Multi-source heterogeneous data fusion processing system for industry based on mobile communication

Abstract

The invention is applicable to the technical field of computers, and provides an industrial multi-source heterogeneous data fusion processing system based on mobile communication, comprising a multi-source signal acquisition module which sends each operation parameter to a data processing module through a 5G network; the visual detection module sends the appearance image data and the temperature data to the data processing module through a 5G network; the inspection robot runs along a set path based on a 5G positioning technology, and sends equipment data to the data processing module through 5G; the data processing module performs network slicing processing on 5G to obtain a plurality of target network slices, and sends the data through the plurality of target network slices; the data analysis module is used for generating a plurality of to-be-processed tasks based on the data; and performing parallel processing on the plurality of to-be-processed tasks to obtain a detection result of each target device. According to the system, data real-time acquisition and real-time processing are realized by using the 5G technology, and the data transmission efficiency and the data processing efficiency are improved.

Description

Technical Field

[0001] The present application belongs to the field of computer technology, and in particular, relates to a multi-source heterogeneous data fusion processing system for industry based on mobile communications. Background Art

[0002] In practical applications, with the rapid development of Industry 4.0, the requirements of the industrial industry for equipment monitoring and maintenance are constantly increasing. In order to achieve timely monitoring and maintenance of equipment, it is usually necessary to obtain the relevant data of each device in real time and integrate a large amount of relevant data in real time. However, when the number of devices is too large and the relevant data corresponding to each of them is too large, the existing technology cannot achieve real-time acquisition of the relevant data of each device and real-time processing of a large amount of relevant data. It can be seen that the existing technology is difficult to meet actual needs. Summary of the invention

[0003] The embodiment of the present application provides a multi-source heterogeneous data fusion processing system for industry based on mobile communications, which can solve the problems existing in the prior art that it is impossible to obtain relevant data of each device in real time, and to perform real-time fusion processing of a large amount of relevant data, which is difficult to meet actual needs.

[0004] In a first aspect, an embodiment of the present application provides a multi-source heterogeneous data fusion processing system for industry based on mobile communications, including: A multi-source signal acquisition module, used for acquiring operating parameters of each first device in the target area, and sending each of the operating parameters to the data processing module through the fifth generation mobile communication network; a visual inspection module, configured to collect appearance image data and temperature data of each of the first devices, and send each of the appearance image data and each of the temperature data to the data processing module via the fifth-generation mobile communication network; An inspection robot, configured to travel along a set path based on the positioning technology of the fifth-generation mobile communication network, collect device data of each second device on the set path, and send each of the device data to the data processing module through the fifth-generation mobile communication network; The data processing module is used to perform network slicing processing on the fifth-generation mobile communication network to obtain multiple target network slices, and send each of the operating parameters, each of the appearance image data, each of the temperature data and each of the device data to the data analysis module through the multiple target network slices; The data analysis module is used to generate multiple tasks to be processed based on each of the operating parameters, each of the appearance image data, each of the temperature data and each of the device data; and to process the multiple tasks to be processed in parallel to obtain the detection results of each target device; the target device is any one of the first device and the second device.

[0005] Optionally, the data processing module is specifically used for: Acquiring target business information of the multi-source heterogeneous data fusion processing system for industry based on mobile communication; Performing network slicing processing on the fifth-generation mobile communication network based on the target service information to obtain a plurality of target network slices; Each of the operating parameters, each of the appearance image data, each of the temperature data, and each of the device data are sent to the data analysis module through multiple target network slices.

[0006] Optionally, performing network slicing processing on the fifth-generation mobile communication network based on the target service information to obtain a plurality of target network slices includes: Based on the target service information, each initial network slice is generated; each initial network slice carries the resource information required by the respective network slice; Based on each of the resource information, the network resources of the fifth-generation mobile communication network are allocated to each of the initial network slices to obtain each of the target network slices.

[0007] Optionally, the generating each initial network slice based on the target service information includes: Obtain historical network demand information; Classifying the target service information based on the historical network demand information to obtain resource information corresponding to each of the initial network slices; Based on each of the resource information, each of the initial network slices is generated.

[0008] Optionally, sending each of the operating parameters, each of the appearance image data, each of the temperature data, and each of the device data to the data analysis module through the plurality of the target network slices includes: Determine the transmission priority of each task to be transmitted based on the target service information; Based on each of the tasks to be transmitted, each of the operating parameters, each of the appearance image data, each of the temperature data, and each of the device data is divided to obtain a first data set corresponding to each of the tasks to be transmitted; Control multiple target network slices to send each of the first data sets to the data analysis module according to the transmission priority of each of the tasks to be transmitted.

[0009] Optionally, the data processing module is further used for: Obtain monitoring indicator information of each of the target network slices; Determine the operating status of each of the target network slices based on the monitoring indicator information of each of the target network slices; Based on the operating status of each of the target network slices, the network resources of each of the target network slices are adjusted.

[0010] Optionally, the data analysis module is specifically used for: Based on the target business information, each of the operating parameters, each of the appearance image data, each of the temperature data, and each of the device data are divided to obtain each of the tasks to be processed; The second data sets corresponding to each of the tasks to be processed are sequentially input into the detection models corresponding to each of the tasks to be processed for parallel processing to obtain the detection results of each of the target devices; the detection models include an anomaly detection model and a fault prediction model.

[0011] Optionally, the multi-source signal acquisition module specifically includes: a plurality of sets of different types of sensor sets and a first communication unit; Each group of the sensor sets is used to collect operating parameters corresponding to the type of the sensor set in a plurality of the first devices; The first communication unit is used to determine a data protocol that matches the sensor, encapsulate each of the operating parameters based on the data protocol, and send the first data obtained after encapsulation to the data processing module through the fifth-generation mobile communication network.

[0012] Optionally, the visual detection module specifically includes: A camera unit, used for collecting appearance image data of each of the first devices; A thermal imaging unit, used to collect temperature data of each of the first devices; a protocol conversion unit, configured to determine the communication protocol of the fifth-generation mobile communication network, and if the current protocol corresponding to the visual detection module does not match the communication protocol, convert the current protocol based on the communication protocol to obtain a target protocol corresponding to the visual detection module; the target protocol is compatible with the fifth-generation mobile communication network; The second communication unit is used to encapsulate each of the appearance image data and each of the temperature data based on the target protocol, and send the second data obtained after encapsulation to the data processing module through the fifth-generation mobile communication network.

[0013] Optionally, the multi-source heterogeneous data fusion processing system for industry based on mobile communication further includes: a human-computer interaction module; The human-computer interaction module is used to output the detection results of each of the target devices through the fifth-generation mobile communication network.

[0014] Compared with the prior art, the multi-source heterogeneous data fusion processing system for industry based on mobile communication provided by the embodiment of the present application has the following beneficial effects: the multi-source signal acquisition module can collect operating parameters from each first device in the target area, covering various types of data sources, which means that the multi-faceted status information of the device during operation can be fully grasped, and the data is transmitted through the 5G network, making full use of the high speed, low latency and large capacity of the 5G network, ensuring that the collected operating parameters can be sent out quickly and stably, reducing the delay and packet loss during data transmission, and even in the face of frequent data collection of a large number of devices, it can also respond efficiently. The visual inspection module can not only obtain the appearance image data of the first device, intuitively present the surface condition of the device, but also collect temperature data to reflect the working status of the device from a thermal perspective. The combination of these two different dimensions of data can more comprehensively detect the device status, and also use the 5G network to send data. With the advantage of 5G, large-capacity image data and temperature data can be quickly transmitted to ensure the timeliness and integrity of the data, and meet the requirements of real-time monitoring for data timeliness. The inspection robot travels along the set path based on the positioning technology of the 5G network. On the one hand, it can carry out orderly inspections of each second device in the target area according to the preset scientific and reasonable route, without missing or mistaking. On the other hand, by using the 5G high-precision positioning technology, it can accurately know its own position, ensure that the collected data corresponds to the accurate device location information, and facilitate subsequent data association and analysis. At the same time, the collected data is sent out through the 5G network, so that the data obtained during the inspection process can be transmitted in time, without being restricted by factors such as distance, ensuring that the data can quickly reach the data processing module for subsequent processing. The data processing module sends various types of data to the data analysis module through different target network slices, realizing the orderly diversion and efficient integrated transmission of data, avoiding mutual interference between different types of data during the transmission process, and ensuring the quality and efficiency of data transmission. The data analysis module has the ability to process multiple tasks to be processed in parallel. Through reasonable algorithms and computing resource allocation, it can analyze multiple tasks at the same time, greatly shortening the overall data analysis time and improving the efficiency of data analysis. In summary, this system can achieve comprehensive, efficient and accurate real-time monitoring and analysis of equipment in the target area through the coordinated cooperation of various modules and taking advantage of the 5G network, which helps to improve the equipment management level, ensure the reliable operation of equipment and reduce operation and maintenance costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0016] Figure 1 It is a structural schematic diagram of a multi-source heterogeneous data fusion processing system for industry based on mobile communication provided by an embodiment of the present application; Figure 2 It is a specific structural diagram of a multi-source heterogeneous data fusion processing system for industry based on mobile communication provided by an embodiment of the present application; Figure 3 is a specific structural diagram of a multi-source heterogeneous data fusion processing system for industry based on mobile communication provided by another embodiment of the present application; Figure 4 is a structural schematic diagram of a multi-source heterogeneous data fusion processing system for industry based on mobile communication provided by another embodiment of the present application; Figure 5 This is a flowchart for implementing a data processing module in a multi-source heterogeneous data fusion processing system for industry based on mobile communication provided by an embodiment of the present application; Figure 6 It is a flow chart for implementing a data processing module in a multi-source heterogeneous data fusion processing system for industry based on mobile communications provided by another embodiment of the present application. DETAILED DESCRIPTION

[0017] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present application. However, it should be clear to those skilled in the art that the present application may also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present application.

[0018] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, wholes, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or combinations thereof.

[0019] It should also be understood that the term “and / or” used in the specification and appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0020] As used in the specification and appended claims of this application, the term "if" can be interpreted as "when" or "uponce" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrase "if it is determined" or "if [described condition or event] is detected" can be interpreted as meaning "uponce it is determined" or "in response to determining" or "uponce [described condition or event] is detected" or "in response to detecting [described condition or event]", depending on the context.

[0021] In addition, in the description of the present application specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.

[0022] References to "one embodiment" or "some embodiments" etc. described in the specification of this application mean that one or more embodiments of the present application include specific features, structures or characteristics described in conjunction with the embodiment. Therefore, the statements "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. that appear in different places in this specification do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0023] In practical applications, with the rapid development of Industry 4.0, the requirements of the industrial industry for equipment monitoring and maintenance are constantly increasing. In order to achieve timely monitoring and maintenance of equipment, it is usually necessary to obtain the relevant data of each device in real time and integrate a large amount of relevant data in real time. However, when the number of devices is too large and the relevant data corresponding to each of them is too large, the existing technology cannot achieve real-time acquisition of the relevant data of each device and real-time processing of a large amount of relevant data. It can be seen that the existing technology is difficult to meet actual needs.

[0024] Therefore, this application proposes a multi-source heterogeneous data fusion processing system for industry based on mobile communications. Through the coordinated cooperation of various modules and taking advantage of the 5G network, it can achieve comprehensive, efficient and accurate monitoring and analysis of equipment in the target area, which helps to improve the level of equipment management, ensure the reliable operation of equipment and reduce operation and maintenance costs.

[0025] See also Figure 1 , Figure 1 This is a schematic diagram of the structure of a multi-source heterogeneous data fusion processing system for industry based on mobile communication provided by an embodiment of the present application. For ease of explanation, only the parts related to this embodiment are shown, which are described in detail as follows: like Figure 1 As shown, the multi-source heterogeneous data fusion processing system 1 for industry based on mobile communication includes: a multi-source signal acquisition module 11, a visual detection module 12, an inspection robot 13, a data processing module 14 and a data analysis module 15. The data processing module 14 is respectively connected to the multi-source signal acquisition module 11, the visual detection module 12, the inspection robot 13, and the data analysis module 15. The communication connection mode includes but is not limited to a wired communication connection and a wireless communication connection.

[0026] Specifically, the multi-source signal acquisition module 11 is used to collect the operating parameters of each first device in the target area, and send each operating parameter to the data processing module through the fifth generation mobile communication network.

[0027] The visual inspection module 12 is used to collect appearance image data and temperature data of each first device, and send each appearance image data and each temperature data to the data processing module through the fifth generation mobile communication network.

[0028] The inspection robot 13 is used to travel along a set path based on the positioning technology of the fifth-generation mobile communication network, collect device data of each second device on the set path, and send each device data to the data processing module through the fifth-generation mobile communication network.

[0029] The data processing module 14 is used to perform network slicing processing on the fifth-generation mobile communication network to obtain multiple target network slices, and send various operating parameters, various appearance image data, various temperature data and various equipment data to the data analysis module through the multiple target network slices.

[0030] The data analysis module 15 is used to generate multiple tasks to be processed based on various operating parameters, various appearance image data, various temperature data and various equipment data; the multiple tasks to be processed are processed in parallel to obtain the detection results of each target device; the target device is any one of the first device and the second device.

[0031] In the embodiment of the present application, the number of the multi-source signal acquisition module 11, the visual detection module 12, and the inspection robot 13 can include multiple (only one is shown in the figure).

[0032] It should be noted that the target area can be determined according to actual needs and is not limited here. For example, the target area can be an industrial area.

[0033] Among them, a large number of industrial equipment are installed in the target area.

[0034] In the embodiment of the present application, the multi-source signal acquisition module 11 is connected to each first device in the target area, so the multi-source signal acquisition module 11 can collect the operating parameters of each first device, wherein each first device is an industrial device.

[0035] Afterwards, the multi-source signal acquisition module 11 may send various operating parameters to the data processing module 14 via the fifth generation mobile communication network (5th Generation Mobile Communication Technology, 5G).

[0036] In one embodiment of the present application, in order to fully reflect the operating status of each first device and provide comprehensive data support for subsequent data analysis, the multi-source data acquisition module may include sensors of multiple different parameter types. Among them, sensors of different parameter types are used to collect operating parameters corresponding to each first device.

[0037] In some possible embodiments, parameter types include, but are not limited to: vibration type, temperature type, speed type, current type, voltage type, liquid level type, pressure type, stress type, flow type, oil water content type, and humidity type, etc. Correspondingly, operating parameters include, but are not limited to: vibration parameters, temperature parameters, speed parameters, current parameters, voltage parameters, liquid level parameters, pressure parameters, stress parameters, flow parameters, oil water content parameters, and humidity parameters, etc.

[0038] In the embodiment of the present application, the relevant personnel can divide the target area into various sub-areas. After that, the relevant personnel can respectively set a plurality of visual inspection modules 12 in each sub-area. Among them, the industrial equipment in each sub-area is the first equipment.

[0039] Based on this, the visual inspection module 12 can collect appearance image data and temperature data of each first device.

[0040] It should be noted that the visual inspection module 12 may include an industrial camera and an infrared thermal imager. Therefore, the visual inspection module 12 may acquire the appearance image data of each first device through the industrial camera, and the visual inspection module 12 may acquire the temperature data of each first device through the infrared thermal imager.

[0041] Afterwards, the visual inspection module 12 can send each appearance image data and each temperature data to the data processing module 14 through the 5G network.

[0042] In the embodiment of the present application, since there are areas in the target area that are difficult for relevant personnel to reach or dangerous, in order to detect areas that are difficult for relevant personnel to reach or dangerous, improve the comprehensiveness and safety of equipment monitoring, and achieve 24-hour uninterrupted monitoring, the above-mentioned multi-source heterogeneous data fusion processing system 1 can drive along the set path through the inspection robot 13 based on the positioning technology of the 5G network, and collect the equipment data of each second device on the set path. Among them, the set path can be planned according to the areas in the actual target area that are difficult for relevant personnel to reach or dangerous.

[0043] It should be noted that the device data includes but is not limited to various operating information of each second device, such as temperature, humidity, voltage, current, and pressure.

[0044] Afterwards, the inspection robot 13 can send the data of each device to the data processing module 14 through the 5G network.

[0045] In the embodiment of the present application, in order to achieve reliability and stability of data transmission and ensure real-time transmission of key data, the data processing module 14 can perform network slicing processing on the 5G network to obtain multiple target network slices. Afterwards, the data processing module 14 can send various operating parameters, various appearance image data, various temperature data, and various device data to the data analysis module 15 through the multiple target network slices.

[0046] In actual applications, network slicing is to dynamically allocate physical network resources (such as bandwidth, computing power, and storage space) to different network slices on the same physical network infrastructure through software-defined networking (SDN) and network function virtualization (NFV) technologies to ensure that each slice can obtain the required resources. It supports the creation of multiple logically isolated virtual networks. Each virtual network (network slice) can be configured according to specific business needs, including parameters such as bandwidth, latency, and security to meet the requirements of different application scenarios.

[0047] In the embodiment of the present application, the data analysis module 15 can generate a plurality of tasks to be processed based on various operating parameters, various appearance image data, various temperature data and various equipment data.

[0048] In some possible embodiments, the data analysis module 15 may obtain target business information corresponding to the multi-source heterogeneous data fusion processing system 1 for industry based on mobile communication. The target business information is used to describe the working purpose of the multi-source heterogeneous data fusion processing system 1 for industry based on mobile communication at this time.

[0049] In an implementation of this embodiment, relevant personnel can input the above target business information on the display interface of the multi-source heterogeneous data fusion processing system 1 for industry based on mobile communication.

[0050] Afterwards, the data analysis module 15 may divide each operating parameter, each appearance image data, each temperature data and each device data based on the target business information to obtain each task to be processed.

[0051] Specifically, the data analysis module 15 can extract key indicators related to operating parameters, appearance image data, temperature data, and device data from the target business information. For example, for the production quality inspection business of electronic products, key indicators may include the operating speed of the device (operating parameters), whether the shell has scratches or deformation (appearance image data), whether the temperature of the internal components is within the normal range (temperature data), and whether each device component is intact and functioning properly (device data).

[0052] Afterwards, the data analysis module 15 may determine the division rules for each task.

[0053] In some possible embodiments, the data analysis module 15 can determine the division rules for each task according to the workflow corresponding to the target business included in the target business information. For example, in the product assembly business, it is necessary to check whether the equipment components are complete before assembly (equipment data task), monitor whether the equipment operating parameters are normal during the assembly process, check whether the appearance meets the requirements after the assembly is completed, and finally check whether the temperature of the product is normal after running for a period of time.

[0054] In some other possible embodiments, the division rule can also be a rule based on data association. Specifically, the data analysis module 15 can divide the tasks according to the association between each operating parameter, each appearance image data, each temperature data and each device data. Exemplarily, if it is found that the abnormal operating parameters of a certain device may cause damage to the appearance or excessive temperature, then the operating parameter check, appearance check and temperature check are divided into a related task to be processed. For example, for the detection of a car engine, if the engine operating parameters show that the combustion is not sufficient, then it is necessary to check the exhaust emissions (appearance related data, such as whether there is black smoke) and whether the engine temperature is abnormal, and these three checks are processed as one task.

[0055] In some other possible embodiments, the data analysis module 15 can also determine the priority of the task according to the urgency and importance of the target business, and divide the tasks according to the priority. For example, for the power system, if the transformer temperature is too high, it may cause a fault, so the inspection task related to the temperature data has a higher priority; for the appearance defect inspection of electronic products, if it is a high-end product display business, the appearance inspection task will also have a higher priority.

[0056] Afterwards, the data analysis module 15 may divide each operating parameter, each appearance image data, each temperature data and each device data according to the above division rules and key indicators to obtain each task to be processed.

[0057] In some possible embodiments, the data analysis module 15 may divide each operating parameter, each appearance image data, each temperature data, and each device data in a single-dimensional manner.

[0058] Specifically, for each operating parameter, the data analysis module 15 may divide each operating parameter according to the above-mentioned division rules and key indicators to obtain each to-be-processed task corresponding to the operating parameter.

[0059] For each appearance image data, the data analysis module 15 can divide each operating parameter according to the above division rules and key indicators to obtain each to-be-processed task corresponding to the appearance image data.

[0060] For each temperature data, the data analysis module 15 may divide each temperature data according to the above division rules and key indicators to obtain each to-be-processed task corresponding to the temperature data.

[0061] For the device data, the data analysis module 15 can divide each device data according to the above division rules and key indicators to obtain each to-be-processed task corresponding to the device data.

[0062] Based on this, the data analysis module 15 can obtain all tasks to be processed.

[0063] In other possible embodiments, considering the mutual influence and correlation between the data, the data analysis module 15 can also combine the data of different dimensions according to the above-mentioned division rules and key indicators, that is, combine and divide the various operating parameters, various appearance image data, various temperature data and various equipment data, so as to obtain various tasks to be processed.

[0064] In the embodiment of the present application, after obtaining multiple tasks to be processed, the data analysis module 15 can process the multiple tasks to be processed in parallel, that is, input each task to be processed into the detection model corresponding to each task to be processed at the same time for detection, and obtain the detection results of each task to be processed. Afterwards, the data analysis module 15 can determine the detection results of each target device according to the detection results of each task to be processed. Wherein, each target device is any one of the first device and the second device.

[0065] It should be noted that the detection results of the above-mentioned tasks to be processed are used to describe the detection results of the devices corresponding to the data contained in the tasks to be processed. Therefore, the data analysis module 15 can determine the detection results of the target devices according to the detection results of the tasks to be processed.

[0066] The detection result of each target device is used to describe whether the operation status of each target device is normal, and whether each target device will fail.

[0067] In some possible embodiments, the above detection model may include multiple models, including but not limited to: an anomaly detection model and a fault prediction model. Wherein, both the anomaly detection model and the fault prediction model can be trained by a pre-built deep learning model.

[0068] From the above, it can be seen that the multi-source heterogeneous data fusion processing system for industry based on mobile communication provided by the embodiment of the present application, the multi-source signal acquisition module can collect operating parameters from each first device in the target area, covering various types of data sources, which means that the various aspects of the status information of the equipment during operation can be fully grasped, and the data is transmitted through the 5G network, making full use of the high speed, low latency and large capacity of the 5G network, ensuring that the collected operating parameters can be sent out quickly and stably, reducing the delay and packet loss during data transmission, and even in the face of frequent data collection of a large number of devices, it can also respond efficiently. The visual inspection module can not only obtain the appearance image data of the first device, intuitively present the surface condition of the device, but also collect temperature data to reflect the working status of the device from a thermal perspective. The combination of these two different dimensions of data can more comprehensively detect the equipment situation, and also use the 5G network to send data. With the advantage of 5G, large-capacity image data and temperature data can be quickly transmitted to ensure the timeliness and integrity of the data, and meet the requirements of real-time monitoring for data timeliness. The inspection robot travels along the set path based on the positioning technology of the 5G network. On the one hand, it can carry out orderly inspections of each second device in the target area according to the preset scientific and reasonable route, without missing or mistaking. On the other hand, by using the 5G high-precision positioning technology, it can accurately know its own position, ensure that the collected data corresponds to the accurate device location information, and facilitate subsequent data association and analysis. At the same time, the collected data is sent out through the 5G network, so that the data obtained during the inspection process can be transmitted in time, without being restricted by factors such as distance, ensuring that the data can quickly reach the data processing module for subsequent processing. The data processing module sends various types of data to the data analysis module through different target network slices, realizing the orderly diversion and efficient integrated transmission of data, avoiding mutual interference between different types of data during the transmission process, and ensuring the quality and efficiency of data transmission. The data analysis module has the ability to process multiple tasks to be processed in parallel. Through reasonable algorithms and computing resource allocation, it can analyze multiple tasks at the same time, greatly shortening the overall data analysis time and improving the efficiency of data analysis. In summary, this system can achieve comprehensive, efficient and accurate monitoring and analysis of equipment in the target area through the coordinated cooperation of various modules and taking advantage of the 5G network, which helps to improve the equipment management level, ensure the reliable operation of equipment and reduce operation and maintenance costs.

[0069] See also Figure 2 , Figure 2 FIG. 1 is a schematic diagram of a specific structure of a multi-source heterogeneous data fusion processing system for industry based on mobile communication provided by an embodiment of the present application. Figure 2 As shown, in this embodiment, the multi-source signal acquisition module 11 specifically includes: a plurality of sensor sets 111 of different types (only two sets are shown in the figure) and a first communication unit 112. Among them: Each group of sensor sets 111 is used to collect operating parameters corresponding to the type of the sensor set 111 in multiple first devices.

[0070] The first communication unit 112 is used to determine a data protocol that matches the sensor, encapsulate various operating parameters based on the data protocol, and send the first data obtained after encapsulation to the data processing module 14 through the fifth-generation mobile communication network.

[0071] In this embodiment, each sensor set 111 is used to collect operating parameters of a parameter type in a plurality of first devices, wherein the parameter type is the same as the type of the sensor set 111 .

[0072] Exemplarily, assuming that the type of a certain sensor set 111 is a vibration type, then the type of the parameter collected by the sensor set 111 is also a vibration type.

[0073] It should be noted that each sensor set 111 includes a plurality of sensors of the same type.

[0074] Afterwards, the first communication unit 112 can determine the data protocol that matches each sensor, encapsulate each operating parameter based on the data protocol, and send the first data obtained after encapsulation to the data processing module 14 through the 5G network.

[0075] In some possible embodiments, when the sensor and the 5G network use different data protocols, the first communication unit 112 can perform protocol conversion to convert the data collected by the sensor into a protocol format that can be recognized and transmitted by the 5G network, such as converting the sensor's private protocol into a universal protocol such as TCP / IP and MQTT.

[0076] Afterwards, the first communication unit 112 can sort the data collected by the sensor, organize it according to certain rules and formats, and select a suitable compression algorithm to compress the data according to the characteristics of the data and the requirements of the 5G network to reduce the amount of data transmission and improve the transmission efficiency. Then the sorted and compressed data is packaged, and necessary information such as the header and check bit are added to ensure reliable transmission in the 5G network.

[0077] From the above, it can be seen that in the multi-source heterogeneous data fusion processing system for industry based on mobile communication provided by this embodiment, the multi-source signal acquisition module can specifically collect operating parameters corresponding to its own type through each set of sensors. This means that sensors can be accurately deployed according to the key operating indicators of different types of first devices, and this targeted collection can comprehensively and focusedly obtain key information on the operating status of the equipment. Afterwards, the first communication unit can determine the data protocol that matches the sensor and send data using the 5G network. Because the 5G network has the characteristics of high speed, low latency, and large capacity, compared with traditional communication methods such as 4G networks or wired networks, the 5G network can support more sensors to transmit data at the same time, and can send data to the data processing module faster.

[0078] See also Figure 3 , Figure 3 FIG. 1 is a schematic diagram of a specific structure of a multi-source heterogeneous data fusion processing system for industry based on mobile communication provided by another embodiment of the present application. Figure 3 As shown, in this embodiment, the visual detection module 12 specifically includes: The camera unit 121 is used to collect appearance image data of each first device.

[0079] The thermal imaging unit 122 is used to collect temperature data of each first device.

[0080] The protocol conversion unit 123 is used to determine the communication protocol of the fifth-generation mobile communication network. If the current protocol corresponding to the visual detection module 12 does not match the communication protocol, the current protocol is converted based on the communication protocol to obtain the target protocol corresponding to the visual detection module 12; the target protocol is compatible with the fifth-generation mobile communication network.

[0081] The second communication unit 124 is used to encapsulate each appearance image data and each temperature data based on the target protocol, and send the encapsulated second data to the data processing module through the fifth-generation mobile communication network.

[0082] In practical applications, the camera unit 121 may be a 4K / 8K ultra-high-definition industrial camera, and the thermal imaging unit 122 may be a high-resolution infrared thermal imager.

[0083] In this embodiment, when the protocol conversion unit 123 detects that the current protocol corresponding to the visual detection module 12 does not match the communication protocol of the 5G network, it means that the data format collected by the visual detection module 12 does not meet the requirements of the 5G network transmission protocol. Therefore, the protocol conversion unit 123 needs to perform protocol conversion to convert the local protocol of the visual data (such as the private data transmission protocol of the camera unit 121 and the thermal imaging unit 122) into a protocol suitable for 5G network transmission, that is, a target protocol, such as the TCP / IP protocol or the UDP protocol. The target protocol is compatible with the 5G network.

[0084] Afterwards, the second communication unit 124 can encapsulate each appearance image data and each temperature data based on the target protocol, and send the encapsulated second data to the data processing module 14 through the 5G network.

[0085] As can be seen from the above, in the multi-source heterogeneous data fusion processing system for industry based on mobile communication provided by this embodiment, the visual inspection module collects data for different physical quantities through the camera unit and the thermal imaging unit, and can simultaneously obtain the appearance image information and temperature information of the first device. This multimodal data acquisition method provides a more comprehensive perspective for equipment status monitoring, which is not limited to a single visual or temperature feature, but combines the two to provide a rich data basis for subsequent more accurate analysis and diagnosis. At the same time, the protocol conversion unit has the ability to automatically detect and convert protocols. It can actively determine whether the protocol currently used by the visual inspection module matches the 5G network communication protocol, and automatically perform the conversion operation if it does not match. This intelligent protocol adaptation process does not require excessive manual intervention, improves the autonomy and adaptability of the system, and enables the visual inspection module to seamlessly access the 5G network without worrying about protocol compatibility issues. Finally, the second communication unit is responsible for integrating the data from different acquisition units (camera unit and thermal imaging unit) and encapsulating them based on the adapted target protocol. This process packages various types of data into a format that meets the transmission requirements of the 5G network, ensuring the integrity and orderliness of the data during network transmission, while also facilitating decapsulation and subsequent processing at the receiving end (data processing module).

[0086] See also Figure 4 , Figure 4 FIG. 1 is a schematic diagram of a multi-source heterogeneous data fusion processing system for industry based on mobile communication provided by another embodiment of the present application. Figure 4 As shown, in this embodiment, the multi-source heterogeneous data fusion processing system 1 for industry based on mobile communication may further include: a human-computer interaction module 16 . The human-computer interaction module 16 is in communication connection with the data analysis module 15 .

[0087] Specifically, the human-computer interaction module 16 is used to output the detection results of each target device through the fifth-generation mobile communication network.

[0088] In one embodiment of the present application, Figure 1 In the corresponding embodiment, in order to achieve accurate slicing of the 5G network, the data processing module 14 can specifically be as follows: Figure 5 Steps S101 to S103 shown send various operating parameters, various appearance image data, various temperature data, and various equipment data to the data analysis module, as detailed below: In S101, target business information of the multi-source heterogeneous data fusion processing system for industry based on mobile communication is obtained.

[0089] In S102, network slicing is performed on the fifth-generation mobile communication network based on the target service information to obtain a plurality of target network slices.

[0090] In this embodiment, the data processing module can perform network slicing processing on the 5G network through the acquired target service information to obtain multiple target network slices.

[0091] In one embodiment of the present application, the data processing module Figure 6 Steps S201 to S203 shown in the figure obtain multiple target network slices, which are described in detail as follows: In S201, each initial network slice is generated based on the target service information; each initial network slice carries the resource information required by the respective network slice.

[0092] In S202, based on each of the resource information, the network resources of the fifth-generation mobile communication network are allocated to each of the initial network slices to obtain each of the target network slices.

[0093] In this embodiment, the data processing module can input the target business information into the large language model for semantic understanding, thereby determining various characteristics and various requirements corresponding to the target business information. Afterwards, the data processing module can determine various business types corresponding to the target business information based on the various characteristics and various requirements.

[0094] In this embodiment, the data processing module pre-stores the correspondence between different service types and different network slice templates. Therefore, the data processing module can determine the various network slice modules corresponding to the target service information according to the various service types determined at this time and the above correspondence, that is, each initial network slice. It should be noted that each initial network slice carries the resource information required by each. Among them, the resource information includes but is not limited to: frequency bands, time slots, power and other resources in the radio access network (RAN), as well as computing resources, storage resources and network bandwidth in the core network.

[0095] In one embodiment of the present application, the data processing module may also obtain each initial network slice according to the following steps, as detailed below: Obtain historical network demand information; Classifying the target service information based on the historical network demand information to obtain resource information corresponding to each of the initial network slices; Based on each of the resource information, each of the initial network slices is generated.

[0096] In this embodiment, the data processing module can obtain the target business information and input it into the large language model for semantic understanding, thereby determining various characteristics and various requirements corresponding to the target business information. Afterwards, the data processing module can determine various business types corresponding to the target business information according to the various characteristics and various requirements.

[0097] Afterwards, the data processing module may obtain the historical network demand information of each of the various service types determined above in the historical time period. The historical time period may be determined according to actual needs and is not limited here.

[0098] In this embodiment, after obtaining the historical network demand information of various service types, the data processing module can extract features of each historical network demand information to obtain key information corresponding to each historical network demand information, wherein the key information is used to describe information that can reflect network demand features.

[0099] Exemplarily, the key information may be indicators such as average bandwidth requirement, maximum number of connections, acceptable delay range, and upper limit of packet loss rate.

[0100] Afterwards, the data processing module classifies the target service information based on the key information corresponding to each service type and determines the resource information corresponding to each initial network slice. The resource information is used to describe the network resources required for each initial network slice.

[0101] In this embodiment, the data processing module can view the various standard network slice templates corresponding to the pre-stored 5G network, and search for network slice templates that match the above resource information, so as to obtain various initial network slices. For example, for high-bandwidth video service resource information, the existing "video transmission optimization" network slice template is matched. If the template basically meets the requirements, the next step can be directly based on it; if it does not completely match, the template needs to be customized and modified to adjust the network function configuration, resource allocation ratio, etc.

[0102] In some possible embodiments, when the data processing module fails to find a network slicing template that matches certain resource information, such as resource information for a new type of special service, the data processing module can customize a new network slicing template to clarify the specific functional configuration and resource allocation plans of each part such as the access network and core network, and determine the customized network slicing module as the initial network template corresponding to the resource information.

[0103] In this embodiment, the data processing module can allocate the network resources of the 5G network to each initial network slice based on various resource information, thereby obtaining each target network slice.

[0104] In S103, each of the operating parameters, each of the appearance image data, each of the temperature data, and each of the device data are sent to the data analysis module through multiple target network slices.

[0105] In this embodiment, the data processing module can send various operating parameters, various appearance image data, various temperature data and various equipment data to the data analysis module through multiple target network slices.

[0106] Specifically, the data processing module can integrate the operating parameters, appearance image data, temperature data, and equipment data from different sources. For example, add corresponding metadata tags to each set of data, indicating key information such as the data type (operating parameters, appearance image data, or other types), the device number, and the collection time, so that the data analysis module can clearly classify and identify the data.

[0107] Afterwards, the data processing module may process the integrated data in a set logical order. For example, the data of the same device may be arranged in sequence according to the device to form a data packet structure that is convenient for subsequent processing.

[0108] Afterwards, the data processing module can send the processed data to the data analysis module.

[0109] In one embodiment of the present application, the data processing module can determine the appropriate target network slice according to the business importance and transmission requirements (such as bandwidth requirements, delay requirements, reliability requirements, etc.) of each data. For example, for some key equipment operating parameters with extremely high real-time requirements, select the target network slice configured with ultra-low delay function; and for data with relatively large bandwidth requirements such as appearance image data, match it to the target network slice with high bandwidth characteristics.

[0110] In this embodiment, the data processing module can accurately match various operating parameters, various appearance image data, various temperature data and various equipment data with the corresponding target network slices according to the functions and applicable business scope of each target network slice, ensuring that each data can be transmitted in the most suitable network slice environment.

[0111] Afterwards, the data processing module can assign each operating parameter, each appearance image data, each temperature data and each device data to the corresponding target network slice entrance according to the results of the above matching, so as to send each operating parameter, each appearance image data, each temperature data and each device data to the data analysis module.

[0112] In another embodiment of the present application, the data processing module may also implement step S103 according to the following steps, which are described in detail as follows: Determine the transmission priority of each task to be transmitted based on the target service information; Based on each of the tasks to be transmitted, each of the operating parameters, each of the appearance image data, each of the temperature data, and each of the device data is divided to obtain a first data set corresponding to each of the tasks to be transmitted; Control multiple target network slices to send each of the first data sets to the data analysis module according to the transmission priority of each of the tasks to be transmitted.

[0113] In this embodiment, the data processing module can determine multiple tasks to be transmitted based on the target business information. After that, the data processing module can continue to analyze the target business information to determine factors such as the real-time requirements, data importance, and criticality to system operation of each task to be transmitted.

[0114] The data processing module can score each task to be transmitted according to the real-time requirements, data importance, and criticality to system operation of each task to be transmitted, and obtain the score of each task to be transmitted.

[0115] Afterwards, the data processing module may determine the transmission priority of each task to be transmitted according to the score of each task to be transmitted.

[0116] It should be noted that the score is positively correlated with the transmission priority, that is, the higher the score, the higher the transmission priority, and the lower the score, the lower the transmission priority.

[0117] In this embodiment, the data processing module can determine the association between various operating parameters, appearance image data, temperature data, and device data and various tasks to be transmitted. For example, for equipment fault diagnosis tasks, key operating parameters of the equipment (such as motor current, speed, etc.), temperature data (to determine whether it is overheated), and appearance image data (whether there are abnormal appearances such as component deformation) may be required; while for equipment performance evaluation tasks, various operating parameters and basic information data of the equipment over a longer period of time are required.

[0118] Afterwards, the data processing module can divide each operating parameter, each appearance image data, each temperature data and each device data according to the above-mentioned determined association relationship, that is, divide the corresponding data into corresponding tasks to be transmitted, thereby obtaining a first data set corresponding to each task to be transmitted.

[0119] In this embodiment, the data processing module can allocate the corresponding first data set to a suitable target network slice for transmission according to the transmission priority of each task to be transmitted. For example, the first data set of a high-priority real-time fault alarm task is allocated to a target network slice with low latency and high reliability; the first data set of a low-priority historical data backup task is allocated to a target network slice with relatively low bandwidth requirements and low cost.

[0120] From the above, it can be seen that the multi-source heterogeneous data fusion processing system for industry based on mobile communications provided by this embodiment, the entire process is carried out around the target business information of the multi-source heterogeneous data fusion processing system. First, the target business information is obtained, and then the 5G network slice processing is performed according to these specific business needs, rather than a general and fixed network configuration method. This means that each target network slice is customized to meet the requirements of a specific business for data transmission in terms of bandwidth, latency, reliability, etc., and can accurately meet the personalized needs of data transmission in different business scenarios.

[0121] In another embodiment of the present application, in order to monitor the operating status of each network slice in real time, adjust resource allocation in time, and ensure service quality, the data processing module may further perform the following steps, which are described in detail as follows: Obtain monitoring indicator information of each of the target network slices; Determine the operating status of each of the target network slices based on the monitoring indicator information of each of the target network slices; Based on the operating status of each of the target network slices, the network resources of each of the target network slices are adjusted.

[0122] It should be noted that the monitoring indicator information includes but is not limited to: network bandwidth utilization, transmission delay, packet loss rate, number of connections, signal strength, and device load.

[0123] The operating status includes but is not limited to: normal operation and serious abnormality.

[0124] In some possible embodiments, the data processing module can determine the corresponding monitoring indicator information according to the types of services carried by different target network slices and their key requirements for network performance. For example, for network slices carrying high-definition video services, focus on indicators such as bandwidth utilization, video stream freeze rate, and packet loss rate; for network slices supporting industrial control services, focus on indicators such as transmission delay, jitter, and connection reliability.

[0125] In this embodiment, for each indicator collected by each target network slice, the data processing module can analyze the indicators according to the preset corresponding performance interval standards to determine the status level of each indicator. For example, if the packet loss rate indicator of a video service network slice is found to be 2%, the indicator is determined to be at the "good" level according to the set packet loss rate classification standard.

[0126] Afterwards, the data processing module can calculate the status level of each indicator in combination with its weight according to the preset comprehensive evaluation rules to obtain the overall operating status of the target network slice. For example, after weighted average calculation, the overall operating status score of an industrial control network slice is 80 points (out of 100 points). According to the pre-set classification criteria, the network slice is judged to be in a "normal operation" state; if another network slice scores less than 60 points, it is judged to be in a "severe abnormal" state. Among them, the preset comprehensive evaluation rules can be determined according to actual needs and are not limited here.

[0127] In this embodiment, the data processing module can determine the corresponding resource adjustment strategy for different operating states. For example, for network slices in the "normal operation" state, the current resource allocation is kept basically stable, but appropriate fine-tuning can be performed according to the business development trend, such as reserving a certain proportion of spare resources; for slices in the "mild abnormal" state, analyze which or which indicators have problems, and increase the allocation of related resources in a targeted manner, such as appropriately widening the available frequency band if the bandwidth is insufficient, and optimizing the core network's routing algorithm to reduce the number of transmission hops if the delay is too high.

[0128] After that, the data processing module can adjust the network resources of each target network slice according to the resource adjustment strategy of each target network slice.

[0129] From the above, it can be seen that the multi-source heterogeneous data fusion processing system for industry based on mobile communication provided in this embodiment can dynamically determine the real-time operating status of each target network slice based on the monitoring indicator information obtained in real time, rather than statically evaluating based on fixed rules or preset time periods. This dynamic evaluation mechanism can quickly respond to changes in the network environment, fluctuations in business traffic, and potential network failures, and promptly discover abnormal conditions or performance bottlenecks during the operation of network slices. Afterwards, according to the evaluation results of the operating status, the network resources of the network slice are adjusted immediately and flexibly. The means of adjustment include but are not limited to the dynamic allocation and reconfiguration of wireless resources (such as frequency band allocation, power adjustment, time slot scheduling, etc.) and core network resources (such as expansion or contraction of computing resources, allocation of storage resources, optimization of network routing, etc.) to adapt to the ever-changing business needs and network conditions, and ensure that each network slice is always in the best operating state.

[0130] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0131] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0132] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A multi-source heterogeneous data fusion processing system for industry based on mobile communication, characterized in that: include: A multi-source signal acquisition module, used for acquiring operating parameters of each first device in the target area, and sending each of the operating parameters to the data processing module through the fifth generation mobile communication network; a visual inspection module, configured to collect appearance image data and temperature data of each of the first devices, and send each of the appearance image data and each of the temperature data to the data processing module via the fifth-generation mobile communication network; an inspection robot, configured to travel along a set path based on the positioning technology of the fifth-generation mobile communication network, collect device data of each second device on the set path, and send each of the device data to the data processing module through the fifth-generation mobile communication network; The data processing module is used to perform network slicing processing on the fifth-generation mobile communication network to obtain multiple target network slices, and send each of the operating parameters, each of the appearance image data, each of the temperature data and each of the device data to the data analysis module through the multiple target network slices; The data analysis module is used to generate a plurality of tasks to be processed based on each of the operating parameters, each of the appearance image data, each of the temperature data and each of the device data; The plurality of tasks to be processed are processed in parallel to obtain detection results of each target device; the target device is any one of the first device and the second device.

2. The multi-source heterogeneous data fusion processing system for industry based on mobile communication according to claim 1, characterized in that: The data processing module is specifically used for: Acquiring target business information of the multi-source heterogeneous data fusion processing system for industry based on mobile communication; Performing network slicing processing on the fifth-generation mobile communication network based on the target service information to obtain a plurality of target network slices; Each of the operating parameters, each of the appearance image data, each of the temperature data, and each of the device data are sent to the data analysis module through multiple target network slices.

3. The multi-source heterogeneous data fusion processing system for industry based on mobile communication according to claim 2, characterized in that: The performing network slicing processing on the fifth-generation mobile communication network based on the target service information to obtain a plurality of the target network slices includes: Based on the target service information, each initial network slice is generated; each initial network slice carries the resource information required by the respective network slice; Based on each of the resource information, the network resources of the fifth-generation mobile communication network are allocated to each of the initial network slices to obtain each of the target network slices.

4. The multi-source heterogeneous data fusion processing system for industry based on mobile communication as claimed in claim 3, characterized in that: The generating each initial network slice based on the target service information includes: Obtain historical network demand information; Classifying the target service information based on the historical network demand information to obtain resource information corresponding to each of the initial network slices; Based on each of the resource information, each of the initial network slices is generated.

5. The multi-source heterogeneous data fusion processing system for industry based on mobile communication as claimed in claim 2, characterized in that: The sending each of the operating parameters, each of the appearance image data, each of the temperature data, and each of the device data to the data analysis module through the plurality of the target network slices includes: Determine the transmission priority of each task to be transmitted based on the target service information; Based on each of the tasks to be transmitted, each of the operating parameters, each of the appearance image data, each of the temperature data, and each of the device data is divided to obtain a first data set corresponding to each of the tasks to be transmitted; Control multiple target network slices to send each of the first data sets to the data analysis module according to the transmission priority of each of the tasks to be transmitted.

6. The multi-source heterogeneous data fusion processing system for industry based on mobile communication according to claim 2, characterized in that: The data processing module is also used for: Obtain monitoring indicator information of each of the target network slices; Determine the operating status of each of the target network slices based on the monitoring indicator information of each of the target network slices; Based on the operating status of each of the target network slices, the network resources of each of the target network slices are adjusted.

7. The multi-source heterogeneous data fusion processing system for industry based on mobile communication as claimed in claim 2, characterized in that: The data analysis module is specifically used for: Based on the target business information, each of the operating parameters, each of the appearance image data, each of the temperature data, and each of the device data are divided to obtain each of the tasks to be processed; The second data sets corresponding to each of the tasks to be processed are sequentially input into the detection models corresponding to each of the tasks to be processed for parallel processing to obtain the detection results of each of the target devices; the detection models include an anomaly detection model and a fault prediction model.

8. The multi-source heterogeneous data fusion processing system for industry based on mobile communication according to claim 1, characterized in that: The multi-source signal acquisition module specifically includes: a plurality of sets of different types of sensors and a first communication unit; Each group of the sensor sets is used to collect operating parameters corresponding to the type of the sensor set in a plurality of the first devices; The first communication unit is used to determine a data protocol that matches the sensor, encapsulate each of the operating parameters based on the data protocol, and send the first data obtained after encapsulation to the data processing module through the fifth-generation mobile communication network.

9. The multi-source heterogeneous data fusion processing system for industry based on mobile communication according to claim 1, characterized in that: The visual inspection module specifically includes: A camera unit, used for collecting appearance image data of each of the first devices; A thermal imaging unit, used to collect temperature data of each of the first devices; a protocol conversion unit, configured to determine the communication protocol of the fifth-generation mobile communication network, and if the current protocol corresponding to the visual detection module does not match the communication protocol, convert the current protocol based on the communication protocol to obtain a target protocol corresponding to the visual detection module; the target protocol is compatible with the fifth-generation mobile communication network; The second communication unit is used to encapsulate each of the appearance image data and each of the temperature data based on the target protocol, and send the second data obtained after encapsulation to the data processing module through the fifth-generation mobile communication network.

10. The multi-source heterogeneous data fusion processing system for industry based on mobile communication according to any one of claims 1 to 9, characterized in that: The multi-source heterogeneous data fusion processing system for industry based on mobile communication further includes: a human-computer interaction module; The human-computer interaction module is used to output the detection results of each of the target devices through the fifth-generation mobile communication network.

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