Method and device for monitoring intelligent cabin production line based on virtual sensor

Abstract

The invention provides an intelligent cabin production line monitoring method and device based on a virtual sensor, and the method comprises the steps: obtaining the initial production data, collected by an entity sensor, of each to-be-monitored device in an intelligent cabin production line, and transmitting the initial production data to the virtual sensor; the virtual sensor comprehensively processes the initial production data and virtual production data generated when the virtual sensor simulates each device to be monitored in the intelligent cabin production line to generate target production data, and sends the target production data to a monitoring system; and the monitoring system analyzes the target production data and determines a monitoring report of the intelligent cabin production line. According to the invention, a data association and synchronization method based on the virtual sensor is introduced, the monitoring cost can be reduced, and accurate synchronization of multi-source data is realized on the basis of meeting the requirements of high precision and high real-time performance, so that the accuracy of a monitoring result is ensured.

Description

Technical Field

[0001] The present application relates to the technical field of intelligent cockpit production lines, and in particular to a monitoring method and device for an intelligent cockpit production line based on virtual sensors. Background Art

[0002] In existing smart cockpit production lines, data acquisition and synchronization technologies mainly rely on traditional physical sensors and monitoring systems. These systems usually connect various sensors through wired or wireless means to collect real-time information such as equipment status and production parameters on the production line, and transmit the data to the central control system for processing and analysis. However, this approach has some limitations. First, the installation and maintenance costs of physical sensors are high, especially in complex production line environments. The wiring and debugging processes of sensors are cumbersome and time-consuming. Secondly, the data acquisition range and accuracy of physical sensors are limited by hardware conditions, making it difficult to meet the requirements of high precision and high real-time performance. In addition, traditional data synchronization methods usually rely on fixed time intervals or event triggering mechanisms, which makes it difficult to achieve accurate synchronization of multi-source data, resulting in insufficient data correlation and affecting the monitoring and optimization of the production process. Summary of the Invention

[0003] In view of this, the purpose of this application is to provide a monitoring method and device for an intelligent cockpit production line based on virtual sensors. This application introduces a data association and synchronization method based on virtual sensors, which can reduce monitoring costs and achieve accurate synchronization of multi-source data on the basis of meeting high-precision and high-real-time requirements, thereby ensuring the accuracy of the monitoring results.

[0004] An embodiment of the present application provides a monitoring method for an intelligent cockpit production line based on a virtual sensor, the monitoring method comprising:

[0005] Obtain the initial production data of each device to be monitored in the smart cockpit production line collected by the physical sensor and send it to the virtual sensor;

[0006] The virtual sensor comprehensively processes the initial production data and virtual production data generated by simulating each device to be monitored in the smart cockpit production line to generate target production data, and sends the target production data to the monitoring system;

[0007] The monitoring system analyzes the target production data to determine a monitoring report for the smart cockpit production line.

[0008] Optionally, obtaining the initial production data of each device to be monitored in the smart cockpit production line collected by the physical sensor and sending the data to the virtual sensor includes:

[0009] The initial production data of each device to be monitored in the smart cockpit production line collected by the physical sensor is obtained, and the initial production data is sent to the virtual sensor through the pre-established OPC data interface.

[0010] Optionally, the virtual sensor performs comprehensive processing on the initial production data and virtual production data generated by simulating each device to be monitored in the smart cockpit production line to generate target production data, including:

[0011] Performing time synchronization processing on the virtual production data according to the time information of the initial production data to obtain first production data; wherein the first production data is time synchronized with the initial production data;

[0012] Performing format unification processing on the initial production data and the first production data according to preset format requirements to obtain second production data and third production data;

[0013] The second production data and the third production data are fused to generate target production data.

[0014] Optionally, before fusing the second production data and the third production data, the monitoring method further includes:

[0015] The second production data and the third production data are preprocessed respectively; wherein the preprocessing includes at least one of the following: denoising processing, filtering processing, smoothing processing, normalization processing, and standardization processing.

[0016] Optionally, when the monitoring system analyzes the target production data, the monitoring method further includes:

[0017] Identifying whether the target production data includes abnormal data;

[0018] If included, an alarm will be issued.

[0019] Optionally, when the monitoring system analyzes the target production data, the monitoring method further includes:

[0020] Processing the target production data according to a preset hierarchical logic to obtain at least one hierarchical production data;

[0021] For each layer of production data, the monitoring result of the monitoring layer corresponding to the layer of production data is determined.

[0022] The embodiment of the present application further provides a monitoring device for an intelligent cockpit production line based on a virtual sensor, the monitoring device comprising:

[0023] The acquisition module is used to obtain the initial production data of each device to be monitored in the smart cockpit production line collected by the physical sensor and send it to the virtual sensor;

[0024] a processing module, configured to comprehensively process the initial production data and virtual production data generated by the virtual sensor through simulation of each device to be monitored in the intelligent cockpit production line, generate target production data, and send the target production data to the monitoring system;

[0025] The analysis module is used for the monitoring system to analyze the target production data and determine the monitoring report of the smart cockpit production line.

[0026] Optionally, when the acquisition module is used to acquire the initial production data of each device to be monitored in the smart cockpit production line collected by the physical sensor and send it to the virtual sensor, the acquisition module is used to:

[0027] The initial production data of each device to be monitored in the smart cockpit production line collected by the physical sensor is obtained, and the initial production data is sent to the virtual sensor through the pre-established OPC data interface.

[0028] Optionally, when the processing module is used to perform comprehensive processing on the initial production data and virtual production data generated by the virtual sensor through simulation of each device to be monitored in the smart cockpit production line to generate target production data, the processing module is used to:

[0029] Performing time synchronization processing on the virtual production data according to the time information of the initial production data to obtain first production data; wherein the first production data is time synchronized with the initial production data;

[0030] Performing format unification processing on the initial production data and the first production data according to preset format requirements to obtain second production data and third production data;

[0031] The second production data and the third production data are fused to generate target production data.

[0032] Optionally, the processing module is further configured to:

[0033] Before fusing the second production data and the third production data, the second production data and the third production data are preprocessed respectively; wherein the preprocessing includes at least one of the following: denoising, filtering, smoothing, normalization, and standardization.

[0034] Optionally, when the monitoring system is used to analyze the target production data, the analysis module is used to:

[0035] Identifying whether the target production data includes abnormal data;

[0036] If included, an alarm will be issued.

[0037] Optionally, when the monitoring system is used to analyze the target production data, the analysis module is further used to:

[0038] Processing the target production data according to a preset hierarchical logic to obtain at least one hierarchical production data;

[0039] For each layer of production data, the monitoring result of the monitoring layer corresponding to the layer of production data is determined.

[0040] An embodiment of the present application also provides an electronic device, comprising: a processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor. When the electronic device is running, the processor and the memory communicate through the bus, and when the machine-readable instructions are executed by the processor, the steps of the monitoring method described above are performed.

[0041] An embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the monitoring method described above are executed.

[0042] An embodiment of the present application provides a monitoring method for an intelligent cockpit production line based on a virtual sensor, the monitoring method comprising: obtaining initial production data of each device to be monitored in the intelligent cockpit production line collected by a physical sensor, and sending the data to the virtual sensor; the virtual sensor comprehensively processes the initial production data and the virtual production data generated by simulating each device to be monitored in the intelligent cockpit production line, generates target production data, and sends the target production data to a monitoring system; the monitoring system analyzes the target production data to determine a monitoring report for the intelligent cockpit production line.

[0043] In this way, the present application introduces a data association and synchronization method based on virtual sensors. Virtual sensors simulate the functions of physical sensors through software, utilize existing hardware devices and data sources, and generate the required monitoring data through algorithm models. This method not only reduces hardware costs, but also improves the flexibility and scalability of data acquisition. In terms of data association, virtual sensors interact with various devices and control systems on the production line through the OPC communication protocol to achieve unified collection and format conversion of multi-source data. In terms of data synchronization, a time synchronization mechanism is adopted to ensure that the data generated by the virtual sensor is consistent with the data of the physical sensor in time, thereby realizing real-time mapping and hierarchical monitoring of production data. This method not only improves the efficiency and accuracy of data acquisition, but also provides reliable data support for the intelligent management and optimization of production lines.

[0044] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without creative work.

[0046] Figure 1 A flowchart of a monitoring method for an intelligent cockpit production line based on virtual sensors provided in an embodiment of the present application;

[0047] Figure 2 A schematic diagram of a process for determining target production data provided in this application;

[0048] Figure 3 A schematic diagram of the structure of a monitoring device for an intelligent cockpit production line based on virtual sensors provided in an embodiment of the present application;

[0049] Figure 4 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0050] In order to make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. The components of the embodiments of the present application generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application for which protection is claimed, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, each other embodiment obtained by those skilled in the art without making creative work falls within the scope of protection of the present application.

[0051] In existing smart cockpit production lines, data acquisition and synchronization technologies mainly rely on traditional physical sensors and monitoring systems. These systems usually connect various sensors through wired or wireless means to collect real-time information such as equipment status and production parameters on the production line, and transmit the data to the central control system for processing and analysis. However, this approach has some limitations. First, the installation and maintenance costs of physical sensors are high, especially in complex production line environments. The wiring and debugging processes of sensors are cumbersome and time-consuming. Secondly, the data acquisition range and accuracy of physical sensors are limited by hardware conditions, making it difficult to meet the requirements of high precision and high real-time performance. In addition, traditional data synchronization methods usually rely on fixed time intervals or event triggering mechanisms, which makes it difficult to achieve accurate synchronization of multi-source data, resulting in insufficient data correlation and affecting the monitoring and optimization of the production process.

[0052] Based on this, an embodiment of the present application provides a monitoring method and device for an intelligent cockpit production line based on virtual sensors. The present application introduces a data association and synchronization method based on virtual sensors, which can reduce monitoring costs and achieve accurate synchronization of multi-source data on the basis of meeting high-precision and high-real-time requirements, thereby ensuring the accuracy of the monitoring results.

[0053] See also Figure 1 , Figure 1 This is a flow chart of a monitoring method for a smart cockpit production line based on virtual sensors provided in an embodiment of the present application. Figure 1 As shown in , the monitoring method provided in the embodiment of the present application includes:

[0054] S101. Obtain initial production data of each device to be monitored in the smart cockpit production line collected by the physical sensor and send it to the virtual sensor.

[0055] S102. The virtual sensor comprehensively processes the initial production data and the virtual production data generated by simulating each device to be monitored in the smart cockpit production line, generates target production data, and sends the target production data to the monitoring system.

[0056] S103: The monitoring system analyzes the target production data to determine a monitoring report for the smart cockpit production line.

[0057] In a virtual sensor-based monitoring method for an intelligent cockpit production line, provided herein, initial production data for each device to be monitored in the intelligent cockpit production line is first acquired by a physical sensor and sent to the virtual sensor. The virtual sensor then processes the received initial production data and virtual production data generated by simulating each device to be monitored in the intelligent cockpit production line to generate target production data, which is then sent to a monitoring system. Finally, the monitoring system analyzes the target production data and generates a monitoring report for the intelligent cockpit production line. This enables precise monitoring of the intelligent cockpit production line.

[0058] The following describes each step in this embodiment in detail;

[0059] S101. Obtain initial production data of each device to be monitored in the smart cockpit production line collected by the physical sensor and send it to the virtual sensor.

[0060] A virtual sensor is a digital tool that uses software algorithms and data processing techniques to indirectly acquire or infer physical quantities (such as temperature, pressure, and vibration). It is not a physical hardware sensor, but rather generates new monitoring signals through data fusion, inference, or prediction based on existing physical sensor data, mathematical models, machine learning algorithms, or physical laws.

[0061] It's important to note that in the design of a virtual sensor, the sensor's functional model must first be defined. This model determines how data from environmental variables is acquired and converted into sensor outputs. Virtual sensors typically rely on environmental modeling to generate input data. The sensor model is driven by collecting historical data or using existing physical datasets. Mathematical models are used to simulate physical phenomena to generate simulated data. Real-time external sensor data is acquired as input and combined with this data for processing and simulation. In the virtual sensor, environmental data is first converted into a form suitable for the sensor. The sensor response is calculated to produce the final simulation result. Virtual sensors also perform multi-sensor fusion, integrating multiple inputs to infer more accurate results. When simulating physical phenomena, the algorithm calculates the response based on physical equations.

[0062] In one embodiment provided in the present application, the initial production data of each device to be monitored in the smart cockpit production line collected by the physical sensor is obtained and sent to the virtual sensor, including: obtaining the initial production data of each device to be monitored in the smart cockpit production line collected by the physical sensor, and sending the initial production data to the virtual sensor through a pre-established OPC data interface.

[0063] Here, when the initial production data is sent to the virtual sensor through the OPC data interface, the OPC communication protocol is followed.

[0064] It should be noted that the OPC protocol is designed to enable intercommunication between different hardware devices and software systems through standardized interfaces, particularly in industrial automation and control systems. OPC DA (Data Access): Real-time data access, used to collect real-time data from devices or control systems. OPC HDA (Historical Data Access): Historical data access, providing access to historical data, commonly used for data storage and playback. OPC A&E (Alarms and Events): Used to collect alarm and event data from devices or systems. Virtual sensors communicate with the device's OPC server through an OPC client.

[0065] Devices provide data services through OPC servers, and virtual sensors obtain real-time or historical data from devices through OPC clients. Devices and sensors on a production line typically provide a series of data points through OPC servers. Virtual sensors need to correctly read this data based on the address, type, and format of the data points. Virtual sensors need to understand the type and location of each data source. This information is typically identified by the device's OPC tag, data point name, or address. Each device's data point may be presented in a different format (such as integer, floating-point number, string, etc.). Virtual sensors access each device's data point through OPC clients. OPC clients request real-time data from devices, and the devices return the data to the virtual sensors through the OPC server.

[0066] S102. The virtual sensor comprehensively processes the initial production data and the virtual production data generated by simulating each device to be monitored in the smart cockpit production line, generates target production data, and sends the target production data to the monitoring system.

[0067] See also Figure 2 , Figure 2 A flow chart of determining target production data provided in this application is as follows: Figure 2In one embodiment provided by the present application, the virtual sensor performs comprehensive processing on the initial production data and the virtual production data generated by simulating each device to be monitored in the smart cockpit production line to generate target production data, including:

[0068] S1021. Perform time synchronization processing on the virtual production data according to the time information of the initial production data to obtain first production data; wherein the first production data is time synchronized with the initial production data.

[0069] S1022. Perform format unification processing on the initial production data and the first production data according to preset format requirements to obtain second production data and third production data.

[0070] S1023: The second production data and the third production data are merged to generate target production data.

[0071] Regarding step S1021, it should be noted that the goal of adopting the time synchronization mechanism is to ensure that the data generated by the virtual sensor is consistent in time with the data of the physical sensor. The data generated by the virtual sensor also needs to be timestamped to ensure that it is time-aligned with the data of the physical sensor. The timestamp of the virtual sensor is usually provided by the system clock. When synchronizing between multiple devices or multiple sensors, a unified time base must be selected. All sensors and devices must calibrate their own clocks according to this base to ensure time consistency. The time synchronization protocol PTP (IEEE1588) can provide synchronization at the microsecond level.

[0072] Even if the clocks of physical and virtual sensors are synchronized, factors such as network latency and processing delays can cause time discrepancies. Therefore, upon receiving data, it must be time-corrected. The latency is estimated by calculating the difference between the sensor data's timestamp and the current system time. The data is then corrected based on the estimated time difference. Virtual sensor data is aligned with physical sensor data using interpolation to reduce time skew. In distributed systems, sensor clock synchronization requires dynamic adjustment. For example, when network latency changes or device clocks drift, the system needs to realign using a synchronization protocol.

[0073] To ensure the stability of time synchronization, the system is usually configured with multiple time synchronization sources. Use multiple NTP servers, or combine GPS, wireless network time synchronization, etc. to ensure the reliability of time synchronization.

[0074] Regarding step S1022, it should be noted that the data sent by the physical sensor to the virtual sensor may be in different formats, and the virtual sensor needs to perform format conversion in order to convert all data into a unified format and standard. Among them, the data of different devices may use different data types, such as integers, floating point numbers, Boolean values, strings, etc. The virtual sensor needs to convert all data into a unified data type (usually floating decimals or floating point numbers). Different devices may use different units. The output data points of the device are usually presented in different data structures (such as single values, arrays, enumeration types, etc.). The virtual sensor will convert this data into a unified structure, usually a standard data object, such as JSON, XML or a custom data structure. The different data tags provided by each device are uniformly mapped to corresponding standard tags to facilitate further processing and analysis of the data. Once the data is converted to a unified format, the virtual sensor can use different algorithms to further process the data.

[0075] Regarding step S1023, in this step, the virtual sensor may use a data fusion algorithm to fuse the second production data and the third production data. In multi-source data fusion, data from different types of sensors are combined into a comprehensive monitoring result.

[0076] Virtual sensors can also perform real-time calculations, such as calculating the average, maximum, minimum, and other statistical information of a process.

[0077] In another embodiment provided in the present application, before the second production data and the third production data are fused, the monitoring method further includes: preprocessing the second production data and the third production data respectively; wherein the preprocessing includes at least one of the following: denoising processing, filtering processing, smoothing processing, normalization processing and standardization processing.

[0078] Here, the Kalman filter technique can be used to smooth the data.

[0079] S103: The monitoring system analyzes the target production data to determine a monitoring report for the smart cockpit production line.

[0080] Here, the determined monitoring report can be displayed through the interactive interface.

[0081] In one embodiment provided in the present application, when the monitoring system analyzes the target production data, the monitoring method further includes: identifying whether the target production data includes abnormal data; and if so, issuing an alarm.

[0082] When an alarm is issued, the alarm reminder can be given by sound, light, etc. Other methods can also be used, which are not limited here.

[0083] In another embodiment provided in the present application, when the monitoring system analyzes the target production data, the monitoring method further includes: processing the target production data according to a preset layered logic to obtain at least one layered production data; and for each layered production data, determining the monitoring result of the monitoring layer corresponding to the layered production data.

[0084] Here, the monitoring layer may include the equipment layer, the production line layer, and the workshop layer. In this way, this solution can realize hierarchical monitoring, and the monitoring results can be visualized, thereby realizing multi-level visualization.

[0085] In this way, the present application introduces a data association and synchronization method based on virtual sensors. Virtual sensors simulate the functions of physical sensors through software, utilize existing hardware devices and data sources, and generate the required monitoring data through algorithm models. This method not only reduces hardware costs, but also improves the flexibility and scalability of data acquisition. In terms of data association, virtual sensors interact with various devices and control systems on the production line through the OPC communication protocol to achieve unified collection and format conversion of multi-source data. In terms of data synchronization, a time synchronization mechanism is adopted to ensure that the data generated by the virtual sensor is consistent with the data of the physical sensor in time, thereby realizing real-time mapping and hierarchical monitoring of production data. This method not only improves the efficiency and accuracy of data acquisition, but also provides reliable data support for the intelligent management and optimization of production lines.

[0086] Based on the same inventive concept, a monitoring device corresponding to the monitoring method is also provided in the embodiment of the present application. Since the principle of solving the problem by the device in the embodiment of the present application is similar to the above-mentioned monitoring method in the embodiment of the present application, the implementation of the device can refer to the implementation of the method, and the repeated parts will not be repeated.

[0087] See also Figure 3 , Figure 3 This is a schematic diagram of the structure of a monitoring device for an intelligent cockpit production line based on a virtual sensor provided in an embodiment of the present application. Figure 3 As shown in FIG, the monitoring device 300 includes:

[0088] An acquisition module 310 is configured to acquire initial production data of each device to be monitored in the smart cockpit production line collected by the physical sensor and send the data to the virtual sensor;

[0089] a processing module 320 configured to comprehensively process the initial production data and virtual production data generated by the virtual sensor through simulation of each device to be monitored in the intelligent cockpit production line, generate target production data, and send the target production data to the monitoring system;

[0090] The analysis module 330 is used for the monitoring system to analyze the target production data and determine a monitoring report for the smart cockpit production line.

[0091] Optionally, when the acquisition module 310 is used to acquire the initial production data of each device to be monitored in the smart cockpit production line collected by the physical sensor and send it to the virtual sensor, the acquisition module 310 is used to:

[0092] The initial production data of each device to be monitored in the smart cockpit production line collected by the physical sensor is obtained, and the initial production data is sent to the virtual sensor through the pre-established OPC data interface.

[0093] Optionally, when the processing module 320 is used to perform comprehensive processing on the initial production data and virtual production data generated by the virtual sensor through simulation of each device to be monitored in the smart cockpit production line to generate target production data, the processing module 320 is used to:

[0094] Performing time synchronization processing on the virtual production data according to the time information of the initial production data to obtain first production data; wherein the first production data is time synchronized with the initial production data;

[0095] Performing format unification processing on the initial production data and the first production data according to preset format requirements to obtain second production data and third production data;

[0096] The second production data and the third production data are fused to generate target production data.

[0097] Optionally, the processing module 320 is further configured to:

[0098] Before fusing the second production data and the third production data, the second production data and the third production data are preprocessed respectively; wherein the preprocessing includes at least one of the following: denoising, filtering, smoothing, normalization, and standardization.

[0099] Optionally, when the monitoring system is used to analyze the target production data, the analysis module 330 is used to:

[0100] Identifying whether the target production data includes abnormal data;

[0101] If included, an alarm will be issued.

[0102] Optionally, when the monitoring system is used to analyze the target production data, the analysis module 330 is used to:

[0103] Processing the target production data according to a preset hierarchical logic to obtain at least one hierarchical production data;

[0104] For each layer of production data, the monitoring result of the monitoring layer corresponding to the layer of production data is determined.

[0105] See also Figure 4 , Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Figure 4 As shown in FIG, the electronic device 400 includes a processor 410 , a memory 420 and a bus 430 .

[0106] The memory 420 stores machine-readable instructions executable by the processor 410. When the electronic device 400 is running, the processor 410 communicates with the memory 420 via the bus 430. When the machine-readable instructions are executed by the processor 410, the above-mentioned Figure 1 as well as Figure 2 The specific implementation of the steps in the method embodiment shown can be found in the method embodiment and will not be repeated here.

[0107] The embodiment of the present application also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the computer program can execute the above-mentioned Figure 1 as well as Figure 2 The specific implementation of the steps in the method embodiment shown can be found in the method embodiment and will not be repeated here.

[0108] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0109] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is merely a logical function division. There may be other division methods in actual implementation. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed may be through some communication interface, indirect coupling or communication connection of devices or units, which may be electrical, mechanical or other forms.

[0110] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0111] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0112] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a non-volatile computer-readable storage medium that is executable by a processor. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling 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 method described in each embodiment of the present application. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0113] Finally, it should be noted that the above-described embodiments are only specific implementation methods of the present application, which are used to illustrate the technical solutions of the present application, rather than to limit them. The scope of protection of the present application is not limited thereto. Although the present application has been described in detail with reference to the above-mentioned embodiments, those skilled in the art should understand that any person skilled in the art can modify or easily conceive of changes to the technical solutions described in the above-mentioned embodiments within the technical scope disclosed in the present application, or perform equivalent replacements for some of the technical features thereof. These modifications, changes, or replacements do not deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should be included in the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

Claims

1. A monitoring method for an intelligent cockpit production line based on virtual sensors, characterized in that: The monitoring method comprises: Obtain the initial production data of each device to be monitored in the smart cockpit production line collected by the physical sensor and send it to the virtual sensor; The virtual sensor comprehensively processes the initial production data and virtual production data generated by simulating each device to be monitored in the smart cockpit production line to generate target production data, and sends the target production data to the monitoring system; The monitoring system analyzes the target production data to determine a monitoring report for the smart cockpit production line.

2. The monitoring method according to claim 1, characterized in that: The obtaining of the initial production data of each device to be monitored in the smart cockpit production line collected by the physical sensor and sending the data to the virtual sensor includes: The initial production data of each device to be monitored in the smart cockpit production line collected by the physical sensor is obtained, and the initial production data is sent to the virtual sensor through the pre-established OPC data interface.

3. The monitoring method according to claim 1, characterized in that The virtual sensor performs comprehensive processing on the initial production data and the virtual production data generated by simulating each device to be monitored in the smart cockpit production line to generate target production data, including: Performing time synchronization processing on the virtual production data according to the time information of the initial production data to obtain first production data; wherein the first production data is time synchronized with the initial production data; Performing format unification processing on the initial production data and the first production data according to preset format requirements to obtain second production data and third production data; The second production data and the third production data are fused to generate target production data.

4. The monitoring method according to claim 3, characterized in that: Before fusing the second production data and the third production data, the monitoring method further includes: The second production data and the third production data are preprocessed respectively; wherein the preprocessing includes at least one of the following: denoising processing, filtering processing, smoothing processing, normalization processing, and standardization processing.

5. The monitoring method according to claim 1, characterized in that: When the monitoring system analyzes the target production data, the monitoring method further includes: Identifying whether the target production data includes abnormal data; If included, an alarm will be issued.

6. The monitoring method according to claim 1, characterized in that: When the monitoring system analyzes the target production data, the monitoring method further includes: Processing the target production data according to a preset hierarchical logic to obtain at least one hierarchical production data; For each layer of production data, the monitoring result of the monitoring layer corresponding to the layer of production data is determined.

7. A monitoring device for an intelligent cockpit production line based on a virtual sensor, characterized in that: The monitoring device comprises: The acquisition module is used to obtain the initial production data of each device to be monitored in the smart cockpit production line collected by the physical sensor and send it to the virtual sensor; a processing module, configured to comprehensively process the initial production data and virtual production data generated by the virtual sensor through simulation of each device to be monitored in the intelligent cockpit production line, generate target production data, and send the target production data to the monitoring system; The analysis module is used for the monitoring system to analyze the target production data and determine the monitoring report of the smart cockpit production line.

8. The monitoring device according to claim 7, characterized in that When the acquisition module is used to acquire the initial production data of each device to be monitored in the smart cockpit production line collected by the physical sensor and send it to the virtual sensor, the acquisition module is used to: The initial production data of each device to be monitored in the smart cockpit production line collected by the physical sensor is obtained, and the initial production data is sent to the virtual sensor through the pre-established OPC data interface.

9. An electronic device, characterized in that: include: A processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor. When the electronic device is running, the processor and the memory communicate through the bus, and the machine-readable instructions are executed by the processor to execute the steps of the monitoring method as described in any one of claims 1 to 6.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the monitoring method according to any one of claims 1 to 6 are executed.

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