monitoring time, recorded as K3.

[0029] The coal mine attachment ratio at each monitoring time was obtained by using the statistical method of K3.

[0030] The reference attachment ratio of coal mines at each monitoring time is extracted from the database, and then the reference attachment ratio of coal mines at the current cumulative monitoring time is extracted, which is recorded as K3′.

[0031] The position of each coal dust attachment interference point is extracted from the running mark information of the target belt, and the position interference weight is set accordingly and recorded as α.

[0032] With the monitoring time as the horizontal axis and the coal mine attachment ratio as the vertical axis, a coal mine attachment growth change curve is constructed, and the slope of the change curve is extracted as the attachment growth rate, which is recorded as β.

[0033] The reference adhesion growth rate is extracted from the benchmark operating state information of the target belt and is recorded as β′.

[0034] Statistical coal mine adhesion of target belt

[0035] Furthermore, the setting of the position interference weight includes: extracting the position and number of each coal dust attachment point from the current image of the target belt.

[0036] The positions of each coal dust attachment point and each coal dust attachment interference point are introduced into the coal dust attachment position judgment model to obtain each primary interference point and each secondary interference point.

[0037] If the number of primary interference locations is equal to the number of coal dust attachment locations, the location interference weight is recorded as 1.

[0038] If the number of primary interference points is less than the number of coal dust attachment points, compare the number of primary interference points with the number of coal dust attachment points, and take the ratio as the ratio of the number of primary interference points, recorded as K1′. Use the same statistical method as K1′ to obtain the ratio of the number of secondary interference points, recorded as K2′.

[0039] Statistical location interference weight ε, K1″ and K2″ are respectively the set reference ratio of the number of primary interference points and the number of secondary interference points, r1 and r2 are respectively the weights of the set ratio of the number of primary interference points and the number of secondary interference points r1>r2, r1+r2=1.

[0040] If the number of primary interference locations and the number of secondary interference locations are both 0, the position interference weight is recorded as 0, and then the position interference weight α is obtained, and the value of α is 1, ε or 0.

[0041] Furthermore, the belt maintenance demand determination includes: if and If there is a degree of compliance that is less than the corresponding set reference, the need for belt maintenance is taken as the judgment result.

[0042] like and If the values ​​are greater than or equal to the corresponding reference conformity, it is judged that no belt maintenance is required.

[0043] Furthermore, the confirmation of each required maintenance item includes: if If the belt position is not within the set reference target belt position compliance range, the belt position will be considered as a maintenance item.

[0044] like If the transportation environment is not within the set reference compliance range, the transportation environment will be taken as a maintenance item.

[0045] like If it is not within the set reference coal mine attachment range, the coal mine attachment will be taken as a maintenance item.

[0046] Furthermore, the confirmation of the maintenance information of each maintenance item requires includes: when the maintenance item requires is the belt position, extracting the historical belt position maintenance times and the time points of each historical belt position maintenance from the historical maintenance log of the target belt, and then confirming the belt position maintenance maintenance degree δ.

[0047] If δ is greater than or equal to the set reference belt position maintenance maintenance degree, the belt position restoration is used as the maintenance information when the required maintenance item is the belt position. Otherwise, the associated trigger cause items of the belt position deviation are extracted from the database, and the associated trigger cause items are used as reference maintenance items, and the reference maintenance items are used as the maintenance information when the required maintenance item is the belt position.

[0048] When the maintenance item required is the transportation environment, the statistical environment deviation degree ψ is used. To set the reference transportation environment compliance.

[0049] Match and compare ψ with the environmental deviation interval corresponding to each transport environment maintenance level to obtain the matched transport environment level, and use the matched transport environment maintenance level as the maintenance information when the required maintenance item is the transport environment.

[0050] When the maintenance item required is coal mine attachment, the coal mine attachment excess is calculated in the same way as ψ, which is recorded as ψ′.

[0051] Match and compare ψ′ with the coal mine attachment excess interval corresponding to each coal mine attachment maintenance level to obtain the matched coal mine attachment maintenance level, and use the matched coal mine attachment maintenance level as the maintenance information when the required maintenance item is coal mine attachment.

[0052] Furthermore, the confirmation of the belt position maintenance maintenance degree includes: according to the time points of each historical belt position maintenance and the current time point, obtaining the interval between the current time point and the last maintenance in history as the current maintenance interval, recorded as T.

[0053] The time points of each historical belt position maintenance are combined in pairs to obtain each belt maintenance group, and then the interval duration of each historical belt position maintenance in each belt maintenance group is obtained as the maintenance interval duration of each belt maintenance group, and it is compared with the set reference maintenance interval duration.

[0054] If the maintenance interval of a belt maintenance group is longer than the set reference maintenance interval, the belt maintenance group is recorded as a qualified belt maintenance group, the number of qualified belt maintenance groups is counted and recorded as D1, and the number of belt maintenance groups is recorded as D2.

[0055] The maintenance interval duration of each belt maintenance group is averaged and the calculated result is used as the maintenance interval duration of the reference belt position, denoted as T′.

[0056] Statistics of belt position maintenance degree δ, K4 is the ratio of the number of qualified belt maintenance groups used as reference.

[0057] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) When the current belt position deviates, the present invention calculates the belt position maintenance degree by combining historical belt maintenance data, and performs belt position maintenance confirmation, thereby solving the current problem of no further analysis of the maintenance status after historical position deviation maintenance, ensuring the targeted belt maintenance, ensuring the timeliness of potential problem discovery, and ensuring the operating stability of the coal mine conveyor.

[0058] (2) The present invention ensures the pertinence of the environmental analysis of the coal mine conveyor belt by analyzing the temporal regularity of temperature, sound loudness and vibration frequency, thereby achieving timely discovery of potential belt failure trends, facilitating predictive maintenance and improving the reliability of coal mine conveyor belt maintenance.

[0059] (3) The present invention sets position weights and combines the attachment growth rate and coal mine attachment ratio to analyze the coal mine attachment of the target belt, thereby breaking the current deficiency of not conducting detailed analysis of the coal mine attachment position, accurately evaluating the impact of the coal mine attachment position on the belt, and then timely discovering local problems of coal mine attachment, while reducing the maintenance complexity of subsequent coal mine attachment maintenance. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0061] Figure 1 It is a schematic diagram of the connection of each module of the system of the present invention. DETAILED DESCRIPTION

[0062] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only 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 ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0063] See also Figure 1 As shown, the present invention provides an intelligent maintenance system for coal mine conveyor belts, the system comprising: a belt information import module, a belt operation monitoring module, a belt operation analysis module, a belt maintenance judgment module, a belt maintenance confirmation module, a database and a belt maintenance execution terminal.

[0064] In the above, the belt operation analysis module is respectively connected to the belt information import module, the belt operation monitoring module and the belt maintenance judgment module, and the belt maintenance confirmation module is also respectively connected to the belt maintenance judgment module, the belt operation monitoring module, the database and the belt maintenance execution terminal.

[0065] The belt information importing module is used to record the coal mine conveyor belt to be repaired as the target belt, and import the reference operation status information and operation mark information of the target belt.

[0066] The belt operation monitoring module is used to monitor the current cumulative monitoring time of the target belt, and monitor the operation status information and monitoring video of the target belt in the current monitoring time period. The operation status information includes the temperature, sound loudness and vibration frequency of the target belt in each monitoring time period.

[0067] It should be supplemented that the temperature, sound loudness and vibration frequency in each monitoring time period are respectively monitored and obtained through corresponding sensors.

[0068] The belt operation analysis module is used to analyze the belt operation status according to the operation status information and monitoring video of the target belt in the current monitoring time period.

[0069] Exemplarily, the belt running status analysis includes: dividing the monitoring video of the target belt in the current monitoring time period into frames to obtain each video frame, and recording the monitoring time point of each video frame, sorting the video frames in chronological order according to the monitoring time, taking the video frame with the last sorting position as the current video frame, and extracting the current image of the target belt from the current video frame.

[0070] The reference image of the target belt is extracted from the reference running state information of the target belt, and the reference image of the target belt is overlapped and compared with the current image to obtain the overlapped image area of ​​the target belt, which is recorded as S1, and the area of ​​the target belt is recorded as S2.

[0071] Compare S1 with S2, and use the ratio as the position compliance of the target belt, denoted as

[0072] Extract the reference temperature, reference vibration frequency and reference sound loudness of the target belt at each monitoring time from the benchmark operating status information of the target belt, and then calculate the transportation environment compliance of the target belt

[0073] Furthermore, the statistically calculating the transport environment compliance of the target belt includes: calculating the transport temperature compliance φ1 of the target belt according to the temperature in each monitoring time period.

[0074] Furthermore, the statistical target belt's transport temperature compliance includes: extracting the maximum temperature from the temperatures of each monitoring time period, recorded as C, constructing a temperature change curve with the monitoring time period as the horizontal coordinate and the temperature as the vertical coordinate, extracting a reference temperature change curve from the benchmark operating status information of the target belt, overlapping and comparing it with the temperature change curve, obtaining the length of the temperature overlap curve, recorded as L3, and recording the length of the temperature change curve as L4.

[0075] Statistical target belt transport temperature compliance φ1, K2 and C′ are the length ratio and temperature of the temperature coincidence curve set as the reference, respectively.

[0076] It should be added that, under normal circumstances, when the length of the temperature overlap curve reaches seventy percent of the length of the temperature change curve, it indicates that the target belt transportation temperature meets the requirements. Therefore, K2 can be specifically taken as 0.7. The C′ is extracted from the coal mine conveyor belt maintenance specification table.

[0077] The maximum vibration frequency is selected from the vibration frequencies in each monitoring time period and is recorded as f.

[0078] A vibration frequency variation curve is constructed with the monitoring time period as the horizontal axis and the vibration frequency as the vertical axis. The reference vibration frequency is extracted from the benchmark operating state information of the target belt, and a vibration frequency reference line is constructed in the vibration frequency variation curve.

[0079] The length of the curve located above the vibration frequency reference curve is located from the vibration frequency variation curve and is recorded as L1, and the length of the vibration frequency variation curve is recorded as L2.

[0080] Statistical target belt transport vibration compliance φ2, K1 and f' are the deviation vibration frequency ratio and vibration frequency of the setting reference respectively.

[0081] It should be added that, under normal circumstances, when the length of the curve above the vibration frequency reference curve reaches thirty percent of the length of the vibration frequency change curve, it indicates that the vibration frequency is abnormal at this time. Therefore, K1 can be specifically taken as 0.3, and the f′ is extracted from the coal mine conveyor belt maintenance specification table.

[0082] The target belt's transport sound loudness compliance is obtained by using the same statistical method as φ2, and is recorded as φ3.

[0083] Statistical target belt transportation environment compliance p1, p2 and p3 are the weights of the set transportation temperature compliance, transportation vibration compliance and transportation sound loudness compliance respectively, p1>p2>p3, p1+p2+p3=1.

[0084] It should be added that p1>p2>p3 is set because running the belt at high temperature will accelerate material aging, reduce the strength and toughness of the belt, and increase the wear rate of the belt. Therefore, temperature abnormality is a direct indication of equipment failure. Excessive vibration frequency of the belt during operation will cause fatigue damage to the belt, accelerate belt wear, and may even cause the belt to break. The loudness of the sound is usually related to the operating state of the belt. The loudness of the sound indicates abnormal conditions in the belt operation, such as material friction or component wear, but usually does not directly cause belt damage. For the convenience of analysis, p1 can be specifically taken as 0.5, p2 can be specifically taken as 0.3, and p3 can be specifically taken as 0.2.

[0085] Extract the reference attachment area of ​​the target belt from the benchmark running status information of the target belt, and then calculate the coal mine attachment degree of the target belt and will and As the result of belt running status analysis.

[0086] Furthermore, the statistical coal mine attachment degree of the target belt includes: extracting the area of ​​each coal mine attachment point from the current video frame, summing them up to obtain the total area of ​​the coal mine attachment point of the current video frame, and comparing it with the surface area of ​​the target belt to obtain the coal mine attachment ratio of the current video frame as the coal mine attachment ratio under the current cumulative monitoring time, recorded as K3.

[0087] The coal mine attachment ratio at each monitoring time was obtained by using the statistical method of K3.

[0088] The reference attachment ratio of coal mines at each monitoring time is extracted from the database, and then the reference attachment ratio of coal mines at the current cumulative monitoring time is extracted, which is recorded as K3′.

[0089] The position of each coal dust attachment interference point is extracted from the running mark information of the target belt, and the position interference weight is set accordingly and recorded as α.

[0090] Furthermore, the setting of the position interference weight includes: extracting the position and number of each coal dust attachment point from the current image of the target belt.

[0091] The positions of each coal dust attachment point and each coal dust attachment interference point are introduced into the coal dust attachment position judgment model to obtain each primary interference point and each secondary interference point.

[0092] It should be added that the specific judgment process of the coal dust attachment position judgment model is as follows: the positions of each coal dust attachment point are overlapped and compared with the positions of each coal dust attachment interference point. If the position of a coal dust attachment point is consistent with the positions of each coal dust attachment interference point, the position of the coal dust attachment point is recorded as a first-level interference point.

[0093] If the position of a coal dust attachment point is inconsistent with the positions of all coal dust attachment interference points, extract the distance between the coal dust attachment point and the positions of all coal dust attachment interference points, and select the shortest distance as the interference distance of the coal dust attachment point; when the interference distance of the coal dust attachment point is smaller than the interference distance of the set reference coal dust attachment point, the position of the coal dust attachment point is recorded as a secondary interference point.

[0094] If the number of primary interference locations is equal to the number of coal dust attachment locations, the location interference weight is recorded as 1.

[0095] If the number of primary interference points is less than the number of coal dust attachment points, compare the number of primary interference points with the number of coal dust attachment points, and take the ratio as the ratio of the number of primary interference points, recorded as K1′. Use the same statistical method as K1′ to obtain the ratio of the number of secondary interference points, recorded as K2′.

[0096] Statistical location interference weight ε, K1″ and K2″ are respectively the set reference ratio of the number of primary interference points and the number of secondary interference points, r1 and r2 are respectively the weights of the set ratio of the number of primary interference points and the number of secondary interference points r1>r2, r1+r2=1.

[0097] It should be added that K1″ and K2″ are both extracted from the technical specification table of coal mine conveyor belt maintenance. The weight of the interference point number ratio is set according to the degree of interference of the location of the interference point on the target belt operation. For the convenience of analysis, r1 can be specifically taken as 0.6, and r2 can be specifically taken as 0.4.

[0098] If the number of primary interference locations and the number of secondary interference locations are both 0, the position interference weight is recorded as 0, and then the position interference weight α is obtained, and the value of α is 1, ε or 0.

[0099] The embodiment of the present invention sets position weights and combines the attachment growth rate and the coal mine attachment ratio to analyze the coal mine attachment of the target belt, thereby breaking the current deficiency of no detailed analysis of the coal mine attachment position, accurately evaluating the impact of the coal mine attachment position on the belt, and then timely discovering local problems of coal mine attachment, while reducing the maintenance complexity of subsequent coal mine attachment maintenance.

[0100] With the monitoring time as the horizontal axis and the coal mine attachment ratio as the vertical axis, a coal mine attachment growth change curve is constructed, and the slope of the change curve is extracted as the attachment growth rate, which is recorded as β.

[0101] The reference adhesion growth rate is extracted from the benchmark operating state information of the target belt and is recorded as β′.

[0102] Statistical coal mine adhesion of target belt

[0103] The belt maintenance judgment module is used to judge the belt maintenance demand based on the belt running status analysis result.

[0104] Exemplarily, the determination of belt maintenance needs includes: if and If there is a degree of compliance that is less than the corresponding set reference, the need for belt maintenance is taken as the judgment result.

[0105] like and If the values ​​are greater than or equal to the corresponding set reference compliance, it will be judged that no belt maintenance is required.

[0106] The belt maintenance confirmation module is used to confirm each required maintenance item and the maintenance information of each required maintenance item when the judgment result is that the belt maintenance is required.

[0107] Exemplarily, the confirmation of each required maintenance item includes: if If the belt position is not within the set reference target belt position compliance range, the belt position will be considered as a maintenance item.

[0108] like If the transportation environment is not within the set reference compliance range, the transportation environment will be taken as a maintenance item.

[0109] like If it is not within the set reference coal mine attachment range, the coal mine attachment will be taken as a maintenance item.

[0110] Exemplarily, the confirmation of the maintenance information of each maintenance item requires includes: when the maintenance item requires is the belt position, extracting the historical belt position maintenance times and the time points of each historical belt position maintenance from the historical maintenance log of the target belt, and then confirming the belt position maintenance maintenance degree δ.

[0111] Furthermore, the confirmation of the belt position maintenance maintenance degree includes: according to the time points of each historical belt position maintenance and the current time point, obtaining the interval between the current time point and the last maintenance in history as the current maintenance interval, recorded as T.

[0112] The time points of each historical belt position maintenance are combined in pairs to obtain each belt maintenance group, and then the interval duration of each historical belt position maintenance in each belt maintenance group is obtained as the maintenance interval duration of each belt maintenance group, and it is compared with the set reference maintenance interval duration.

[0113] If the maintenance interval of a belt maintenance group is longer than the set reference maintenance interval, the belt maintenance group is recorded as a qualified belt maintenance group, the number of qualified belt maintenance groups is counted and recorded as D1, and the number of belt maintenance groups is recorded as D2.

[0114] The maintenance interval duration of each belt maintenance group is averaged and the calculated result is used as the maintenance interval duration of the reference belt position, denoted as T′.

[0115] Statistics of belt position maintenance degree δ, K4 is the ratio of the number of qualified belt maintenance groups used as reference.

[0116] It should be added that, under normal circumstances, when the number of qualified belt maintenance groups reaches 80% of the number of belt maintenance groups, it indicates that the historical belt position maintenance is qualified. Therefore, K4 can be specifically taken as 0.8.

[0117] The embodiment of the present invention performs belt position maintenance from two aspects: the current belt position and the historical belt position maintenance data, thereby solving the current deficiency of not further analyzing the maintenance status after the historical position deviation maintenance, ensuring the targeted belt maintenance, ensuring the timeliness of potential problem discovery, and ensuring the operating stability of the coal mine conveyor.

[0118] If δ is greater than or equal to the set reference belt position maintenance maintenance degree, the belt position restoration is used as the maintenance information when the required maintenance item is the belt position. Otherwise, the associated trigger cause items of the belt position deviation are extracted from the database, and the associated trigger cause items are used as reference maintenance items, and the reference maintenance items are used as the maintenance information when the required maintenance item is the belt position.

[0119] When the maintenance item required is the transportation environment, the statistical environment deviation degree ψ is used. To set the reference transportation environment compliance.

[0120] It should be added that the set temperature, set vibration frequency and set sound loudness of each monitoring time period are extracted from the coal mine conveyor belt maintenance technical specification table. The statistical method is similar to the statistical method

[0121] Match and compare ψ with the environmental deviation interval corresponding to each transport environment maintenance level to obtain the matched transport environment level, and use the matched transport environment maintenance level as the maintenance information when the required maintenance item is the transport environment.

[0122] When the maintenance item required is coal mine attachment, the coal mine attachment excess is calculated in the same way as ψ, which is recorded as ψ′.

[0123] Match and compare ψ′ with the coal mine attachment excess interval corresponding to each coal mine attachment maintenance level to obtain the matched coal mine attachment maintenance level, and use the matched coal mine attachment maintenance level as the maintenance information when the required maintenance item is coal mine attachment.

[0124] The embodiment of the present invention ensures the pertinence of the coal mine conveyor belt environmental analysis by analyzing the temporal regularity of temperature, sound loudness and vibration frequency, thereby achieving timely discovery of potential belt failure trends, facilitating predictive maintenance and improving the reliability of coal mine conveyor belt maintenance.

[0125] The database is used to store the historical maintenance log of the target belt, store the reference attachment ratio of the coal mine under each monitoring time, and store each associated triggering factor item of the belt position deviation.

[0126] The belt maintenance execution terminal is used to execute corresponding maintenance according to each required maintenance item and the maintenance information of each required maintenance item.

[0127] The above contents are merely examples and explanations of the concept of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, they shall all fall within the protection scope of the present invention.

Claims

1. An intelligent maintenance system for coal mine conveyor belts, characterized in that: The system includes: The belt information import module is used to record the coal mine conveyor belt to be repaired as the target belt, and import the benchmark operation status information and operation mark information of the target belt; The belt operation monitoring module is used to monitor the current cumulative transportation time of the target belt, and monitor the operation status information and monitoring video of the target belt in the current monitoring time period. The operation status information includes the temperature, sound loudness and vibration frequency of the target belt in each monitoring time period; The belt operation analysis module is used to analyze the belt operation status according to the operation status information and monitoring video of the target belt in the current monitoring time period; The belt maintenance judgment module is used to judge the need for belt maintenance based on the analysis results of the belt operation status; The belt maintenance confirmation module is used to confirm each required maintenance item and the maintenance information of each required maintenance item when the judgment result is that the belt maintenance is required; A database for storing the historical maintenance log of the target belt, storing the reference attachment ratio of the coal mine at each monitoring time, and storing the associated triggering factors of the belt position deviation; The belt maintenance execution terminal is used to execute corresponding maintenance according to each required maintenance item and the maintenance information of each required maintenance item.

2. The intelligent maintenance system for coal mine conveyor belt according to claim 1 is characterized in that: The belt running status analysis includes: Divide the monitoring video of the target belt in the current monitoring time period into frames to obtain each video frame, and record the monitoring time point of each video frame, sort the video frames in chronological order according to the monitoring time, take the video frame with the last sorting position as the current video frame, and extract the current image of the target belt from the current video frame; Extracting a reference image of the target belt from the reference running state information of the target belt, and overlapping and comparing the reference image of the target belt with the current image to obtain an overlapping image area of ​​the target belt, which is recorded as S1, and the area of ​​the target belt is recorded as S2; Compare S1 with S2, and use the ratio as the position compliance of the target belt, denoted as Extract the reference temperature, reference vibration frequency and reference sound loudness of the target belt at each monitoring time from the benchmark operating status information of the target belt, and then calculate the transportation environment compliance of the target belt Extract the reference attachment area of ​​the target belt from the benchmark running status information of the target belt, and then calculate the coal mine attachment degree of the target belt and will and As the result of belt running status analysis.

3. The intelligent maintenance system for coal mine conveyor belt according to claim 2 is characterized in that: The statistical target belt's transport environment compliance includes: According to the temperature of each monitoring period, the target belt's transportation temperature compliance is calculated and recorded as φ1; The maximum vibration frequency is selected from the vibration frequencies of each monitoring time period and is recorded as f; A vibration frequency variation curve is constructed with the monitoring time period as the horizontal coordinate and the vibration frequency as the vertical coordinate, a reference vibration frequency is extracted from the benchmark operating state information of the target belt, and a vibration frequency reference line is constructed in the vibration frequency variation curve; Locate the length of the curve above the vibration frequency reference curve from the vibration frequency change curve, record it as L1, and record the length of the vibration frequency change curve as L2; Statistical target belt transport vibration compliance φ2, K1 and f′ are the deviation vibration frequency ratio and vibration frequency of the set reference respectively; According to the statistical method of φ2, the target belt's transport sound loudness compliance is obtained, which is recorded as φ3; Statistical target belt transportation environment compliance p1, p2 and p3 are the weights of the set transportation temperature compliance, transportation vibration compliance and transportation sound loudness compliance respectively, p1>p2>p3, p1+p2+p3=1.

4. The intelligent maintenance system for coal mine conveyor belt according to claim 3 is characterized in that: The statistical target belt transportation temperature compliance includes: The maximum temperature is extracted from the temperature of each monitoring time period, recorded as C, and the temperature change curve is constructed with the monitoring time period as the horizontal axis and the temperature as the vertical axis. The reference temperature change curve is extracted from the benchmark operating state information of the target belt, and the reference temperature change curve is overlapped and compared with the temperature change curve to obtain the length of the temperature overlap curve, recorded as L3, and the length of the temperature change curve is recorded as L4; Statistical target belt transport temperature compliance φ1, K2 and C′ are the length ratio and temperature of the temperature coincidence curve set as the reference, respectively.

5. The intelligent maintenance system for coal mine conveyor belt according to claim 2 is characterized in that: The coal mine adhesion of the statistical target belt includes: The area of ​​each coal mine attachment point is extracted from the current video frame, and the sum is calculated to obtain the total area of ​​the coal mine attachment point in the current video frame, and the total area is compared with the surface area of ​​the target belt to obtain the coal mine attachment ratio in the current video frame as the coal mine attachment ratio under the current cumulative monitoring time, which is recorded as K3; According to the statistical method of K3, the coal mine attachment ratio under each monitoring time is obtained; Extract the reference attachment ratio of coal mines at each monitoring time from the database, and then extract the reference attachment ratio of coal mines at the current cumulative monitoring time, which is recorded as K3′; Extract the position of each coal dust attachment interference point from the running mark information of the target belt, and set the position interference weight accordingly, which is recorded as α; With the monitoring time as the horizontal axis and the coal mine attachment ratio as the vertical axis, a coal mine attachment growth curve is constructed, and the slope of the change curve is extracted as the attachment growth rate, which is recorded as β; Extract the reference adhesion growth rate from the benchmark operating status information of the target belt, denoted as β′; Statistical coal mine adhesion of target belt 6. The intelligent maintenance system for coal mine conveyor belt according to claim 5, characterized in that: The step of setting the position interference weight comprises: Extracting the positions and number of coal dust attachment locations from the current image of the target belt; The positions of each coal dust attachment point and each coal dust attachment interference point are introduced into the coal dust attachment position judgment model to obtain each primary interference point and each secondary interference point; If the number of primary interference locations is equal to the number of coal dust attachment locations, the location interference weight is recorded as 1; If the number of primary interference points is less than the number of coal dust attachment points, the number of primary interference points is compared with the number of coal dust attachment points, and the ratio is taken as the primary interference number ratio, recorded as K1′. The secondary interference number ratio is obtained by the same statistical method as K1′, recorded as K2′. Statistical location interference weight ε, K″1 and K″2 are respectively the ratio of the number of primary interference points and the ratio of the number of secondary interference points of the set reference, r1 and r2 are respectively the weights of the ratio of the number of primary interference points and the ratio of the number of secondary interference points of the set reference, r1>r2, r1+r2=1; If the number of primary interference locations and the number of secondary interference locations are both 0, the position interference weight is recorded as 0, and then the position interference weight α is obtained, and the value of α is 1, ε or 0.

7. The intelligent maintenance system for coal mine conveyor belt according to claim 2, characterized in that: The belt maintenance demand determination includes: like and If there is a compliance degree less than the corresponding set reference, the need for belt maintenance is taken as the judgment result; like and If the values ​​are greater than or equal to the corresponding set reference compliance, it will be judged that no belt maintenance is required.

8. The intelligent maintenance system for coal mine conveyor belt according to claim 2, characterized in that: The confirmation of each required maintenance item includes: like If the belt position is not within the set reference target belt position compliance range, the belt position will be considered as a maintenance item; like If it is not within the set reference transportation environment compliance range, the transportation environment will be taken as a maintenance item; like If it is not within the set reference coal mine attachment range, the coal mine attachment will be taken as a maintenance item.

9. The intelligent maintenance system for coal mine conveyor belt according to claim 5, characterized in that: The confirmation of the maintenance information of each maintenance item requires includes: When the required maintenance item is the belt position, the historical belt position maintenance times and the time points of each historical belt position maintenance are extracted from the historical maintenance log of the target belt, and then the belt position maintenance maintenance degree δ is determined; If δ is greater than or equal to the set reference belt position maintenance maintenance degree, the belt position restoration is used as the maintenance information when the required maintenance item is the belt position. Otherwise, the associated triggering factors of the belt position deviation are extracted from the database, and the associated triggering factors are used as the reference maintenance items, and the reference maintenance items are used as the maintenance information when the required maintenance item is the belt position. When the maintenance item required is the transportation environment, the statistical environment deviation degree ψ is used. To set the reference transportation environment compliance; Match and compare ψ with the environmental deviation interval corresponding to each transport environment maintenance level to obtain the matching transport environment level, and use the matching transport environment maintenance level as the maintenance information when the required maintenance item is the transport environment; When the maintenance item required is coal mine attachment, the coal mine attachment excess is calculated in the same way as ψ, which is recorded as ψ′; Match and compare ψ′ with the coal mine attachment excess interval corresponding to each coal mine attachment maintenance level to obtain the matched coal mine attachment maintenance level, and use the matched coal mine attachment maintenance level as the maintenance information when the required maintenance item is coal mine attachment.

10. The intelligent maintenance system for coal mine conveyor belt according to claim 9, characterized in that: The confirmation of the belt position maintenance degree includes: According to the time points of each belt position maintenance in history and the current time point, the interval between the current time point and the last maintenance in history is obtained as the current maintenance interval, recorded as T; The time points of each historical belt position maintenance are combined in pairs to obtain each belt maintenance group, and then the interval length of each historical belt position maintenance in each belt maintenance group is obtained as the maintenance interval length of each belt maintenance group, and it is compared with the set reference maintenance interval length; If the maintenance interval of a belt maintenance group is longer than the set reference maintenance interval, the belt maintenance group is recorded as a qualified belt maintenance group, the number of qualified belt maintenance groups is counted and recorded as D1, and the number of belt maintenance groups is recorded as D2; The maintenance intervals of each belt maintenance group are averaged and the calculated result is used as the maintenance interval of the reference belt position, recorded as T′; Statistics of belt position maintenance degree δ, K4 is the ratio of the number of qualified belt maintenance groups used as reference.

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