Multi-motor Load Control Method for Warehouse Tool Magazine and Storage Medium

Abstract

The present invention relates to the technical field of automatic control of tool magazines, and particularly to a multi-motor load control method and a storage medium for a storage tool magazine. The method includes: collecting in real time the operation data of a first motor, a second motor and at least one redundant motor in the storage tool magazine to generate a first dynamic load index of the first motor and a second dynamic load index of the second motor; establishing a control strategy based on the first dynamic load index and the second dynamic load index; when the first dynamic load index exceeds the limit and the second dynamic load index is lower than the safety threshold, triggering a task migration rule to dynamically adjust the sub-task allocation; when both the first dynamic load index and the second dynamic load index exceed the limit, triggering a redundant motor activation rule to allocate high-load tasks to the redundant motor. Through the present invention, the problems of low efficiency and equipment overload risk caused by uneven load distribution in the traditional multi-motor system of the storage tool magazine are effectively solved.

Description

Technical Field

[0001] The present invention relates to the technical field of automatic control of tool magazines, and particularly to a multi-motor load control method and a storage medium for a storage tool magazine. Background Art

[0002] As one of the core components of a numerically controlled machine tool, the multi-motor system of a storage tool magazine is responsible for driving key actions such as tool access, positioning, and tool change mechanisms. Traditional control methods usually manage motor operation based on fixed task allocation rules or single-sensor threshold monitoring.

[0003] In the prior art, a pre-set motor start-stop timing or a static load threshold alarm mechanism is mostly adopted. For example, the shutdown protection is triggered by detecting whether the motor current exceeds a preset upper limit, or tasks are allocated to each motor according to a fixed ratio. However, such methods are difficult to dynamically respond to complex working condition changes such as sudden changes in tool replacement frequency and environmental temperature fluctuations, resulting in long-term overload operation of high-load motors, which causes life attenuation, while low-load motors are in an idle state, resulting in energy waste. At the same time, static threshold monitoring only intervenes after a fault occurs, and cannot prevent overload risks through real-time load balancing. Redundant motors also lack an intelligent activation strategy and cannot share sudden loads in time, ultimately leading to a decline in overall efficiency, an increase in maintenance costs, and inefficiencies and equipment overload risks caused by uneven load distribution among multiple motors.

[0004] The information disclosed in this background art section is only intended to deepen the understanding of the overall background art of the present disclosure, and should not be regarded as an admission or any form of suggestion that this information constitutes the prior art known to those skilled in the art. Summary of the Invention

[0005] The present invention provides a multi-motor load control method and a storage medium for a storage tool magazine, which can effectively solve the problems in the background art.

[0006] In order to achieve the above object, the technical solution adopted by the present invention is:

[0007] A multi-motor load control method for a storage tool magazine, the method includes:

[0008] Real-time collect the operation data of a first motor, a second motor and at least one redundant motor in the storage tool magazine, and generate a first dynamic load index of the first motor and a second dynamic load index of the second motor;

[0009] Based on the first dynamic load index and the second dynamic load index, establish a control strategy;

[0010] When the first dynamic load index exceeds the limit and the second dynamic load index is lower than the safety threshold, trigger a task migration rule and dynamically adjust the subtask allocation;

[0011] When both the first dynamic load index and the second dynamic load index exceed the limit, trigger the redundant motor activation rule and allocate high-load tasks to the redundant motor;

[0012] During the execution process, according to the control strategy and the operation data, adjust the operation parameters and queue priorities of the first motor, the second motor, and the redundant motor, and update the dynamic load index in real time.

[0013] Furthermore, establish a control strategy, including:

[0014] When the first dynamic load index is greater than the first threshold and the second dynamic load index is less than the second threshold, determine the number of subtasks migrated from the first motor to the second motor according to the difference between the first dynamic load index and the second dynamic load index;

[0015] Based on the remaining load capacity of the second motor, insert the subtasks into the task queue of the second motor in a weighted allocation manner;

[0016] When both the first dynamic load index and the second dynamic load index are greater than the third threshold, activate the redundant motor and start the pre-start verification process;

[0017] If the verification passes, allocate the tasks ranked top N in terms of load weight in the task queues of the first motor and the second motor to the redundant motor, where N is determined by the maximum load capacity of the redundant motor.

[0018] Furthermore, inserting the subtasks into the task queue of the second motor in a weighted allocation manner includes:

[0019] Dynamically allocate the insertion priority of the subtasks in the task queue according to the load weight of the subtasks and the remaining load capacity of the second motor, where the subtasks with higher load weights are preferentially inserted into the idle period;

[0020] Real-time calculate the predicted load index of the second motor after inserting the subtasks. If the predicted load index exceeds the second threshold, remove some of the subtasks in ascending order of load weight until the remaining capacity constraint is met;

[0021] Insert the determined subtasks into the task queue, update the remaining load capacity of the second motor, and synchronously trigger the recalculation of the dynamic load index of the first motor to verify the task migration effect.

[0022] Furthermore, the determination of the first threshold, the second threshold, and the third threshold includes:

[0023] Analyze historical operation data and count load fluctuation ranges of the first motor and the second motor under normal operating conditions;

[0024] Based on the average value and distribution width of the load fluctuation range, setting the initial first threshold, the second threshold and the third threshold;

[0025] Real-time detection of environmental variables, when the ambient temperature exceeds the rated operating temperature range, reducing the values of the first threshold and the third threshold, the reduction amplitude being proportional to the temperature excess;

[0026] When the power supply voltage fluctuation rate exceeds a safe range, increasing the value of the second threshold to increase the conservatism of task migration;

[0027] Based on the predicted load change trend of the task queue in the future time period, if the load continues to increase, the first threshold and the third threshold are increased in advance according to the predicted increase ratio.

[0028] Furthermore, the effect of task migration is verified, including:

[0029] After the task queue of the second motor is updated, recalculating the first dynamic load index of the first motor and the second dynamic load index of the second motor;

[0030] generating a secondary migration instruction or a task migration instruction based on the recalculated first dynamic load index and the second dynamic load index;

[0031] The secondary migration instruction triggers the migration of additional subtasks from the first motor to the second motor or the redundant motor;

[0032] The task migration instruction triggers reverse migration of part of the subtasks of the second motor to the first motor;

[0033] According to the execution result of the secondary migration instruction or the task relocation instruction, updating the weight allocation rule and the remaining capacity reservation parameter in the control strategy;

[0034] The updated weight allocation rule and the remaining capacity reservation parameter are synchronized to the multi-source data fusion model to dynamically generate a load index of the corresponding motor.

[0035] Further, generating a first dynamic load index of the first motor and a second dynamic load index of the second motor includes:

[0036] Dynamically allocating weight coefficients of the current signal, the vibration signal, and the temperature signal according to the real-time operating conditions of the first motor and the second motor;

[0037] When the first motor is in the high-frequency tool change stage, the weight coefficient of the vibration signal of the first motor is increased;

[0038] When the temperature signal of the second motor continuously exceeds the rated temperature rise rate, the weight coefficient of the temperature signal of the second motor is preferentially increased;

[0039] Based on the corresponding weight coefficients, the current signal, the vibration signal, and the temperature signal are weighted and fused to generate the first dynamic load index of the first motor and the second dynamic load index of the second motor respectively.

[0040] Further, the adjustment range of the weight coefficient includes:

[0041] The volatility of the first dynamic load index and the second dynamic load index is monitored in real time, and according to the duration of the excess of the volatility, the weight adjustment range is divided into multiple increasing levels;

[0042] When the duration of the volatility exceeding the limit is in the first interval, the weight coefficient of the signal with the largest volatility is reduced according to the first adjustment range;

[0043] When the duration of the volatility exceeding the limit is in the second interval, the weight coefficient is reduced according to the second adjustment range, and the second adjustment range is greater than the first adjustment range;

[0044] When the duration of the volatility exceeding the limit reaches the third interval, the weight coefficients of all signals are reset to the initial values and a global load evaluation calibration is triggered.

[0045] Further, the determination basis of the high-frequency tool change stage includes:

[0046] The number of tool changes of the first motor within a time window is statistically counted in real time. If the number of tool changes exceeds the critical value, it is determined as the high-frequency tool change stage;

[0047] When the number of tool change instructions to be executed in the current task queue of the storage tool magazine reaches the density limit, the critical value is dynamically lowered to trigger the determination of the high-frequency tool change stage in advance;

[0048] A dynamic correction coefficient is generated according to the historical tool change data, and the critical value is periodically adjusted. The dynamic correction coefficient is negatively correlated with the historical average tool change frequency of the first motor.

[0049] A computer-readable storage medium stores computer instructions thereon, and the computer instructions are used to cause a computer to execute the multi-motor load control method for the storage tool magazine.

[0050] Through the technical solution of the present invention, the following technical effects can be achieved:

[0051] Through the dynamic load evaluation and real-time closed-loop control strategy, the adaptive load balance of multi-motor collaborative work is realized, the operation efficiency of the warehouse tool magazine is improved, the motor failure rate is reduced, and the service life of the equipment is extended.

[0052] The above description is only an overview of the technical solution of this application. In order to be able to understand the technical means of this application more clearly, it can be implemented according to the content of the specification. And in order to make the above and other purposes, features and advantages of this application more obvious and understandable, the specific implementation manners of this application are specifically given below. Brief Description of the Drawings

[0053] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments recorded in the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0054] Figure 1 It is a schematic flow chart of the multi-motor load control method for the warehouse tool magazine;

[0055] Figure 2 It is a schematic flow chart of the control strategy;

[0056] Figure 3 It is a schematic flow chart of inserting tasks into the task queue according to the weight distribution method;

[0057] Figure 4 It is a schematic flow chart of generating the dynamic load index. Detailed Description of the Embodiments

[0058] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments.

[0059] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which this invention belongs. The terms used in the description of this invention are only for the purpose of describing specific embodiments, and are not intended to limit this invention. The term "and / or" used herein includes any and all combinations of one or more of the related listed items.

[0060] Embodiment 1;

[0061] Such as Figure 1As shown, the present application provides a multi-motor load control method for a warehousing tool magazine. The method includes:

[0062] S10: Real-time collect the operation data of the first motor, the second motor and at least one redundant motor in the warehousing tool magazine, and generate a first dynamic load index of the first motor and a second dynamic load index of the second motor;

[0063] S20: Based on the first dynamic load index and the second dynamic load index, establish a control strategy;

[0064] S30: When the first dynamic load index exceeds the limit and the second dynamic load index is lower than the safety threshold, trigger a task migration rule and dynamically adjust the subtask allocation;

[0065] S40: When both the first dynamic load index and the second dynamic load index exceed the limit, trigger a redundant motor activation rule and allocate high-load tasks to the redundant motor;

[0066] S50: During the execution process, according to the control strategy and the operation data, adjust the operation parameters and queue priorities of the first motor, the second motor and the redundant motor, and update the dynamic load index in real time.

[0067] Specifically, first, it is necessary to collect in real time the operation data of the first motor, the second motor, and at least one redundant motor in the warehouse tool magazine. The operation data usually includes sensor data such as the current, temperature, and vibration of the motor. These data will be used to generate the first dynamic load index and the second dynamic load index. These dynamic load indexes are calculated through multi-source data fusion technology (such as weighted fusion of current, vibration, and temperature signals), reflecting the working load state of the motor. According to the generated first dynamic load index and second dynamic load index, next, it is necessary to establish a control strategy based on the first dynamic load index and the second dynamic load index. The core of the control strategy is to determine the working load state of each motor, compare the load indexes of the first motor and the second motor to judge whether they exceed the limit, and determine whether it is necessary to adjust the task allocation and start the redundant motor. When the dynamic load index of the first motor exceeds the limit and the load of the second motor is lower than the safety threshold, the task migration rule is triggered, which is manifested as migrating some subtasks from the overloaded first motor to the second motor with a lighter load. The number of migrated tasks is dynamically determined based on the difference between the load indexes of the first motor and the second motor and the remaining load capacity of the second motor. When the loads of both the first and second motors exceed the set threshold, the redundant motor will be activated. At this time, the redundant motor is started and the high-load tasks are assigned to the redundant motor. The selection of the redundant motor is based on its maximum load capacity and the requirements of the current task queue. During the execution process, according to the operation data collected in real time and the pre-established control strategy, the operation parameters of all motors are dynamically adjusted, such as the speed, load, etc. of the motor, as well as the queue priority and the allocation priority of tasks among different motors. If task migration occurs or the redundant motor is activated, these parameters and priorities need to be updated in real time. In addition, the dynamic load indexes of all motors will be updated according to real-time changes to ensure the adaptability of the control strategy.

[0068] Through the technical solution of the present invention, based on dynamic load assessment and real-time closed-loop control strategy, the adaptive load balancing of multi-motor collaborative work is realized, the operation efficiency of the warehouse tool magazine is improved, the motor failure rate is reduced, and the service life of the equipment is extended.

[0069] Furthermore, as Figure 2 shown, establishing a control strategy includes:

[0070] When the first dynamic load index is greater than the first threshold and the second dynamic load index is less than the second threshold, determine the number of subtasks migrated from the first motor to the second motor according to the difference between the first dynamic load index and the second dynamic load index;

[0071] Based on the remaining load capacity of the second motor, insert the subtasks into the task queue of the second motor in a weighted allocation manner;

[0072] When both the first dynamic load index and the second dynamic load index are greater than the third threshold, activate the redundant motor and start the pre-start verification process;

[0073] If the verification passes, assign the tasks ranked top N in the task queues of the first motor and the second motor to the redundant motor, where N is determined by the maximum load capacity of the redundant motor.

[0074] As a preference of the above embodiments, when the first dynamic load index is greater than the first threshold and the second dynamic load index is less than the second threshold, the number of subtask migrations is determined. In this scenario, it is first necessary to determine whether the first dynamic load index and the second dynamic load index respectively exceed the preset thresholds. If the first dynamic load index is greater than the first threshold, it indicates that the load of the first motor is too high and it may face an overload risk. If the second dynamic load index is less than the second threshold, it means that the load of the second motor is relatively low and it has sufficient load capacity to handle additional tasks. Next, the number of subtasks to be migrated from the first motor to the second motor is determined. Based on the difference between the first dynamic load index and the second dynamic load index (i.e., the load gap), a suitable number of subtasks is calculated. This calculation usually takes into account the proportion of the load gap, that is, the larger the load gap, the more tasks may be migrated. And the load capacity of the second motor, the number of task migrations cannot exceed the remaining load capacity of the second motor. For example, when the load index of the first motor is 100% (overloaded) and the load index of the second motor is 40% (far from overloaded), it can be decided to migrate 10 subtasks to ensure load balance. After calculating the number of subtasks to be migrated, these subtasks need to be inserted into the task queue of the second motor. To ensure reasonable task allocation and maximize the motor load utilization efficiency, a weight allocation method is adopted. Subtasks can be weighted and allocated according to factors such as priority, task difficulty, and resource requirements. If the remaining load capacity of the second motor is relatively large, more subtasks can be allocated.If the remaining capacity is small, the allocation quantity needs to be reduced. In actual operation, the insertion of subtasks may need to be adjusted according to the task priorities in the queue to ensure that important tasks are processed first. In another scenario, when both the first dynamic load index and the second dynamic load index exceed the third threshold, it indicates that the loads of the two main motors are both approaching or exceeding the maximum capacity, and the redundant motor will be activated. The process of activating the redundant motor includes starting a pre-start verification process, which mainly checks whether the redundant motor is working properly, including whether its electrical and mechanical systems are normal and whether its load-bearing capacity meets the requirements. The verification process may include the detection of voltage, temperature, vibration, etc., as well as the self-check process of each component of the motor and the verification of the system status to ensure that the redundant motor can operate stably under high load conditions. Once the redundant motor passes the verification, it can enter the task allocation stage. From the task queues of the first motor and the second motor, select the top N tasks with the highest load weights and allocate them to the redundant motor. The value of N is determined by the maximum load capacity of the redundant motor to ensure that the redundant motor does not work overloaded. The calculation method of N usually considers the current remaining load capacity of the redundant motor and the priorities of the tasks to ensure reasonable task allocation within the capacity range of the redundant motor. For example, assume that the maximum load capacity of the redundant motor is 60%, and there are 20 tasks in each of the task queues of the first and second motors. Then select the top 10 tasks with the highest load weights (ensuring that the load of the redundant motor does not exceed its maximum load capacity) and allocate these tasks to the redundant motor. During the entire implementation process, continuously monitor the load status of the motors in real time and make dynamic adjustments according to the load index. Through the reasonable migration of tasks and the activation of redundant motors, it is possible to avoid overloading of a single motor and ensure that all tasks can be processed in a timely manner. In the case of low load, tasks will be dynamically migrated from high-load motors to low-load motors. In the case of high load, redundant motors will be activated to undertake part of the tasks, further optimizing resource utilization.

[0075] Furthermore, as Figure 3 shown, inserting subtasks into the task queue of the second motor according to the weight allocation method includes:

[0076] Dynamically allocate the insertion priority of subtasks in the task queue according to the load weight of the subtasks and the remaining load capacity of the second motor, where subtasks with higher load weights are preferentially inserted into the idle time slots;

[0077] Real-time calculate the predicted load index of the second motor after inserting the subtasks. If the predicted load index exceeds the second threshold, sequentially remove some subtasks from the lowest to the highest load weight until the remaining capacity constraint is met;

[0078] Insert the determined subtasks into the task queue, update the remaining load capacity of the second motor, and synchronously trigger the recalculation of the dynamic load index of the first motor to verify the task migration effect.

[0079] As an optimization of the above embodiments, when inserting subtasks into the task queue of the second motor, it is first necessary to dynamically determine the insertion priority according to the load weight of each subtask and the remaining load capacity of the second motor. Each subtask has a weight value related to its workload. Generally, the heavier the task load, the more motor resources are required. The remaining load capacity of the second motor determines whether more subtasks can be received and how many tasks can be received. If the remaining capacity of the motor is large, more tasks can be inserted; if the remaining capacity is small, task insertion needs to be restricted. On this basis, tasks with higher load weights should be inserted into the queue first and arranged during the idle period of the motor. The idle period refers to the time period when the second motor has a lighter load during its working cycle. Inserting high-load tasks at this time can effectively avoid overloading. After the subtasks are inserted into the task queue according to the priority, it is necessary to calculate the predicted load index of the second motor after inserting the subtasks in real time. The predicted load index is calculated based on the current load situation, that is, the tasks that the second motor has processed, the remaining capacity, and the load of the newly inserted subtasks, that is, the load impact of each newly inserted subtask on the motor. If the predicted load index exceeds the second threshold, it means that the load of the second motor has approached or exceeded its bearing capacity. At this time, the task queue needs to be adjusted. When the predicted load index exceeds the second threshold, some subtasks are removed in ascending order of load weight until the load of the motor meets the remaining capacity constraint. This process requires sorting the subtasks in the task queue and preferentially removing subtasks with lower loads to try to retain those high-load and more important tasks. For example, assuming that the predicted load index of the second motor exceeds the standard, subtasks with smaller load weights are removed from the queue until the load of the second motor is reduced below the safety threshold. After ensuring that the subtasks can be reasonably inserted and the load is adjusted, the determined subtasks are inserted into the task queue of the second motor. After the tasks are inserted, the remaining load capacity of the second motor is updated to reflect the current load situation. The updated load capacity will affect the scheduling of subsequent tasks. If the remaining capacity is insufficient, more task migrations may be adjusted according to the load strategy or redundant motors may be started. To verify the effect of task migration, the dynamic load index of the first motor is synchronously triggered to recalculate. This step is to confirm the load change of the first motor after task migration and check whether the load balance is optimized. If the load of the first motor is still in a high-load state, it may be necessary to further adjust the task allocation or activate redundant motors. If the load is effectively balanced, it is considered that the task migration is effective and the task queue allocation is successful.

[0080] Furthermore, the determination of the first threshold, the second threshold, and the third threshold includes:

[0081] Analyze the historical operation data and count the load fluctuation ranges of the first motor and the second motor under normal working conditions;

[0082] Set initial first threshold, second threshold and third threshold based on the average value and distribution width of the load fluctuation range;

[0083] Detect environmental variables in real time. When the environmental temperature exceeds the rated operating temperature range, reduce the values of the first threshold and the third threshold, and the reduction amplitude is proportional to the temperature excess;

[0084] When the power supply voltage volatility exceeds the safe range, increase the value of the second threshold to increase the conservativeness of task migration;

[0085] Based on the predicted load change trend of the task queue in the future time period, if the load continues to increase, adjust up the first threshold and the third threshold in advance according to the predicted increase ratio.

[0086] As a preference of the above embodiments, it is necessary to collect the operation data of the first motor and the second motor under normal working conditions. These data usually include indicators such as the load, current, rotation speed, and temperature of the motor. By analyzing these historical data, the load fluctuation range can be obtained, that is, under normal working conditions, the maximum fluctuation range of the motor load, as well as the average value and distribution width of the load fluctuation, that is, calculate the average value and distribution width (standard deviation or variance) of the load, which provides a reference for threshold setting. The analysis of these historical data can help us determine reasonable first, second, and third thresholds, avoid these thresholds being too conservative or too loose, and ensure that the motor can operate stably under normal operating conditions; according to the load fluctuation range, average value, and distribution width analyzed from the historical operation data, set the first threshold for judging whether the first motor is overloaded, usually set near the upper limit of the load fluctuation range of the first motor; set the second threshold for judging whether the second motor is close to overload, set at the upper limit of the normal working load of the second motor; set the third threshold for triggering the activation of the redundant motor, usually set at a certain critical point of the loads of the two motors to ensure that the redundant motor can intervene in time when the load is too heavy; in actual operation, the ambient temperature may affect the working performance of the motor. When the ambient temperature exceeds the rated working temperature range of the motor, the load-bearing capacity of the motor may decrease. Therefore, it is necessary to monitor the ambient temperature in real time and dynamically adjust the thresholds when it exceeds the rated working temperature, such as reducing the values of the first threshold and the third threshold. In order to avoid overloading the motor under high-temperature conditions, correspondingly reduce the first threshold and the third threshold to reduce the risk of motor overload; or the reduction amplitude is proportional to the temperature excess, and the adjustment amplitude is determined according to the degree of temperature exceeding the rated value; when the power supply voltage volatility exceeds the safe range, the performance of the motor may be affected, resulting in an increase in load fluctuation. In order to avoid frequent task migrations of the motor under power supply fluctuations, increase the second threshold to allow more load changes, thereby reducing frequent load migrations, or increase the amplitude of the threshold proportional to the amplitude of the voltage fluctuation. For example, if the power supply voltage fluctuation exceeds the safe range by 5%, the second threshold can be increased by 5%; predict the task queue in the next period of time to judge whether the task load will continue to increase. The load prediction can be analyzed through factors such as the nature, quantity, and priority of the tasks. For example, if the task quantity increases, or some high-load tasks are about to be executed, the system can predict the load change in advance; if it is predicted that the load will continue to increase, adjust the thresholds in advance. In order to avoid frequent overload of the motor due to load increase, increase the first threshold and the third threshold in advance to give the motor more load tolerance space and avoid premature triggering of task migrations or activation of redundant motors. The upward adjustment amplitude of the threshold is determined based on the predicted load increase ratio.

[0087] Furthermore, verifying the task migration effect includes:

[0088] After the task queue of the second motor is updated, recalculating the first dynamic load index of the first motor and the second dynamic load index of the second motor;

[0089] Generate a secondary migration instruction or a task migration instruction based on the recalculated first dynamic load index and the second dynamic load index;

[0090] The secondary migration instruction triggers the migration of the additional subtask from the first motor to the second motor or the redundant motor;

[0091] The task migration instruction triggers the reverse migration of part of the subtasks of the second motor to the first motor;

[0092] According to the execution result of the secondary migration instruction or the task re-migration instruction, the weight allocation rule and the remaining capacity reservation parameter in the control strategy are updated;

[0093] The updated weight allocation rules and the remaining capacity reservation parameters are synchronized to the multi-source data fusion model to dynamically generate the load index of the corresponding motor.

[0094] As a preferred embodiment of the above, after the task queue of the second motor is updated, the dynamic load indexes of the two motors are recalculated, namely, the first dynamic load index of the first motor and the second dynamic load index of the second motor. These load indices reflect the current workload of the motors, taking into account the changes in tasks and the current ability of the motors to handle tasks. The calculation of the load index may involve considering the complexity of the task, the execution time, the current load of the motor, and the performance of the motor; based on the recalculated load index, it is determined whether the task needs to be migrated or whether the task needs to be migrated back; secondary migration instruction: when the load of the first motor is too high and the second motor or the redundant motor has sufficient idle resources, the task is triggered to migrate from the first motor to the second motor or the redundant motor, and additional sub-task migration is performed; task migration instruction: when the load of the second motor is too high, some tasks may need to be migrated back from the second motor to the first motor to balance the load of the two motors; secondary migration instruction: according to the current load situation, the task migration is triggered from the first motor to the second motor or the redundant motor. Transfer additional subtasks to the first motor to ensure that the load of the motor is balanced; Task migration instruction: When the load of the second motor exceeds expectations, some tasks will be migrated from the second motor to the first motor to help reduce the load pressure of the second motor; According to the execution results of the secondary migration instruction or the task migration instruction, update the weight allocation rules and remaining capacity reservation parameters in the load control strategy; According to the load situation after migration, adjust the task allocation weights of different motors to ensure that the load can be reasonably allocated according to the performance and current status of the motor; Remaining capacity reservation parameters, consider the remaining available resources of the motor, update the reserved capacity parameters to avoid excessive load, and ensure that the motor will not have insufficient resources during task execution; The updated weight allocation rules and remaining capacity reservation parameters are synchronized to the multi-source data fusion model. This fusion model combines real-time data from multiple motors to dynamically adjust the load index of each motor. The dynamically generated load index reflects the current load situation of each motor and guides subsequent task allocation and migration decisions.

[0095] Further, if Figure 4 As shown, generating a first dynamic load index of the first motor and a second dynamic load index of the second motor includes:

[0096] Dynamically allocating weight coefficients of the current signal, the vibration signal, and the temperature signal according to the real-time operating conditions of the first motor and the second motor;

[0097] When the first motor is in the high-frequency tool-changing stage, the weight coefficient of the vibration signal of the first motor is increased;

[0098] When the temperature signal of the second motor continues to exceed the rated temperature rise rate, the weight coefficient of the temperature signal of the second motor is preferentially increased;

[0099] Based on the corresponding weight coefficients, the current signal, vibration signal, and temperature signal are weighted and fused to generate the first dynamic load index of the first motor and the second dynamic load index of the second motor, respectively.

[0100] As a preference of the above embodiments, when generating the dynamic load index, it is necessary to comprehensively consider various sensor signals (such as current signals, vibration signals, and temperature signals). Since the importance of these signals varies under different working conditions, it is necessary to dynamically adjust the weight coefficient of each signal according to the real-time working conditions of the motor. These signals reflect the load, operating status, and health status of the motor; the current signal reflects the load of the motor. When the motor load is high, the weight coefficient of the current signal will be increased; the vibration signal reflects the mechanical health status of the motor. Usually, when there is mechanical wear or abnormal vibration in the motor, the weight coefficient of the vibration signal should be increased to detect faults in time; the temperature signal reflects the thermal state of the motor. If the motor is in a high-temperature environment for a long time, it may cause overload or damage. Therefore, the weight coefficient of the temperature signal also needs to be adjusted according to the working state and temperature change of the motor; when the first motor is in the high-frequency tool change stage, the load of the motor fluctuates greatly during the tool change process. The vibration signal is crucial for judging the load and health status of the motor. Therefore, the weight coefficient of the vibration signal is increased. During the high-frequency tool change stage, the change of the vibration signal may be more intense. Therefore, it is necessary to increase the weight coefficient of the vibration signal, which helps to more accurately reflect the operating condition of the motor under high load. For example, when the first motor is in the high-frequency tool change stage, the weight coefficient of the vibration signal is increased to ensure that the change of vibration receives more attention and emphasis; for the second motor, the temperature signal reflects the heat dissipation status of the motor. When the temperature of the motor continuously exceeds the rated temperature rise rate, it indicates that the motor may be in a state of high load or insufficient heat dissipation. At this time, the temperature signal becomes particularly important. Therefore, the weight coefficient of the temperature signal is preferentially increased. If the temperature exceeds the preset rate threshold, the weight coefficient of the temperature signal is increased to strengthen the influence of temperature on the calculation of the load index; according to the dynamically adjusted weight coefficients, the current signal, vibration signal, and temperature signal are weighted and fused. This means that each signal will contribute to the calculation of the load index according to its current weight coefficient. The current signal, vibration signal, and temperature signal are respectively real-time data obtained from sensors according to the real-time working conditions of the motor; for the first motor, the first dynamic load index is dynamically calculated according to its real-time working conditions (including load, vibration, temperature, etc.). When the motor is in different working conditions, the weight coefficients of the signals will change dynamically, so as to obtain a more accurate load index. If the first motor is performing a high-frequency tool change operation, the weight of the vibration signal will be relatively increased. If the current signal of the first motor indicates that its load is high, the weight of the current signal will be appropriately increased to ensure that the load change is reflected; similarly, the second dynamic load index of the second motor is calculated based on the weighted fusion of the current, vibration, and temperature signals. According to the change of the working conditions, the weight coefficients of each signal are adjusted in real time. If the temperature signal of the second motor continuously rises and exceeds the predetermined temperature rise rate, the weight coefficient of the temperature signal will be preferentially increased. If the current signal of the second motor changes greatly, indicating a large load fluctuation, the weight of the current signal will be increased.

[0101] Furthermore, the adjustment range of the weight coefficient includes:

[0102] Real-time monitor the volatility of the first dynamic load index and the second dynamic load index, and divide the weight adjustment range into multiple increasing levels according to the duration of the volatility exceeding the limit;

[0103] When the duration of the volatility exceeding the limit is in the first interval, reduce the weight coefficient of the signal with the largest volatility by the first adjustment range;

[0104] When the duration of the volatility exceeding the limit is in the second interval, reduce the weight coefficient by the second adjustment range, and the second adjustment range is greater than the first adjustment range;

[0105] When the duration of the volatility exceeding the limit reaches the third interval, reset the weight coefficients of all signals to the initial values and trigger a global load evaluation and calibration.

[0106] Preferably, as in the above embodiments, it is necessary to continuously monitor the volatility of the dynamic load indices of the first motor and the second motor, that is, the change amplitude of their load indices within a unit time. Specifically, by sampling the load indices at regular intervals and calculating the change amount of the load indices, the volatility is obtained. When the load index fluctuation exceeds a predetermined threshold, the system starts to record the duration of the overlimit. Once the load index volatility exceeds the set threshold (for example, the fluctuation exceeds 10% per second), the timing starts, and the duration of this fluctuation overlimit state is recorded. This duration determines the subsequent weight adjustment. The length of the volatility duration will determine the way of weight adjustment. The duration is divided into three intervals, and each interval corresponds to a different weight adjustment strategy. The first interval is short-term fluctuation. When the duration of the volatility overlimit is short, it is considered that the motor may have only experienced a short-term perturbation, and usually no significant adjustment is required. Identify the signal with the largest volatility (current, vibration or temperature signal), and according to the fluctuation of this signal, reduce the weight coefficient of this signal by the first adjustment amplitude. The second interval is medium-term fluctuation. When the duration of the volatility overlimit is of medium length, it indicates that the motor load may have changed significantly or is under certain pressure. Identify the signal with the largest volatility, and according to the fluctuation of this signal, reduce the weight coefficient of this signal by the second adjustment amplitude. The second adjustment amplitude is larger than the first adjustment amplitude. The third interval is long-term continuous fluctuation. If the volatility continuously exceeds the limit, it indicates that there may be serious problems with the motor load, which may lead to instability or overload. At this time, reset the weight coefficients of all signals to the initial values. This operation makes the weights of all signals return to the initial set values, re-evaluate the current working load of the motor, detect the health status of the motor, adjust the load control strategy of the motor, and calibrate the signals of all sensors. The core purpose of the global load evaluation and calibration process is to ensure that the motor does not continue to be in an unstable state by re-sampling data, detecting abnormal behaviors and the health status of the motor. To ensure that there are corresponding response mechanisms in different fluctuation ranges, the weight adjustment amplitude is designed as an increasing structure.

[0107] Furthermore, the determination basis for the high-frequency tool change stage includes:

[0108] Real-time statistics of the number of tool changes of the first motor within a time window. If the number of tool changes exceeds the critical value, it is determined that it is in the high-frequency tool change stage;

[0109] When the number of tool change instructions to be executed in the current task queue of the storage tool magazine reaches the density limit, the critical value is dynamically lowered to trigger the determination of the high-frequency tool change stage in advance;

[0110] Generate a dynamic correction coefficient based on historical tool change data, and periodically adjust the critical value. The dynamic correction coefficient is negatively correlated with the historical average tool change frequency of the first motor.

[0111] As a preference of the above embodiments, first, the number of tool changes of the first motor within a set time window is statistically recorded in real time. The time window can be of a fixed length. Each time the first motor completes a tool change operation, a tool change event is recorded. At the end of each time window, the total number of tool changes within the current window is counted. If this number exceeds the set critical value, it is determined that the first motor enters the high-frequency tool change stage. Under normal circumstances, the critical value is a fixed number. However, if a dense queue of tool change tasks has been detected currently, the high-frequency tool change stage needs to be triggered in advance. For example, by continuously monitoring the current task queue of the storage tool magazine, when the number of tool change instructions to be executed reaches the preset density upper limit within a unit time, it indicates that frequent tool change operations will occur in the future. At this time, the original critical value will be dynamically lowered, so as to determine that the first motor enters the high-frequency tool change stage earlier. To improve the scientificity and adaptability of the critical value setting, a dynamic correction coefficient based on historical tool change data is introduced, which specifically includes collecting and analyzing historical tool change data, regularly analyzing the historical tool change frequency of the first motor, daily tool change count statistics, and average tool change interval. Based on the analysis results, a dynamic correction coefficient is generated. The dynamic correction coefficient is negatively correlated with the historical average tool change frequency. That is, when the historical average tool change frequency is high, to avoid frequent entry into the high-frequency tool change judgment state, the critical value is increased. When the historical average tool change frequency is low, the critical value is decreased to be more sensitive to changes. The dynamic correction coefficient can be updated daily, weekly, or according to the task cycle, and is applied to the dynamic adjustment of the critical value, so as to have long-term self-adaptive adjustment ability. Considering the above bases comprehensively, a judgment process is constructed: First, real-time tool change statistics are performed to determine whether the number of tool changes within the current time window exceeds the critical value. Second, the density analysis of the task queue is carried out. If the task density is high, the critical value is dynamically decreased. Third, historical data-driven, the critical value is periodically corrected according to the tool change frequency trend. Once the currently statistically recorded number of tool changes exceeds the corrected critical value, it is determined to be in the high-frequency tool change stage. Subsequently, the weight coefficient of the vibration signal of the first motor is increased, which is used as an important reference for subsequent load index judgment.

[0112] Embodiment 2;

[0113] Based on the same inventive concept as a multi-motor load control method for a storage tool magazine in the foregoing embodiments, the present invention also provides a computer-readable storage medium, on which computer instructions are stored, and the computer instructions are used to cause a computer to execute the multi-motor load control method for a storage tool magazine.

[0114] The above storage medium in the present invention can effectively implement the multi-motor load control method for a storage tool magazine, and the technical effects that can be achieved are as described in the above embodiments, which will not be elaborated here.

[0115] Although the present application has been described in connection with specific features and their embodiments, it will be apparent that various modifications and combinations can be made without departing from the spirit and scope of the present application. Accordingly, the present specification and the drawings are merely exemplary illustrations of the present application as defined by the appended claims and are considered to cover any and all modifications, variations, combinations, or equivalents within the scope of the present application. Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalent technologies, the present application is intended to include these changes and modifications.

Claims

1. A multi-motor load control method for a storage tool magazine, characterized in that The method includes: Collecting in real time the operation data of a first motor, a second motor and at least one redundant motor in a warehousing tool magazine, and generating a first dynamic load index of the first motor and a second dynamic load index of the second motor, including: Dynamically allocating weight coefficients of a current signal, a vibration signal and a temperature signal according to the real-time working conditions of the first motor and the second motor; When the first motor is in the high-frequency tool change stage, increasing the weight coefficient of the vibration signal of the first motor; When the temperature signal of the second motor continuously exceeds the rated temperature rise rate, preferentially increasing the weight coefficient of the temperature signal of the second motor; Based on the corresponding weight coefficients, performing weighted fusion on the current signal, the vibration signal and the temperature signal to respectively generate the first dynamic load index of the first motor and the second dynamic load index of the second motor; Monitoring in real time the volatility of the first dynamic load index and the second dynamic load index, dividing the weight adjustment range into multiple increasing levels according to the duration of the exceeded volatility, dividing the duration into three intervals, and each interval corresponding to a different weight adjustment strategy; When the duration of the exceeded volatility is in the first interval, reducing the weight coefficient of the signal with the largest volatility by a first adjustment range; When the duration of the exceeded volatility is in the second interval, reducing the weight coefficient by a second adjustment range, and the second adjustment range is greater than the first adjustment range; When the duration of the exceeded volatility reaches the third interval, resetting the weight coefficients of all signals to the initial values and triggering a global load evaluation and calibration. If the volatility continuously exceeds the limit, re-evaluating the working load of the current motor, detecting the health condition of the motor, adjusting the load control strategy of the motor, and calibrating the signals of all sensors; Wherein, the first interval is short-term fluctuation, the second interval is medium-term fluctuation, and the third interval is long-term continuous fluctuation; Establishing a control strategy based on the first dynamic load index and the second dynamic load index; When the first dynamic load index exceeds the limit and the second dynamic load index is lower than the safety threshold, triggering a task migration rule and dynamically adjusting the sub-task allocation; When both the first dynamic load index and the second dynamic load index exceed the limit, triggering a redundant motor activation rule and allocating high-load tasks to the redundant motor; During the execution process, adjusting the operation parameters and queue priorities of the first motor, the second motor and the redundant motor according to the control strategy and the operation data, and updating the dynamic load index in real time.

2. The multi-motor load control method for a storage tool magazine according to claim 1, wherein Establishing a control strategy includes: When the first dynamic load index is greater than a first threshold and the second dynamic load index is less than a second threshold, determining the number of sub-tasks migrated from the first motor to the second motor according to the difference between the first dynamic load index and the second dynamic load index; Based on the remaining load capacity of the second motor, inserting the sub-tasks into the task queue of the second motor in a weight allocation manner; When the first dynamic load index and the second dynamic load index are both greater than a third threshold, activating the redundant motor and starting a pre-start verification process; If the verification is passed, the tasks with the top N load weights in the task queues of the first motor and the second motor are allocated to the redundant motor, where N is determined by the maximum load capacity of the redundant motor.

3. The multi-motor load control method for a storage tool magazine according to claim 2, wherein, Inserting the subtask into the task queue of the second motor in a weight distribution manner includes: According to the load weight of the subtask and the remaining load capacity of the second motor, dynamically assigning the insertion priority of the subtask in the task queue, wherein the subtask with a higher load weight is preferentially inserted into the idle period; Calculating in real time the predicted load index of the second motor after inserting the subtask, and if the predicted load index exceeds the second threshold, removing some of the subtasks in order from low to high according to the load weights until the remaining capacity constraint is met; The determined subtask is inserted into the task queue, and the remaining load capacity of the second motor is updated, and the dynamic load index of the first motor is synchronously triggered to be recalculated to verify the effect of task migration.

4. The multi-motor load control method for a storage tool magazine according to claim 2, wherein The determination of the first threshold, the second threshold and the third threshold includes: Analyze historical operation data and count load fluctuation ranges of the first motor and the second motor under normal operating conditions; Based on the average value and distribution width of the load fluctuation range, setting the initial first threshold, the second threshold and the third threshold; Real-time detection of environmental variables, when the ambient temperature exceeds the rated operating temperature range, reducing the values of the first threshold and the third threshold, the reduction amplitude being proportional to the temperature excess; When the power supply voltage fluctuation rate exceeds a safe range, increasing the value of the second threshold to increase the conservatism of task migration; Based on the predicted load change trend of the task queue in the future time period, if the load continues to increase, the first threshold and the third threshold are increased in advance according to the predicted increase ratio.

5. The multi-motor load control method for a storage tool magazine according to claim 3, wherein Verify the effect of task migration, including: After the task queue of the second motor is updated, recalculating the first dynamic load index of the first motor and the second dynamic load index of the second motor; generating a secondary migration instruction or a task migration instruction based on the recalculated first dynamic load index and the second dynamic load index; The secondary migration instruction triggers the migration of additional subtasks from the first motor to the second motor or the redundant motor; The task migration instruction triggers reverse migration of part of the subtasks of the second motor to the first motor; According to the execution result of the secondary migration instruction or the task relocation instruction, updating the weight allocation rule and the remaining capacity reservation parameter in the control strategy; The updated weight allocation rule and the remaining capacity reservation parameter are synchronized to the multi-source data fusion model to dynamically generate a load index of the corresponding motor.

6. The multi-motor load control method for a storage tool magazine according to claim 1, wherein, The basis for determining the high-frequency tool change stage includes: Real-time count the number of tool changes of the first motor within a time window. If the number of tool changes exceeds the critical value, it is determined as the high-frequency tool change stage; When the number of tool change instructions to be executed in the current task queue of the storage tool magazine reaches the density upper limit, dynamically lower the critical value to trigger the determination of the high-frequency tool change stage in advance; Generate a dynamic correction coefficient based on historical tool change data, and periodically adjust the critical value. The dynamic correction coefficient is negatively correlated with the historical average tool change frequency of the first motor.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing a computer to execute the storage tool magazine multi-motor load control method according to any one of claims 1 to 6.

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