Intelligent management method for production of high-speed rotating transmission device

Abstract

The invention relates to the technical field of intelligent management, in particular to an intelligent management method for production of a high-speed rotating transmission device, which comprises the following steps: extracting operation data, calculating deviation and marking abnormity, adjusting load generation configuration in combination with task information, judging a beat overlapping splitting priority recording path, and generating a regulation and control sequence by screening equipment. And extracting a temperature and pressure trend over-limit reset beat generation scheme. According to the method, a periodic alternation model is constructed by combining task numbers and running states to dynamically generate a load adjustment mode, so that the task adaptability is improved, a continuous scheduling channel is constructed by utilizing output time period difference judgment and beat conflict splitting, the task connection fluency is improved, and a resource configuration structure is optimized through equipment number de-weighting and conflict empowerment sorting; and the regulation and control efficiency is enhanced, real-time pre-judgment and cooling regulation are realized based on the temperature and pressure change trend, the operation safety guarantee is enhanced, and the accuracy, responsiveness and stability of intelligent management and control are integrally improved.

Description

Technical Field

[0001] The present invention relates to the field of intelligent management technology, and in particular to an intelligent management method for the production of high-speed rotating transmission devices. Background Art

[0002] The field of intelligent management technology includes automated control and optimization management systems used in manufacturing and industrial fields. The core content of this technology field is to intelligently monitor, manage and optimize the production process by using modern information technology, data acquisition and analysis methods. Intelligent management systems usually include functions such as real-time data acquisition, status monitoring, production scheduling, fault prediction, process optimization and decision support. This field is widely used in industrial production, equipment maintenance, logistics management and other aspects, aiming to improve production efficiency, reduce human operation errors, and ensure the stability and efficiency of the system.

[0003] Among them, the intelligent management method for the production of high-speed rotating transmission devices refers to an intelligent management method for the production process of high-speed rotating transmission devices. This method collects data during the operation of the device, conducts real-time monitoring and analysis, and then optimizes the operating efficiency of the transmission device. In this patent, the transmission device status monitoring, real-time data analysis, and adaptive adjustment technology are mainly used, and the real-time acquisition and analysis of various parameters in the rotating transmission system are carried out to regulate and control. These technical means involve dynamic monitoring and data acquisition of the transmission device, use information processing methods and analysis models to evaluate the operating status of the device, and make reasonable adjustments based on the evaluation results to ensure that the transmission device operates in an efficient and safe state.

[0004] In the process of transmission device status management in the existing technology, the operation data is mostly concentrated on the acquisition of static indicators and the evaluation of results. There is a lack of an advance judgment mechanism based on fluctuation trends, which results in abnormal components being identified only after the operation deviates greatly, resulting in a response lag problem. Task load adjustment relies on a static load model and lacks correlation judgment at the cycle alternation level. The differences in load characteristics of different tasks during execution are difficult to accurately match, and it is easy to cause invalid adjustment or excessive adjustment. In the scheduling process, the time periods of upstream and downstream tasks are not structured for difference analysis, and the beat conflicts between tasks cannot be effectively identified and decomposed, resulting in scheduling interruptions or equipment waiting. Equipment resource allocation usually adopts a unified priority mapping rule, without considering the number of path conflicts and the frequency of equipment crossover under concurrent execution. Tasks are prone to path conflict overlap during peak execution, resulting in frequent resource contention. Although temperature and pressure data are collected under high-frequency operation, continuous change trend analysis and active intervention logic are not constructed. It is difficult to cover the dynamic changes in the operating status with threshold trigger strategies alone, and the adjustment strategy does not respond in time, increasing equipment loss and safety risks. For example, during the switching of continuous processes, the lack of linkage response to load changes and cooling status can easily cause thermal fatigue of equipment or operation interruption. In summary, the existing technology has significant deficiencies in the timeliness, pertinence and coordination of abnormal response, task matching, scheduling coordination and state adjustment. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose an intelligent management method for the production of high-speed rotating transmission devices.

[0006] In order to achieve the above object, the present invention adopts the following technical solution: an intelligent management method for the production of high-speed rotating transmission devices, comprising the following steps: S1: Obtain the operating data of the motor, gear, and bearing in the high-speed rotating transmission device, extract the frequency, power consumption, and speed per unit time, calculate the fluctuation deviation, mark the components that exceed the fluctuation range as abnormal nodes, and generate a list of abnormal components to be managed; S2: extracting the cycle frequency and load of the current task of the motor according to the component operation status and task number in the list of abnormal components to be managed, calculating the load adjustment method and generating a task control state configuration group; S3: Through the task control state configuration group, the difference between the output time periods of the upstream and downstream task channels is calculated to determine whether there is a beat overlap. If there is an overlap, the task priority is split and the path is recorded to generate a dispatch path list; S4: According to the deployment path list, the concurrent task execution segments are screened, the device numbers in the cross-running segments are deduplicated, the control priority is generated by sorting the number of path conflicts, and the path priority table is output; S5: extract the path priority table to determine whether it exceeds the defined threshold value. If so, call the control parameters of the equipment cooling components and reset the beat to generate an intelligent management solution.

[0007] As a further solution of the present invention, the list of abnormal components to be managed includes the motor operating status, gear operating status, bearing operating status, abnormal node number, fluctuation deviation value, standard operating upper and lower limits, unit time frequency, power consumption, and speed; the task control status configuration group includes motor cycle frequency, operating load, load adjustment method, task node interruption option, frequency and load adjustment combination item, and adjustment method type; the allocation path list includes task segment priority splitting results, channel path information, beat change data, upstream and downstream task channel output time periods, and beat overlap conflict judgment results; the path priority sorting table includes task number, equipment number, cross-operation time period equipment number, allocation index, path conflict number, path operation weight value, regulation order, and number mapping structure; the intelligent management solution includes continuous temperature change, operating pressure change trend, threshold group definition boundary, cooling component control parameters, and beat reset operation.

[0008] As a further solution of the present invention, the specific steps of S1 are: S101: Acquire the operating data of the motor, gear, and bearing, extract the frequency, power consumption, and speed parameter values, calculate the frequency fluctuation value per unit time, analyze the power consumption change rate and speed deviation, and generate the operating characteristic fluctuation value; S102: according to the fluctuation amount of the operating characteristics, calling the frequency fluctuation upper and lower limit interval values, the power consumption change rate limit value and the speed deviation tolerance value, comparing the fluctuation value of the component with the corresponding reference value in turn, judging whether it exceeds the interval range, marking the component number that does not meet the reference as an abnormal node, and obtaining the abnormal node number set; S103: Based on the abnormal node number set, extract the frequency, power consumption, and speed operating status parameters of the corresponding numbered node in the current time period, combine the number and the status to construct a structure, arrange the structure data in the order of the number, and generate a list of abnormal components to be managed.

[0009] As a further solution of the present invention, the specific steps of S2 are: S201: extracting the cycle frequency and operation load of the motor in the time period corresponding to the current task number according to the operation status and task number of the components in the list of abnormal components to be managed, calculating the frequency-load alternation degree index of the cycle segment based on the pairing value of the task execution cycle and the load peak interval, and generating the frequency-load alternation intensity value; S202: According to the frequency load alternation intensity value, call the task node interruption attribute identifier corresponding to the task number, screen the frequency load alternation intensity value, determine whether the task node has an interruption attribute, and set the load adjustment mode to switching type and slow release type according to the interruption attribute, and establish an adjustment mode type identifier group; S203: Based on the adjustment mode type identification group, the frequency value, the load value and the corresponding adjustment mode type identification under the task node are combined to form ternary combination items in the order of task numbers, and missing combinations are filtered out to generate a task control state configuration group.

[0010] As a further solution of the present invention, the frequency load alternation degree index calculation formula of the period segment is specifically: ; in, Represents the frequency load alternation degree index of the cycle segment, Representative The frequency value of the period segment, Representative The frequency value of the period segment, Representative The load value of a cycle segment, Representative The load value of a cycle segment, Representative The duration of a cycle segment, Representative The duration of a cycle segment, Represents the total number of cycle segments.

[0011] As a further solution of the present invention, the specific steps of S3 are: S301: Call the beat change data of the adjustment combination item in the task control state configuration group, perform synchronous comparison on the output time periods set in the corresponding upstream and downstream task channels, calculate the time period data difference based on the time node of the task segment, extract all task segment pairs with a time difference less than or equal to zero, and obtain the beat overlap conflict comparison value; S302: According to the beat overlap conflict comparison value, a priority splitting operation is performed on the task segments with time overlap, the priority parameters defined in the task number sequence are called, and the execution order of the channel nodes with the same task path identifier is readjusted according to the priority sorting result, and the adjusted task number and channel path identifier combination is recorded to obtain a task segment channel path information set; S303: Based on the task segment channel path information set, filter all the reachable paths in the combination of task numbers and channel paths, remove the path branches including conflict identifiers, retain the execution channel combination items without beat conflicts, and establish a dispatch path list.

[0012] As a further solution of the present invention, the time period data difference calculation formula is specifically: ; in, Represents the data difference of the time period, Representative The end time of the output time period of each task channel, Representative The time node of each task segment, Represents the total number of cycle segments.

[0013] As a further solution of the present invention, the specific steps of S4 are: S401: According to the correspondence between the task number and the equipment number in the dispatch path list, the concurrent tasks in the same time period in the current batch are screened, all equipment numbers in the cross-operation time period are extracted, duplicate numbers are removed and reorganized according to the task number, a bidirectional mapping index structure of the equipment number and the task number is constructed, and an equipment scheduling index value is generated; S402: Based on the device scheduling index value, count the number of repetitions of the cross-running device number under each path, aggregate them by path number, use the number of repetitions of the device number as the number of conflicts within the path, sort the path numbers from high to low according to the number of conflicts, and generate a path operation weight value; S403: According to the path operation weight value and in combination with the index mapping relationship between the device number and the task number, the control items in the path number sequence are extracted and output in sequence, a sequential combination mapping between the task number and the path number is established, and a path priority table is generated.

[0014] As a further solution of the present invention, the specific steps of S5 are: S501: extract the bound device number according to the task number currently ranked first in the path priority sorting table, call the temperature change and pressure change trend data continuously recorded by the sensor attached to the device number in the current running cycle, calculate the corresponding numerical interval index based on the temperature change slope and the pressure change difference, compare it with the upper and lower boundaries of the temperature threshold value and the pressure threshold value bound to the device, and generate a state threshold offset value; S502: According to the state threshold offset value, the task number whose temperature or pressure parameter exceeds the corresponding threshold boundary is screened, the current control parameter set of the cooling component mounted on the device corresponding to the task number is extracted, the cooling frequency value, cooling duration and pressure response time recorded in the current operation cycle are called, the beat correction combination item is constructed, and the beat overlap control amount is generated; S503: Based on the beat overlap control amount, the corresponding equipment number, cooling component parameters and beat control amount are combined to construct a structure to form mapping data of task number and reset parameter, and the mapping structure is output according to the task number sequence to generate an intelligent management solution.

[0015] As a further solution of the present invention, the corresponding numerical interval index calculation formula is specifically: ; in, Represents the corresponding numerical interval indicator, Representative The temperature value of a time period, Representative The temperature value of a time period, Representative The pressure value of a time period, Representative The pressure value of a time period, Representative The length of time for the temperature change in a time period, Representative The length of time for the pressure change in a time period, Represents the number of temperature and pressure data points.

[0016] Compared with the prior art, the advantages and positive effects of the present invention are: In the present invention, a periodic alternation model is constructed by combining task numbers with operating states to dynamically generate load adjustment methods, thereby improving task adaptability. A continuous scheduling channel is constructed by using output time period difference judgment and beat conflict splitting to improve task connection smoothness. Equipment number deduplication and conflict weighted sorting are used to optimize the resource allocation structure and enhance control efficiency. Real-time prediction and cooling adjustment are achieved based on temperature and pressure change trends, thereby strengthening operational safety and improving the accuracy, responsiveness and stability of intelligent management and control as a whole. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0018] Figure 1 It is a schematic diagram of the steps of the present invention. DETAILED DESCRIPTION

[0019] The technical solution of the present invention is described below in conjunction with the accompanying drawings.

[0020] In the embodiments of the present invention, words such as "exemplarily" and "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "example" in the present invention should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of the word "example" is intended to present the concept in a specific way. In addition, in the embodiments of the present invention, the meaning expressed by "and / or" can be both, or it can be either of the two.

[0021] In the embodiments of the present invention, "image" and "picture" can sometimes be used interchangeably. It should be noted that when the difference between them is not emphasized, the meanings they intend to express are the same. "of", "corresponding, relevant" and "corresponding" can sometimes be used interchangeably. It should be noted that when the difference between them is not emphasized, the meanings they intend to express are the same.

[0022] In the embodiments of the present invention, sometimes the subscripts such as W 1 It may be written in non-subscript form such as W1. When the difference is not emphasized, the meaning is the same.

[0023] In order to make the technical problems, technical solutions and advantages to be solved by the present invention more clear, a detailed description will be given below with reference to the accompanying drawings and specific embodiments.

[0024] See also Figure 1 , an intelligent management method for the production of high-speed rotating transmission devices, comprising the following steps: S1: Obtain the operating data of the motor, gear, and bearing in the high-speed rotating transmission device, extract the frequency, power consumption, and speed per unit time, and calculate the fluctuation deviation value. Compare and judge the deviation value with the upper and lower limits of the standard operation, mark the components that exceed the fluctuation range as abnormal nodes, combine the abnormal node number and the operating status to form a structure, and generate a list of abnormal components to be managed; S2: According to the component operation status and task number in the list of abnormal components to be managed, the cycle frequency and operation load of the motor under the current task are extracted, and the load adjustment method is calculated through the periodic alternation relationship between frequency and load. The adjustment method type is selected according to whether the task node can be interrupted, and the frequency and load adjustment combination items are established to generate the task control state configuration group; S3: Call the beat change data of the adjustment combination item in the task control status configuration group, calculate the difference between the output time periods corresponding to the upstream and downstream task channels, and determine whether there is a beat overlap conflict based on the result. If there is an overlap, the task segments are prioritized and the channel path information is recorded to generate a dispatch path list; S4: According to the correspondence between the task number and the equipment number in the dispatch path list, the concurrent task execution segments in the current batch are screened, the equipment numbers in the cross-running segments are deduplicated and the allocation index is constructed, the path operation weight values ​​are generated by sorting according to the number of path conflicts, the control order is output in combination with the number mapping structure, and the path priority sorting table is generated; S5: According to the device bound to the current priority task number in the path priority table, extract the continuous temperature change and operating pressure change trend collected by the sensor to determine whether it exceeds the threshold group definition boundary. If so, call the current control parameters of the cooling component mounted on the device and perform the beat reset operation to generate an intelligent management plan.

[0025] The list of abnormal components to be managed includes the motor operating status, gear operating status, bearing operating status, abnormal node number, fluctuation deviation value, standard operating upper and lower limits, unit time frequency, power consumption, and speed. The task control status configuration group includes motor cycle frequency, operating load, load adjustment method, task node interruption option, frequency and load adjustment combination item, and adjustment method type. The dispatching path list includes task segment priority splitting results, channel path information, beat change data, upstream and downstream task channel output time periods, and beat overlap conflict judgment results. The path priority sorting table includes task number, equipment number, cross-operation time period equipment number, allocation index, path conflict number, path operation weight value, control order, and number mapping structure. The intelligent management plan includes continuous temperature change, operating pressure change trend, threshold group definition boundary, cooling component control parameters, and beat reset operation.

[0026] The specific steps of S1 are: S101: Acquire the operating data of the motor, gear, and bearing, extract the frequency, power consumption, and speed parameter values, calculate the frequency fluctuation value per unit time, analyze the power consumption change rate and speed deviation, and generate the operating characteristic fluctuation value; First, the key parameters such as frequency, power consumption and speed are monitored and recorded in real time through the equipment sensors. The operating frequency of the motor is generally measured in Hertz (Hz) and is collected regularly through the frequency sensor. Power consumption data is usually obtained through current and voltage sensors, and speed data is obtained through a tachometer, and the measurement unit is usually revolutions per minute (RPM). For example, the frequency of the motor may be 50Hz, the power consumption is 120W, and the speed is 1500RPM. Next, based on these data, the frequency fluctuation value per unit time is calculated. In order to obtain the fluctuation value, it is necessary to calculate the maximum and minimum differences in the frequency value within a certain period of time. Assuming that the change in the motor frequency during the sampling period is from 45Hz to 55Hz, the fluctuation value is 10Hz. The power consumption change rate is calculated by the ratio method, that is, the change in power consumption within a certain period of time is divided by the initial power consumption. Assuming that the power consumption increases from 120W to 130W, the change rate is (130W-120W) / 120W=8.33%. The speed deviation is calculated by comparing it with the set standard speed value (such as 1500RPM). If the speed deviates from the standard value by 10RPM, the deviation is 10RPM. Through these steps, the extracted frequency fluctuation, power consumption change rate and speed deviation can be further used to generate the operating characteristic fluctuation, thus providing a basis for the next step of abnormality detection.

[0027] S102: according to the fluctuation amount of the operating characteristics, the frequency fluctuation upper and lower limit interval values, the power consumption change rate limit value and the speed deviation tolerance value are called, and the fluctuation value of the component is compared with the corresponding reference value in turn to determine whether it exceeds the interval range, and the component number that does not meet the reference is marked as an abnormal node, and the abnormal node number set is obtained; First, the upper and lower limits of the frequency fluctuation, the limit value of the power consumption change rate, and the tolerance value of the speed deviation need to be set according to the device type and actual operating conditions. The frequency fluctuation value is usually set to ±5Hz, the power consumption change rate may be set to ±10%, and the speed deviation may be set to ±50RPM. For example, if the frequency fluctuation range of the device is 45Hz to 55Hz, then the actual fluctuation exceeds this range and is considered abnormal. If the frequency fluctuation is 12Hz, it exceeds the preset interval value. If the power consumption change rate exceeds ±10% (such as the change rate is 12%), it is considered abnormal. If the speed deviates from 1500RPM±50RPM, that is, the deviation exceeds 200RPM, it is abnormal. These data are compared with the preset reference value to determine whether they exceed the set range. If they exceed the range, they are marked as abnormal nodes. In this way, the problematic device components can be quickly located and an abnormal node number set can be generated for subsequent processing.

[0028] S103: Based on the abnormal node number set, extract the frequency, power consumption, and speed operation status parameters of the corresponding numbered node in the current period, combine the number and the status to construct a structure, arrange the structure data in the order of the number, and generate a list of abnormal components to be managed; The frequency, power consumption and speed state parameters of the corresponding components in the current time period are further extracted. These data are integrated and paired with the corresponding component numbers to generate structure data. Each structure includes a component number and corresponding operating status parameters. For example, a motor with a component number of 001 has a frequency of 53Hz, a power consumption of 128W, and a speed of 1520RPM. These data will be arranged in the order of the component numbers and form a list of abnormal components to be managed. Through the organization of the structure, the specific operating status of each component in the current time period can be clarified, helping subsequent maintenance personnel to quickly and accurately identify and handle abnormal components, thereby optimizing the operation and maintenance strategy of the equipment.

[0029] The specific steps of S2 are: S201: extracting the cycle frequency and operation load of the motor in the time period corresponding to the current task number according to the operation status and task number of the components in the list of abnormal components to be managed, calculating the frequency-load alternation degree index of the cycle segment based on the pairing value of the task execution cycle and the load peak interval, and generating the frequency-load alternation intensity value; The calculation formula of the frequency load alternation degree index of the period segment is as follows: ; in, Represents the frequency load alternation degree index of the cycle segment, Representative The frequency value of the period segment, Representative The frequency value of the period segment, Representative The load value of a cycle segment, Representative The load value of a cycle segment, Representative The duration of a cycle segment, Representative The duration of a cycle segment, Represents the total number of cycle segments; This formula is used to calculate the frequency-load alternation index of the cycle segment. Its main purpose is to measure the alternating fluctuation of frequency and load during the operation of the motor. The acquisition and quantification methods of each parameter are as follows: Representative The frequency value of a cycle segment is collected in real time by the frequency sensor during the operation of the motor. For example, the frequency of a device is 50Hz in a certain cycle segment, and the monitoring device provides this value through the frequency sensor. It is known that Hz.

[0030] Representative The frequency value of each cycle segment is determined by the frequency data collected by the frequency sensor in the previous cycle segment. The frequency is 48 Hz, so Hz.

[0031] Representative The load value of a cycle segment is measured in real time by a current or power sensor. The load of each cycle segment is 70%, which is obtained through the power sensor.

[0032] Representative The load value of a period. The load of each cycle segment is 65%.

[0033] Representative The duration of each cycle segment is in seconds. This value is calculated by the motor control system or monitoring system. The duration of each cycle segment is 10 seconds.

[0034] Representative The duration of each cycle segment is in seconds. The duration of each cycle segment is 8 seconds.

[0035] Represents the total number of cycle segments. For example, in a monitoring cycle, there are 5 cycle segments, so .

[0036] For actual calculation, a specific cycle segment is selected for derivation. Assume that the frequency of the second cycle segment is 50 Hz, the load is 70%, and the frequency of the first cycle segment is 48 Hz, the load is 65%, and the duration of the cycle segment is 10 seconds and 8 seconds respectively.

[0037] Calculate the difference between the frequencies of the second period and the first period: ; Calculate the difference between the loads of the second cycle segment and the first cycle segment: ; Compute the sum of the time differences: ; Substitute these values ​​into the formula to calculate: ; ; ; ; The result shows that the degree of alternation between frequency and load is 0.747, which means that during this monitoring period, the alternation between motor frequency and load is moderate. The magnitude of this value reflects the frequency of fluctuation between frequency and load in the system. The larger the value, the more drastic the alternation between frequency and load.

[0038] S202: According to the frequency load alternation intensity value, call the task node interruption attribute identifier corresponding to the task number, screen the frequency load alternation intensity value, determine whether the task node has an interruption attribute, and set the load adjustment mode to switching type and slow release type according to the interruption attribute, and establish an adjustment mode type identifier group; Next, the task node interrupt attribute identifier corresponding to the task number is called to determine whether the task has the interrupt attribute. The task node interrupt attribute identifier is used to determine whether an interruption may occur during the execution of the task or whether special control measures are required. For example, the task node may indicate that if the alternating intensity exceeds a certain threshold (such as 80%), the interruption strategy needs to be enabled. By comparing with the interrupt attribute identifier, the frequency load alternating intensity value that exceeds the threshold is screened out. After determining whether it has the interrupt attribute, the load adjustment method is set according to the attribute. If the task node has the interrupt attribute, the load adjustment method is switching type, that is, it directly switches to the new load state; if it does not have the interrupt attribute, the slow release type adjustment method is adopted, that is, the load is gradually adjusted. For example, if the frequency load alternating intensity value is 85% and the task node indicates that it has the interrupt attribute, the load adjustment method will be set to switching type; if the alternating intensity is 70% and the task node does not have the interrupt attribute, it is set to slow release type adjustment method. Through this process, an adjustment method type identification group is established, and the identification group contains the adjustment method type corresponding to each task node for subsequent control decisions.

[0039] S203: Based on the adjustment mode type identification group, the frequency value, the load value and the corresponding adjustment mode type identification under the task node are combined to form a ternary combination item in the order of the task number, and the missing item combination is filtered out to generate a task control state configuration group; Combine the frequency value and load value under the task node with the corresponding adjustment mode type identifier to form a ternary combination item. Each ternary combination item includes frequency, load and adjustment mode type, and the three constitute a complete adjustment strategy. For example, if the task number is 001, the frequency of the node under it is 50Hz, the load is 75%, and the adjustment mode is switching type, then the combination item of the node is (50Hz, 75%, switching type). By performing similar combinations of the frequency, load and adjustment mode type of all task nodes, the task control state configuration group is obtained. The combination process needs to ensure that the frequency and load data of each task node are complete. If the data of a task node is incomplete, the combination item needs to be excluded. For example, if the task node lacks load data, the ternary combination item of the node is screened out. Through these operations, a task control state configuration group is finally generated, which contains all operable task node combination items for further task scheduling and execution management.

[0040] The specific steps of S3 are: S301: Call the beat change data of the adjustment combination item in the task control state configuration group, perform synchronous comparison on the output time periods set in the corresponding upstream and downstream task channels, calculate the time period data difference based on the time node of the task segment, extract all task segment pairs with a time difference less than or equal to zero, and obtain the beat overlap conflict comparison value; The specific calculation formula for the time period data difference is: ; in, Represents the data difference of the time period, Representative The end time of the output time period of each task channel, Representative The time node of each task segment, Represents the total number of cycle segments; This formula is used to calculate the difference in time period data, reflecting the difference between the task period time node and the task channel output time period. The acquisition and quantification methods of each parameter are as follows: Representative The end time of the output time period of each task channel is usually obtained in real time by the task management system or control system. For example, the output time period of the first task channel is from 10 seconds to 20 seconds, so Second.

[0041] Representative The time node of a task segment refers to the time point at which the task is actually executed, which is determined by the system according to the task schedule. For example, the time node of the first task segment is 15 seconds, that is, Second.

[0042] Represents the total number of task segment pairs. For example, in a task plan, there are 3 task segment pairs to be processed. .

[0043] For actual calculation, a specific task segment is selected for derivation. Assuming there are 3 task segments, the output time period of the task channel and the time node of the task segment are as follows: The first task segment: the output time segment of the task channel Seconds, task segment time node Second; The second task segment: the output time segment of the task channel Seconds, task segment time node Second; The third task segment: the output time segment of the task channel Seconds, task segment time node Second.

[0044] Step 1: Calculate the time difference of each task segment For the first task segment, calculate the time difference: ; For the second task segment, calculate the time difference: ; For the third task segment, calculate the time difference: ; Step 2: Calculate the weighted time difference For the first task segment, calculate the weighted time difference: ; For the second task segment, calculate the weighted time difference: ; For the third task segment, calculate the weighted time difference: ; Step 3: Calculate the sum ; Step 4: Calculate the difference in time period data ; The result shows that the overlap between the task segment and the task channel output time period is 5.67, indicating that there is a moderate time difference between the task segment and the output time period. Through this value, we can further judge the overlap of time periods and take corresponding scheduling or optimization measures.

[0045] S302: according to the beat overlap conflict comparison value, a priority splitting operation is performed on the task segments with time overlap, the priority parameters defined in the task number sequence are called, and the execution order of the channel nodes with the same task path identifier is readjusted according to the priority sorting result, and the adjusted task number and channel path identifier combination is recorded to obtain the task segment channel path information set; According to the beat overlap conflict comparison value, the priority splitting operation needs to be performed next, especially for task segments with time overlap. First, the time overlap relationship of the task segments needs to be obtained through comparison and calculation. If the time periods of two task segments overlap, the priority splitting operation is performed. During the splitting process, the system calls the priority parameters defined in the task number sequence. These priority parameters represent the priority of task execution. The priority value can be a number (for example, the priority of task 1 is high priority 10, and the priority of task 2 is medium priority 5). For channel nodes with the same task path identifier, the system readjusts the execution order according to the priority sorting result. For example, if the priority of task 1 is higher than that of task 2, task 1 will be executed first, and the adjusted execution order is task 1→task 2. Then, the system records the adjusted task number and channel path identifier combination to generate a task segment channel path information set. This information set is used for subsequent path scheduling and task management. Assuming that task 1 and task 2 have time overlap and task 1 has a higher priority, task 1 will be executed in advance and task 2 will be delayed, eventually forming a task segment channel path set containing adjustment information.

[0046] S303: Based on the task segment channel path information set, filter all the reachable paths in the combination of task number and channel path, remove the path branches including conflict identifiers, retain the execution channel combination items without beat conflict, and establish a dispatch path list; Based on the task segment channel path information set, the next step is to filter out the reachable paths in all task number and channel path combinations. This process depends on the feasibility and conflict detection of task paths. The system first traverses all task number and channel path combinations to determine which paths are reachable. For example, task 3 may have two paths: path A and path B, where path A is not affected by beat conflicts, while path B may conflict with other task segments. The system will remove the path branches including conflict identifiers and retain the execution channel combination items without beat conflicts. The conflict identifier is generated by the beat overlap conflict comparison value, and any path involving overlap or conflict will be excluded. For example, if path A and path B overlap, path B will be removed, and only path A will be retained. Through this screening process, the system finally obtains a dispatch path list that contains all execution channel combination items without beat conflicts. These combination items can be used for subsequent task scheduling to ensure that tasks are executed in the correct order and path, thereby optimizing overall production or operation efficiency.

[0047] The specific steps of S4 are: S401: According to the correspondence between the task number and the equipment number in the dispatch path list, the concurrent tasks in the same time period in the current batch are screened, all equipment numbers in the cross-operation time period are extracted, and after removing the duplicate numbers, they are reorganized according to the task number, and a bidirectional mapping index structure between the equipment number and the task number is constructed to generate the equipment scheduling index value; First, it is necessary to filter out the concurrent tasks in the same time period in the current batch, identify the task numbers of these tasks and extract the corresponding equipment numbers. For example, suppose task A uses equipment 1 and equipment 2 in time period 1, and task B uses equipment 3 and equipment 4 in the same time period. Next, the system will extract all equipment numbers in the cross-operation time period, and take equipment 1, equipment 2, equipment 3, and equipment 4 as the equipment number set. In order to avoid repeated calculations, the repeated equipment numbers are then eliminated to obtain a unique equipment number list. Assuming that equipment 2 and equipment 3 appear repeatedly during this process, the system will eliminate them. Then, the task numbers are reorganized, and task A and task B will reallocate the equipment according to their respective task numbers to ensure the independence of the equipment and the clarity of task execution. Finally, the system constructs a bidirectional mapping index structure of equipment numbers and task numbers, and associates each task number with its corresponding equipment number, for example, task A corresponds to equipment 1 and equipment 2, and task B corresponds to equipment 3 and equipment 4. Through this operation, the system generates equipment scheduling index values, providing a clear scheduling management system between tasks and equipment.

[0048] S402: Based on the device scheduling index value, count the number of repetitions of the cross-running device number under each path, aggregate them by path number, use the number of repetitions of the device number as the number of conflicts within the path, sort the path numbers from high to low according to the number of conflicts, and generate a path operation weight value; Based on the device scheduling index value, the next step is to count the number of repetitions of the cross-running device numbers under each path. The specific operation is to traverse each path and count the device numbers that appear repeatedly in each path. For example, suppose path 1 contains device 1, device 2, device 3, and device 4, where device 1 and device 2 appear twice in the path, and device 3 and device 4 appear once each, then the number of repetitions of device 1 and device 2 is 2, and the number of repetitions of device 3 and device 4 is 1. Next, the system aggregates the number of repetitions of the device numbers in each path and calculates the number of conflicts for each path. For example, the number of conflicts for path 1 is the sum of the number of repetitions of device 1 and device 2, that is, the number of conflicts is 2. The number of conflicts for all paths will be sorted from high to low, and the path with the most conflicts is considered to be the most influential and is processed first. Through this sorting, the system can generate a path operation weight value and assign a corresponding weight value to each path according to the size of the number of conflicts in the path. Paths with high conflict numbers will be assigned higher operation weight values ​​and will be executed first. Ultimately, this process generates a path operation weight value to help subsequent path scheduling decisions.

[0049] S403: extracting control items in the path number sequence and outputting them in order according to the path operation weight value and the index mapping relationship between the device number and the task number, establishing a sequential combination mapping between the task number and the path number, and generating a path priority sorting table; According to the path operation weight value, the next step is to extract the control items in the path number sequence in combination with the index mapping relationship between the device number and the task number, and output them in sequence. First, the system sorts the paths according to the path operation weight values ​​and selects the paths with high weight values ​​for scheduling control. For example, assuming that the weight value of path 1 is 5 and the weight value of path 2 is 3, path 1 will be given priority. According to the order of the paths and the control items, the system extracts the control items of each path. For example, the control items of path 1 may include the adjustment of device 1 and device 2. Then, the system establishes a sequential combination mapping between the task number and the path number, records the sequential relationship between the task number and the path number, and forms an executable sequential list. For example, task A executes path 1 first, and task B executes path 2 later. In this way, the system generates a path priority table, and ensures that each task is executed in a reasonable order according to the path priority and task execution order, thereby optimizing the overall scheduling strategy.

[0050] The specific steps of S5 are: S501: according to the task number currently ranked first in the path priority sorting table, extract the bound device number, call the temperature change and pressure change trend data continuously recorded by the sensor attached to the device number in the current running cycle, calculate the corresponding numerical interval index based on the temperature change slope and the pressure change difference, compare it with the upper and lower boundaries of the temperature threshold value and pressure threshold value bound to the device, and generate a state threshold offset value; The calculation formula for the corresponding numerical interval indicator is as follows: ; in, Represents the corresponding numerical interval indicator, Representative The temperature value of a time period, Representative The temperature value of a time period, Representative The pressure value of a time period, Representative The pressure value of a time period, Representative The length of time for the temperature change in a time period, Representative The length of time for the pressure change in a time period, Represents the number of temperature and pressure data points; This formula is used to calculate the comprehensive changes in temperature and pressure to obtain the state threshold offset value of the device. The specific method for obtaining and calculating each parameter is as follows: Representative The temperature data is recorded and provided by the temperature sensor in real time. For example, the temperature recorded by the temperature sensor of the device in the second period is 80°C, which means °C.

[0051] Representative The temperature value of the previous period is provided by the same sensor. For example, the temperature of the first period is 75°C, which means °C.

[0052] Representative The pressure data is recorded and provided by the pressure sensor in real time. For example, the pressure recorded in the second period is 1.5 MPa, which means MPa.

[0053] Representative For example, the pressure recorded in the first period is 1.4 MPa, which means MPa.

[0054] Representative The length of time the temperature changes in a time period, in seconds. For example, the temperature increases from 75°C to 80°C in 10 seconds, so Second.

[0055] Representative The length of time the pressure changes in a time period is in seconds. For example, the process of increasing the pressure from 1.4MPa to 1.5MPa also occurs within 10 seconds, so Second.

[0056] Represents the total number of data points. For this example, the number of data points is 2, which means .

[0057] Calculation process: For the second cycle, calculate the temperature change rate: ; For the second cycle segment, calculate the pressure change rate: ; Multiply the two together to get the weighted change: ; Repeat this process for the second period to get the change. Since there are only two data points, the sum of this calculation is: ; Result analysis: The result shows that the trend value of temperature and pressure is 0.005. This value represents the comprehensive offset of the temperature and pressure changes of the equipment status in the current operation cycle. Through this indicator, the system can further evaluate whether the equipment meets the set threshold and make adjustments or optimization decisions based on the equipment status.

[0058] S502: According to the state threshold offset value, the task number whose temperature or pressure parameter exceeds the corresponding threshold boundary is screened, the current control parameter set of the cooling component mounted on the device corresponding to the task number is extracted, the cooling frequency value, cooling duration and pressure response time recorded in the current operation cycle are called, the beat correction combination item is constructed, and the beat overlap control amount is generated; According to the calculated state threshold offset value, the system will filter out the task number whose temperature or pressure parameter exceeds the corresponding threshold boundary. Assuming that in this monitoring, the temperature change value of the device is 28°C and the pressure is 1.6MPa, the pressure exceeds the set threshold value. Therefore, the system will select the corresponding task number, namely task A, for subsequent processing. Next, the system extracts the current control parameter set of the cooling component mounted on the device corresponding to the task number. The cooling component may include cooling pumps, fans and other devices, and their control parameter sets may include cooling frequency values, cooling durations and pressure response times. Assuming that the cooling frequency is 50Hz, the cooling duration is 10 minutes, and the pressure response time is 3 minutes, the system will construct a beat correction combination item based on these control parameters. The beat correction combination item is combined with the actual operation of the device. For example, when the pressure changes greatly, the cooling intensity may need to be increased, and the system will adjust the cooling frequency. Finally, the system will generate a beat overlap control amount, indicating that during the execution of the task, the working state of the cooling device needs to be adjusted in time according to the pressure change.

[0059] S503: Based on the beat overlap control amount, the corresponding equipment number, cooling component parameters and beat control amount are combined to construct a structure to form mapping data between the task number and the reset parameter, and the mapping structure is output according to the task number sequence to generate an intelligent management plan; Based on the generated beat overlap control quantity, the system combines the corresponding equipment number, cooling component parameters and beat control quantity to construct a structure. For example, the equipment numbers of task A are 1 and 2, the control parameters of the cooling components include cooling frequency 50Hz, cooling duration 10 minutes and pressure response time 3 minutes, and the beat control quantity is to increase the cooling frequency to 60Hz. After encapsulating these parameters into a structure, the system forms mapping data between task numbers and reset parameters, indicating the parameter adjustment requirements for each task. Then, the mapping structure is output in the task number sequence to form an adjustment table. Finally, this table will be provided to the control system for real-time management and scheduling as part of the intelligent management solution to ensure that during task execution, the working mode of the cooling system is adjusted according to the status of the equipment, thereby optimizing the stability of task execution and equipment protection.

[0060] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. An intelligent management method for the production of high-speed rotating transmission devices, characterized in that: The following steps are involved: S1: Obtain the operating data of the motor, gear, and bearing in the high-speed rotating transmission device, extract the frequency, power consumption, and speed per unit time, calculate the fluctuation deviation, mark the components that exceed the fluctuation range as abnormal nodes, and generate a list of abnormal components to be managed; S2: extracting the cycle frequency and load of the current task of the motor according to the component operation status and task number in the list of abnormal components to be managed, calculating the load adjustment method and generating a task control state configuration group; S3: Through the task control state configuration group, the difference between the output time periods of the upstream and downstream task channels is calculated to determine whether there is a beat overlap. If there is an overlap, the task priority is split and the path is recorded to generate a dispatch path list; S4: According to the deployment path list, the concurrent task execution segments are screened, the device numbers in the cross-running segments are deduplicated, the control priority is generated by sorting the number of path conflicts, and the path priority table is output; S5: extract the path priority table to determine whether it exceeds the defined threshold value. If so, call the control parameters of the equipment cooling components and reset the beat to generate an intelligent management solution.

2. The intelligent management method for the production of high-speed rotating transmission devices according to claim 1, characterized in that: The list of abnormal components to be managed includes the motor operating status, gear operating status, bearing operating status, abnormal node number, fluctuation deviation value, standard operating upper and lower limits, unit time frequency, power consumption, and rotation speed. The task control status configuration group includes motor cycle frequency, operating load, load adjustment method, task node interruption option, frequency and load adjustment combination item, and adjustment method type. The allocation path list includes task segment priority splitting results, channel path information, beat change data, upstream and downstream task channel output time periods, and beat overlap conflict judgment results. The path priority sorting table includes task number, equipment number, cross-operation time period equipment number, allocation index, path conflict number, path operation weight value, regulation order, and number mapping structure. The intelligent management plan includes continuous temperature change, operating pressure change trend, threshold group definition boundary, cooling component control parameters, and beat reset operation.

3. The intelligent management method for the production of high-speed rotating transmission devices according to claim 1, characterized in that: The specific steps of S1 are: S101: Acquire the operating data of the motor, gear, and bearing, extract the frequency, power consumption, and speed parameter values, calculate the frequency fluctuation value per unit time, analyze the power consumption change rate and speed deviation, and generate the operating characteristic fluctuation value; S102: according to the fluctuation amount of the operating characteristics, calling the frequency fluctuation upper and lower limit interval values, the power consumption change rate limit value and the speed deviation tolerance value, comparing the fluctuation value of the component with the corresponding reference value in turn, judging whether it exceeds the interval range, marking the component number that does not meet the reference as an abnormal node, and obtaining the abnormal node number set; S103: Based on the abnormal node number set, extract the frequency, power consumption, and speed operating status parameters of the corresponding numbered node in the current time period, combine the number and the status to construct a structure, arrange the structure data in the order of the number, and generate a list of abnormal components to be managed.

4. The intelligent management method for the production of high-speed rotating transmission devices according to claim 1, characterized in that: The specific steps of S2 are: S201: extracting the cycle frequency and operation load of the motor in the time period corresponding to the current task number according to the operation status and task number of the components in the list of abnormal components to be managed, calculating the frequency-load alternation degree index of the cycle segment based on the pairing value of the task execution cycle and the load peak interval, and generating the frequency-load alternation intensity value; S202: According to the frequency load alternation intensity value, call the task node interruption attribute identifier corresponding to the task number, screen the frequency load alternation intensity value, determine whether the task node has an interruption attribute, and set the load adjustment mode to switching type and slow release type according to the interruption attribute, and establish an adjustment mode type identifier group; S203: Based on the adjustment mode type identification group, the frequency value, the load value and the corresponding adjustment mode type identification under the task node are combined to form ternary combination items in the order of task numbers, and missing combinations are filtered out to generate a task control state configuration group.

5. The intelligent management method for the production of high-speed rotating transmission devices according to claim 4, characterized in that: The specific calculation formula of the frequency load alternation index of the period segment is: ； in, Represents the frequency load alternation degree index of the cycle segment, Representative The frequency value of the period segment, Representative The frequency value of the period segment, Representative The load value of a cycle segment, Representative The load value of a cycle segment, Representative The duration of a cycle segment, Representative The duration of a cycle segment, Represents the total number of cycle segments.

6. The intelligent management method for the production of high-speed rotating transmission devices according to claim 1, characterized in that: The specific steps of S3 are: S301: Call the beat change data of the adjustment combination item in the task control state configuration group, perform synchronous comparison on the output time periods set in the corresponding upstream and downstream task channels, calculate the time period data difference based on the time node of the task segment, extract all task segment pairs with a time difference less than or equal to zero, and obtain the beat overlap conflict comparison value; S302: According to the beat overlap conflict comparison value, a priority splitting operation is performed on the task segments with time overlap, the priority parameters defined in the task number sequence are called, and the execution order of the channel nodes with the same task path identifier is readjusted according to the priority sorting result, and the adjusted task number and channel path identifier combination is recorded to obtain a task segment channel path information set; S303: Based on the task segment channel path information set, filter all the reachable paths in the combination of task numbers and channel paths, remove the path branches including conflict identifiers, retain the execution channel combination items without beat conflicts, and establish a dispatch path list.

7. The intelligent management method for the production of high-speed rotating transmission devices according to claim 6, characterized in that: The specific calculation formula for the data difference of the time period is: ； in, Represents the data difference of the time period, Representative The end time of the output time period of each task channel, Representative The time node of each task segment, Represents the total number of cycle segments.

8. The intelligent management method for the production of high-speed rotating transmission devices according to claim 1, characterized in that: The specific steps of S4 are: S401: According to the correspondence between the task number and the equipment number in the dispatch path list, the concurrent tasks in the same time period in the current batch are screened, all equipment numbers in the cross-operation time period are extracted, duplicate numbers are removed and reorganized according to the task number, a bidirectional mapping index structure of the equipment number and the task number is constructed, and an equipment scheduling index value is generated; S402: Based on the device scheduling index value, count the number of repetitions of the cross-running device number under each path, aggregate them by path number, use the number of repetitions of the device number as the number of conflicts within the path, sort the path numbers from high to low according to the number of conflicts, and generate a path operation weight value; S403: According to the path operation weight value and in combination with the index mapping relationship between the device number and the task number, the control items in the path number sequence are extracted and output in sequence, a sequential combination mapping between the task number and the path number is established, and a path priority table is generated.

9. The intelligent management method for the production of high-speed rotating transmission devices according to claim 1, characterized in that: The specific steps of S5 are: S501: extract the bound device number according to the task number currently ranked first in the path priority sorting table, call the temperature change and pressure change trend data continuously recorded by the sensor attached to the device number in the current running cycle, calculate the corresponding numerical interval index based on the temperature change slope and the pressure change difference, compare it with the upper and lower boundaries of the temperature threshold value and the pressure threshold value bound to the device, and generate a state threshold offset value; S502: According to the state threshold offset value, the task number whose temperature or pressure parameter exceeds the corresponding threshold boundary is screened, the current control parameter set of the cooling component mounted on the device corresponding to the task number is extracted, the cooling frequency value, cooling duration and pressure response time recorded in the current operation cycle are called, the beat correction combination item is constructed, and the beat overlap control amount is generated; S503: Based on the beat overlap control amount, the corresponding equipment number, cooling component parameters and beat control amount are combined to construct a structure to form mapping data of task number and reset parameter, and the mapping structure is output according to the task number sequence to generate an intelligent management solution.

10. The intelligent management method for the production of high-speed rotating transmission devices according to claim 9, characterized in that: The corresponding numerical interval index calculation formula is specifically as follows: ； in, Represents the corresponding numerical interval indicator, Representative The temperature value of the time period, Representative The temperature value of a time period, Representative The pressure value of a time period, Representative The pressure value of a time period, Representative The length of time for the temperature change in a time period, Representative The length of time for the pressure change in a time period, Represents the number of temperature and pressure data points.

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