Intelligent shape recognition and accurate reset control system for large-scale skip of vertical shaft

Abstract

The present application relates to the technical field of skip identification control, and more particularly to a vertical shaft large skip intelligent form identification and accurate reset control system. The vertical shaft large skip intelligent form identification and accurate reset control system comprises a fatigue area acquisition module, a fatigue area acquisition submodule, an area division module, an average height change acquisition module, a loading area adjustment module, a cargo height adjustment submodule, a loading area adjustment submodule, an area monitoring adjustment module and a frequency adjustment module. The present application adjusts the loading area by combining the real-time cargo height and historical height change data of each area to reduce damage and prolong the service life of the equipment. The tolerance frequency of each area is adjusted by a frequency adjustment formula to ensure that the equipment remains stable under different operating conditions, making the reset control of the skip more accurate.

Description

Technical Field

[0001] The present invention relates to the technical field of skip identification and control, and in particular to an intelligent form identification and precise resetting control system for a large-scale skip in a vertical shaft. Background Art

[0002] As the core equipment in the mine hoisting system, the vertical shaft skip is responsible for the efficient transportation of materials such as ore and coal. During long-term use, the internal structure of the skip will be affected by load impact and fatigue damage, resulting in a decrease in local structural strength and even deformation safety hazards. Especially during the skip hoisting process, the deformation of the skip becomes more complex and challenging to reset. Currently, the fatigue damage of mine skips mainly relies on regular maintenance and manual monitoring, but this method has problems such as long monitoring cycles, poor real-time performance, and high maintenance costs. In addition, the cargo loading method of the skip usually adopts traditional uniform loading or empirical loading, which does not consider the dynamic changes of the fatigue zone, which can easily aggravate fatigue damage and shorten the equipment life. Summary of the Invention

[0003] In order to overcome the defects of cargo loading damage and reset control rigidity, the present invention provides an intelligent shape recognition and precise reset control system for large-scale vertical shaft skips.

[0004] The technical implementation scheme of the present invention is: intelligent shape recognition and precise resetting control system for large vertical shaft skips, including:

[0005] A fatigue area acquisition module is used to obtain the fatigue area of ​​the skip using the SN curve formula and the Miner criterion according to the historical usage data of the skip;

[0006] A fatigue area acquisition submodule, wherein the fatigue area acquisition submodule obtains the cumulative fatigue damage degree of the bucket according to the fatigue life of the bucket using the Miner criterion, and obtains the fatigue area of ​​the bucket according to the cumulative fatigue damage degree;

[0007] A region division module, wherein the region division module is used to divide the region in the bucket;

[0008] an average height change acquisition module, the average height change acquisition module being used to acquire historical cargo height change data, and to acquire average height change data based on the historical cargo height change data;

[0009] A loading area adjustment module, the loading area adjustment module is used to obtain the real-time cargo height of each area in the skip when the cargo is loaded, and adjust the cargo loading area according to the fatigue area of ​​the skip;

[0010] A cargo height adjustment submodule, which adjusts the cargo height of each area according to the real-time cargo height of each area and the average height change data of each area;

[0011] A loading area adjustment submodule, which adjusts the cargo height of each area according to the real-time cargo height of each area and the average height change data of each area;

[0012] A regional monitoring and adjustment module, wherein the regional monitoring and adjustment module is used to obtain monitoring data of the skip during operation and adjust the tolerance times of each region according to the monitoring data;

[0013] A times adjustment module is used to adjust the number of times that each area of ​​the skip exceeds a second preset range during operation using a frequency adjustment formula according to the monitoring data.

[0014] Preferably, the fatigue area acquisition module is used to obtain the fatigue area of ​​the bucket according to the historical usage data of the bucket using the SN curve formula and the Miner criterion, including: obtaining the historical usage data of the bucket, the historical usage data of the bucket including the actually measured stress amplitude, the fatigue strength coefficient and fatigue index of the bucket material, obtaining the fatigue life of the target area of ​​the bucket according to the historical usage data of the bucket using the SN curve formula, obtaining the cumulative fatigue damage degree of the bucket according to the fatigue life of the bucket using the Miner criterion, and obtaining the fatigue area of ​​the bucket according to the cumulative fatigue damage degree, wherein the SN curve formula is:

[0015] ;

[0016] Where, is the fatigue life of the target area of ​​the skip; is the actual measured stress amplitude; is the fatigue strength coefficient of the skip material; is the fatigue index of the skip material.

[0017] Preferably, the fatigue area acquisition submodule obtains the cumulative fatigue damage of the bucket using the Miner criterion according to the fatigue life of the bucket, and obtains the fatigue area of ​​the bucket according to the cumulative fatigue damage, including: obtaining the number of load cycles actually experienced by the bucket target area and the corresponding fatigue life under different stress states, obtaining the cumulative fatigue damage of the bucket target area using the Miner criterion, when the cumulative fatigue damage is greater than a first preset threshold and less than 1, the bucket target area is regarded as a fatigue area; when the cumulative fatigue damage is greater than or equal to 1, the bucket target area is regarded as a damaged area, and the damaged area is identified and repaired using a deep learning model; wherein the Miner criterion is:

[0018] ;

[0019] wherein, is the cumulative fatigue damage degree of the target area of the skip; is the number of cycles under the stress level; is the fatigue life under the stress level; is the load stress level.

[0020] Preferably, the area division module is configured to divide the area in the skip, including: dividing the area in the skip to obtain a first area, a second area and a third area, wherein the first area is a left area in the skip; the second area is a middle area in the skip; and the third area is a right area in the skip.

[0021] Preferably, the average height variation obtaining module is configured to obtain historical cargo height variation data, and obtain average height variation data based on the historical cargo height variation data, including: obtaining historical cargo height variation data of each area in the skip when the skip runs on the guide rail, and averaging the historical cargo height variation data of each area in a preset time period to obtain average height variation data of each area.

[0022] Preferably, the loading area adjusting module is configured to obtain real-time cargo heights of each area in the skip when the cargo is loaded, and adjust the cargo loading area according to the fatigue area of the skip, including: when the fatigue area of the skip is in the first area, adjusting the cargo loading area to the third area, obtaining real-time cargo heights of each area, and adjusting the cargo heights of each area according to the real-time cargo heights of each area and the average height variation data of each area; when the fatigue area of the skip is in the third area, adjusting the cargo loading area to the first area, obtaining real-time cargo heights of each area, and adjusting the cargo heights of each area according to the real-time cargo heights of each area and the average height variation data of each area; and when the fatigue area of the skip is in the first area and the third area at the same time or does not exist, adjusting the cargo loading area to the second area, obtaining real-time cargo heights of each area, and adjusting the cargo heights of each area according to the real-time cargo heights of each area and the average height variation data of each area.

[0023] Preferably, the cargo height adjustment submodule adjusts the cargo height of each area according to the real-time cargo height of each area and the average height change data of each area, including: using an initial adjustment formula according to the real-time cargo height of the first area and the third area and the average height change data of each area to obtain the adjusted initial cargo height of each area, and adjusting the cargo height of each area according to the initial cargo height of each area, wherein the initial adjustment formula is:

[0024] ;

[0025] Where, Initial cargo height adjusted for the target area; is the standard cargo height for the target area; is the average height change data of the target area; is the maximum cargo height in the target area; is the adjustment factor.

[0026] Preferably, the loading area adjustment submodule adjusts the cargo height of each area according to the real-time cargo height of each area and the average height change data of each area, including: when the fatigue area of ​​the skip is in the first area, adjusting the cargo loading area to the third area, and when the real-time cargo height of the third area reaches the maximum cargo height of the third area or the real-time cargo height of the first area is higher than the highest height of the fatigue area in the first area, adjusting the cargo loading area to other areas so that the cargo height of each area increases to the adjusted initial cargo height; when the fatigue area of ​​the skip is in the third area, adjusting the cargo loading area to the first area, and when the real-time cargo height of the first area reaches the maximum cargo height of the first area or the real-time cargo height of the third area is higher than the highest height of the fatigue area in the third area, adjusting the cargo loading area to other areas so that the cargo height of each area increases to the adjusted initial cargo height.

[0027] Preferably, the area monitoring adjustment module is used to obtain monitoring data of the skip during operation, and adjust the tolerance times of each area according to the monitoring data, including: obtaining monitoring data of the skip during operation, the monitoring data including the number of times the skip shakes beyond a first preset range during operation, the height of the cargo in the skip in each area, and the number of fatigue areas in each area of ​​the skip, and adjusting the tolerance times of each area of ​​the skip exceeding a second preset range during operation using a frequency adjustment formula according to the monitoring data.

[0028] Preferably, the number adjustment module uses a frequency adjustment formula according to the monitoring data to adjust the number of times each area of ​​the skip exceeds the second preset range during operation, including: wherein the frequency adjustment formula is:

[0029] ;

[0030] In the formula, is the tolerance number of the target region exceeding the second preset range during the operation of the bucket after adjustment; is the tolerance number of the target region exceeding the second preset range during the operation of the bucket; is the tolerance number of the target region exceeding the second preset range during the operation of the bucket; is the tolerance number of the target region exceeding the second preset range during the operation of the bucket; is the initial cargo height of the target region after adjustment; is the maximum cargo height of the target region; is the number of shaking of the target region exceeding the first preset range during the operation of the bucket; is the number of shaking of the target region exceeding the first preset range during the operation of the bucket; is the number of fatigue regions in the target region; is the number of fatigue regions in the target region; is the adjustment parameter.

[0031] Compared with the prior art, the present application has the following beneficial effects:

[0032] 1. The present application calculates the cumulative fatigue damage degree and dynamically identifies the fatigue region by using the S-N curve formula and the Miner criterion, combined with the historical use data of the bucket, to avoid irreversible damage caused by long-term stress accumulation and improve the reliability of the equipment;

[0033] 2. The present application dynamically adjusts the loading region by dividing the internal regions of the bucket and combining the real-time cargo height and historical height change data of each region, and when the fatigue degree of the target region is high, the system can automatically optimize the loading strategy to reduce damage and prolong the service life of the equipment;

[0034] 3. The present application dynamically adjusts the tolerance number of each region exceeding the second preset range based on the frequency adjustment formula by real-time acquisition of monitoring data, including the shaking number of the bucket, the cargo height of the cargo in each region in the bucket, and the number of fatigue regions in each region in the bucket, to ensure that the equipment remains stable under different operating conditions and reduces abnormal vibration or unbalanced load conditions. BRIEF DESCRIPTION OF DRAWINGS

[0035] Figure 1 is the system architecture diagram of the present application;

[0036] Figure 2 is the block diagram of the loading region adjustment module of the present application. DETAILED DESCRIPTION

[0037] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. 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 making creative efforts are within the scope of protection of the present invention.

[0038] Intelligent shape recognition and precise reset control system for large vertical shaft skips, such as Figure 1 and Figure 2 Shown, including:

[0039] The fatigue area acquisition module is used to obtain the fatigue area of ​​the skip using the SN curve formula and Miner criterion according to the historical usage data of the skip;

[0040] Obtain the historical usage data of the skip. The historical usage data of the skip includes the actually measured stress amplitude, fatigue strength coefficient and fatigue index of the skip material. The fatigue life of the target area of ​​the skip is obtained using the SN curve formula based on the historical usage data of the skip. The cumulative fatigue damage degree of the skip is obtained using the Miner criterion based on the fatigue life of the skip. The fatigue area of ​​the skip is obtained based on the cumulative fatigue damage degree. The SN curve formula is:

[0041] ;

[0042] Where, is the fatigue life of the target area of ​​the skip; is the actual measured stress amplitude; is the fatigue strength coefficient of the skip material; is the fatigue index of the skip material.

[0043] It should be noted that is the actual measured stress amplitude, and is the range of cyclic stress variation that the skip bears under different loading conditions; is the fatigue strength coefficient of the skip material, which is determined by the characteristics of the material itself and is usually obtained through experiments or material manuals; is the fatigue index of the skip material, which indicates the sensitivity of the material to fatigue damage. It is also provided by experiments or material databases. Through this calculation, the theoretical maximum number of cycles that each area of ​​the skip can withstand under different stress levels is determined.

[0044] The fatigue area acquisition submodule obtains the cumulative fatigue damage of the bucket using the Miner criterion according to the fatigue life of the bucket, and obtains the fatigue area of ​​the bucket according to the cumulative fatigue damage;

[0045] The actual number of load cycles experienced by the target area of ​​the bucket and the corresponding fatigue life under different stress states are obtained, and the cumulative fatigue damage degree of the target area of ​​the bucket is obtained using the Miner criterion. When the cumulative fatigue damage degree is greater than the first preset threshold and less than 1, the target area of ​​the bucket is regarded as a fatigue area; when the cumulative fatigue damage degree is greater than or equal to 1, the target area of ​​the bucket is regarded as a damaged area, and the deep learning model is used to identify and repair the damaged area. The Miner criterion is:

[0046] ;

[0047] Where, is the cumulative fatigue damage degree of the target area of ​​the skip; For the Number of cycles under graded stress; For the Fatigue life under level stress; is the load stress level.

[0048] It should be noted that, through sensor monitoring and operation data analysis, the number of load cycles actually experienced by the target area of ​​the skip under different stress levels and the fatigue life corresponding to different stresses are statistically analyzed. When the cumulative fatigue damage degree of the target area of ​​the skip is between the first preset threshold and 1, the target area is marked as a fatigue area, indicating that the area is in high fatigue damage and the load distribution needs to be optimized to extend its service life; when the cumulative fatigue damage degree of the target area of ​​the skip is greater than or equal to 1, the system marks the target area as a damaged area, and uses a deep learning model to intelligently identify the damaged area and generate a repair plan, which includes structural reinforcement, material replacement or operation mode adjustment.

[0049] The area division module is used to divide the area within the bucket;

[0050] The area in the bucket is divided into a first area, a second area and a third area, wherein the first area is the left area in the bucket; the second area is the middle area in the bucket; and the third area is the right area in the bucket.

[0051] It should be noted that the target area of ​​the skip is a part of the area planned in advance within the first area, the second area and the third area.

[0052] An average height change acquisition module is used to obtain historical cargo height change data and obtain average height change data based on the historical cargo height change data;

[0053] Obtain the historical cargo height change data of each area when the skip is running on the guide rail, take the average of the historical cargo height change data of each area within a preset time period based on the historical cargo height change data, and obtain the average height change data of each area.

[0054] It should be noted that, based on the historical cargo height change data, the historical cargo height change data of each area within the preset time period are averaged to obtain the average height change data of each area. The average height change data of each area is dynamically adjusted over time. The average value of all historical cargo height change data within the preset time period separated from the current time is taken to obtain the average height change data of each area. The historical cargo height change data is the data of changes in cargo height in the first area, second area and third area of ​​the skip due to the influence of the vibration and tilt of the skip guide rail when the cargo relies on the skip to rise from the bottom to the top.

[0055] The loading area adjustment module is used to obtain the real-time cargo height of each area in the bucket when loading cargo, and adjust the cargo loading area according to the fatigue area of ​​the bucket;

[0056] When the fatigue zone of the skip is in the first zone, the loading zone of the cargo is adjusted to the third zone, the real-time cargo height of each zone is obtained, and the cargo height of each zone is adjusted according to the real-time cargo height of each zone and the average height change data of each zone; when the fatigue zone of the skip is in the third zone, the loading zone of the cargo is adjusted to the first zone, the real-time cargo height of each zone is obtained, and the cargo height of each zone is adjusted according to the real-time cargo height of each zone and the average height change data of each zone; when the fatigue zone of the skip is in the first zone and the third zone at the same time or there is no fatigue zone of the skip, the loading zone of the cargo is adjusted to the second zone, the real-time cargo height of each zone is obtained, and the cargo height of each zone is adjusted according to the real-time cargo height of each zone and the average height change data of each zone.

[0057] It should be noted that during the cargo loading process, the system uses sensors or machine vision to detect the cargo height in each area of ​​the skip in real time and stores it in the data center. When the fatigue area of ​​the skip is in the first area, the loading area of ​​the cargo is adjusted to the third area, that is, the center of gravity of the load is shifted to the area with less force, so as to reduce the additional load in the fatigue area and prevent the cargo from continuously eroding the fatigue area, thereby increasing the damage to the fatigue area. Then, through the cargo height adjustment sub-module, the degree of skip deflection caused by the vibration and tilt of the skip guide rail is reduced; when the fatigue area of ​​the skip is in the third area, the loading area of ​​the cargo is adjusted to the first area; when the fatigue area of ​​the skip is in the first area and the third area at the same time or there is no fatigue area, the loading area of ​​the cargo is adjusted to the second area, that is, the central area of ​​the skip or other optimal force-bearing area, to improve the overall load balance and reduce the occurrence of stress concentration points.

[0058] The cargo height adjustment submodule adjusts the cargo height of each area according to the real-time cargo height of each area and the average height change data of each area;

[0059] The initial adjustment formula is used based on the real-time cargo height of the first and third areas and the average height change data of each area to obtain the adjusted initial cargo height of each area. The cargo height of each area is adjusted based on the initial cargo height of each area, where the initial adjustment formula is:

[0060] ;

[0061] Where, Initial cargo height adjusted for the target area; is the standard cargo height for the target area; is the average height change data of the target area; is the maximum cargo height in the target area; is the adjustment factor.

[0062] It should be noted that the initial cargo height of each area is adjusted according to the average height change data of each area to reduce the degree of bucket deflection caused by factors such as the vibration and tilt of the bucket guide rail. is the standard cargo height of the target area, i.e. the set value before adjustment; The average height change data of the target area reflects the height change trend of the area after the skip is lifted; It is the maximum cargo height in the target area, i.e. the safe loading limit value.

[0063] The loading area adjustment submodule adjusts the cargo height of each area according to the real-time cargo height of each area and the average height change data of each area;

[0064] When the fatigue area of ​​the skip is in the first area, the loading area of ​​the cargo is adjusted to the third area, and when the real-time cargo height in the third area reaches the maximum cargo height of the third area or the real-time cargo height in the first area is higher than the highest height of the fatigue area in the first area, the loading area of ​​the cargo is adjusted to other areas, so that the cargo height of each area is increased to the adjusted initial cargo height; when the fatigue area of ​​the skip is in the third area, the loading area of ​​the cargo is adjusted to the first area, and when the real-time cargo height in the first area reaches the maximum cargo height of the first area or the real-time cargo height in the third area is higher than the highest height of the fatigue area in the third area, the loading area of ​​the cargo is adjusted to other areas, so that the cargo height of each area is increased to the adjusted initial cargo height.

[0065] It should be noted that the real-time cargo height is the current cargo height of each area, which is data obtained by real-time monitoring through sensors or machine vision systems; when the real-time cargo height of the third area reaches the maximum cargo height of the third area or the real-time cargo height of the first area is higher than the highest height of the fatigue area in the first area, the system will stop loading cargo in the third area and transfer the loading area to other areas, such as the second area or other areas not affected by fatigue, so that the fatigue area in the first area will not be directly contacted when the cargo is loaded, thereby extending the overall use time of the bucket; similarly, when the real-time cargo height in the first area reaches the maximum cargo height of the first area or the real-time cargo height of the third area is higher than the highest height of the fatigue area in the third area, the system will stop loading cargo in the first area and adjust the loading area to other areas.

[0066] The regional monitoring and adjustment module is used to obtain the monitoring data of the bucket during operation and adjust the tolerance times of each area according to the monitoring data;

[0067] Obtain monitoring data of the skip during operation, the monitoring data including the number of times the skip shakes beyond a first preset range during operation, the height of cargo in each area of ​​the skip, and the number of fatigue areas in each area of ​​the skip. Adjust the tolerance number of times each area of ​​the skip exceeds a second preset range during operation based on the frequency adjustment formula using the monitoring data.

[0068] It should be noted that the number of shakes exceeding the first preset range is the number of times the bucket shakes during the operation of the bucket. When the amplitude of the shake exceeds the predetermined first preset range, it reflects that acceptable abnormal vibrations have occurred in the operation of the bucket; the number of fatigue areas in each area of ​​the bucket, for example, there are three fatigue areas in the first area. The increase in fatigue areas means that the tolerance number of times the area exceeds the second preset range needs to be reduced, and the area should be better monitored to predict abnormal phenomena in the area in advance, and better reset control should be performed based on the tolerance number of times the area exceeds the second preset range.

[0069] The number adjustment module uses the frequency adjustment formula based on the monitoring data to adjust the number of times that each area of ​​the skip exceeds the second preset range during operation.

[0070] The frequency adjustment formula is:

[0071] ;

[0072] Where, After adjustment, the skip bucket is in operation. The number of times the area exceeds the tolerance of the second preset range; The first The number of times the area exceeds the tolerance of the second preset range; Initial cargo height adjusted for the target area; is the maximum cargo height in the target area; The first The number of times the area shakes beyond the first preset range; For Jidoudi the number of fatigue zones within the area; To adjust the parameters.

[0073] It should be noted that the more fatigue areas there are, the more serious the depression or bulge in the skip area will be. When it exceeds the second preset range, it is more likely to collide with the surrounding walls, causing increased damage to the skip. Therefore, the tolerance times are adjusted by area to more flexibly adapt to work requirements in different environments and improve the adaptability and long-term stability of the equipment.

[0074] While the present invention has been described with reference to exemplary embodiments, it is to be understood that the invention is not limited to the disclosed exemplary embodiments. The scope of the following claims is to be accorded the broadest interpretation so as to encompass all modifications and equivalent structures and functions.

Claims

1. Intelligent shape recognition and precise reset control system for large vertical shaft skips, characterized by: include: A fatigue area acquisition module is used to obtain the fatigue area of ​​the skip using the SN curve formula and the Miner criterion according to the historical usage data of the skip; A fatigue area acquisition submodule, wherein the fatigue area acquisition submodule obtains the cumulative fatigue damage degree of the bucket according to the fatigue life of the bucket using the Miner criterion, and obtains the fatigue area of ​​the bucket according to the cumulative fatigue damage degree; A region division module, wherein the region division module is used to divide the region in the bucket; an average height change acquisition module, the average height change acquisition module being used to acquire historical cargo height change data, and to acquire average height change data based on the historical cargo height change data; A loading area adjustment module, the loading area adjustment module is used to obtain the real-time cargo height of each area in the skip when the cargo is loaded, and adjust the cargo loading area according to the fatigue area of ​​the skip; A cargo height adjustment submodule, which adjusts the cargo height of each area according to the real-time cargo height of each area and the average height change data of each area; A loading area adjustment submodule, which adjusts the cargo height of each area according to the real-time cargo height of each area and the average height change data of each area; A regional monitoring and adjustment module, wherein the regional monitoring and adjustment module is used to obtain monitoring data of the skip during operation and adjust the tolerance times of each region according to the monitoring data; A times adjustment module is used to adjust the number of times that each area of ​​the skip exceeds a second preset range during operation using a frequency adjustment formula according to the monitoring data.

2. The intelligent shape recognition and precise reset control system for large vertical shaft skips according to claim 1 is characterized in that: The fatigue area acquisition module is used to obtain the fatigue area of ​​the bucket according to the historical usage data of the bucket using the SN curve formula and the Miner criterion, including: obtaining the historical usage data of the bucket, the historical usage data of the bucket including the actually measured stress amplitude, the fatigue strength coefficient and fatigue index of the bucket material; obtaining the fatigue life of the target area of ​​the bucket according to the historical usage data of the bucket using the SN curve formula; obtaining the cumulative fatigue damage degree of the bucket according to the fatigue life of the bucket using the Miner criterion; and obtaining the fatigue area of ​​the bucket according to the cumulative fatigue damage degree, wherein the SN curve formula is: ； Where, is the fatigue life of the target area of ​​the skip; is the actual measured stress amplitude; is the fatigue strength coefficient of the skip material; is the fatigue index of the skip material.

3. The intelligent shape recognition and precise reset control system for large vertical shaft skips according to claim 2 is characterized in that: The fatigue area acquisition submodule obtains the cumulative fatigue damage of the bucket using the Miner criterion according to the fatigue life of the bucket, and obtains the fatigue area of ​​the bucket according to the cumulative fatigue damage, including: obtaining the number of load cycles actually experienced by the bucket target area and the corresponding fatigue life under different stress states, obtaining the cumulative fatigue damage of the bucket target area using the Miner criterion, when the cumulative fatigue damage is greater than a first preset threshold and less than 1, the bucket target area is regarded as a fatigue area; when the cumulative fatigue damage is greater than or equal to 1, the bucket target area is regarded as a damaged area, and the damaged area is identified and repaired using a deep learning model; wherein the Miner criterion is: ； Where, is the cumulative fatigue damage degree of the target area of ​​the skip; For the Number of cycles under graded stress; For the Fatigue life under level stress; is the load stress level.

4. The intelligent shape recognition and precise resetting control system for large vertical shaft skips according to claim 1 is characterized in that: The area division module is used to divide the area within the bucket, including: dividing the area within the bucket to obtain a first area, a second area and a third area, wherein the first area is the left area within the bucket; the second area is the middle area within the bucket; and the third area is the right area within the bucket.

5. The intelligent shape recognition and precise resetting control system for large vertical shaft skips according to claim 4 is characterized in that: The average height change acquisition module is used to obtain historical cargo height change data, and obtain average height change data based on the historical cargo height change data, including: obtaining historical cargo height change data of each area when the bucket is running on the guide rail, taking the average value of the historical cargo height change data of each area within a preset time period based on the historical cargo height change data, and obtaining the average height change data of each area.

6. The intelligent shape recognition and precise resetting control system for large vertical shaft skips according to claim 5 is characterized in that: The loading area adjustment module is used to obtain the real-time cargo height of each area in the bucket when the cargo is loaded, and adjust the cargo loading area according to the fatigue area of ​​the bucket, including: when the fatigue area of ​​the bucket is in the first area, adjusting the cargo loading area to the third area, obtaining the real-time cargo height of each area, and adjusting the cargo height of each area according to the real-time cargo height of each area and the average height change data of each area; when the fatigue area of ​​the bucket is in the third area, adjusting the cargo loading area to the first area, obtaining the real-time cargo height of each area, and adjusting the cargo height of each area according to the real-time cargo height of each area and the average height change data of each area; when the fatigue area of ​​the bucket is in the first area and the third area at the same time or there is no fatigue area of ​​the bucket, adjusting the cargo loading area to the second area, obtaining the real-time cargo height of each area, and adjusting the cargo height of each area according to the real-time cargo height of each area and the average height change data of each area.

7. The intelligent shape recognition and precise resetting control system for large vertical shaft skips according to claim 6 is characterized in that: The cargo height adjustment submodule adjusts the cargo height of each area according to the real-time cargo height of each area and the average height change data of each area, including: using an initial adjustment formula according to the real-time cargo height of the first area and the third area and the average height change data of each area to obtain the adjusted initial cargo height of each area, and adjusting the cargo height of each area according to the initial cargo height of each area, wherein the initial adjustment formula is: ； Where, Initial cargo height adjusted for the target area; is the standard cargo height for the target area; is the average height change data of the target area; is the maximum cargo height in the target area; is the adjustment factor.

8. The intelligent shape recognition and precise resetting control system for large vertical shaft skips according to claim 7 is characterized in that: The loading area adjustment submodule adjusts the cargo height of each area according to the real-time cargo height of each area and the average height change data of each area, including: when the fatigue area of ​​the skip is in the first area, adjusting the cargo loading area to the third area, and when the real-time cargo height of the third area reaches the maximum cargo height of the third area or the real-time cargo height of the first area is higher than the highest height of the fatigue area in the first area, adjusting the cargo loading area to other areas so that the cargo height of each area increases to the adjusted initial cargo height; when the fatigue area of ​​the skip is in the third area, adjusting the cargo loading area to the first area, and when the real-time cargo height of the first area reaches the maximum cargo height of the first area or the real-time cargo height of the third area is higher than the highest height of the fatigue area in the third area, adjusting the cargo loading area to other areas so that the cargo height of each area increases to the adjusted initial cargo height.

9. The intelligent shape recognition and precise resetting control system for large vertical shaft skips according to claim 1 is characterized in that: The area monitoring adjustment module is used to obtain monitoring data of the skip during operation, and adjust the tolerance times of each area according to the monitoring data, including: obtaining monitoring data of the skip during operation, the monitoring data including the number of times the skip shakes beyond a first preset range during operation, the height of the cargo in the skip in each area, and the number of fatigue areas in each area of ​​the skip, and adjusting the tolerance times of each area of ​​the skip exceeding a second preset range during operation using a frequency adjustment formula according to the monitoring data.

10. The intelligent shape recognition and precise resetting control system for large vertical shaft skips according to claim 9 is characterized in that: The number adjustment module uses a frequency adjustment formula according to the monitoring data to adjust the number of times that each area of ​​the skip exceeds the second preset range during operation, including: wherein the frequency adjustment formula is: ； Where, After adjustment, the skip bucket is in operation. The number of times the area exceeds the tolerance of the second preset range; The first The number of times the area exceeds the tolerance of the second preset range; Initial cargo height adjusted for the target area; is the maximum cargo height in the target area; The first The number of times the area shakes beyond the first preset range; For Jidoudi the number of fatigue zones within the area; To adjust the parameters.

Images