Equipment state detection method and device based on complex event and digital twinning, equipment and storage medium

Abstract

The invention discloses an equipment state detection method and device based on complex events and digital twinning, equipment and a storage medium. The method comprises the following steps: acquiring real data after initializing an equipment state; the data items of the real data comprise machine tool operation parameters, main shaft rotating speed, feeding amount, machine tool main shaft temperature and machine tool main shaft vibration amplitude; constructing a digital twinborn model according to the equipment; real data is preprocessed through the virtual-real interaction module, and the preprocessed real data is input into the digital twinborn model to realize virtual-real synchronization; constructing a database comprising an equipment operation and maintenance index system according to simulation data generated by the digital twin model and the preprocessed real data; constructing a rule base according to the data of the database and the equipment operation and maintenance index system; the rule base is used for determining the running state of the current equipment; according to the invention, real-time monitoring, fault prediction and accurate maintenance of the equipment operation state are realized through the rule base.

Description

Technical Field

[0001] The present invention relates to the field of equipment detection, and particularly to a method, device, equipment and storage medium for equipment status detection based on complex events and digital twins. Background Art

[0002] Traditional equipment detection and maintenance methods often rely on manual inspections and regular maintenance. This method is not only inefficient but also difficult to cope with complex and changeable industrial environments. With the increase in equipment complexity, traditional detection means are no longer sufficient to meet the requirements for real-time monitoring and precise maintenance of equipment operation status.

[0003] Currently, some intelligent detection technologies have been applied to the maintenance of industrial equipment, such as vibration monitoring, temperature monitoring, etc. However, these technologies can only provide single-dimensional data and are difficult to comprehensively reflect the operation status of equipment. At the same time, they lack real-time performance and predictability, and cannot detect potential faults in advance, resulting in high maintenance costs and low efficiency. On the other hand, as an emerging digital means, digital twin technology has shown great application potential in many fields. In the field of intelligent equipment detection and maintenance, the application of digital twin technology is still in its infancy. Therefore, there is an urgent need for an intelligent detection method that can monitor the operation status of equipment in real time and accurately predict faults.

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

[0005] The purpose of the present invention is to be able to monitor the operation status of equipment in real time, predict faults and perform precise maintenance.

[0006] The present invention provides a method for equipment status detection based on complex events and digital twins, including the steps of:

[0007] S11. After initializing the equipment status, collect real data; the data items of the real data include: machine tool operation parameters, spindle speed, feed rate, machine tool spindle temperature, and machine tool spindle vibration amplitude;

[0008] S12. Construct a digital twin model according to the equipment;

[0009] S13. Preprocess the real data through a virtual-real interaction module and input the preprocessed real data into the digital twin model to achieve virtual-real synchronization;

[0010] S14. Construct a database including an equipment operation and maintenance index system based on the simulation data generated by the digital twin model and the preprocessed real data;

[0011] S15. Construct a rule base according to the data in the database and the construction rules of the equipment operation and maintenance index system; the rule base is used to determine the current operating state of the equipment; the rule base includes: simple events, event association rules, and complex event flows.

[0012] Preferably, in the embodiment of the present invention, it further includes: generating a maintenance instruction according to the complex event flow and performing real-time regulation on the equipment.

[0013] Preferably, in the embodiment of the present invention, it further includes:

[0014] Visually display the digital twin model, the current equipment state, the parameter settings of the equipment, and the maintenance plan for the abnormal equipment state.

[0015] Preferably, in the embodiment of the present invention, it further includes:

[0016] Real-time send and receive the real data through the virtual-real interaction module; temporarily store the simulation data and the real data.

[0017] Preferably, in the embodiment of the present invention, constructing the rule base includes:

[0018] Define simple events, where the simple events include point events and continuous events;

[0019] Establish event association rules;

[0020] Establish a complex event processing flow according to the simple events and the event association rules.

[0021] Preferably, in the embodiment of the present invention, defining the simple events includes the formula:

[0022] E = (i, name, O, data, C, T)

[0023] In the formula, E is a simple event; i is a different event identifier; name is the event name; O is the specific object where the event occurs; data is the data parameter where the event occurs and is sourced from the database; C is the set of conditions for the event to occur; T is the time when the event occurs, which can be a time point, corresponding to a point event, or a time period, corresponding to a continuous event.

[0024] Preferably, in the embodiment of the present invention, establishing the event association rules includes:

[0025] Collect domain knowledge and data;

[0026] Determine the type and structure of the association rules;

[0027] Design an extraction algorithm for the association rules;

[0028] Manually verify and optimize the association rules.

[0029] On the other hand of the present invention, there is also provided a device for detecting the state of equipment based on complex events and digital twins, including:

[0030] A real data acquisition unit for acquiring real data after initializing the equipment state; the data items of the real data include: machine tool operation parameters, spindle speed, feed rate, machine tool spindle temperature, and machine tool spindle vibration amplitude;

[0031] A digital twin model construction unit for constructing a digital twin model according to the equipment;

[0032] A virtual-real synchronization unit for preprocessing the real data through a virtual-real interaction module and inputting the preprocessed real data into the digital twin model to achieve virtual-real synchronization;

[0033] A database construction unit for constructing a database including an equipment operation and maintenance index system according to the simulation data generated by the digital twin model and the preprocessed real data;

[0034] A rule base construction unit for constructing a rule base according to the data in the database and the equipment operation and maintenance index system; the rule base is used to determine the current operating state of the equipment; the rule base includes: simple events, event association rules, and complex event streams.

[0035] On the other hand of the embodiments of the present invention, there is also provided a device for detecting the state of equipment based on complex events and digital twins; the device for detecting the state of equipment based on complex events and digital twins includes a computer program stored on a medium, the computer program includes program instructions, and when the program instructions are executed by a computer, the computer is made to execute the methods described in the above aspects and achieve the same technical effects.

[0036] On the other hand of the embodiments of the present invention, there is also provided a storage medium, on which a computer program is stored, and when the computer program is executed by a processor, each step of the method for detecting the state of equipment based on complex events and digital twins described in any one of the above is implemented.

[0037] Compared with the prior art, the present invention has the following beneficial effects:

[0038] In the present invention, multi-dimensional simulation data is generated in the digital twin model; a database including an equipment operation and maintenance index system is constructed according to the simulation data and the real data; a rule base is constructed according to the data in the database and the equipment operation and maintenance index system; the current operating state of the equipment is determined through the rule base; real-time monitoring, fault prediction, and precise maintenance of the equipment operating state are achieved through the rule base.

[0039] Furthermore, the present invention analyzes the operation data of the equipment in real time through the complex event processing flow of the rule library, discovers potential faults in advance, and provides a scientific basis for predictive maintenance.

[0040] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention and be able to implement it according to the content of the specification, and at the same time to make the above and other purposes, technical features and advantages of the present invention more understandable, one or more preferred embodiments are listed below and described in detail with reference to the accompanying drawings as follows. Brief Description of the Drawings

[0041] In order to more clearly illustrate the technical solution of the present invention, the drawings required for the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0042] Figure 1 is the step diagram of the equipment status detection method based on complex events and digital twins described in the present invention;

[0043] Figure 2 is the schematic diagram of module connection in the equipment status detection method based on complex events and digital twins described in the present invention;

[0044] Figure 3 is the flow chart of the virtual-real interaction module described in the present invention:

[0045] Figure 4 is the equipment status detection flow chart described in the present invention;

[0046] Figure 5 is the complex event processing flow chart described in the present invention;

[0047] Figure 6 is the structural schematic diagram of the equipment status detection device based on complex events and digital twins described in the present invention;

[0048] Figure 7 is the structural schematic diagram of the equipment status detection device based on complex events and digital twins described in the present invention. Detailed Embodiments

[0049] The following combines the accompanying drawings to describe the detailed embodiments of the present invention in detail, but it should be understood that the protection scope of the present invention is not limited by the detailed embodiments.

[0050] Unless otherwise clearly stated, the term "comprising" throughout the specification and claims

[0051] Or its variations such as "comprising" or "including" etc. shall be understood to include the stated elements or components, without excluding other elements or other components.

[0052] In this text, terms such as "first", "second", etc. are used to distinguish two different elements or parts, rather than to limit a specific position or relative relationship. In other words, in some embodiments, terms such as "first", "second", etc. can also be interchanged with each other.

[0053] Embodiment 1

[0054] In order to perform real-time monitoring, fault prediction and precise maintenance on the operating state of equipment, such as Figure 1 and Figure 2 shown, in an embodiment of the present invention, a method for detecting the state of equipment based on complex events and digital twins is provided, including the steps:

[0055] S11. After initializing the equipment state, collect real data; the data items of the real data include: machine tool operating parameters, spindle speed, feed rate, machine tool spindle temperature, and machine tool spindle vibration amplitude;

[0056] The inventive concept of the present invention includes: Most current intelligent detection technologies can only provide data in a single dimension, making it difficult to comprehensively reflect the operating state of equipment. At the same time, these technologies often lack real-time performance and predictability, and cannot detect potential faults in advance, resulting in high maintenance costs and low efficiency. On the one hand, complex event processing technology is a technology that can process and analyze a large amount of real-time data, identify and respond to complex event patterns in the data stream; on the other hand, digital twin technology, as an emerging digital means, has shown great application potential in multiple fields; in the intelligent detection and maintenance of equipment, complex event processing technology can monitor the operating state of equipment in real time, identify and analyze potential fault patterns, and provide strong support for predictive maintenance. Therefore, the inventor combines digital twin technology with complex event processing technology to achieve real-time monitoring and precise prediction of the operating state of equipment.

[0057] In an embodiment of the present invention, sensors are deployed on key components of the equipment, such as: vibration sensors, temperature sensors, and current sensors on the spindle to collect corresponding real-time data; in specific application scenarios, the corresponding functions can be implemented through a data acquisition module.

[0058] S12. Construct a digital twin model according to the equipment;

[0059] In the implementation of the present invention, field mapping is carried out on physical equipment, a 3D model is established using software, and a twin is developed based on the twin modeling software. The twin has a mechanism model of the physical equipment. The mechanism model can perform parameter estimation according to the operating state of the equipment, calculate multi-scale unmeasurable data, so as to perform virtual operation and generate simulation data when the physical equipment is not running. To ensure the authenticity of the digital twin model, the digital twin model has high geometric accuracy and assembly position relationship accuracy, so as to accurately restore the actual motion state of the equipment.

[0060] S13. Preprocess the real data through the virtual-real interaction module, and input the preprocessed real data into the digital twin model to achieve virtual-real synchronization.

[0061] In the embodiment of the present invention, the real data collected in step S11 is input into the virtual-real interaction module. After the virtual-real interaction module preprocesses the real data, it is input into the digital twin model, so that virtual-real synchronization can be maintained. The process of the virtual-real interaction module is as Figure 3 shown.

[0062] Furthermore, in the embodiment of the present invention, the virtual-real interaction module sends and receives real data in real time, and temporarily stores the simulation data and real data.

[0063] The virtual-real interaction module can also write the simulation data generated by the digital twin model into the database.

[0064] In a specific application scenario, the virtual-real interaction module is respectively connected to the data acquisition module and the digital twin model to establish a connection between the physical entity and the virtual model. The virtual-real interaction module is designed as five sub-modules:

[0065] (1) The module for interacting with the control system of the physical equipment and the deployed sensors: The main task is to interact with the physical equipment. The C# program needs to connect to the physical equipment to realize the sending and receiving of data. Appropriate interfaces and protocols are designed for this module to ensure the accuracy and real-time of the data. The program can obtain information such as the operating state and parameter settings of the equipment, providing data support for subsequent virtual-real interaction.

[0066] (2) The module for establishing communication with the twin software: The C# program needs to establish a stable communication connection with the twin software to realize real-time data transmission and synchronization. The module needs to design a set of communication mechanisms to ensure that the program can send control instructions to the twin software and receive data from the twin software. By handling abnormal situations in the communication process, the integrity and reliability of the data are guaranteed. Through the communication with the twin software, the program can transmit the data of the physical equipment into the virtual world, realizing data sharing and interaction between the virtual and the real.

[0067] (3) Module for establishing communication with physical equipment: The C# program also needs to establish a direct communication connection with the physical equipment itself. This usually involves communicating with the controller to obtain real-time data of the equipment through specific interfaces and protocols. This module needs to handle tasks such as parsing communication protocols, encoding and decoding data, so that the program can accurately obtain the operating status, fault information, etc. of the equipment. Monitor the operation of the equipment in real time.

[0068] (4) Module for processing data transmitted from the control system and sensors: A large amount of data will be generated during the operation of electromechanical equipment, such as position information, speed information, temperature information, etc. The data needs to be effectively processed and analyzed to provide valuable information for subsequent interactions. The C# program needs to design a data processing module responsible for receiving data from physical equipment and performing necessary preprocessing, filtering, and conversion. The working process of the data processing module can transform the original data into information that is instructive for decision-making.

[0069] (5) Module for temporary data storage: The program needs to temporarily store a lot of data, including real-time data obtained, data exchanged with the twin software, and intermediate results generated within the program. To facilitate subsequent data processing and analysis, the program needs to design a temporary data storage module. Select a suitable storage strategy, and a reasonable data access interface needs to be designed to ensure that other modules can easily obtain and store data. The working process of the temporary data storage module can effectively manage and utilize data resources.

[0070] S14. Construct a database including an equipment operation and maintenance index system based on the simulation data generated according to the digital twin model and the preprocessed real data;

[0071] In the embodiment of the present invention, an equipment operation and maintenance index system is generated by analyzing the requirements in aspects such as operation and maintenance analysis, real-time data monitoring and analysis, accurate identification and recording, and equipment operation and maintenance scheduling and guidance. Then, the operation and maintenance data required for detecting the equipment status is extracted; the key data during the equipment operation process is deployed, simulation data is generated through the digital twin model, and a database is established according to the equipment operation and maintenance index system. In practical applications, the influxDB time-series database can be used to store data and store historical data.

[0072] S15. Construct a rule library according to the data in the database and the construction rules of the equipment operation and maintenance index system; the rule library is used to determine the current operating status of the equipment; the rule library includes: simple events, event association rules, and complex event streams.

[0073] In the embodiment of the present invention, constructing the rule library includes:

[0074] Define simple events, and simple events include point events and continuous events;

[0075] Establish event association rules;

[0076] Establish a complex event processing flow based on simple events and event association rules.

[0077] In the embodiments of the present invention, point events change continuously over time, and continuous events maintain the corresponding events unchanged for a period of time; simple events are events with simple semantics, which can enable maintenance personnel to quickly understand the current device state.

[0078] Define simple events, including the formula:

[0079] E = (i, name, O, data, C, T)

[0080] In the formula, E is a simple event; i is a different event identifier; name is the event name; O is the specific object where the event occurs; data is the data parameter where the event occurs and is sourced from the database; C is the set of conditions for the event to occur; T is the time when the event occurs, which can be a time point corresponding to a point event or a time period corresponding to a continuous event.

[0081] Event association rules are used to record the relationships between events and also store the rules for some events to be triggered by one or more conditions.

[0082] The establishment of event association relationship rules is a complex but crucial process, including the following steps:

[0083] S151. Collect domain knowledge and data

[0084] It is necessary to collect domain knowledge and data related to equipment maintenance. This includes the structure of the equipment, working principle, common faults and their causes, historical maintenance records, etc. At the same time, it is also necessary to collect event data generated during the operation of the equipment, such as sensor readings, alarm information, etc. These data will serve as the basis for establishing the rule library.

[0085] S152. Determine the type and structure of association rules

[0086] After collecting sufficient data and knowledge, it is necessary to determine the type and structure of the association rules. Association rules can be defined based on the time, type, attributes, etc. of events. For example, association rules based on a time window can be defined to detect combinations of events occurring within a specific time period; or association rules based on event types can be defined to detect the association relationships between different types of events.

[0087] S153. Design a rule extraction algorithm

[0088] To automatically extract association rules from data, appropriate rule extraction algorithms need to be designed. These algorithms can be implemented based on technologies such as data mining and machine learning. Association rule mining algorithms (such as Apriori, FP-Growth, etc.) can be used to discover the association relationships between events; or clustering algorithms can be used to identify groups of events with similar characteristics.

[0089] S154, Manual Verification and Optimization

[0090] The automatically extracted association rules may need to be manually verified and optimized. This is because the algorithms may not be able to fully capture the nuances in domain knowledge and business logic. Therefore, domain experts or technicians need to be invited to review and adjust the extracted rules to ensure their accuracy and practicality.

[0091] S155, Establishing a Rule Base and Continuously Updating

[0092] The verified and optimized association rules will be added to the rule base. The rule base should have a good organizational structure and query interface for easy subsequent use and maintenance. At the same time, as the equipment maintenance work progresses and new knowledge emerges continuously, the rule base needs to be continuously updated and improved. This can be achieved by regularly reviewing existing rules, adding new rules, and optimizing existing rules, etc.

[0093] S156, Implementation and Monitoring

[0094] Finally, the established rule base of event association relationships needs to be applied to the actual equipment maintenance work. During the implementation process, the performance and effects of the rule base need to be closely monitored, and adjustments and optimizations should be made according to the actual situation. At the same time, an effective monitoring mechanism also needs to be established to track the usage of the rule base and the detection effects of equipment failures.

[0095] Complex Event Processing (CEP), such as Figure 5 the complex event processing flow shown, matches and combines the extracted events by invoking predefined rules, logical conditions, or patterns in the event association relationship rule base to detect and identify complex events; this stage involves combining simple events into more complex events and determining the association relationships between events, helping users quickly understand the background, reasons, and impacts of events occurring and taking corresponding response measures in a timely manner.

[0096] In specific application scenarios, the corresponding functions can be implemented through the complex event processing module; the complex event processing module extracts key indicators for detailed analysis, determines the operating status of the current device through preset event definition rules, and if the analysis results show that the preset thresholds or conditions are met, the corresponding event response mechanism will be automatically triggered. At the same time, the complex event processing module is connected to the database, and the database provides the data required for status detection.

[0097] Furthermore, in the embodiments of the present invention, maintenance instructions are generated according to complex event streams to perform real-time regulation on the equipment, specifically as Figure 4 shown in the equipment status detection process. The maintenance instructions are accurately transmitted to the control system of the equipment to achieve real-time regulation; the control system will evaluate whether the current data sampling has reached the preset termination condition. If the termination condition has been reached, the entire monitoring process will safely terminate, and the detailed equipment status and maintenance plan will be displayed on the upper-layer application module; otherwise, if the termination condition is not reached, the control system will start a new cycle of data sampling, analysis, triggering, and response again. If the analysis result shows that the preset conditions are not met, the event triggering and response links will be directly skipped, and the system will directly enter the judgment stage of sampling end to evaluate whether to continue monitoring or take other measures.

[0098] In order to provide users with an intuitive monitoring experience, in the embodiments of the present invention, the digital twin model, the current equipment status, the setting of various equipment parameters, and the maintenance plan for equipment status anomalies are visually displayed; the digital twin model uses three-dimensional simulation to accurately reproduce the mechanical movement of the physical equipment, making it visually presented in the information world; in specific applications, the function of visual display can be realized through the upper-layer application module.

[0099] In summary, in the embodiments of the present invention, multidimensional simulation data is generated in the digital twin model; a database including an equipment operation and maintenance index system is constructed according to the simulation data and real data; a rule library is constructed according to the data in the database and the equipment operation and maintenance index system; the operating status of the current equipment is determined through the rule library; and real-time monitoring, fault prediction, and precise maintenance of the equipment operating status are realized through the rule library.

[0100] Furthermore, the present invention analyzes the operation data of the equipment in real time through the complex event processing flow of the rule library, discovers potential faults in advance, and provides a scientific basis for predictive maintenance.

[0101] Embodiment 2

[0102] Corresponding to the method embodiment, on the other hand, in the embodiments of the present invention, an equipment status detection device based on complex events and digital twins is also provided. Figure 6 shows a schematic structural diagram of the equipment status detection device based on complex events and digital twins provided by the embodiments of the present invention. The equipment status detection device based on complex events and digital twins is Figure 1 the device corresponding to the equipment status detection method based on complex events and digital twins described in the corresponding embodiment, that is, it is implemented in the form of a virtual device. Figure 1In the corresponding embodiment, for the equipment status detection method based on complex events and digital twins, each virtual module constituting the equipment status detection device based on complex events and digital twins can be executed by an electronic device, such as a network device, a terminal device, or a server. Specifically, the equipment status detection device based on complex events and digital twins in the embodiments of the present invention includes:

[0103] A real data acquisition unit 01, configured to acquire real data after initializing the equipment status; the data items of the real data include: machine tool operation parameters, spindle speed, feed rate, machine tool spindle temperature, and machine tool spindle vibration amplitude;

[0104] In the embodiments of the present invention, the real data acquisition unit 01 includes a control system unit and a sensor acquisition unit of the device; the control system unit can read the device operation parameters; the sensor unit, specifically, such as a temperature acquisition unit is deployed on the spindle to detect the temperature change during processing, a humidity acquisition unit is deployed on the inner wall of the machine tool to detect the processing environment humidity, and both the vibration acquisition unit and the current acquisition unit detect the vibration amplitude and current during spindle processing.

[0105] A digital twin model construction unit 02, configured to construct a digital twin model according to the equipment;

[0106] In the embodiments of the present invention, a twin is established on the twin software through the physical equipment, which has high geometric accuracy and assembly position relationship accuracy and can accurately restore the actual motion state of the equipment; the twin has a mechanism model of the physical device, which can improve the accuracy of the digital twin model and enhance the prediction ability; the mechanism model can perform parameter estimation according to the operating state of the engine, calculate multi-scale unmeasurable data, so as to generate virtual operation and simulation data when the physical entity is not running.

[0107] A virtual-real synchronization unit 03, configured to preprocess the real data through a virtual-real interaction module and input the preprocessed real data into the digital twin model to achieve virtual-real synchronization;

[0108] In the embodiments of the present invention, the real data acquired by the real data acquisition unit 01 is input into the virtual-real interaction module, and the virtual-real interaction module preprocesses the real data and then inputs it into the digital twin model, so as to maintain virtual-real synchronization.

[0109] The virtual-real interaction module is a C# program on the PC side, specifically including five modules:

[0110] 1. A module for interacting with the control system of the physical equipment and the deployed sensors.

[0111] 2. A module for establishing communication with the twin software.

[0112] 3. A module for establishing communication with physical equipment.

[0113] 4. A module for processing data transmitted by the control system and sensors.

[0114] 5. A module for temporarily storing data.

[0115] The database construction unit 04 is used to construct a database including an equipment operation and maintenance index system according to the simulation data generated by the digital twin model and the real data after preprocessing.

[0116] In the embodiment of the present invention, an equipment operation and maintenance index system is generated by analyzing the requirements in aspects such as operation and maintenance, real-time data monitoring and analysis, accurate identification and recording, and equipment operation and maintenance scheduling and guidance. Then, the operation and maintenance data required to detect the equipment status is extracted; the key data during the equipment operation process is deployed, the simulation data is generated through the digital twin model, and the database is established according to the equipment operation and maintenance index system.

[0117] In a specific application scenario, a time-series database can be used, which is connected to the virtual-real interaction module; the simulation data generated during the operation of the storage device is stored.

[0118] The rule base construction unit 05 is used to construct a rule base according to the data in the database and the equipment operation and maintenance index system; the rule base is used to determine the current operation state of the equipment; the rule base includes: simple events, event association rules, and complex event flows.

[0119] In the embodiment of the present invention, constructing a rule base includes:

[0120] Defining simple events, where simple events include point events and continuous events;

[0121] Establishing event association rules;

[0122] Establishing a complex event processing flow according to simple events and event association rules.

[0123] Furthermore, in the implementation of the present invention, there is also a visualization unit, which visually displays the digital twin model, the current equipment state, the setting of various equipment parameters, and the maintenance plan for equipment state anomalies; the digital twin model uses a three-dimensional simulation method to accurately reproduce the mechanical movement of the physical equipment, making it visually presented in the information world.

[0124] In a specific application scenario, the user can view the database data through the upper-layer application module, view the equipment operation data during the operation in real time, and can change the equipment maintenance plan through historical data. The whole process reflects a high degree of automation and intelligence, ensuring the accuracy and efficiency of equipment detection.

[0125] It should be noted that the specific implementation manner and technical effects of the equipment status detection device based on complex events and digital twins in the embodiments of the present invention can be referred to Figure 1 the corresponding equipment status detection method based on complex events and digital twins, which will not be elaborated here.

[0126] Embodiment III

[0127] Corresponding to the method embodiment, in the embodiment of the present invention, an equipment status detection device based on complex events and digital twins is further provided, such as a terminal, a server, etc. Among them, the server can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms. The terminal can be a smart phone, a tablet computer, a notebook computer, a desktop computer, etc., but is not limited thereto.

[0128] An example diagram of the hardware structure block diagram of the equipment status detection device based on complex events and digital twins provided in the embodiment of the present invention is as Figure 7 shown, and may include:

[0129] Processor 1, communication interface 2, memory 3, and communication bus 4;

[0130] Among them, the processor 1, the communication interface 2, and the memory 3 complete mutual communication through the communication bus 4;

[0131] Optionally, the communication interface 2 can be an interface of a communication module, such as an interface of a GSM module;

[0132] The processor 1 may be a central processing unit CPU, or a specific integrated circuit ASIC (Application Specific Integrated Circuit), or one or more integrated circuits configured to implement the embodiments of the present application.

[0133] The memory 3 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk memory.

[0134] Among them, the processor 1 is specifically configured to execute the computer program stored in the memory 3 to perform the following steps:

[0135] S11. After initializing the equipment status, collect real data; the data items of the real data include: machine tool operation parameters, spindle speed, feed rate, machine tool spindle temperature, and machine tool spindle vibration amplitude;

[0136] S12. Construct a digital twin model based on the equipment;

[0137] S13. Preprocess the real data through the virtual-real interaction module, and input the preprocessed real data into the digital twin model to achieve virtual-real synchronization;

[0138] S14. Construct a database including an equipment operation and maintenance index system based on the simulation data generated by the digital twin model and the preprocessed real data;

[0139] S15. Construct a rule base based on the data in the database and the equipment operation and maintenance index system; the rule base is used to determine the current operating state of the equipment; the rule base includes: simple events, event association rules, and complex event flows.

[0140] The above product can execute the method provided by the embodiment of the present invention, and has the corresponding function modules and beneficial effects for executing the method. For technical details not described in detail in this embodiment, reference can be made to the equipment status detection method based on complex events and digital twins provided by the embodiment of the present invention.

[0141] Embodiment 4

[0142] In the embodiment of the present invention, a storage medium is further provided. The storage medium can store a program suitable for execution by a processor, and the program is used for:

[0143] S11. Collect real data after initializing the equipment status; the data items of the real data include: machine tool operation parameters, spindle speed, feed rate, machine tool spindle temperature, and machine tool spindle vibration amplitude;

[0144] S12. Construct a digital twin model based on the equipment;

[0145] S13. Preprocess the real data through the virtual-real interaction module, and input the preprocessed real data into the digital twin model to achieve virtual-real synchronization;

[0146] S14. Construct a database including an equipment operation and maintenance index system based on the simulation data generated by the digital twin model and the preprocessed real data;

[0147] S15. Construct a rule base based on the data in the database and the equipment operation and maintenance index system; the rule base is used to determine the current operating state of the equipment; the rule base includes: simple events, event association rules, and complex event flows.

[0148] Optionally, the refined functions and extended functions of the program can be referred to the above description.

[0149] The above products can execute the method provided by the embodiments of the present invention, and have the corresponding functional modules and beneficial effects for executing the method. For technical details not described in detail in this embodiment, reference may be made to the methods provided in other embodiments of the present invention.

[0150] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of this application.

[0151] In several embodiments provided in this application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. Additionally, the couplings or direct couplings or communication connections shown or discussed among each other can be through some interfaces, and the indirect couplings or communication connections of devices or units can be in electrical, mechanical, or other forms.

[0152] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they can be located in one place, or can be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0153] In addition, in each embodiment of this application, the functional units can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit.

[0154] It should be understood that in the embodiments of this application, the dependent claims, each embodiment, and features can be combined with each other to achieve the solution of the foregoing technical problems.

[0155] When the above-mentioned functions are implemented in the form of software function units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of this application. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs that can store program codes.

[0156] The foregoing description of the disclosed embodiments enables those skilled in the art to implement or use this application. Various modifications to these embodiments will be obvious to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application will not be limited to the embodiments shown herein, but rather will be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. An equipment status detection method based on complex events and digital twins, characterized in that, Including the steps: S11. After initializing the equipment status, collect real data; The data items of the real data include: machine tool operation parameters, spindle speed, feed rate, machine tool spindle temperature, and machine tool spindle vibration amplitude; S12. Build a digital twin model according to the equipment; S13. Preprocess the real data through the virtual-real interaction module, and input the preprocessed real data into the digital twin model to achieve virtual-real synchronization; S14. Build a database including an equipment operation and maintenance index system based on the simulation data generated by the digital twin model and the preprocessed real data; S15. Build a rule base according to the data in the database and the equipment operation and maintenance index system; the rule base is used to determine the current operation status of the equipment; the rule base includes: simple events, event association rules, and complex event streams.

2. The method for detecting the equipment state based on complex events and digital twins according to claim 1, wherein It also includes: Generate maintenance instructions according to the complex event stream and perform real-time regulation on the equipment.

3. The equipment status detection method based on complex events and digital twins according to claim 1, wherein It also includes: Visually display the digital twin model, the current equipment status, the settings of each parameter of the equipment, and the maintenance plan for equipment status anomalies.

4. The method for detecting the equipment state based on complex events and digital twins according to claim 1, wherein It also includes: Send and receive the real data in real time through the virtual-real interaction module; Temporarily store the simulation data and the real data.

5. The method for detecting the equipment status based on complex events and digital twins according to claim 1, wherein Building the rule base includes: Define simple events, and the simple events include point events and continuous events; Establish event association rules; Establish a complex event processing flow according to the simple events and the event association rules.

6. The method for detecting equipment status based on complex events and digital twin according to claim 5, characterized in that Defining the simple event includes the formula: E = (i, name, O, data, C, T) In the formula, E is a simple event; i is different event identifiers; name is the event name; O is the specific object where the event occurs; data is the data parameter where the event occurs and comes from the database; C is the set of conditions for the event to occur; T is the time when the event occurs, which is a time point or time period, corresponding to point events and continuous events.

7. The method for detecting the equipment status based on complex events and digital twins according to claim 5, wherein Establishing the event association rules includes: Collect domain knowledge and data; Determine the type and structure of the association rules; Design an extraction algorithm for the association rules; Manually verify and optimize the association rules.

8. An equipment status detection device based on complex events and digital twins, characterized in that, It includes: A real data acquisition unit for collecting real data after initializing the equipment status; The data items of the real data include: machine tool operation parameters, spindle speed, feed rate, machine tool spindle temperature, and machine tool spindle vibration amplitude; A digital twin model construction unit for constructing a digital twin model according to the equipment; A virtual-real synchronization unit for preprocessing the real data through the virtual-real interaction module and inputting the preprocessed real data into the digital twin model to achieve virtual-real synchronization; A database construction unit for constructing a database including an equipment operation and maintenance index system based on the simulation data generated by the digital twin model and the preprocessed real data; A rule base construction unit for constructing a rule base according to the data in the database and the equipment operation and maintenance index system; the rule base is used to determine the current operation state of the equipment; the rule base includes: simple events, event association rules, and complex event streams.

9. An equipment status detection device based on complex events and digital twins, characterized in that, Comprising: A memory for storing computer programs; A processor for calling and executing the computer program to implement the steps of the equipment state detection method based on complex events and digital twins according to any one of claims 1-7.

10. A storage medium, characterized in that, Including a software program, the software program being adapted to be executed by a processor to implement the steps of the equipment state detection method based on complex events and digital twins according to any one of claims 1-7.

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