Dynamic combination maintenance decision and automation operation process optimization method for terminal equipment

Abstract

The application discloses a wharf equipment dynamic combination maintenance decision and automatic operation process optimization method, and relates to the process optimization management and control field.The wharf equipment dynamic combination maintenance decision and automatic operation process optimization method comprises the following steps: transmission stability evaluation; maintenance data transmission stability optimization; and automatic guided vehicle scheduling accuracy evaluation.The application evaluates the maintenance data transmission stability of the track crane after the track crane performs the position maintenance, and if the maintenance data transmission stability is optimized, the qualified degree of the maintenance data transmission stability optimization is quantitatively evaluated.If the maintenance data transmission stability is not optimized, the automatic guided vehicle scheduling accuracy is evaluated, so that the track crane fault maintenance and the automatic guided vehicle scheduling optimization accuracy are improved, and the problem of low track crane fault maintenance and automatic guided vehicle scheduling optimization accuracy in the prior art is solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of process optimization management and control, in particular to a terminal equipment dynamic combination maintenance decision and automation operation process optimization method. BACKGROUND

[0002] In the automated terminal unmanned operation scene, the joint operation of automated guided vehicles and automated rail-mounted cranes is the core key link to improve the efficiency of terminal loading and unloading. The conventional operation process is that the rail-mounted crane picks up containers from the ship and cooperates with the automated guided vehicle to complete the unloading operation. The development of modern information technology provides strong technical support for the joint operation of automated guided vehicles and automated rail-mounted cranes. For example, high-precision positioning technology can ensure that the automated guided vehicle and the automated rail-mounted crane accurately stop and dock; wireless communication technology can realize real-time information transmission and interaction between devices; the automation control system can accurately control and schedule the devices to realize the automation and intelligence of joint operation. At the same time, the application of artificial intelligence, big data and other technologies can analyze and optimize operation data, and continuously improve the efficiency and performance of joint operation.

[0003] The existing method is mainly based on double communication paths. The rail-mounted crane and the central dispatching system can transmit data through multiple communication paths. If a path fails due to failure, the system can automatically switch to the standby path to ensure the continuity and stability of data transmission.

[0004] For example, the AGV path optimization method of the automated container terminal disclosed in the invention patent with the announcement number CN110942203B includes: taking the bay and the container area as the node, taking the distance between the container area and the bay with scheduling task relationship as the edge, constructing the AGV scheduling model, and taking the minimum value of the constructed AGV scheduling model as the objective function to solve the minimum value to determine the optimal path of the AGV.

[0005] For example, the joint maintenance strategy and task scheduling parallel machine system processing optimization method disclosed in the invention patent with the announcement number CN113723803B includes: describing the degradation of the machine according to the Wiener process, establishing a mathematical model of the processing time required to process all workpieces in the parallel machine system, solving the optimal processing position of all workpieces on the parallel machine system according to the processing time mathematical model, and arranging the processing sequence of all workpieces to be processed according to the optimal processing position.

[0006] However, in the process of implementing the technical scheme of the present application, the present application finds that the above-mentioned technology at least has the following technical problems:

[0007] In existing technologies, the collaborative operation of automated guided vehicles (AGVs) and automated rail-mounted gantry cranes is a core element in improving the efficiency of loading and unloading at automated terminals when no one is involved in operation and maintenance. After the rail-mounted gantry crane grabs a container from the ship, it is unloaded in cooperation with the AGV.

[0008] When performing maintenance on a rail-mounted gantry crane's container grabbing, inaccurate maintenance (such as inaccurate calibration of the grabbing position after maintenance) may lead to communication link instability after maintenance. This instability can cause errors in the transmission of maintenance signals and the updating of maintenance data for the grabbing position. Consequently, the dispatch center may not be able to correctly identify the repair status of the rail-mounted gantry crane, which in turn affects the accuracy of dispatching automated guided vehicles (AGVs) for container unloading operations. This results in low accuracy in both rail-mounted gantry crane grabbing maintenance and AGV dispatch optimization. Summary of the Invention

[0009] This application provides a method for dynamic combination maintenance decision-making and automated operation process optimization for dock equipment, which solves the problem of low accuracy in the prior art for rail-mounted gantry crane fault repair and automated guided vehicle (AGV) scheduling optimization, and improves the accuracy of rail-mounted gantry crane fault repair and AGV scheduling optimization.

[0010] This application provides a method for dynamic combination maintenance decision-making and automated operation process optimization for terminal equipment, including the following steps: After maintenance of the rail-mounted gantry crane's gripping position, a stability assessment of the rail-mounted gantry crane's gripping maintenance data transmission is performed to determine whether maintenance data transmission stability optimization is needed. The rail-mounted gantry crane's gripping maintenance data transmission stability assessment is used to quantify the stability of fault maintenance signal transmission, and maintenance data transmission stability optimization is used to improve the stability of fault maintenance signal transmission. If maintenance data transmission stability optimization is performed, the pass rate of maintenance data transmission stability optimization is quantitatively assessed based on the optimization results to determine whether to continue with the automated guided vehicle (AGV) scheduling accuracy assessment. If maintenance data transmission stability optimization is not performed, the AGV scheduling accuracy is assessed based on the acquired AGV scheduling parameters to determine whether to perform a second maintenance status feedback. The AGV scheduling accuracy assessment is used to quantify the scheduling accuracy of loading and unloading operations after maintenance of the rail-mounted gantry crane.

[0011] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages:

[0012] 1、By performing track crane grabbing maintenance data transmission stability evaluation after track crane grabbing position maintenance, if maintenance data transmission stability optimization is performed, the qualified degree of maintenance data transmission stability optimization is quantitatively evaluated to determine whether to continue automatic guided vehicle scheduling accuracy evaluation, if maintenance data transmission stability optimization is not performed, automatic guided vehicle scheduling accuracy evaluation is performed to determine whether to perform second maintenance state feedback, thereby realizing the improvement of the accuracy of track crane grabbing maintenance state feedback, and further realizing the improvement of the accuracy of track crane grabbing fault maintenance and automatic guided vehicle scheduling optimization, effectively solving the problem of low accuracy of track crane grabbing fault maintenance and automatic guided vehicle scheduling optimization in the prior art.

[0013] 2、By performing coupling processing on the communication link switching stability data and the corresponding preset communication link switching factor to obtain maintenance data switching accuracy characteristic value, and then performing proximity degree analysis on the maintenance data switching accuracy characteristic value and the preset maintenance data switching accuracy value to obtain maintenance data switching accuracy judgment value, thereby realizing the improvement of the reliability of maintenance data transmission stability optimization, and further realizing the improvement of the accuracy of maintenance data transmission stability optimization.

[0014] 3、By coupling the automatic guided vehicle scheduling data to obtain the automatic guided vehicle scheduling accuracy characteristic value, and then comparing the automatic guided vehicle scheduling accuracy characteristic value with the preset automatic guided vehicle scheduling accuracy value, when the automatic guided vehicle scheduling accuracy characteristic value is not greater than the preset automatic guided vehicle scheduling accuracy value, the second maintenance state feedback is performed, thereby improving the effectiveness of automatic guided vehicle scheduling accuracy evaluation, and further realizing the accurate evaluation of automatic guided vehicle scheduling accuracy. BRIEF DESCRIPTION OF DRAWINGS

[0015] Figure 1 The flowchart of the wharf equipment dynamic combination maintenance decision and automatic operation process optimization method provided by the embodiment of the application;

[0016] Figure 2 The specific flowchart provided by the embodiment of the application. DETAILED DESCRIPTION

[0017] The embodiment of the application provides a wharf equipment dynamic combination maintenance decision and automatic operation process optimization method, solves the low accuracy of track crane grabbing fault maintenance and automatic guided vehicle scheduling optimization in the prior art, and realizes the improvement of the accuracy of track crane grabbing fault maintenance and automatic guided vehicle scheduling optimization.

[0018] The technical scheme in the embodiment of the application is used for solving the low accuracy of track crane grabbing fault maintenance and automatic guided vehicle scheduling optimization, and the general idea is as follows:

[0019] The track crane grabbing fault maintenance and the automatic guided vehicle scheduling optimization accuracy are improved.

[0020] In order to better understand the above technical scheme, the above technical scheme will be described in detail in combination with the description of the drawings and the specific embodiments.

[0021] As shown in the figures, Figure 1The diagram shows a flowchart of a method for dynamic combined maintenance decision-making and automated operation process optimization for dock equipment provided in this application embodiment. The method includes the following steps: Transmission stability assessment: After maintenance of the rail-mounted gantry crane's gripping position, a stability assessment of the rail-mounted gantry crane's gripping maintenance data transmission is performed. When the monitored link time difference value is greater than 0, maintenance data transmission stability optimization is performed. When the monitored link time difference value is not greater than 0, an automated guided vehicle (AGV) scheduling accuracy assessment is performed. The rail-mounted gantry crane gripping maintenance data transmission stability assessment is used to quantify the stability of fault maintenance signal transmission, and maintenance data transmission stability optimization is used to improve the stability of fault maintenance signal transmission. Maintenance data transmission stability optimization: If maintenance data transmission stability optimization is performed, the pass rate of maintenance data transmission stability optimization is quantitatively assessed based on the optimization results to determine whether to continue with the AGV scheduling accuracy assessment. AGV scheduling accuracy assessment: If maintenance data transmission stability optimization is not performed, the AGV scheduling accuracy is assessed based on the acquired AGV scheduling parameters to determine whether to perform a second maintenance status feedback. The AGV scheduling accuracy assessment is used to quantify the scheduling accuracy of loading and unloading operations after maintenance of the rail-mounted gantry crane.

[0022] In this embodiment, as Figure 2 The flowchart shown is a specific process provided in an embodiment of this application. A link time difference value is obtained through transmission stability assessment. When the monitored link time difference value is greater than 0, maintenance data transmission stability optimization is performed; otherwise, automated guided vehicle (AGV) scheduling accuracy assessment is performed. An optimization priority judgment value and a maintenance data switching accuracy feature value are obtained through maintenance data transmission stability optimization. Based on the optimization priority judgment value, the priority for adjusting the bandwidth ratio of the rail-mounted gantry communication link and the priority for adjusting the communication load migration amount are determined. A backup link preheating compression level is set based on the maintenance data switching accuracy feature value, which helps improve the accuracy of maintenance data transmission stability optimization. An AGV scheduling accuracy feature value is obtained through AGV scheduling accuracy assessment. Based on the AGV scheduling accuracy feature value, it is determined whether a second maintenance status feedback is performed, which helps balance the performance of data transmission and AGV scheduling, thereby improving the accuracy of rail-mounted gantry fault detection and maintenance and AGV scheduling optimization.

[0023] In the unmanned operation scene of the automated wharf, the coordination between the rail-mounted crane container grabbing fault maintenance and the automated guided vehicle scheduling is crucial. Through the transmission stability evaluation, maintenance data transmission stability optimization and automated guided vehicle scheduling accuracy evaluation, the rail-mounted crane fault maintenance signal and the grabbing position maintenance data (such as grabbing position offset, grabbing position calibration value, etc.) can be accurately and stably transmitted to the scheduling center, avoiding scheduling errors caused by communication link problems; it helps to improve the scheduling accuracy of the automated guided vehicle and avoid unloading operation delays caused by scheduling errors; reduces the problem of inaccurate rail-mounted crane grabbing position calibration caused by maintenance data transmission errors, and improves the accuracy of rail-mounted crane fault maintenance.

[0024] Further, after the rail-mounted crane grabbing position maintenance, the rail-mounted crane grabbing maintenance data transmission stability evaluation is performed to determine whether to perform maintenance data transmission stability optimization, and the specific process is as follows: obtaining a link time difference value, determining whether to perform maintenance data transmission stability optimization based on the link time difference value; when the monitored link time difference value is greater than 0, sending a rail-mounted crane grabbing position maintenance communication link instability prompt, and performing maintenance data transmission stability optimization; when the monitored link time difference value is not greater than 0, sending a rail-mounted crane grabbing position maintenance communication link stability prompt, and performing automated guided vehicle scheduling accuracy evaluation; the link time difference value is represented by the difference between the time of the fault maintenance signal transmitted to the preset central scheduling center within a preset time period and the preset fault maintenance signal transmission time, and is used to reflect the delay degree of the fault maintenance signal transmission.

[0025] Specifically, if the maintenance data transmission stability optimization is performed, the qualified degree of the maintenance data transmission stability optimization is quantitatively evaluated based on the optimization result, and the specific process is as follows: a first maintenance state feedback is performed, the first maintenance state feedback indicating that a prompt is sent to the preset personnel to re-capture the position calibration and maintenance at a preset time period during the communication link stability optimization; an optimization priority judgment value is obtained, the optimization priority judgment value including a communication link bandwidth proportion factor and a communication load migration amount factor, and a difference comparison is performed; the communication link bandwidth proportion factor and the communication load migration amount factor are compared; when the communication link bandwidth proportion factor is greater than the communication load migration amount factor, it indicates that the communication load migration amount needs to be adjusted more than the rail-mounted crane communication link bandwidth proportion, and the communication load migration amount adjustment is performed first, and then the rail-mounted crane communication link bandwidth proportion adjustment is performed; when the communication link bandwidth proportion factor is equal to the communication load migration amount factor, it indicates that the degree of adjustment of the communication load migration amount and the degree of adjustment of the rail-mounted crane communication link bandwidth proportion are the same, and the communication load migration amount adjustment and the rail-mounted crane communication link bandwidth proportion adjustment are performed simultaneously; when the communication link bandwidth proportion factor is less than the communication load migration amount factor, it indicates that the rail-mounted crane communication link bandwidth proportion needs to be adjusted more than the communication load migration amount, and the rail-mounted crane communication link bandwidth proportion adjustment is performed first, and then the communication load migration amount adjustment is performed; it is judged whether the link time difference value re-acquired after the communication link stability optimization is greater than 0; when the link time difference value re-acquired after the communication link stability optimization is still greater than 0, a communication link stability optimization unqualified prompt is sent, the standby communication link is switched to, and the rail-mounted crane maintenance conversion stability optimization is performed, the rail-mounted crane maintenance conversion stability optimization being used to improve the stability when the automated guided vehicle is dispatched during the communication path conversion; the communication link stability optimization includes the rail-mounted crane communication link bandwidth proportion adjustment and the communication load migration amount adjustment; the communication link bandwidth proportion factor is obtained by approaching degree analysis of the preset minimum bandwidth proportion obtained from the database and the rail-mounted crane communication link bandwidth proportion; the communication load migration amount factor is obtained by approaching degree analysis of the non-scheduled data amount and the preset maximum data amount obtained from the database, wherein the preset minimum bandwidth proportion and the preset maximum data amount are set in advance by the preset personnel; and the preset link time difference value is represented by the average value of the link time difference values of the historical time period.

[0026] It should be noted that the approaching degree analysis in the embodiments of the present application indicates that the ratio operation is performed. Before the method for designing the dynamic combination maintenance decision of the terminal equipment and the automated operation process optimization provided in the present application, a database storing various types of setting data is established. The database includes but is not limited to preset switching time consumption, preset maintenance signal transmission success times, and preset maintenance signal transmission interruption times, etc. The various types of values in the database are directly set by technical personnel. For example, the preset fault maintenance signal transmission time is represented by the average value of the fault maintenance signal transmission time in the historical time period to the preset central dispatch center.

[0027] In the present embodiment, when the communication link bandwidth proportion factor is greater than the communication load migration amount factor, the communication load migration amount adjustment is performed first, and then the rail-mounted crane communication link bandwidth proportion adjustment is performed, that is, the rail-mounted crane communication link bandwidth proportion is gradually reduced through the amplitude corresponding to the rail-mounted crane communication link optimization factor, and the number of idle links for the equipment is gradually increased through the amplitude corresponding to the rail-mounted crane communication link optimization factor, which helps to reduce the pressure of the current communication link. When the communication link bandwidth proportion factor is less than the communication load migration amount factor, the rail-mounted crane communication link bandwidth proportion adjustment is performed first, and then the communication load migration amount adjustment is performed, which helps to optimize the load distribution and meet the load demand. When the communication link bandwidth proportion factor is equal to the communication load migration amount factor, the communication load migration amount adjustment and the rail-mounted crane communication link bandwidth proportion adjustment are performed simultaneously, which helps to achieve the best optimization effect, and thus the effect of improving the accuracy of the rail-mounted crane fault maintenance and automated guided vehicle dispatching optimization is achieved.

[0028] By performing the rail-mounted crane communication link bandwidth proportion adjustment and the communication load migration amount adjustment, the fault maintenance signal transmission error and the grasping position maintenance data update error caused by unstable communication link can be reduced, thereby reducing the error of the preset dispatch center in identifying the rail-mounted crane repair state, improving the accuracy of the automated guided vehicle dispatching, and avoiding the unloading operation delay caused by dispatching error.

[0029] Further, the track crane communication link bandwidth ratio adjustment represents sending a prompt to the preset personnel to gradually reduce the track crane communication link bandwidth ratio by the amplitude corresponding to the track crane communication link optimization factor; the communication load migration amount adjustment represents sending a prompt to the preset personnel to gradually increase the number of idle links for the pre-device by the amplitude corresponding to the track crane communication link optimization factor, and migrating the non-automated guided vehicle scheduling data to the idle link for the pre-device; the track crane communication link optimization factor is obtained by ratio analysis (i.e., ratio operation) of the link time difference value after the first maintenance state feedback and the preset link time difference value obtained from the database, and is used to adjust the stability of the fault maintenance signal transmission; the non-scheduling data amount represents the data amount corresponding to the non-automated guided vehicle scheduling data (such as the shore crane operation time, the current task list of the track crane, etc.); the communication link stability optimization is used to reduce the instability of the communication link when scheduling the automated guided vehicle due to the track crane maintenance.

[0030] Specifically, the track crane maintenance conversion stability optimization includes obtaining a maintenance data switching accuracy characteristic value and setting a standby link preheating compression level; the specific process of obtaining the maintenance data switching accuracy characteristic value is as follows:

[0031] First, the time consumption and switching accuracy characteristic value are obtained by approaching degree analysis of the preset switching time consumption and the switching time consumption, which is used to reflect the influence of the switching time consumption on the stability of the communication path conversion. Specifically, the expression of the time consumption and switching accuracy characteristic value is E represents the number of the preset switching time period, V represents the total number of the preset switching time period, Q1(E) represents the time consumption and switching accuracy characteristic value of the Eth preset switching time period, HS(E) represents the switching time consumption of the Eth preset switching time period, HS(0) represents the preset switching time consumption, and the total time required for recording the time stamp in the preset switching time period is recorded as the switching time consumption.

[0032] Then, the transmission success and switching accuracy characteristic value is obtained by approaching degree analysis of the maintenance signal transmission success number and the preset maintenance signal transmission success number, which is used to reflect the influence of the maintenance signal transmission success number on the stability of the communication path conversion. Specifically, the expression of the transmission success and switching accuracy characteristic value is Q2(E) represents the transmission success and switching accuracy characteristic value of the Eth preset switching time period, WXC(E) represents the maintenance signal transmission success number of the Eth preset switching time period, WXC(0) represents the preset maintenance signal transmission success number, and the total number of successfully transmitted maintenance signals (such as control instructions and state feedback) in the preset switching time period is recorded as the maintenance signal transmission success number by monitoring the maintenance signals in the preset receiving end by the signal counter and the network analyzer.

[0033] Then, the transmission interruption and switching accuracy characteristic value is obtained by approaching degree analysis on the preset maintenance signal transmission interruption times and the maintenance signal transmission interruption times, and is used for reflecting the influence of the maintenance signal transmission interruption times on the stability of the communication path conversion. Specifically, the expression of the transmission interruption and switching accuracy characteristic value is WXS(E) represents the maintenance signal transmission interruption times of the Eth preset switching time period, WXS(0) represents the preset maintenance signal transmission interruption times, and Q3(E) represents the transmission interruption and switching accuracy characteristic value of the Eth preset switching time period. The total number of the maintenance signals (such as control instructions and state feedbacks) that are not successfully transmitted to the preset receiving end within the preset switching time period is recorded as the maintenance signal transmission interruption times by using the signal counter and the network analyzer to monitor the preset receiving end.

[0034] Finally, the maintenance data switching accuracy characteristic value is obtained by weighting operation and coupling processing of the communication link switching stability data and the corresponding preset communication link switching factor. The maintenance data switching accuracy characteristic value is used for reflecting the comprehensive influence of the communication link switching stability parameters and the preset communication link switching stability parameters on the stability of the communication path conversion.

[0035] The maintenance data switching accuracy characteristic value is obtained by the following method:

[0036] Q(E) = R1 x Q1(E) + R2 x Q2(E) + R3 x Q3(E);

[0037] In the formula, Q(E) represents the maintenance data switching accuracy characteristic value of the Eth preset switching time period, R1 represents the preset time consumption and switching accuracy factor, R2 represents the preset transmission success and switching accuracy factor, and R3 represents the preset transmission interruption and switching accuracy factor.

[0038] In summary, the communication link switching stability data includes the time consumption and switching accuracy characteristic value, the transmission success and switching accuracy characteristic value, and the transmission interruption and switching accuracy characteristic value. The preset communication link switching factor includes the preset time consumption and switching accuracy factor, the preset transmission success and switching accuracy factor, and the preset transmission interruption and switching accuracy factor, and is used for reflecting the influence degree of the communication link switching stability data on the maintenance data switching accuracy characteristic value. The communication link switching stability parameters include the switching time consumption, the maintenance signal transmission success times, and the maintenance signal transmission interruption times. The preset communication link switching stability parameters include the preset switching time consumption, the preset maintenance signal transmission success times, and the preset maintenance signal transmission interruption times.

[0039] The units of the switching time consumption and the preset switching time consumption are milliseconds. The units of the maintenance signal transmission success times, the maintenance signal transmission interruption times, the preset maintenance signal transmission success times, and the preset maintenance signal transmission interruption times are all unitless.

[0040] It should be noted that the preset communication link switching stability parameter is represented by the average value of the historical time period communication link switching stability parameter; the embodiment provides a set of mapping groups containing mapping sets, the mapping sets are used to reflect the mapping relationship corresponding to the communication link switching stability data and the preset communication link switching factor, and the preset communication link switching factor can be obtained by inputting real-time communication link switching stability data into the corresponding mapping group; wherein the mapping relationship in the mapping set can be a one-to-one or many-to-one relationship; for example, the weight value range is 0-1.

[0041] In the embodiment, the communication link switching stability data is further analyzed to obtain a maintenance data switching accuracy characteristic value. The larger the communication link switching stability data is, the stronger the influence of the switching time consumption on the stability of the communication path conversion, the stronger the influence of the number of successful maintenance signal transmissions on the stability of the communication path conversion, and the stronger the influence of the number of maintenance signal transmission interruptions on the stability of the communication path conversion, resulting in a larger maintenance data switching accuracy characteristic value. In summary, in the embodiment, the communication link switching stability data and the maintenance data switching accuracy characteristic value are positively correlated.

[0042] The communication link switching stability parameters monitored in the embodiment have the characteristics of mutual correlation, which need to be associated for describing their common action. The longer the switching time consumption is, the longer the communication link stays in an unstable state, which increases the possibility of interruption during the maintenance signal transmission process, which may cause signal loss or transmission error, thereby increasing the number of transmission interruptions; the increase of the switching time consumption may cause the communication link to fail to establish a stable connection in the switching process, resulting in the failure of the maintenance signal transmission, and further reducing the number of successful maintenance signal transmissions; the increase of the number of successful maintenance signal transmissions means the decrease of the number of transmission interruptions, if the more the number of successful maintenance signal transmissions is, the switching process can be completed faster, which helps to reduce the retry and waiting time, and further results in the smaller switching time consumption. By analyzing the comprehensive influence between the parameters, the number of maintenance signal transmission interruptions is accurately evaluated for the stability of the communication path conversion, and the effect of improving the accuracy of the track crane fault maintenance and automatic guided vehicle scheduling optimization is achieved.

[0043] Further, the eligibility of the maintenance data transmission stability optimization is quantitatively evaluated based on the optimization result to determine whether to continue the automated guided vehicle scheduling accuracy evaluation, and the specific process is as follows: based on the maintenance data switching accuracy characteristic value and the preset maintenance data switching accuracy value obtained from the database, the approach degree is analyzed to obtain the maintenance data switching accuracy judgment value; when the maintenance data switching accuracy judgment value is greater than 1, a communication link switching qualified prompt is sent, and the automated guided vehicle scheduling accuracy evaluation is continued; when the maintenance data switching accuracy judgment value is not greater than 1, a communication link switching unqualified prompt is sent, and a standby link preheating compression level is set; when the maintenance data switching accuracy judgment value obtained after the standby link preheating compression level is set is still not greater than 1, a maintenance decision alarm prompt is sent (when the maintenance data switching accuracy judgment value is greater than 1, the automated guided vehicle scheduling accuracy evaluation is continued); the maintenance data switching accuracy judgment value is the result of the ratio operation of the maintenance data switching accuracy characteristic value and the preset maintenance data switching accuracy value, wherein the preset maintenance data switching accuracy value is represented by the average value of the maintenance data switching accuracy characteristic value in the historical time period.

[0044] The specific process of setting the standby link preheating compression level is as follows: the preheating time is monitored, the preheating time represents the time required from switching to the standby communication link to the stable working state of the link, and the preheating time and the preset preheating time are compared to obtain the standby link preheating compression level, the preset preheating time is represented by the average value of the communication link preheating time in the historical time period; the standby link preheating compression level includes a first preheating time shortening level and a second preheating time shortening level; the first preheating time shortening level represents the level corresponding to the preheating time not greater than the preset preheating time divided by the preset preheating time; the second preheating time shortening level represents the level corresponding to the preheating time greater than the preset preheating time divided by the preset preheating time; a prompt is sent to the preset personnel to divide the maintenance data switching accuracy judgment value not greater than 1 into switching levels to obtain the maintenance data switching level, the maintenance data switching level includes a first maintenance data switching level and a second maintenance data switching level, the first maintenance data switching level corresponds to the maintenance data switching accuracy judgment value in the range corresponding to the minimum value of the maintenance data switching accuracy judgment value and the minimum value of the preset switching range, and the minimum value of the maintenance data switching accuracy judgment value is less than the minimum value of the preset switching range, the second maintenance data switching level corresponds to the maintenance data switching accuracy judgment value in the range corresponding to the maximum value of the maintenance data switching accuracy judgment value and the maximum value of the preset switching range, and the maximum value of the maintenance data switching accuracy judgment value is greater than the maximum value of the preset switching range.

[0045] switching and preheating matching is performed, indicating that the first-level maintenance data switching level and the first-level preheating time shortening level are matched, and the second-level maintenance data switching level and the second-level preheating time shortening level are matched; after the switching and preheating matching is performed, second-time backup communication link switching is performed, indicating that the communication link switching is performed again based on the result of the switching and preheating matching; a maintenance data switching accurate judgment value after the second-time backup communication link switching is obtained, if the maintenance data switching accurate judgment value after the second-time backup communication link switching is still not greater than 1, the communication link switching is performed again, and when the number of times of the communication link switching is greater than a preset maximum switching value, if the maintenance data switching accurate judgment value is still not greater than 1, a maintenance decision warning prompt is sent, and the preset maximum switching value is set in advance by the preset personnel; if the maintenance data switching accurate judgment value after the second-time backup communication link switching is greater than 1, a switching qualified prompt is sent, and automatic guided vehicle scheduling accuracy evaluation is continued.

[0046] In the embodiment, by monitoring the preheating time, the preheating time not greater than the preset preheating time is divided into a first-level preheating time shortening level, and the preheating time greater than the preset preheating time is divided into a second-level preheating time shortening level; by monitoring the maintenance data switching accurate judgment value not greater than 1, the maintenance data switching accurate judgment value not greater than 1 is divided to obtain a maintenance data switching level based on a preset switching range set in advance by the preset personnel; the maintenance data switching level and the backup link preheating compression level are switched and preheated. For example, the first-level maintenance data switching level and the first-level preheating time shortening level are matched, and the second-level maintenance data switching level and the second-level preheating time shortening level are matched, which helps to ensure that the switching quality and the link preheating ability are matched, and avoids switching failure caused by unstable link; by setting the maintenance data switching level and the backup link preheating compression level, the preheating time can be allocated according to the switching time demand of different levels, and by matching the maintenance data switching level and the preheating time shortening level, the switching and the preheating ability of the link can be matched; based on the result of the switching and preheating matching, the link is switched again, which helps to verify the effectiveness of the switching and preheating matching; by monitoring the number of times of the communication link switching, the communication link is switched again, and when the number of times of the communication link switching is greater than the preset maximum switching value, a maintenance decision warning prompt is directly sent, which helps to avoid the interruption of the automatic guided vehicle scheduling caused by the link failure, and thus the accuracy of the track crane grabbing fault maintenance and the automatic guided vehicle scheduling optimization is improved.

[0047] Further, based on the obtained automatic guided vehicle scheduling parameters, automatic guided vehicle scheduling accuracy evaluation is performed, and the specific process is as follows:

[0048] Firstly, the first scheduling accuracy characteristic value is obtained by performing weighting operation on the first scheduling accuracy factor combined with the approaching degree analysis on the correct matching automatic guided vehicle quantity and the preset correct matching automatic guided vehicle quantity, and is used to reflect the influence of the correct matching automatic guided vehicle quantity on the automatic guided vehicle loading and unloading operation scheduling accuracy after the rail-mounted gantry is maintained, specifically, D represents the number of the preset scheduling time period, L represents the total number of the preset scheduling time period, F1(D) represents the first scheduling accuracy characteristic value of the Dth preset scheduling time period, CGP(D) represents the correct matching automatic guided vehicle quantity of the Dth preset scheduling time period, CGP(0) represents the preset correct matching automatic guided vehicle quantity, and C1 represents the first scheduling accuracy factor. The quantity of the automatic guided vehicle that correctly matches the scheduling instruction in the preset scheduling time period monitored by the preset scheduling center is recorded as the correct matching automatic guided vehicle quantity.

[0049] Then, the second scheduling accuracy characteristic value is obtained by performing weighting operation on the second scheduling accuracy factor combined with the approaching degree analysis on the preset average automatic guided vehicle scheduling position deviation and the average automatic guided vehicle scheduling position deviation, and is used to reflect the influence of the average automatic guided vehicle scheduling position deviation on the automatic guided vehicle loading and unloading operation scheduling accuracy after the rail-mounted gantry is maintained, specifically, F2(D) represents the second scheduling accuracy characteristic value of the Dth preset scheduling time period, DDP(D) represents the average automatic guided vehicle scheduling position deviation of the Dth preset scheduling time period, DDP(0) represents the preset average automatic guided vehicle scheduling position deviation, and C2 represents the second scheduling accuracy factor. The distance between the position allocated by the preset scheduling center to the automatic guided vehicle and the actual operation position in the preset scheduling time period is monitored by the preset scheduling center, and the average value is taken as the average automatic guided vehicle scheduling position deviation.

[0050] Next, the third scheduling accuracy characteristic value is obtained by performing weighting operation on the third scheduling accuracy factor combined with the approaching degree analysis on the preset average rail-mounted gantry-scheduling task synchronization time delay and the average rail-mounted gantry-scheduling task synchronization time delay, and is used to reflect the influence of the average rail-mounted gantry-scheduling task synchronization time delay on the automatic guided vehicle loading and unloading operation scheduling accuracy after the rail-mounted gantry is maintained, specifically, F3(D) represents the third scheduling accuracy characteristic value of the Dth preset scheduling time period, DDT(D) represents the average rail-mounted gantry-scheduling task synchronization time delay of the Dth preset scheduling time period, DDT(0) represents the preset average rail-mounted gantry-scheduling task synchronization time delay, and C3 represents the third scheduling accuracy factor. The time length from the time when the rail-mounted gantry issues an instruction to the time when the automatic guided vehicle receives the instruction in the preset scheduling time period is monitored by the preset scheduling center, and the average value is taken as the average rail-mounted gantry-scheduling task synchronization time delay.

[0051] Finally, the automatic guided vehicle scheduling accuracy characteristic value is obtained by coupling processing of the automatic guided vehicle scheduling data; the automatic guided vehicle scheduling accuracy characteristic value is used to reflect the effect of the automatic guided vehicle scheduling parameters and the preset automatic guided vehicle scheduling parameters on the automatic guided vehicle loading and unloading operation scheduling accuracy after the rail-mounted gantry is maintained.

[0052] The automatic guided vehicle scheduling accuracy characteristic value is obtained by the following method:

[0053] F(D) = F1(D) + F2(D) + F3(D);

[0054] In the formula, F(D) represents the automatic guided vehicle scheduling accuracy characteristic value of the Dth preset scheduling time period.

[0055] In summary, the automatic guided vehicle scheduling data includes the first scheduling accuracy characteristic value, the second scheduling accuracy characteristic value, and the third scheduling accuracy characteristic value; the automatic guided vehicle scheduling parameters include the correct matching automatic guided vehicle quantity, the average automatic guided vehicle scheduling position deviation, and the average rail-mounted gantry-scheduling task synchronization time delay; the preset automatic guided vehicle scheduling parameters include the preset loading and unloading scheduling parameters and the preset loading and unloading scheduling parameter factors; the preset loading and unloading scheduling parameters include the preset correct matching automatic guided vehicle quantity, the preset average automatic guided vehicle scheduling position deviation, and the preset average rail-mounted gantry-scheduling task synchronization time delay; the preset loading and unloading scheduling parameter factors include the first scheduling accuracy factor, the second scheduling accuracy factor, and the third scheduling accuracy factor, which are used to reflect the influence degree of the automatic guided vehicle scheduling data on the automatic guided vehicle scheduling accuracy characteristic value; wherein the correct matching automatic guided vehicle quantity and the preset correct matching automatic guided vehicle quantity are both unitless; the average automatic guided vehicle scheduling position deviation and the preset average automatic guided vehicle scheduling position deviation are both in millimeters; and the average rail-mounted gantry-scheduling task synchronization time delay and the preset average rail-mounted gantry-scheduling task synchronization time delay are both in milliseconds.

[0056] It should be noted that the preset loading and unloading scheduling parameters are represented by the average values of the historical time period automatic guided vehicle scheduling parameters; the embodiment provides a set of mapping groups containing mapping sets, which are used to reflect the mapping relationship corresponding to the automatic guided vehicle scheduling data and the preset loading and unloading scheduling parameter factors; the preset loading and unloading scheduling parameter factors can be obtained by inputting real-time automatic guided vehicle scheduling data into the corresponding mapping groups; wherein the mapping relationship in the mapping set can be a one-to-one or many-to-one relationship; for example, the weight value range is 0-1.

[0057] In the embodiment, the automatic guided vehicle scheduling data is comprehensively analyzed to further obtain an automatic guided vehicle scheduling accuracy characteristic value. The larger the automatic guided vehicle scheduling data is, the stronger the effect of the number of correctly matched automatic guided vehicles on the automatic guided vehicle loading and unloading operation scheduling accuracy after the rail-mounted gantry is maintained, the stronger the effect of the average automatic guided vehicle scheduling position deviation on the automatic guided vehicle loading and unloading operation scheduling accuracy after the rail-mounted gantry is maintained, and the stronger the effect of the average rail-mounted gantry-scheduling task synchronization time delay on the automatic guided vehicle loading and unloading operation scheduling accuracy after the rail-mounted gantry is maintained, resulting in a larger automatic guided vehicle scheduling accuracy characteristic value. In summary, in the embodiment, the automatic guided vehicle scheduling data and the automatic guided vehicle scheduling accuracy characteristic value are positively correlated.

[0058] The automatic guided vehicle scheduling parameters monitored in the embodiment have the characteristics of mutual correlation, and need to be associated for describing their common action. The more the number of correctly matched automatic guided vehicles is, the more likely the scheduling pressure of a single automatic guided vehicle is reduced, thereby reducing the average position deviation caused by scheduling conflicts, and further resulting in a smaller average automatic guided vehicle scheduling position deviation. The larger the average rail-mounted gantry-scheduling task synchronization time delay is, the more likely the scheduling position prediction of the automatic guided vehicle by the preset scheduling center is inaccurate, thereby increasing the position deviation, and further resulting in a larger average automatic guided vehicle scheduling position deviation. By analyzing the comprehensive influence between the parameters, the accurate evaluation of the automatic guided vehicle loading and unloading operation scheduling accuracy after the rail-mounted gantry is maintained is realized, and further the accuracy of the rail-mounted gantry grabbing fault maintenance and automatic guided vehicle scheduling optimization is improved.

[0059] Further, based on the obtained automatic guided vehicle scheduling parameters, the automatic guided vehicle scheduling accuracy is evaluated to determine whether to perform a second maintenance state feedback. The specific process is as follows: difference comparison is performed based on the automatic guided vehicle scheduling accuracy characteristic value and the preset automatic guided vehicle scheduling accuracy value obtained from the database; when the automatic guided vehicle scheduling accuracy characteristic value is greater than the preset automatic guided vehicle scheduling accuracy value, a maintenance decision qualified prompt is sent; when the automatic guided vehicle scheduling accuracy characteristic value is not greater than the preset automatic guided vehicle scheduling accuracy value, a maintenance decision unqualified prompt is sent, and a second maintenance state feedback is performed; the second maintenance state feedback indicates that when the automatic guided vehicle scheduling accuracy characteristic value is not greater than the preset automatic guided vehicle scheduling accuracy value, a prompt is sent to the preset personnel to re-calibrate the grabbing position and perform maintenance.

[0060] In the embodiment, the preset AGV scheduling accuracy value is represented by the average value of the AGV scheduling accuracy characteristic values in the historical time period; when the AGV scheduling accuracy characteristic value is greater than the preset AGV scheduling accuracy value, it indicates that the maintenance decision is qualified, otherwise, the second maintenance state feedback is performed, such as sending a prompt to the preset personnel to correct the positioning error of the AGV, by correcting the positioning error of the AGV, it is ensured that the AGV can accurately reach the specified position to complete the cargo grabbing and transportation task, so as to ensure the execution accuracy of the cargo grabbing task; through the second maintenance state feedback, the qualification of the first maintenance state feedback can be verified, the second maintenance state feedback can help the preset personnel to more accurately locate the problem, which is helpful to optimize the grabbing position maintenance decision, based on the problem positioning information provided by the second maintenance state feedback, the preset personnel can optimize the grabbing position maintenance decision in combination with the actual situation. For example, adjusting the allocation of maintenance resources; by monitoring the AGV scheduling accuracy characteristic value, the cargo grabbing failure or delay caused by the positioning error is reduced, the loading and unloading efficiency of the wharf is improved, and the accuracy of the track crane grabbing fault maintenance and AGV scheduling optimization is improved.

[0061] In summary, the embodiment of the present application performs track crane grabbing maintenance data transmission stability evaluation after track crane grabbing position maintenance, if maintenance data transmission stability optimization is performed, the qualified degree of the maintenance data transmission stability optimization is quantitatively evaluated to determine whether to continue to perform AGV scheduling accuracy evaluation, if maintenance data transmission stability optimization is not performed, AGV scheduling accuracy evaluation is performed to determine whether to perform second maintenance state feedback, thereby improving the accuracy of track crane grabbing maintenance state feedback, and further improving the accuracy of track crane grabbing fault maintenance and AGV scheduling optimization, effectively solving the problem of low accuracy of track crane grabbing fault maintenance and AGV scheduling optimization in the prior art.

[0062] Those skilled in the art will appreciate that embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROMs, optical storage, etc.) containing computer-usable program code.

[0063] The present application is described in reference to the flowchart illustrations and / or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart illustrations and / or block diagrams. Figure 1 one or more functions specified in the flowchart illustrations and / or block diagrams. Figure 1 one or more functions specified in the flowchart illustrations and / or block diagrams.

[0064] These computer program instructions can also be stored in a computer- readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instructions which implement the functions specified in the flowchart illustrations and / or block diagrams. Figure 1 one or more functions specified in the flowchart illustrations and / or block diagrams. Figure 1 one or more functions specified in the flowchart illustrations and / or block diagrams.

[0065] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart illustrations and / or block diagrams. Figure 1 one or more functions specified in the flowchart illustrations and / or block diagrams. Figure 1 one or more functions specified in the flowchart illustrations and / or block diagrams.

[0066] While preferred embodiments of the application have been described, modifications and variations can be apparent to those skilled in the art once aware of the general underlying concepts. Accordingly, the appended claims intend to embrace all such modifications and variations as fall within the scope of the application.

[0067] Obviously, numerous modifications and variations of the present application are possible in light of the above teachings. It is therefore to be understood that within the scope of the appended claims and their equivalents, the application can be practiced otherwise than as specifically described.

Claims

1. A method for dynamic combination maintenance decision and automated operation process optimization of terminal equipment, characterized in that, The method comprises the following steps: After the track crane grabbing position maintenance is performed, track crane grabbing maintenance data transmission stability evaluation is performed to determine whether to perform maintenance data transmission stability optimization, the track crane grabbing maintenance data transmission stability evaluation is used to quantify the stability of the fault maintenance signal transmission, and the maintenance data transmission stability optimization is used to improve the stability of the fault maintenance signal transmission; If the maintenance data transmission stability optimization is performed, the qualified degree of the maintenance data transmission stability optimization is quantitatively evaluated based on the optimization result to determine whether to continue the automated guided vehicle scheduling accuracy evaluation; If the maintenance data transmission stability optimization is not performed, the automated guided vehicle scheduling accuracy evaluation is performed based on the obtained automated guided vehicle scheduling parameters to determine whether to perform second maintenance state feedback, and the automated guided vehicle scheduling accuracy evaluation is used to quantify the loading and unloading operation scheduling accuracy after the track crane maintenance is performed; The track crane grabbing position maintenance is performed, and the track crane grabbing maintenance data transmission stability evaluation is performed to determine whether to perform maintenance data transmission stability optimization, and the specific process is as follows: The link time difference value is obtained, and it is determined whether to perform maintenance data transmission stability optimization based on the link time difference value; When the monitored link time difference value is greater than 0, a track crane grabbing position maintenance communication link instability prompt is sent, and the maintenance data transmission stability optimization is performed; When the monitored link time difference value is not greater than 0, a track crane grabbing position maintenance communication link stability prompt is sent, and the automated guided vehicle scheduling accuracy evaluation is performed; The link time difference value is used to reflect the delay degree of the fault maintenance signal transmission; If the maintenance data transmission stability optimization is performed, the qualified degree of the maintenance data transmission stability optimization is quantitatively evaluated based on the optimization result, and the specific process is as follows: The first maintenance state feedback is performed, which indicates that a prompt is sent to the preset personnel to re-perform the grabbing position calibration and maintenance within a preset time period during the communication link stability optimization; An optimization priority judgment value is obtained, the optimization priority judgment value comprises a communication link bandwidth proportion factor and a communication load migration amount factor, and difference comparison is performed; When the communication link bandwidth proportion factor is greater than the communication load migration amount factor, the communication load migration amount adjustment is performed first, and then the track crane communication link bandwidth proportion adjustment is performed; When the communication link bandwidth proportion factor is equal to the communication load migration amount factor, the communication load migration amount adjustment and the track crane communication link bandwidth proportion adjustment are simultaneously performed; When the communication link bandwidth proportion factor is less than the communication load migration amount factor, the track crane communication link bandwidth proportion adjustment is performed first, and then the communication load migration amount adjustment is performed; When the re-obtained link time difference value is still greater than 0 after the communication link stability optimization is performed, a communication link stability optimization unqualified prompt is sent, the standby communication link is switched to, and the track crane maintenance conversion stability optimization is performed, and the track crane maintenance conversion stability optimization is used to improve the stability of scheduling the automated guided vehicle when the communication path conversion is performed. The communication link stability optimization comprises adjusting the track crane communication link bandwidth proportion and adjusting the communication load migration amount; The communication link bandwidth proportion factor is obtained by approaching degree analysis of the preset minimum bandwidth proportion obtained from the database and the track crane communication link bandwidth proportion; The communication load migration amount factor is obtained by approaching degree analysis of the non-scheduled data amount and the preset maximum data amount obtained from the database.

2. The method for dynamic combination maintenance decision-making and automated operation process optimization of terminal equipment as described in claim 1, characterized in that, The adjusting the track crane communication link bandwidth proportion means sending a prompt to the preset personnel to gradually reduce the track crane communication link bandwidth proportion by the corresponding amplitude of the track crane communication link optimization factor; The adjusting the communication load migration amount means sending a prompt to the preset personnel to gradually increase the number of idle links of the pre-equipment by the corresponding amplitude of the track crane communication link optimization factor, and migrating the non-automated guided vehicle scheduling data to the idle links of the pre-equipment; The track crane communication link optimization factor is obtained by proportion analysis of the link time difference value after the first maintenance state feedback and the preset link time difference value obtained from the database, and is used to adjust the stability of the fault maintenance signal transmission; The communication link stability optimization is used to reduce the instability of the communication link when scheduling the automated guided vehicle due to the track crane grabbing maintenance.

3. The method for dynamic combination maintenance decision-making and automated operation process optimization of terminal equipment as described in claim 1, characterized in that, The track crane maintenance conversion stability optimization comprises obtaining maintenance data switching accuracy characteristic values and setting standby link preheating compression levels; The specific process of obtaining the maintenance data switching accuracy characteristic values is as follows: The switching time and switching accuracy characteristic values are obtained by approaching degree analysis of the preset switching time and the switching time, which are used to reflect the influence of the switching time on the stability of the communication path conversion; The transmission success and switching accuracy characteristic values are obtained by approaching degree analysis of the number of maintenance signal transmission successes and the preset number of maintenance signal transmission successes, which are used to reflect the influence of the number of maintenance signal transmission successes on the stability of the communication path conversion; The transmission interruption and switching accuracy characteristic values are obtained by approaching degree analysis of the preset number of maintenance signal transmission interruptions and the number of maintenance signal transmission interruptions, which are used to reflect the influence of the number of maintenance signal transmission interruptions on the stability of the communication path conversion; The maintenance data switching accuracy characteristic values are obtained by weighting operation of the communication link switching stability data and the corresponding preset communication link switching factors, and then coupling processing; The maintenance data switching accuracy characteristic values are used to reflect the comprehensive influence of the communication link switching stability data and the preset communication link switching stability data on the stability of the communication path conversion; The preset communication link switching stability data comprises the switching time and switching accuracy characteristic values, the transmission success and switching accuracy characteristic values, and the transmission interruption and switching accuracy characteristic values; The preset communication link switching factor is used to reflect the influence degree of the communication link switching stability data on the maintenance data switching accuracy characteristic values; The communication link switching stability data comprises the switching time, the number of maintenance signal transmission successes, and the number of maintenance signal transmission interruptions.

4. The method for dynamic combination maintenance decision-making and automated operation process optimization of terminal equipment as described in claim 3, characterized in that, The maintenance data transmission stability optimization qualification degree is quantitatively evaluated based on the optimization result to determine whether to continue the automatic guided vehicle scheduling accuracy evaluation, and the specific process is as follows: Based on the maintenance data switching accuracy characteristic value and the preset maintenance data switching accuracy value obtained from the database, the approach degree analysis is performed to obtain a maintenance data switching accuracy judgment value; When the maintenance data switching accuracy judgment value is greater than 1, a communication link switching qualified prompt is sent, and the automatic guided vehicle scheduling accuracy evaluation is continued; When the maintenance data switching accuracy judgment value is not greater than 1, a communication link switching unqualified prompt is sent, and a standby link preheating compression level is set. When the maintenance data switching accuracy judgment value obtained after the standby link preheating compression level is set is still not greater than 1, a maintenance decision alarm prompt is sent.

5. The method for dynamic combination maintenance decision-making and automated operation process optimization of terminal equipment as described in claim 4, characterized in that, The specific process of setting the standby link preheating compression level is as follows: The preheating time is monitored, the preheating time represents the time required from switching to the standby communication link to the stable working state of the link, and the preheating time and the preset preheating time are compared to obtain the standby link preheating compression level; The standby link preheating compression level includes a first preheating time shortening level and a second preheating time shortening level; The first preheating time shortening level represents the level corresponding to the preheating time not greater than the preset preheating time divided by the preset preheating time as a standard; The second preheating time shortening level represents the level corresponding to the preheating time greater than the preset preheating time divided by the preset preheating time as a standard; A prompt is sent to a preset person to divide the maintenance data switching accuracy judgment value not greater than 1 into a maintenance data switching level, which includes a first maintenance data switching level and a second maintenance data switching level. The first maintenance data switching level corresponds to a range of the minimum value of the maintenance data switching accuracy judgment value and the minimum value of the preset switching range, and the minimum value of the maintenance data switching accuracy judgment value is less than the minimum value of the preset switching range. The second maintenance data switching level corresponds to a range of the maximum value of the maintenance data switching accuracy judgment value and the maximum value of the preset switching range, and the maximum value of the maintenance data switching accuracy judgment value is greater than the maximum value of the preset switching range; Switching and preheating matching is performed based on the maintenance data switching level and the standby link preheating compression level, which means sending a prompt to a preset person to match the first maintenance data switching level and the first preheating time shortening level, and match the second maintenance data switching level and the second preheating time shortening level; After switching and preheating matching, the second standby communication link switching is performed, which means that based on the result of switching and preheating matching, the communication link is switched again; After switching and preheating matching, the second standby communication link switching is performed, which means that based on the result of switching and preheating matching, the communication link is switched again; The maintenance data switching accuracy judgment value after the second backup communication link switching is obtained. If the maintenance data switching accuracy judgment value after the second backup communication link switching is still not greater than 1, the communication link switching is performed again. If the number of communication link switching is greater than the preset maximum switching value, and the maintenance data switching accuracy judgment value is still not greater than 1, a maintenance decision warning prompt is sent; If the maintenance data switching accuracy judgment value after the second backup communication link switching is greater than 1, a switching qualified prompt is sent, and the automatic guided vehicle scheduling accuracy evaluation is continued.

6. The method for dynamic combination maintenance decision and automation operation process optimization of port equipment according to claim 1, characterized in that, The automatic guided vehicle scheduling accuracy evaluation is performed based on the obtained automatic guided vehicle scheduling parameters, and the specific process is as follows: After the approaching degree analysis of the correct matching automatic guided vehicle quantity and the preset correct matching automatic guided vehicle quantity, the first scheduling accuracy characteristic value is obtained by weighting operation combined with the first scheduling accuracy factor, which is used to reflect the effect of the correct matching automatic guided vehicle quantity on the automatic guided vehicle loading and unloading operation scheduling accuracy after the track crane is maintained; After the approaching degree analysis of the preset average automatic guided vehicle scheduling position deviation and the average automatic guided vehicle scheduling position deviation, the second scheduling accuracy characteristic value is obtained by weighting operation combined with the second scheduling accuracy factor, which is used to reflect the effect of the average automatic guided vehicle scheduling position deviation on the automatic guided vehicle loading and unloading operation scheduling accuracy after the track crane is maintained; After the approaching degree analysis of the preset average track crane-scheduling task synchronization time delay and the average track crane-scheduling task synchronization time delay, the third scheduling accuracy characteristic value is obtained by weighting operation combined with the third scheduling accuracy factor, which is used to reflect the effect of the average track crane-scheduling task synchronization time delay on the automatic guided vehicle loading and unloading operation scheduling accuracy after the track crane is maintained; The automatic guided vehicle scheduling accuracy characteristic value is obtained by coupling the automatic guided vehicle scheduling data; The automatic guided vehicle scheduling accuracy characteristic value is used to reflect the effect of the automatic guided vehicle scheduling parameters and the preset automatic guided vehicle scheduling parameters on the automatic guided vehicle loading and unloading operation scheduling accuracy after the track crane is maintained.

7. The method for dynamic combination maintenance decision-making and automated operation process optimization of terminal equipment as described in claim 6, characterized in that, The automatic guided vehicle scheduling data includes the first scheduling accuracy characteristic value, the second scheduling accuracy characteristic value and the third scheduling accuracy characteristic value; The automatic guided vehicle scheduling parameters include the correct matching automatic guided vehicle quantity, the average automatic guided vehicle scheduling position deviation and the average track crane-scheduling task synchronization time delay; The preset automatic guided vehicle scheduling parameters include the preset loading and unloading scheduling parameters and the preset loading and unloading scheduling parameter factor; The preset loading and unloading scheduling parameters include the preset correct matching automatic guided vehicle quantity, the preset average automatic guided vehicle scheduling position deviation and the preset average track crane-scheduling task synchronization time delay; The preset loading and unloading scheduling parameter factor is used to reflect the influence degree of the automatic guided vehicle scheduling data on the automatic guided vehicle scheduling accuracy characteristic value.

8. The method for dynamic combination maintenance decision-making and automated operation process optimization of terminal equipment as described in claim 6, characterized in that, The automatic guided vehicle scheduling accuracy evaluation is performed based on the obtained automatic guided vehicle scheduling parameters to determine whether to perform the second maintenance state feedback, and the specific process is as follows: The preset automatic guided vehicle scheduling accuracy value is obtained from a database, and a difference comparison is performed based on the automatic guided vehicle scheduling accuracy characteristic value and the preset automatic guided vehicle scheduling accuracy value; When the automatic guided vehicle scheduling accuracy characteristic value is greater than the preset automatic guided vehicle scheduling accuracy value, a maintenance decision qualified prompt is sent; When the automatic guided vehicle scheduling accuracy characteristic value is not greater than the preset automatic guided vehicle scheduling accuracy value, a maintenance decision unqualified prompt is sent, and a second maintenance state feedback is performed; The second maintenance state feedback indicates that when the automatic guided vehicle scheduling accuracy characteristic value is not greater than the preset automatic guided vehicle scheduling accuracy value, a prompt is sent to preset personnel to re-perform the grabbing position calibration and maintenance.

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