Abnormal emergency management and control method and device for intelligent liquid outlet machine and computer equipment

Abstract

The invention relates to an abnormal emergency management and control method and device for an intelligent liquid outlet machine and computer equipment. The method comprises the following steps: acquiring current task information of the intelligent liquid outlet machine and current monitoring information of each structural component, and querying each target structural component and task monitoring demand information associated with the current task information; according to task monitoring demand information of the current task information, identifying a first abnormal structural component in each target structural component, and according to a component monitoring strategy of each structural component, identifying a second abnormal structural component in each structural component; and on the basis of the current monitoring information of each first abnormal structural component and each second abnormal structural component, generating an abnormal monitoring result of the intelligent liquid outlet machine through an abnormal analysis strategy of the intelligent liquid outlet machine, and on the basis of the abnormal monitoring result of the intelligent liquid outlet machine, generating an emergency processing scheme of the intelligent liquid outlet machine. By means of the method, the emergency treatment efficiency of the abnormal discharging amount can be improved.

Description

Technical Field

[0001] The present application relates to the field of big data analysis technology, and in particular to an abnormal emergency management method, device and computer equipment for an intelligent liquid dispensing machine. Background Art

[0002] Abnormal discharge volume is a common problem in modern industrial production, particularly in manufacturing and food processing. This can be caused by equipment failure, pipe blockage, changes in material properties, and other factors. Abnormal discharge volume directly impacts production efficiency and product quality. Therefore, timely and accurate monitoring and resolution of abnormal discharge volume is crucial to ensuring the normal operation of production lines.

[0003] Traditional technical solutions for monitoring and handling abnormal discharge volumes typically involve manual monitoring and manual operation. During manual monitoring, workers need to regularly check the status of the discharge pipe and raw material barrel, and immediately take appropriate measures if any abnormalities are detected. During manual operation, workers rely on experience and judgment to decide how to refill and handle abnormal situations. However, manual monitoring and manual operation are inefficient and unable to respond promptly to rapid changes in discharge volume, which can easily lead to production delays and waste of resources. Furthermore, manual monitoring is one-sided and, influenced by human experience, often lacks accuracy in identifying and analyzing abnormalities, resulting in inefficient emergency response to abnormal discharge volumes. Summary of the Invention

[0004] Based on this, it is necessary to provide an abnormal emergency control method, device, computer equipment, computer-readable storage medium and computer program product for an intelligent liquid discharge machine to address the above technical problems.

[0005] In a first aspect, the present application provides an abnormal emergency control method for an intelligent liquid dispensing machine, comprising:

[0006] Obtaining current task information of the intelligent liquid dispensing machine and current monitoring information of each structural component of the intelligent liquid dispensing machine, and querying each target structural component associated with the current task information and task monitoring requirement information of the current task information;

[0007] Based on the current monitoring information of each target structural component and by using the task monitoring requirement information of the current task information, a first abnormal structural component among each target structural component is identified; and based on the current monitoring information of each structural component and by using the component monitoring strategy of each structural component, a second abnormal structural component among each structural component is identified;

[0008] Based on the current monitoring information of each of the first abnormal structural components and the current monitoring information of each of the second abnormal structural components, the abnormal monitoring results of the intelligent liquid dispensing machine are generated through the abnormal analysis strategy of the intelligent liquid dispensing machine, and based on the abnormal monitoring results of the intelligent liquid dispensing machine, an emergency treatment plan for the intelligent liquid dispensing machine is generated.

[0009] Optionally, the querying of each target structural component associated with the current task information and task monitoring requirement information of the current task information includes:

[0010] In a task database, query the task type corresponding to the current task information and the task flow corresponding to the current task information, and identify the participating structural components of the task flow and the associated structural components corresponding to the task type;

[0011] Performing component deduplication processing on each of the participating structural components and each of the associated structural components, screening each target structural component associated with the task information, and querying the structure monitoring requirement information of the current task information in the liquid discharge machine monitoring database based on the task flow and the task type;

[0012] The structure monitoring requirement information of the current task information is used as the task monitoring requirement information of the current task information.

[0013] Optionally, the identifying a first abnormal structural component among the target structural components based on the current monitoring information of the target structural components and through the task monitoring requirement information of the current task information includes:

[0014] Based on the current monitoring information of each target structural component, identifying the current operating data of each target structural component, and based on the task monitoring requirement information of the current task information, identifying the indicator monitoring scheme of each monitoring indicator type of the current task information and the monitoring structural component corresponding to each monitoring indicator type;

[0015] Based on the current operating data of each of the target structural components, the monitoring indicator values of each of the monitoring indicator types are monitored respectively through the indicator monitoring scheme of each of the monitoring indicator types, and based on the monitoring indicator values of each of the monitoring indicator types and the monitoring structural components corresponding to each monitoring indicator type, the first abnormal structural component in each of the target structural components is identified.

[0016] Optionally, the identifying a second abnormal structural component among the structural components based on current monitoring information of the structural components and using a component monitoring strategy of the structural components includes:

[0017] Based on the current monitoring information of each structural component, the structural operation data of each structural component is identified, and for each structural component, based on the structural operation data of the structural component and using the component monitoring strategy of the structural component, the target monitoring result of the structural component at each monitoring target is identified;

[0018] Based on the target monitoring results of each monitoring target, the abnormal monitoring targets in each monitoring target are queried through the standard operation database of the structural components, and the structural components with abnormal monitoring targets are regarded as the second abnormal structural components in each structural components.

[0019] Optionally, the generating of the abnormality monitoring result of the intelligent liquid dispensing machine by the abnormality analysis strategy of the intelligent liquid dispensing machine based on the current monitoring information of each of the first abnormal structural components and the current monitoring information of each of the second abnormal structural components includes:

[0020] Dividing each of the first abnormal structural components into abnormal structural component groups corresponding to each abnormal monitoring indicator type, and querying the task abnormality type of the current task information based on the monitoring indicator value of each of the abnormal monitoring indicator types;

[0021] Based on the current monitoring information of each first abnormal structural component of the abnormal structural component group corresponding to each monitoring indicator type, identifying the monitoring information deviation value of each first abnormal structural component through the abnormality analysis strategy of the task abnormality type, and using the task abnormality type of the current task information and the monitoring information deviation value of each first abnormal structural component as the first abnormal monitoring result;

[0022] For each second abnormal structural component, based on the abnormality monitoring target of the second abnormal structural component, the abnormality cause of the second abnormal structural component is identified through the abnormality monitoring and analysis network, and based on the current monitoring information of the second abnormal structural component and the abnormality cause of the second abnormal structural component, the degree of structural abnormality of the second abnormal structural component is inquired;

[0023] taking the abnormality cause of each second abnormal structural component and the degree of structural abnormality of each second abnormal structural component as a second abnormality monitoring result;

[0024] The first abnormality monitoring result and the second abnormality monitoring result are used as the abnormality monitoring results of the intelligent liquid dispensing machine.

[0025] Optionally, generating an emergency treatment plan for the intelligent liquid dispensing machine based on the abnormality monitoring result of the intelligent liquid dispensing machine includes:

[0026] For the first abnormality monitoring result, based on the task abnormality type of the current task information, querying the task emergency processing strategy of the current task information in the task abnormality emergency database, and generating a first emergency processing plan for the first abnormality monitoring result based on the monitoring information deviation value of each first abnormal structural component and using each task emergency processing strategy;

[0027] For each second abnormal structural component, based on the abnormality cause of the second abnormal structural component, query the structural abnormality emergency database for each initial emergency treatment plan corresponding to the second abnormal structural component, and based on the degree of the structural abnormality of the second abnormal structural component, select a target emergency treatment plan for the second abnormal structural component from each of the initial emergency treatment plans;

[0028] The target emergency treatment plan for all second abnormal structural components is used as the second emergency treatment plan for the second abnormal monitoring result, and the first emergency treatment plan for the first abnormal monitoring result and the second emergency treatment plan for the second abnormal monitoring result are used as the emergency treatment plan for the intelligent liquid discharge machine.

[0029] In a second aspect, the present application also provides an abnormal emergency control device for an intelligent liquid dispensing machine, comprising:

[0030] an acquisition module, configured to acquire current task information of the intelligent liquid dispensing machine and current monitoring information of each structural component of the intelligent liquid dispensing machine, and query each target structural component associated with the current task information and task monitoring requirement information of the current task information;

[0031] an identification module, configured to identify a first abnormal structural component among each of the target structural components based on current monitoring information of each of the target structural components and through task monitoring requirement information of the current task information, and to identify a second abnormal structural component among each of the structural components based on current monitoring information of each of the structural components and through a component monitoring strategy of each of the structural components;

[0032] A generation module is used to generate abnormal monitoring results of the intelligent liquid dispensing machine based on the current monitoring information of each of the first abnormal structural components and the current monitoring information of each of the second abnormal structural components through the abnormal analysis strategy of the intelligent liquid dispensing machine, and generate an emergency treatment plan for the intelligent liquid dispensing machine based on the abnormal monitoring results of the intelligent liquid dispensing machine.

[0033] Optionally, the acquisition module is specifically configured to:

[0034] In a task database, query the task type corresponding to the current task information and the task flow corresponding to the current task information, and identify the participating structural components of the task flow and the associated structural components corresponding to the task type;

[0035] Performing component deduplication processing on each of the participating structural components and each of the associated structural components, screening each target structural component associated with the task information, and querying the structure monitoring requirement information of the current task information in the liquid discharge machine monitoring database based on the task flow and the task type;

[0036] The structure monitoring requirement information of the current task information is used as the task monitoring requirement information of the current task information.

[0037] Optionally, the identification module is specifically configured to:

[0038] Based on the current monitoring information of each target structural component, identifying the current operating data of each target structural component, and based on the task monitoring requirement information of the current task information, identifying the indicator monitoring scheme of each monitoring indicator type of the current task information and the monitoring structural component corresponding to each monitoring indicator type;

[0039] Based on the current operating data of each of the target structural components, the monitoring indicator values of each of the monitoring indicator types are monitored respectively through the indicator monitoring scheme of each of the monitoring indicator types, and based on the monitoring indicator values of each of the monitoring indicator types and the monitoring structural components corresponding to each monitoring indicator type, the first abnormal structural component in each of the target structural components is identified.

[0040] Optionally, the identification module is specifically configured to:

[0041] Based on the current monitoring information of each structural component, the structural operation data of each structural component is identified, and for each structural component, based on the structural operation data of the structural component and using the component monitoring strategy of the structural component, the target monitoring result of the structural component at each monitoring target is identified;

[0042] Based on the target monitoring results of each monitoring target, the abnormal monitoring targets in each monitoring target are queried through the standard operation database of the structural components, and the structural components with abnormal monitoring targets are regarded as the second abnormal structural components in each structural components.

[0043] Optionally, the generating module is specifically configured to:

[0044] Dividing each of the first abnormal structural components into abnormal structural component groups corresponding to each abnormal monitoring indicator type, and querying the task abnormality type of the current task information based on the monitoring indicator value of each of the abnormal monitoring indicator types;

[0045] Based on the current monitoring information of each first abnormal structural component of the abnormal structural component group corresponding to each monitoring indicator type, identifying the monitoring information deviation value of each first abnormal structural component through the abnormality analysis strategy of the task abnormality type, and using the task abnormality type of the current task information and the monitoring information deviation value of each first abnormal structural component as the first abnormal monitoring result;

[0046] For each second abnormal structural component, based on the abnormality monitoring target of the second abnormal structural component, the abnormality cause of the second abnormal structural component is identified through the abnormality monitoring and analysis network, and based on the current monitoring information of the second abnormal structural component and the abnormality cause of the second abnormal structural component, the degree of structural abnormality of the second abnormal structural component is inquired;

[0047] taking the abnormality cause of each second abnormal structural component and the degree of structural abnormality of each second abnormal structural component as a second abnormality monitoring result;

[0048] The first abnormality monitoring result and the second abnormality monitoring result are used as the abnormality monitoring results of the intelligent liquid dispensing machine.

[0049] Optionally, the generating module is specifically configured to:

[0050] For the first abnormality monitoring result, based on the task abnormality type of the current task information, querying the task emergency processing strategy of the current task information in the task abnormality emergency database, and generating a first emergency processing plan for the first abnormality monitoring result based on the monitoring information deviation value of each first abnormal structural component and using each task emergency processing strategy;

[0051] For each second abnormal structural component, based on the abnormality cause of the second abnormal structural component, query the structural abnormality emergency database for each initial emergency treatment plan corresponding to the second abnormal structural component, and based on the degree of the structural abnormality of the second abnormal structural component, select a target emergency treatment plan for the second abnormal structural component from each of the initial emergency treatment plans;

[0052] The target emergency treatment plan for all second abnormal structural components is used as the second emergency treatment plan for the second abnormal monitoring result, and the first emergency treatment plan for the first abnormal monitoring result and the second emergency treatment plan for the second abnormal monitoring result are used as the emergency treatment plan for the intelligent liquid discharge machine.

[0053] In a third aspect, the present application provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of any one of the methods described in the first aspect when executing the computer program.

[0054] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of any one of the methods in the first aspect.

[0055] In a fifth aspect, the present application provides a computer program product, wherein the computer program product comprises a computer program, and when the computer program is executed by a processor, the steps of any one of the methods in the first aspect are implemented.

[0056] The above-mentioned abnormal emergency management method, device and computer equipment of the intelligent liquid dispensing machine obtain the current task information of the intelligent liquid dispensing machine and the current monitoring information of each structural component of the intelligent liquid dispensing machine, and query each target structural component associated with the current task information and the task monitoring requirement information of the current task information; based on the current monitoring information of each target structural component, through the task monitoring requirement information of the current task information, identify the first abnormal structural component in each target structural component, and based on the current monitoring information of each structural component, through the component monitoring strategy of each structural component, identify the second abnormal structural component in each structural component; based on the current monitoring information of each first abnormal structural component and the current monitoring information of each second abnormal structural component, through the intelligent liquid dispensing machine abnormal analysis strategy, generate the abnormal monitoring result of the intelligent liquid dispensing machine, and based on the abnormal monitoring result of the intelligent liquid dispensing machine, generate the emergency treatment plan of the intelligent liquid dispensing machine. This solution improves the comprehensiveness, timeliness, and accuracy of monitoring the intelligent liquid dispensing machine by separately monitoring each structural component of the intelligent liquid dispensing machine and obtaining the current monitoring information of each structural component in real time. Then, this solution judges the abnormal structural components in each structural component from the perspective of the current task information and the structural components themselves, thereby improving the comprehensiveness and accuracy of abnormal identification of abnormal structural components. After that, this solution intelligently generates abnormal monitoring results of the intelligent liquid dispensing machine and generates an emergency treatment plan for the intelligent liquid dispensing machine from the perspective of the current task information and the structural components themselves, thereby effectively solving the abnormal causes of each abnormal structural component and each abnormal situation of each abnormal structural component, effectively avoiding the inefficiency and one-sidedness of manual monitoring and manual operation, as well as the low accuracy of identification and analysis of abnormal situations, thereby comprehensively improving the efficiency of emergency treatment of abnormal discharge volume. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following briefly introduces the drawings required for use in the embodiments or related technical descriptions. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0058] Figure 1 Schematic diagram of a flow chart of an abnormal emergency control method for an intelligent liquid dispensing machine in one embodiment;

[0059] Figure 2 A schematic diagram of a process for an example of emergency management and control of an intelligent liquid dispensing machine in one embodiment;

[0060] Figure 3 This is a structural block diagram of an abnormal emergency control device of an intelligent liquid dispensing machine in one embodiment;

[0061] Figure 4 FIG. 1 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0062] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0063] The abnormal emergency control method of the intelligent liquid dispensing machine provided in the embodiment of the present application can be applied to the application environment of the abnormal emergency control of the intelligent liquid dispensing machine. Among them, the control module can be a terminal, and the terminal can be but not limited to various personal computers, laptops, mid-range computers, etc. Among them, the terminal improves the comprehensiveness, timeliness and accuracy of monitoring of the intelligent liquid dispensing machine by monitoring each structural component of the intelligent liquid dispensing machine separately and obtaining the current monitoring information of each structural component in real time. Then, this solution judges the abnormal structural components in each structural component respectively from the perspective of the current task information and each structural component itself, thereby improving the comprehensiveness of abnormal identification of abnormal structural components and the accuracy of abnormal identification. Then, this solution intelligently generates abnormal monitoring results of the intelligent liquid discharge machine and generates an emergency treatment plan for the intelligent liquid discharge machine from the perspective of current task information and each structural component itself, thereby effectively solving the abnormal causes of each abnormal structural component and each abnormal condition of each abnormal structural component, effectively avoiding the inefficiency and one-sidedness of manual monitoring and manual operation, as well as the low accuracy of identification and analysis of abnormal conditions, thereby comprehensively improving the emergency treatment efficiency of abnormal discharge volume.

[0064] In an exemplary embodiment, Figure 1 As shown, a method for emergency control of abnormalities of an intelligent liquid dispensing machine is provided, which is described by taking the application of the method to a terminal as an example, and includes the following steps S101 to S103. Among them:

[0065] Step S101: obtaining the current task information of the intelligent liquid dispensing machine and the current monitoring information of each structural component of the intelligent liquid dispensing machine, and querying each target structural component associated with the current task information and the task monitoring requirement information of the current task information.

[0066] In this embodiment, when the intelligent liquid dispensing machine is operating, the terminal acquires in real time the sensor data transmitted by the sensors installed on each structural component of the intelligent liquid dispensing machine, obtains the current monitoring information of each structural component, and obtains the task information currently being executed by the intelligent liquid dispensing machine from the control device of the intelligent liquid dispensing machine, obtaining the current task information. The structural components include, but are not limited to, structural components such as the discharge pipe, the refilling bucket, the weighing device, the control device, the valve, and the temperature control device. The current task information includes, but is not limited to, the discharge task for each product type, the refilling task, the self-cleaning task for each discharge pipe, etc. The terminal then queries the target structural components associated with the current task information and the task monitoring requirement information of the current task information. The target structural components associated with each current task information can be different or the same, and the number of target structural components associated with each current task information can be unique or non-unique. The task monitoring requirement information includes the indicator monitoring plan for each monitoring indicator type that needs to be monitored for the current task information. Examples of monitoring indicator types include liquid output deviation, liquid output rate deviation, temperature fluctuation range, and deviation between weighing change and barrel weight change. The specific query process will be described in detail later.

[0067] Step S102: Based on the current monitoring information of each target structural component and through the task monitoring requirement information of the current task information, a first abnormal structural component in each target structural component is identified; and based on the current monitoring information of each structural component and through the component monitoring strategy of each structural component, a second abnormal structural component in each structural component is identified.

[0068] In this embodiment, the terminal identifies the first abnormal structural component in each target structural component based on the current monitoring information of each target structural component and the task monitoring requirement information of the current task information, and identifies the second abnormal structural component in each structural component based on the current monitoring information of each structural component and the component monitoring strategy of each structural component. The first abnormal structural component is a structural component associated with the current task information that has an abnormality when executing the current task information, and the second abnormal structural component is a structural component in each structural component that has an abnormality during operation. The structural component can be both the first abnormal structural component and the second abnormal structural component, and the abnormal reasons for the two abnormal structural components are different. It can also be the first abnormal structural component or the second abnormal structural component alone. That is, when the structural component executing the current task information has an abnormality, it can be that the abnormality occurs during operation, or it can be that the abnormality does not occur during operation and only occurs when executing the current task. Alternatively, while the information for executing a single level mission may not be abnormal, an abnormal component may have developed during actual operation. For example, if the discharge volume of each discharge pipe is abnormal, but the discharge volume is within the normal discharge range of each pipe, then the discharge pipe is only a first abnormal component. However, if the discharge pipe is damaged and leaking, the discharge volume is normal, but the actual amount of liquid in the discharge barrel decreases abnormally, then the discharge pipe is only a second abnormal component. Therefore, through the above monitoring method, comprehensive and accurate monitoring of each component structure can be carried out, improving the accuracy and comprehensiveness of monitoring of each abnormal structure.

[0069] Step S103, based on the current monitoring information of each first abnormal structural component and the current monitoring information of each second abnormal structural component, the abnormal monitoring results of the intelligent liquid dispensing machine are generated through the abnormal analysis strategy of the intelligent liquid dispensing machine, and based on the abnormal monitoring results of the intelligent liquid dispensing machine, an emergency treatment plan for the intelligent liquid dispensing machine is generated.

[0070] In this embodiment, the terminal generates abnormal monitoring results of the intelligent liquid dispensing machine based on the current monitoring information of each first abnormal structural component and the current monitoring information of each second abnormal structural component through the intelligent liquid dispensing machine abnormal analysis strategy, and generates an emergency treatment plan for the intelligent liquid dispensing machine based on the abnormal monitoring results of the intelligent liquid dispensing machine. Among them, the abnormal analysis strategy of the liquid dispensing machine is a strategy for performing abnormal analysis on the first abnormal structural component and the second abnormal structural component respectively, wherein the abnormal monitoring results include a first abnormal monitoring result corresponding to the first abnormal structural component and a second abnormal monitoring result corresponding to the second abnormal structural component. The specific monitoring process will be described in detail later.

[0071] Based on the above scheme, by separately monitoring each structural component of the intelligent liquid dispensing machine and obtaining the current monitoring information of each structural component in real time, the comprehensiveness, timeliness and accuracy of monitoring of the intelligent liquid dispensing machine are improved. Then, this scheme judges the abnormal structural components in each structural component from the perspective of the current task information and the structural components themselves, thereby improving the comprehensiveness of abnormal identification of abnormal structural components and the accuracy of abnormal identification. After that, this scheme intelligently generates abnormal monitoring results of the intelligent liquid dispensing machine and generates an emergency treatment plan for the intelligent liquid dispensing machine from the perspective of the current task information and the structural components themselves, thereby effectively solving the abnormal causes of each abnormal structural component and each abnormal situation of each abnormal structural component, effectively avoiding the inefficiency and one-sidedness of manual monitoring and manual operation, as well as the low accuracy of identification and analysis of abnormal situations, thereby comprehensively improving the efficiency of emergency treatment of abnormal discharge volume.

[0072] Optionally, query the target structural components associated with the current task information and the task monitoring requirement information of the current task information, including: querying the task type corresponding to the current task information and the task process corresponding to the current task information in the task database, and identifying the participating structural components of the task process and the associated structural components corresponding to the task type; performing component deduplication processing on the participating structural components and the associated structural components, screening the target structural components associated with the task information, and querying the structural monitoring requirement information of the current task information in the liquid discharge machine monitoring database based on the task process and the task type; and using the structural monitoring requirement information of the current task information as the task monitoring requirement information of the current task information.

[0073] In this embodiment, the terminal searches the task database for the task type and task flow corresponding to the current task information, and identifies the participating structural components of the task flow and the associated structural components corresponding to the task type. The participating structural components of the task flow are the structural components required to execute each step of the task flow, while the associated structural components corresponding to the task type are structural components that are not directly involved in the task flow but are associated with the task flow. For example, the participating structural components of the liquid discharge task of product type A are the control equipment, discharge barrel, and discharge pipe, while the associated structural components are the weighing equipment, temperature control equipment, etc.

[0074] The terminal performs component deduplication on all participating structural components and associated structural components, screening the target structural components associated with the task information. Based on the task flow and task type, the terminal queries the liquid dispensing machine monitoring database for the structural monitoring requirements for the current task information. The liquid dispensing machine monitoring database includes a correspondence between each task flow and each task type and the structural monitoring requirements information. Finally, the terminal uses the structural monitoring requirements information for the current task information as the task monitoring requirements information for the current task information.

[0075] Based on the above scheme, by comprehensively analyzing the associated structural components and participating structural components of the current task information, the comprehensiveness of the query on the target structural components associated with the current task information is improved. Then, the task monitoring requirement information of the current task information can be directly queried and obtained through the task process and task type, thereby improving the query efficiency of the task monitoring requirement information.

[0076] Optionally, based on the current monitoring information of each target structural component, the first abnormal structural component in each target structural component is identified through the task monitoring requirement information of the current task information, including: based on the current monitoring information of each target structural component, the current operating data of each target structural component is identified, and based on the task monitoring requirement information of the current task information, the indicator monitoring scheme of each monitoring indicator type of the current task information and the monitoring structural component corresponding to each monitoring indicator type are identified; based on the current operating data of each target structural component, the monitoring indicator value of each monitoring indicator type is monitored separately through the indicator monitoring scheme of each monitoring indicator type, and based on the monitoring indicator value of each monitoring indicator type and the monitoring structural component corresponding to each monitoring indicator type, the first abnormal structural component in each target structural component is identified.

[0077] In this embodiment, the terminal identifies the current operating data of each target structural component based on the current monitoring information of each target structural component, and identifies the indicator monitoring scheme for each monitoring indicator type of the current task information and the monitoring structural component corresponding to each monitoring indicator type based on the task monitoring requirement information of the current task information. The monitoring structural component is the target structural component primarily monitored by the indicator monitoring scheme. The indicator monitoring scheme is a scheme that performs a comprehensive analysis and calculation on the current operating data of each target structural component to generate a monitoring indicator value for that monitoring indicator type. The monitoring indicator scheme includes a data analysis scheme and an indicator evaluation scheme. The data analysis scheme is used to analyze the data value of the monitoring indicator type corresponding to the current operating data of each target structural component, such as the liquid output deviation value of each discharge pipe of the liquid output deviation indicator type. The indicator evaluation scheme is used to evaluate the indicator value corresponding to the data value of the monitoring indicator type and use the indicator value as the monitoring indicator value. The indicator evaluation scheme includes the data value range corresponding to each indicator value. The terminal directly uses the indicator value corresponding to the data value range adapted to the data value of the monitoring indicator type as the monitoring indicator value.

[0078] Then, based on the current operating data of each target structural component, the terminal monitors the monitoring indicator value of each monitoring indicator type using the indicator monitoring solution for each monitoring indicator type, and identifies the first abnormal structural component in each target structural component based on the monitoring indicator value of each monitoring indicator type and the monitoring structural component corresponding to each monitoring indicator type. Each first abnormal structural component is a monitoring structural component associated with an abnormal monitoring indicator type corresponding to a monitoring indicator value that exceeds a monitoring indicator threshold value in each monitoring indicator type.

[0079] Based on the above solution, abnormal structural components are identified by classifying monitoring indicators, thereby improving the comprehensiveness and accuracy of the identification of abnormal structural components.

[0080] Optionally, based on the current monitoring information of each structural component, the second abnormal structural component in each structural component is identified through the component monitoring strategy of each structural component, including: based on the current monitoring information of each structural component, the structural operation data of each structural component is identified, and for each structural component, based on the structural operation data of the structural component, the target monitoring result of the structural component in each monitoring target is identified through the component monitoring strategy of the structural component; based on the target monitoring result of each monitoring target, the abnormal monitoring target in each monitoring target is queried through the standard operation database of the structural component, and the structural component with the abnormal monitoring target is regarded as the second abnormal structural component in each structural component.

[0081] In this embodiment, the terminal identifies the structural operation data of each structural component based on the current monitoring information of each structural component, and for each structural component, based on the structural operation data of the structural component, identifies the target monitoring results of the structural component at each monitoring target through the component monitoring strategy of the structural component. Specifically, for each structural component, the terminal distributes and sorts the structural operation data of the structural component in chronological order to obtain the data distribution information of the structural component, and identifies the current monitoring data of each monitoring target of the structural component through the component monitoring strategy, and uses the current monitoring data of the structural component as the target monitoring results of each monitoring target. Among them, the monitoring targets of each structural component are different. For example, the monitoring targets of the discharge pipe include liquid discharge rate, liquid discharge volume, liquid discharge rate fluctuation range, etc. The component monitoring strategy is a strategy for identifying the monitoring data of each monitoring target based on the data distribution information and the monitoring method of each monitoring target.

[0082] Then, based on the target monitoring results for each monitoring target, the terminal searches the standard operation database for that structural component and the structural component database for that structural component for abnormal monitoring targets among those monitoring targets, and identifies the structural component with the abnormal monitoring target as the second abnormal structural component among those structural components. The structural component database stores the normal monitoring data range for each monitoring target of that structural component. The terminal selects monitoring targets whose monitoring data exceeds the normal monitoring range and identifies them as abnormal monitoring targets.

[0083] Based on the above scheme, by analyzing and monitoring each monitoring target separately for each structure, the abnormal monitoring targets of each structural component can be queried and identified, thereby improving the accuracy and comprehensiveness of identifying abnormal information of structural components.

[0084] Optionally, based on the current monitoring information of each first abnormal structural component and the current monitoring information of each second abnormal structural component, an abnormal monitoring result of the intelligent liquid dispensing machine is generated through the abnormal analysis strategy of the intelligent liquid dispensing machine, including: dividing each first abnormal structural component into abnormal structural component groups corresponding to each abnormal monitoring indicator type, and querying the task abnormality type of the current task information based on the monitoring indicator value of each abnormal monitoring indicator type; based on the current monitoring information of each first abnormal structural component of the abnormal structural component group corresponding to each monitoring indicator type, identifying the monitoring information deviation value of each first abnormal structural component through the abnormal analysis strategy of the task abnormality type, and querying the task abnormality type of the current task information The abnormality type and the monitoring information deviation value of each first abnormal structural component are used as the first abnormality monitoring result; for each second abnormal structural component, based on the abnormal monitoring target of the second abnormal structural component, the abnormal cause of the second abnormal structural component is identified through the abnormal monitoring analysis network, and based on the current monitoring information of the second abnormal structural component and the abnormal cause of the second abnormal structural component, the structural abnormality degree of the second abnormal structural component is queried; the abnormal cause of each second abnormal structural component and the structural abnormality degree of each second abnormal structural component are used as the second abnormality monitoring result; the first abnormality monitoring result and the second abnormality monitoring result are used as the abnormality monitoring result of the intelligent liquid discharger.

[0085] In this embodiment, the terminal divides each first abnormal structural component into abnormal structural component groups corresponding to each abnormal monitoring indicator type and queries the task abnormality type of the current task information based on the monitoring indicator value of each abnormal monitoring indicator type. The database stores the abnormal monitoring indicator types corresponding to different task abnormality types, as well as the monitoring indicator value range corresponding to each abnormal monitoring indicator type. By querying this correspondence, the terminal directly obtains the task abnormality type of the current task information, improving the efficiency of identifying task abnormality types.

[0086] Based on the current monitoring information of each first abnormal structural component of the abnormal structural component group corresponding to each monitoring indicator type, the terminal identifies the monitoring information deviation value of each first abnormal structural component through the abnormal analysis strategy of the task abnormality type, and uses the task abnormality type of the current task information and the monitoring information deviation value of each first abnormal structural component as the first abnormal monitoring result. The monitoring information deviation value is the operating data deviation value of the first abnormal structure. For example, when the liquid discharge volume is abnormal, the monitoring information deviation value includes the abnormal liquid discharge volume of each discharge pipe, or the weighing abnormality of the weighing equipment, etc. The abnormal analysis strategy is a calculation strategy for the monitoring information deviation value of each abnormal structural component for each task abnormality type.

[0087] For each second abnormal structural component, the terminal identifies the abnormal cause of the second abnormal structural component through the abnormal monitoring analysis network based on the abnormal monitoring target of the second abnormal structural component, and queries the structural abnormality degree of the second abnormal structural component based on the current monitoring information of the second abnormal structural component and the abnormal cause of the second abnormal structural component. The abnormal monitoring analysis network is a classifier neural network based on reinforcement learning. It is used to analyze the abnormal cause of the abnormal structural component from each abnormal monitoring target. Each abnormal cause is stored in the database with the structural abnormality degree corresponding to different monitoring information ranges. Then, the terminal identifies the structural abnormality degree of each second abnormal structural component by querying the above correspondence. Finally, the terminal uses the abnormal cause of each second abnormal structural component and the structural abnormality degree of each second abnormal structural component as the second abnormal monitoring result.

[0088] The terminal uses the first abnormality monitoring result and the second abnormality monitoring result as the abnormality monitoring result of the intelligent liquid dispensing machine.

[0089] Based on the above solution, by dividing the abnormal structural components, the cause of the abnormality, the degree of abnormality, and the type of abnormality are analyzed, thereby improving the comprehensiveness and accuracy of abnormal monitoring of each abnormal structure.

[0090] Optionally, based on the abnormal monitoring results of the intelligent liquid dispenser, an emergency treatment plan for the intelligent liquid dispenser is generated, including: for the first abnormal monitoring result, based on the task abnormality type of the current task information, querying the task emergency treatment strategy of the current task information in the task abnormality emergency database, and based on the monitoring information deviation value of each first abnormal structural component, generating a first emergency treatment plan for the first abnormal monitoring result through each task emergency treatment strategy; for each second abnormal structural component, based on the abnormal cause of the second abnormal structural component, querying the initial emergency treatment plans corresponding to the second abnormal structural component in the structural abnormality emergency database, and based on the structural abnormality degree of the second abnormal structural component, screening the target emergency treatment plan for the second abnormal structural component in each initial emergency treatment plan; using the target emergency treatment plans of all second abnormal structural components as the second emergency treatment plan for the second abnormal monitoring result, and using the first emergency treatment plan for the first abnormal monitoring result and the second emergency treatment plan for the second abnormal monitoring result as the emergency treatment plan for the intelligent liquid dispenser.

[0091] In this embodiment, the terminal searches for the task emergency response strategy of the current task information in the task abnormality emergency database based on the task abnormality type of the current task information for the first abnormality monitoring result, and generates a first emergency response plan for the first abnormality monitoring result through each task emergency response strategy based on the monitoring information deviation value of each first abnormal structural component. Among them, the task abnormality emergency database stores task emergency response strategies corresponding to different task abnormality types, and each task emergency response strategy corresponds to the monitoring information deviation range of each abnormal structural component corresponding to the task abnormality type. Therefore, based on the current monitoring information of each first abnormal structural component, the terminal directly selects the first emergency response plan for the first abnormality monitoring result in each task emergency response strategy through range matching.

[0092] For each second-abnormal structural component, the terminal searches the structural abnormality emergency database for the corresponding initial emergency response plans based on the cause of the abnormality of the second abnormal structural component. Based on the degree of the structural abnormality of the second abnormal structural component, the terminal selects a target emergency response plan for the second abnormal structural component from among the initial emergency response plans. Each initial emergency response plan corresponds to a range of structural abnormality degrees, and the terminal selects the target emergency response plan for the second abnormal structural component from among the initial emergency response plans through range adaptation.

[0093] Finally, the terminal uses the target emergency treatment plan for all second abnormal structural components as the second emergency treatment plan for the second abnormal monitoring result, and uses the first emergency treatment plan for the first abnormal monitoring result and the second emergency treatment plan for the second abnormal monitoring result as the emergency treatment plan for the intelligent liquid dispenser.

[0094] Based on the above solution, by querying the solution and performing range adaptation, emergency response plans for different abnormal monitoring results can be efficiently generated, thereby improving the generation efficiency and accuracy of emergency response plans.

[0095] The application also provides an example of abnormal emergency control of a smart liquid dispensing machine, such as Figure 2 As shown, the specific processing process includes the following steps:

[0096] Step S201: Acquire current task information of the intelligent liquid dispensing machine and current monitoring information of each structural component of the intelligent liquid dispensing machine.

[0097] Step S202 : In the task database, the task type corresponding to the current task information and the task flow corresponding to the current task information are searched, and the participating structural components of the task flow and the associated structural components corresponding to the task type are identified.

[0098] In step S203, duplicate components are removed from all participating structural components and associated structural components, target structural components associated with the task information are screened, and based on the task flow and task type, the structure monitoring requirement information of the current task information is queried in the liquid discharge machine monitoring database.

[0099] Step S204: Using the structure monitoring requirement information of the current task information as the task monitoring requirement information of the current task information.

[0100] Step S205: Based on the current monitoring information of each target structural component, the current operating data of each target structural component is identified, and based on the task monitoring requirement information of the current task information, the indicator monitoring scheme of each monitoring indicator type of the current task information and the monitoring structural component corresponding to each monitoring indicator type are identified.

[0101] Step S206: Based on the current operating data of each target structural component, the monitoring indicator value of each monitoring indicator type is monitored separately through the indicator monitoring scheme of each monitoring indicator type, and based on the monitoring indicator value of each monitoring indicator type and the monitoring structural component corresponding to each monitoring indicator type, the first abnormal structural component in each target structural component is identified.

[0102] Step S207 , based on the current monitoring information of each structural component, the structural operation data of each structural component is identified, and for each structural component, based on the structural operation data of the structural component and through the component monitoring strategy of the structural component, the target monitoring result of the structural component at each monitoring target is identified.

[0103] Step S208 , based on the target monitoring results of each monitoring target, query the abnormal monitoring targets among the monitoring targets through the standard operation database of the structural components, and take the structural components with abnormal monitoring targets as the second abnormal structural components among the structural components.

[0104] Step S209 : dividing each first abnormal structural component into abnormal structural component groups corresponding to each abnormal monitoring indicator type, and querying the task abnormality type of the current task information based on the monitoring indicator value of each abnormal monitoring indicator type.

[0105] Step S210, based on the current monitoring information of each first abnormal structural component of the abnormal structural component group corresponding to each monitoring indicator type, the monitoring information deviation value of each first abnormal structural component is identified through the abnormal analysis strategy of the task abnormality type, and the task abnormality type of the current task information and the monitoring information deviation value of each first abnormal structural component are used as the first abnormal monitoring result.

[0106] In step S211, for each second abnormal structural component, based on the abnormal monitoring target of the second abnormal structural component, the abnormal cause of the second abnormal structural component is identified through the abnormal monitoring analysis network, and based on the current monitoring information of the second abnormal structural component and the abnormal cause of the second abnormal structural component, the structural abnormality degree of the second abnormal structural component is inquired.

[0107] In step S212, the abnormality cause of each second abnormal structural component and the degree of structural abnormality of each second abnormal structural component are taken as the second abnormality monitoring result.

[0108] Step S213: Use the first abnormality monitoring result and the second abnormality monitoring result as the abnormality monitoring result of the intelligent liquid dispensing machine.

[0109] In step S214, for the first abnormal monitoring result, based on the task abnormality type of the current task information, the task emergency handling strategy of the current task information is queried in the task abnormality emergency database, and based on the monitoring information deviation value of each first abnormal structural component, the first emergency handling plan for the first abnormal monitoring result is generated through each task emergency handling strategy.

[0110] Step S215: For each second abnormal structural component, based on the abnormal cause of the second abnormal structural component, query the structural abnormality emergency database for each initial emergency treatment plan corresponding to the second abnormal structural component, and based on the degree of structural abnormality of the second abnormal structural component, select the target emergency treatment plan for the second abnormal structural component from each initial emergency treatment plan.

[0111] Step S216: Use the target emergency treatment plan for all second abnormal structural components as the second emergency treatment plan for the second abnormal monitoring result, and use the first emergency treatment plan for the first abnormal monitoring result and the second emergency treatment plan for the second abnormal monitoring result as the emergency treatment plan for the intelligent liquid dispensing machine.

[0112] It should be understood that, although the various steps in the flowcharts involved in the various embodiments described above are displayed in sequence according to the instructions of the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the flowcharts involved in the various embodiments described above can include multiple steps or multiple stages, and these steps or stages are not necessarily executed and completed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of steps or stages in other steps.

[0113] Based on the same inventive concept, the embodiments of the present application also provide an abnormal emergency control device for an intelligent liquid dispensing machine for implementing the abnormal emergency control method for the intelligent liquid dispensing machine involved above. The implementation solution provided by this device is similar to the implementation solution described in the above method. Therefore, the specific limitations in the embodiments of one or more abnormal emergency control devices for intelligent liquid dispensing machines provided below can be found in the above-mentioned limitations on the abnormal emergency control method for intelligent liquid dispensing machines, and will not be repeated here.

[0114] In an exemplary embodiment, Figure 3 As shown, an abnormal emergency control device for an intelligent liquid dispensing machine is provided, including: an acquisition module 310, an identification module 320 and a generation module 330, wherein:

[0115] An acquisition module 310 is configured to acquire current task information of the intelligent liquid dispensing machine and current monitoring information of each structural component of the intelligent liquid dispensing machine, and query each target structural component associated with the current task information and task monitoring requirement information of the current task information;

[0116] an identification module 320 configured to identify, based on the current monitoring information of each target structural component and the task monitoring requirement information of the current task information, a first abnormal structural component among each target structural component, and to identify, based on the current monitoring information of each structural component and the component monitoring strategy of each structural component, a second abnormal structural component among each structural component;

[0117] The generation module 330 is used to generate the abnormal monitoring results of the intelligent liquid dispensing machine based on the current monitoring information of each of the first abnormal structural components and the current monitoring information of each of the second abnormal structural components through the abnormal analysis strategy of the intelligent liquid dispensing machine, and generate the emergency treatment plan of the intelligent liquid dispensing machine based on the abnormal monitoring results of the intelligent liquid dispensing machine.

[0118] Optionally, the acquisition module 310 is specifically configured to:

[0119] In a task database, query the task type corresponding to the current task information and the task flow corresponding to the current task information, and identify the participating structural components of the task flow and the associated structural components corresponding to the task type;

[0120] Performing component deduplication processing on each of the participating structural components and each of the associated structural components, screening each target structural component associated with the task information, and querying the structure monitoring requirement information of the current task information in the liquid discharge machine monitoring database based on the task flow and the task type;

[0121] The structure monitoring requirement information of the current task information is used as the task monitoring requirement information of the current task information.

[0122] Optionally, the identification module 320 is specifically configured to:

[0123] Based on the current monitoring information of each target structural component, identifying the current operating data of each target structural component, and based on the task monitoring requirement information of the current task information, identifying the indicator monitoring scheme of each monitoring indicator type of the current task information and the monitoring structural component corresponding to each monitoring indicator type;

[0124] Based on the current operating data of each of the target structural components, the monitoring indicator values of each of the monitoring indicator types are monitored respectively through the indicator monitoring scheme of each of the monitoring indicator types, and based on the monitoring indicator values of each of the monitoring indicator types and the monitoring structural components corresponding to each monitoring indicator type, the first abnormal structural component in each of the target structural components is identified.

[0125] Optionally, the identification module 320 is specifically configured to:

[0126] Based on the current monitoring information of each structural component, the structural operation data of each structural component is identified, and for each structural component, based on the structural operation data of the structural component and using the component monitoring strategy of the structural component, the target monitoring result of the structural component at each monitoring target is identified;

[0127] Based on the target monitoring results of each monitoring target, the abnormal monitoring targets in each monitoring target are queried through the standard operation database of the structural components, and the structural components with abnormal monitoring targets are regarded as the second abnormal structural components in each structural components.

[0128] Optionally, the generating module 330 is specifically configured to:

[0129] Dividing each of the first abnormal structural components into abnormal structural component groups corresponding to each abnormal monitoring indicator type, and querying the task abnormality type of the current task information based on the monitoring indicator value of each of the abnormal monitoring indicator types;

[0130] Based on the current monitoring information of each first abnormal structural component of the abnormal structural component group corresponding to each monitoring indicator type, identifying the monitoring information deviation value of each first abnormal structural component through the abnormality analysis strategy of the task abnormality type, and using the task abnormality type of the current task information and the monitoring information deviation value of each first abnormal structural component as the first abnormal monitoring result;

[0131] For each second abnormal structural component, based on the abnormality monitoring target of the second abnormal structural component, the abnormality cause of the second abnormal structural component is identified through the abnormality monitoring and analysis network, and based on the current monitoring information of the second abnormal structural component and the abnormality cause of the second abnormal structural component, the degree of structural abnormality of the second abnormal structural component is inquired;

[0132] taking the abnormality cause of each second abnormal structural component and the degree of structural abnormality of each second abnormal structural component as a second abnormality monitoring result;

[0133] The first abnormality monitoring result and the second abnormality monitoring result are used as the abnormality monitoring results of the intelligent liquid dispensing machine.

[0134] Optionally, the generating module 330 is specifically configured to:

[0135] For the first abnormality monitoring result, based on the task abnormality type of the current task information, querying the task emergency processing strategy of the current task information in the task abnormality emergency database, and generating a first emergency processing plan for the first abnormality monitoring result based on the monitoring information deviation value of each first abnormal structural component and using each task emergency processing strategy;

[0136] For each second abnormal structural component, based on the abnormality cause of the second abnormal structural component, query the structural abnormality emergency database for each initial emergency treatment plan corresponding to the second abnormal structural component, and based on the degree of the structural abnormality of the second abnormal structural component, select a target emergency treatment plan for the second abnormal structural component from each of the initial emergency treatment plans;

[0137] The target emergency treatment plan for all second abnormal structural components is used as the second emergency treatment plan for the second abnormal monitoring result, and the first emergency treatment plan for the first abnormal monitoring result and the second emergency treatment plan for the second abnormal monitoring result are used as the emergency treatment plan for the intelligent liquid discharge machine.

[0138] Each module in the abnormal emergency control device of the intelligent liquid dispensing machine can be implemented in whole or in part through software, hardware, or a combination thereof. Each module can be embedded in or independent of the processor of the computer device in hardware form, or can be stored in the memory of the computer device in software form, so that the processor can call and execute the corresponding operations of each module.

[0139] In an exemplary embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as shown in FIG. Figure 4As shown. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit and an input device. The processor, the memory and the input / output interface are connected via a system bus, and the communication interface, the display unit and the input device are connected to the system bus via the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be implemented through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, an abnormal emergency control method for an intelligent liquid dispensing machine is implemented. The display unit of the computer device is used to form a visually visible picture, which can be a display screen, a projection device or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device casing, or an external keyboard, touchpad or mouse.

[0140] Those skilled in the art will understand that Figure 4 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0141] In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the steps of the abnormal emergency management method of the intelligent liquid dispensing machine are implemented.

[0142] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of the abnormal emergency management method of the intelligent liquid dispensing machine are implemented.

[0143] In one embodiment, a computer program product is provided, including a computer program, which, when executed by a processor, implements the steps of the abnormal emergency management method of the intelligent liquid dispensing machine.

[0144] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0145] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, database or other media used in the embodiments provided in this application may include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory may include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processor involved in the various embodiments provided herein may be, but are not limited to, a general-purpose processor, a central processing unit, a graphics processing unit, a digital signal processor, a programmable logic unit, a data processing logic unit based on quantum computing, and the like.

[0146] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0147] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and these modifications and improvements fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A method for emergency control of an intelligent liquid dispensing machine, characterized in that: The method comprises: Obtaining current task information of the intelligent liquid dispensing machine and current monitoring information of each structural component of the intelligent liquid dispensing machine, and querying each target structural component associated with the current task information and task monitoring requirement information of the current task information; Based on the current monitoring information of each target structural component and by using the task monitoring requirement information of the current task information, a first abnormal structural component among each target structural component is identified; and based on the current monitoring information of each structural component and by using the component monitoring strategy of each structural component, a second abnormal structural component among each structural component is identified; Based on the current monitoring information of each of the first abnormal structural components and the current monitoring information of each of the second abnormal structural components, the abnormal monitoring results of the intelligent liquid dispensing machine are generated through the abnormal analysis strategy of the intelligent liquid dispensing machine, and based on the abnormal monitoring results of the intelligent liquid dispensing machine, an emergency treatment plan for the intelligent liquid dispensing machine is generated.

2. The method according to claim 1, characterized in that The querying of each target structural component associated with the current task information and the task monitoring requirement information of the current task information includes: In a task database, query the task type corresponding to the current task information and the task flow corresponding to the current task information, and identify the participating structural components of the task flow and the associated structural components corresponding to the task type; Performing component deduplication processing on each of the participating structural components and each of the associated structural components, screening each target structural component associated with the task information, and querying the structure monitoring requirement information of the current task information in the liquid discharge machine monitoring database based on the task flow and the task type; The structure monitoring requirement information of the current task information is used as the task monitoring requirement information of the current task information.

3. The method according to claim 1, characterized in that The identifying, based on the current monitoring information of each target structural component and using the task monitoring requirement information of the current task information, a first abnormal structural component among each target structural component includes: Based on the current monitoring information of each target structural component, identifying the current operating data of each target structural component, and based on the task monitoring requirement information of the current task information, identifying the indicator monitoring scheme of each monitoring indicator type of the current task information and the monitoring structural component corresponding to each monitoring indicator type; Based on the current operating data of each of the target structural components, the monitoring indicator values of each of the monitoring indicator types are monitored respectively through the indicator monitoring scheme of each of the monitoring indicator types, and based on the monitoring indicator values of each of the monitoring indicator types and the monitoring structural components corresponding to each monitoring indicator type, the first abnormal structural component in each of the target structural components is identified.

4. The method according to claim 1, wherein The identifying, based on the current monitoring information of each of the structural components and using a component monitoring strategy for each of the structural components, a second abnormal structural component among the structural components includes: Based on the current monitoring information of each structural component, the structural operation data of each structural component is identified, and for each structural component, based on the structural operation data of the structural component and using the component monitoring strategy of the structural component, the target monitoring result of the structural component at each monitoring target is identified; Based on the target monitoring results of each monitoring target, the abnormal monitoring targets in each monitoring target are queried through the standard operation database of the structural components, and the structural components with abnormal monitoring targets are regarded as the second abnormal structural components in each structural components.

5. The method according to claim 3, characterized in that The abnormality analysis strategy of the intelligent liquid dispensing machine is used to generate the abnormality monitoring result of the intelligent liquid dispensing machine based on the current monitoring information of each of the first abnormal structural components and the current monitoring information of each of the second abnormal structural components, including: Dividing each of the first abnormal structural components into abnormal structural component groups corresponding to each abnormal monitoring indicator type, and querying the task abnormality type of the current task information based on the monitoring indicator value of each of the abnormal monitoring indicator types; Based on the current monitoring information of each first abnormal structural component of the abnormal structural component group corresponding to each monitoring indicator type, identifying the monitoring information deviation value of each first abnormal structural component through the abnormality analysis strategy of the task abnormality type, and using the task abnormality type of the current task information and the monitoring information deviation value of each first abnormal structural component as the first abnormal monitoring result; For each second abnormal structural component, based on the abnormality monitoring target of the second abnormal structural component, the abnormality cause of the second abnormal structural component is identified through the abnormality monitoring and analysis network, and based on the current monitoring information of the second abnormal structural component and the abnormality cause of the second abnormal structural component, the degree of structural abnormality of the second abnormal structural component is inquired; taking the abnormality cause of each second abnormal structural component and the degree of structural abnormality of each second abnormal structural component as a second abnormality monitoring result; The first abnormality monitoring result and the second abnormality monitoring result are used as the abnormality monitoring results of the intelligent liquid dispensing machine.

6. The method according to claim 5, characterized in that The generating of an emergency treatment plan for the intelligent liquid dispensing machine based on the abnormality monitoring result of the intelligent liquid dispensing machine includes: For the first abnormality monitoring result, based on the task abnormality type of the current task information, querying the task emergency processing strategy of the current task information in the task abnormality emergency database, and generating a first emergency processing plan for the first abnormality monitoring result based on the monitoring information deviation value of each first abnormal structural component and using each task emergency processing strategy; For each second abnormal structural component, based on the abnormality cause of the second abnormal structural component, query the structural abnormality emergency database for each initial emergency treatment plan corresponding to the second abnormal structural component, and based on the degree of the structural abnormality of the second abnormal structural component, select a target emergency treatment plan for the second abnormal structural component from each of the initial emergency treatment plans; The target emergency treatment plan for all second abnormal structural components is used as the second emergency treatment plan for the second abnormal monitoring result, and the first emergency treatment plan for the first abnormal monitoring result and the second emergency treatment plan for the second abnormal monitoring result are used as the emergency treatment plan for the intelligent liquid discharge machine.

7. An abnormal emergency control device for an intelligent liquid dispensing machine, characterized in that: The device comprises: an acquisition module, configured to acquire current task information of the intelligent liquid dispensing machine and current monitoring information of each structural component of the intelligent liquid dispensing machine, and query each target structural component associated with the current task information and task monitoring requirement information of the current task information; an identification module, configured to identify a first abnormal structural component among each of the target structural components based on current monitoring information of each of the target structural components and through task monitoring requirement information of the current task information, and to identify a second abnormal structural component among each of the structural components based on current monitoring information of each of the structural components and through a component monitoring strategy of each of the structural components; A generation module is used to generate abnormal monitoring results of the intelligent liquid dispensing machine based on the current monitoring information of each of the first abnormal structural components and the current monitoring information of each of the second abnormal structural components through the abnormal analysis strategy of the intelligent liquid dispensing machine, and generate an emergency treatment plan for the intelligent liquid dispensing machine based on the abnormal monitoring results of the intelligent liquid dispensing machine.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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