A multi-protocol compatible multi-data parsing method

Abstract

The application relates to the technical field of industrial equipment communication, and provides a multi-protocol compatible multi-data analysis method, which specifically comprises the following steps: determining target industrial equipment to be analyzed industrial data through an industrial server; performing transmission path identification and behavior characteristic identification on the to-be-analyzed industrial data, determining a data transmission mode and a behavior characteristic; wherein the transmission path identification is based on a preset communication path framework network, and the behavior characteristic identification is based on a preset industrial equipment behavior directory; according to the data transmission mode, determining a protocol type to which the to-be-analyzed industrial data belongs; according to the protocol type and the behavior characteristic, determining a target analysis strategy in a preset analysis database; and according to the target analysis strategy, collecting the to-be-analyzed industrial data of the industrial equipment through the industrial server to perform analysis processing, and the analysis processing is visualized data set. The application can automatically select a suitable analysis strategy according to the data transmission mode and the protocol type based on the industrial server.

Description

Technical Field

[0001] The present invention relates to the field of industrial data acquisition, and in particular to a multi-protocol compatible multi-data parsing method. Background Art

[0002] In today's Industrial Internet environment, the diversity of industrial devices and the complexity of communication protocols present significant challenges in data parsing and integration. Traditional data parsing methods often rely on dedicated parsers developed for specific protocols, which not only complicates system architecture but also significantly reduces system scalability and flexibility when faced with the coexistence of multiple protocols.

[0003] In addition, new types of industrial equipment are constantly emerging, and each device may adopt different data transmission standards and communication protocols, which further increases the difficulty of data analysis.

[0004] Patent CN202311566470.X, "A Multi-Protocol Parsing Method and System for Industrial Internet of Things," provides a multi-protocol parsing method and system for Industrial Internet of Things (IIoT) that supports parsing multiple protocol types, addressing the challenges of difficult IIoT gateway access, low parsing efficiency, and protocol expansion. Based on the Modbus TCP protocol, the system introduces a multi-protocol parsing core to represent simplified protocol features. This core represents multiple heterogeneous protocols, significantly reducing computational overhead and improving message processing and parsing efficiency, thus completing the IIoT multi-protocol device access and data parsing process. Overall, the system improves the unified formatting process for messages and data across multiple heterogeneous IIoT protocols, enhancing the capabilities of data access devices and possessing significant practical value in building smart factory data interconnection. By configuring the gateway with device information and key acquisition parameters, the system parses and processes multiple protocols, obtaining key acquisition parameters. This system enables the formatting and parsing of communication protocols and data for heterogeneous industrial devices, addressing the data acquisition challenges associated with connecting heterogeneous devices to IoT platforms.

[0005] However, it configures parsing strategies through the protocol parsing core, and cannot configure the most suitable parsing strategies and protocol switching methods based on the data of industrial equipment or IoT devices. It can only perform parsing and switching within general protocols, and cannot directly parse and convert the parsed data into a visual form. Moreover, when new protocols emerge, the parser needs to be redesigned, resulting in long maintenance and upgrade cycles, which seriously affects the efficient use and real-time analysis of industrial data. Summary of the Invention

[0006] The present invention proposes a multi-protocol compatible multi-data parsing method to solve the problem that it is impossible to configure the most suitable parsing strategy and protocol switching method according to the data of industrial equipment or Internet of Things devices. It can only perform parsing and switching within the general protocol, and cannot directly parse and convert the parsed data into a visual form. Moreover, when a new protocol appears, it is necessary to redesign the parser, resulting in a long maintenance and upgrade cycle, which seriously affects the efficient use and real-time analysis of industrial data.

[0007] The present invention proposes a multi-protocol compatible multi-data parsing method, comprising:

[0008] Determine the industrial data to be parsed of the target industrial equipment through the industrial server;

[0009] Determine the data transmission mode and behavior characteristics of the industrial data to be analyzed through transmission path identification and behavior feature identification; wherein, transmission path identification includes a preset communication path framework network, and behavior feature identification includes a preset industrial equipment behavior catalog;

[0010] Determine the protocol type to which the industrial data to be parsed belongs based on the data transmission mode;

[0011] Determine the target parsing strategy in the preset parsing database based on the protocol type and behavior characteristics;

[0012] According to the target parsing strategy, the industrial data to be parsed is converted into the target format and parsed into a visual data set.

[0013] Furthermore, the industrial server includes a first parsing and processing server and a second parsing and processing server;

[0014] The first parsing processing server is used to receive the monitoring results of the target industrial equipment, and when the monitoring results meet the preset parsing behavior, determine the target industrial equipment for the industrial data to be parsed, and generate a first parsing work order for the target industrial equipment;

[0015] The second parsing processing server is used to receive the parsing request from the management end, determine the target industrial equipment in the parsing request, and generate a second parsing work order for the target industrial equipment.

[0016] Furthermore, the first parsing processing server determines the target industrial device of the industrial data to be parsed, including the following steps:

[0017] Receive monitoring results of industrial equipment by a monitoring mechanism preset in the industrial server, determine the data behavior entropy value of each industrial equipment, and determine the behavior trend change point corresponding to the data behavior entropy value of each industrial equipment;

[0018] According to the behavioral trend change points of each industrial equipment, determine the corresponding trend change maximum and minimum values ​​of each industrial equipment;

[0019] According to the maximum and minimum trend changes corresponding to each industrial equipment, the data behavior entropy value corresponding to each industrial equipment is evaluated for distribution status and a distribution status map is determined;

[0020] According to the distribution situation map, it is judged whether each industrial equipment meets the distribution area of ​​the preset analytical behavior entropy value, and the industrial equipment that meets the distribution area of ​​the preset analytical behavior entropy value is taken as the target industrial equipment.

[0021] Furthermore, the second resolution processing server determines the target industrial device in the resolution request, including the following steps:

[0022] A list of industrial devices capable of data parsing is pre-set; the list of industrial devices includes a pre-loaded list of Class I industrial devices and a list of Class II industrial devices whose data complexity attributes fall within a preset data complexity attribute range during self-checking. Industrial devices in the Class I industrial devices list generate parsing requests through an active approval mode, while industrial devices in the Class II industrial devices list generate parsing requests through an automatic approval mode.

[0023] A target industrial device in a category of industrial device list is used to initiate a first network request;

[0024] When there is a request exception in the first network request, the target industrial equipment in the first category industrial equipment list is automatically classified into the second category industrial equipment list, and a second network request is initiated.

[0025] Furthermore, the transmission path identification includes the following steps:

[0026] Collect data logs, network configuration information, and application configuration information of the industrial data to be analyzed based on the communication path framework network;

[0027] Determine the path nodes of the transmission path of the industrial data to be parsed based on the data log;

[0028] Determine the routing path, network interface configuration information, and DNS records of the industrial data to be parsed based on the network configuration information, and determine the configuration parameters of the transmission path based on the communication transmission nodes;

[0029] Based on the application configuration information and configuration parameters, determine the proxy settings, port mapping, and protocol selection for the industrial data to be parsed, and determine the transmission path.

[0030] Furthermore, the feature recognition includes the following steps:

[0031] Based on the data log, determine the set of behavioral events of the industrial data to be analyzed in the transmission path;

[0032] According to the preset industrial equipment behavior catalog, determine whether the target behavior event in the behavior event set is in the industrial equipment behavior catalog;

[0033] When a target behavior event exists in the industrial equipment behavior directory, event information of the target behavior event is obtained;

[0034] Extract behavioral features based on event information.

[0035] Furthermore, determining the protocol type to which the industrial data to be parsed belongs based on the data transmission mode includes:

[0036] Determine the transmission protocol of the industrial data to be parsed based on the data transmission mode;

[0037] Determine the corresponding data feature interval according to the transmission protocol; wherein the data feature interval is not unique, and each data feature interval corresponds to a unique industrial data type;

[0038] According to the data feature value, traverse all data packets of the industrial data to be parsed in the target industrial equipment and determine the industrial data type corresponding to each data packet;

[0039] According to the industrial data type, determine the protocol type to which the industrial data to be parsed belongs.

[0040] Furthermore, the target parsing strategy is determined in a preset parsing database according to the protocol type and behavior characteristics;

[0041] Determine, based on the protocol type, a first parsing strategy list associated with the preset parsing database; wherein the sorting order of the first parsing strategy list is sorted according to a first priority, the first priority sorting being based on a degree of association between the protocol type and different parsing strategies in the first parsing strategy list;

[0042] Determine, based on the behavioral characteristics, a second parsing strategy list associated with the preset parsing database; wherein the sorting order of the second parsing strategy list corresponds to the alternative setting according to the first priority sorting, and the parsing strategy at each sorting position in the first priority sorting has an alternative association with the same position in the second parsing strategy list;

[0043] Constructing a dual parsing strategy for the industrial data to be parsed according to the first parsing strategy list and the second parsing strategy list;

[0044] According to the dual parsing strategy and the preset parsing database, the parsing efficiency of the same sorting position in the first parsing strategy list and the second parsing strategy list is determined, and a second priority sorting is generated;

[0045] According to the second priority sorting, the target resolution strategy is determined.

[0046] Furthermore, the analysis process includes the following steps:

[0047] According to the target parsing strategy, the data attribute code of the industrial data to be parsed is obtained;

[0048] According to the data attribute code, determine the data information field of each industrial data after parsing;

[0049] According to the data field information, the parsing result data is mapped to determine the parsing content.

[0050] Furthermore, the parsing process is to visualize the data set, including:

[0051] Obtain the data analysis results of the industrial data to be analyzed; wherein the data analysis results are connected to the corresponding visualization chart in the form of a data set;

[0052] According to the visualization chart, the data analysis results are loaded through the preset calculation strategy to generate corresponding visualization content. The beneficial effects of the present invention are:

[0053] This invention utilizes an industrial server-based data collection method, enabling closer proximity to industrial equipment and reducing network latency. Through a pre-defined communication path framework network and behavioral signature catalog, it automatically identifies transmission paths and behavioral signatures. It automatically selects appropriate parsing strategies based on data transmission mode and protocol type, eliminating the need to develop separate parsers for each protocol. The resulting visual dataset facilitates user understanding and analysis, improving data usability.

[0054] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or will be understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings.

[0055] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0057] Figure 1 FIG1 is a diagram illustrating an implementation process of a multi-protocol compatible multi-data parsing method according to an embodiment of the present invention;

[0058] Figure 2 A schematic diagram of port execution and services of an industrial server in an embodiment of the present invention;

[0059] Figure 3 This is a configuration diagram of the target resolution strategy in an embodiment of the present invention. DETAILED DESCRIPTION

[0060] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0061] like Figure 1 As shown, this embodiment provides a multi-protocol compatible multi-data parsing method, including:

[0062] Determine the industrial data to be parsed of the target industrial equipment through the industrial server;

[0063] Determine the data transmission mode and behavior characteristics of the industrial data to be analyzed through transmission path identification and behavior feature identification; wherein, transmission path identification includes a preset communication path framework network, and behavior feature identification includes a preset industrial equipment behavior catalog;

[0064] Determine the protocol type to which the industrial data to be parsed belongs based on the data transmission mode;

[0065] Determine the target parsing strategy in the preset parsing database based on the protocol type and behavior characteristics;

[0066] According to the target parsing strategy, the industrial data to be parsed is converted into the target format and parsed into a visual data set.

[0067] The principle of the above technical solution is:

[0068] During the implementation of this invention, an industrial server is configured to receive the industrial data to be parsed from the target industrial equipment. The industrial server is connected to the industrial equipment and equipped with a monitoring mechanism to monitor various behavioral events in the industrial equipment. When these events occur, data parsing is performed. The industrial server configuration includes hardware and software setup to receive and process the industrial data to be parsed from various industrial equipment. The industrial data to be parsed is then collected from the target industrial equipment and parsed in the industrial server for visual display. The industrial server is connected to the industrial equipment network and processes the data uploaded by the industrial equipment.

[0069] In traditional technologies, this needs to be achieved by using various communication protocols, such as HTTP, HTTPS, TCP / IP, etc. In addition, it is also necessary to ensure the integrity and security of the data to ensure that only authorized users can access and process the data.

[0070] In the specific implementation process of the present invention, the industrial data to be analyzed is first determined, and then the transmission path and behavioral characteristics of the industrial data to be analyzed are identified, and then it is determined how to analyze it and how to convert it into a data format that can be identified and processed by the industrial server.

[0071] In this process, transmission path identification is based on a pre-defined communication path framework network. This network model, encompassing a series of network connections and communication protocols, describes the transmission paths of industrial data between different devices. It also determines the data format of the industrial data to be parsed within the industrial devices and converts the data into a format that can be parsed and processed by the industrial server. Transmission path identification identifies the actual transmission path of the industrial data to be parsed from its source to its final destination, encompassing the data source and data transmission process, as well as all intermediate nodes and interfaces along this path. Behavioral signature identification is based on a pre-defined industrial device behavior catalog. This catalog contains behavioral models of different industrial devices, describing their behavior under different circumstances. Industrial behavior is based on data and includes both abnormal and normal behavior. Behavioral signature identification identifies the behavioral characteristics contained in the industrial data to be parsed. After determining the transmission path for the industrial data to be parsed, the protocol type of the data to be parsed is determined based on information such as the protocol and parameters within the path.

[0072] The data to be parsed is then converted into a standard, universal format or a format that can be processed by the industrial server. After determining the protocol type and behavioral characteristics of the industrial data to be parsed, the corresponding parsing strategy is searched in a pre-set parsing database.

[0073] The parsing database stores parsing rules and algorithms corresponding to different industrial devices and protocols. This allows for rapid identification of the parsing methods and algorithms for the industrial data to be parsed, as well as the protocols that the data collected from industrial devices must conform to. Once the target parsing strategy is determined, the data can be converted into a format suitable for parsing and then processed. The specific steps involved in the parsing process are determined by the user's desired outcome and include data format conversion, cleaning, analysis, and visualization.

[0074] The beneficial effects of the above technical solution are:

[0075] This invention utilizes an industrial server-based data collection method, enabling closer proximity to industrial equipment and reducing network latency. Through a pre-defined communication path framework network and behavioral signature catalog, it automatically identifies transmission paths and behavioral signatures. It automatically selects appropriate parsing strategies based on data transmission mode and protocol type, eliminating the need to develop separate parsers for each protocol. The resulting visual dataset facilitates user understanding and analysis, improving data usability.

[0076] As an embodiment of the present invention: the industrial server includes a first parsing and processing server and a second parsing and processing server;

[0077] The first parsing processing server is used to receive the monitoring results of the target industrial equipment, and when the monitoring results meet the preset parsing behavior, determine the target industrial equipment for the industrial data to be parsed, and generate a first parsing work order for the target industrial equipment;

[0078] The second parsing processing server is used to receive the parsing request from the management end, determine the target industrial equipment in the parsing request, and generate a second parsing work order for the target industrial equipment.

[0079] The principle of the above technical solution is:

[0080] like Figure 2 As shown, in actual implementation, when an industrial server receives industrial data to be parsed, its first parsing server receives the industrial data to be parsed from the target industrial device and stores it in an internal database. The first parsing server analyzes the received industrial data to be parsed and processes it using a preset parsing algorithm to identify behavioral characteristics. Preset parsing algorithms include convolutional neural networks based on deep learning features, scale-invariant feature transformation models, or oriented gradient histograms.

[0081] If the monitoring results of the industrial data to be parsed meet the preset parsing behavior, the first parsing processing server will pass this data to the second parsing processing server. Based on the identified behavioral characteristics, the first parsing processing server will search for the corresponding parsing rules in the preset industrial equipment behavior directory, and determine the name and model of the target industrial equipment based on these rules, configure the corresponding parsing code, and the storage area for the parsed data. The first parsing processing server will then generate a first parsing work order for the target industrial equipment and return it to the requester. In actual implementation, the first parsing processing server can visualize the generated first parsing work order for the target industrial equipment and present it to the management end in the form of a chart or text.

[0082] Receiving a parsing request, which is an external command, parses the administrator's selected industrial data based on the external command. The second parsing server receives a parsing request from the administrator, which includes information such as the name and model of the target industrial device to be parsed. Determining the target industrial device: The second parsing server queries its database for relevant information and uses a pre-set parsing algorithm to determine the name and model of the target industrial device. If the target industrial device has been determined, the second parsing server generates a second parsing work order for the target industrial device and returns it to the requester. Otherwise, it notifies the requester that more information is needed to determine the target industrial device.

[0083] The beneficial effects of the above technical solution are:

[0084] Through the above solution, the present invention can perform parsing processing for different industrial equipment by setting different parsing work orders.

[0085] As an embodiment of the present invention, the first parsing processing server determines the target industrial device of the industrial data to be parsed, including the following steps:

[0086] Receive monitoring results of industrial equipment by a monitoring mechanism preset in the industrial server, determine the data behavior entropy value of each industrial equipment, and determine the behavior trend change point corresponding to the data behavior entropy value of each industrial equipment;

[0087] According to the behavioral trend change points of each industrial equipment, determine the corresponding trend change maximum and minimum values ​​of each industrial equipment;

[0088] According to the maximum and minimum trend changes corresponding to each industrial equipment, the data behavior entropy value corresponding to each industrial equipment is evaluated for distribution status and a distribution status map is determined;

[0089] According to the distribution situation map, it is judged whether each industrial equipment meets the distribution area of ​​the preset analytical behavior entropy value, and the industrial equipment that meets the distribution area of ​​the preset analytical behavior entropy value is taken as the target industrial equipment.

[0090] The principle of the above technical solution is:

[0091] In actual implementation, behavioral analysis is performed on industrial equipment data to determine the data behavioral entropy value and corresponding behavioral trend change points for each device. Data behavioral entropy refers to the sum of the frequency and probability of occurrence of each value corresponding to different data behaviors in a dataset. A behavioral trend change point refers to the corresponding point in the trend of change for each value of different data behaviors in a dataset. When a trend change point occurs, a behavioral event occurs at that time or in that portion of the data. The specific entropy value determines the behavioral event. Data behavioral entropy values ​​and behavioral trend change points have maximum and minimum trend change values, representing the behavioral interval during the data behavior generation process. Based on the identified behavioral trend change points, the maximum and minimum trend change values ​​for each industrial device are calculated. The data variation range and magnitude of each device are then measured based on these maximum and minimum trend change values. The data behavioral entropy values ​​for each industrial device are then evaluated for distribution and a distribution trend map is plotted. The distribution trend map is a visualization tool used to intuitively understand the distribution and overall trend of the data behavioral entropy values ​​for industrial equipment, thereby identifying specific data behavioral information. The distribution situation map can be drawn according to different colors, line densities, etc. to highlight abnormal points and obvious trend changes.

[0092] The beneficial effects of the above technical solution are:

[0093] The first analysis and processing server of the present invention can determine the industrial equipment with significant data changes, thereby determining the corresponding industrial equipment and the behavioral events generated by the corresponding industrial equipment.

[0094] As an embodiment of the present invention, the second resolution processing server determines the target industrial device in the resolution request, including the following steps:

[0095] A list of industrial devices capable of data parsing is pre-set; the list of industrial devices includes a pre-loaded list of Class I industrial devices and a list of Class II industrial devices whose data complexity attributes fall within a preset data complexity attribute range during self-checking. Industrial devices in the Class I industrial devices list generate parsing requests through an active approval mode, while industrial devices in the Class II industrial devices list generate parsing requests through an automatic approval mode.

[0096] A target industrial device in a category of industrial device list is used to initiate a first network request;

[0097] When there is a request exception in the first network request, the target industrial equipment in the first category industrial equipment list is automatically classified into the second category industrial equipment list, and a second network request is initiated.

[0098] The principle of the above technical solution is:

[0099] In the actual implementation of the present invention, the industrial equipment list includes some commonly used industrial equipment types and models, and should also include some specific types of equipment. For example, a pre-loaded industrial equipment list may include common industrial equipment types, such as PLC, DCS, SCADA system, etc.

[0100] During the self-check process, the list of Category 2 industrial equipment with data complexity attributes within the preset data complexity attribute range includes some relatively complex equipment types, such as robots, drones, and smart factories. For some common equipment types, manual approval is used to send parsing requests; for some more complex equipment types, automatic approval is used to send parsing requests.

[0101] In addition, some specific resolution request priorities can also be set. For example, for critical equipment or equipment in emergency situations, a higher resolution request priority can be set. During the sending of the resolution request, the response of the industrial equipment needs to be monitored and tracked. If after sending the resolution request, the device has an abnormal response, such as request timeout, incomplete returned data, unable to resolve, etc., it is necessary to take corresponding measures, such as resending the resolution request, notifying relevant personnel for maintenance, etc. At the same time, different resolution strategies need to be adopted according to the different types of equipment. In the present invention, when the first resolution request is issued, if the device fails to respond normally or the resolution fails, the resolution strategy will be triggered, so that the industrial equipment will automatically be classified as a Class II industrial equipment list and the resolution request will be re-initiated.

[0102] The beneficial effects of the above technical solution are:

[0103] The present invention can use different resolution strategies for different resolution requests. If there is a resolution request that cannot be responded to, it will switch to a channel for automatic resolution processing for processing.

[0104] As an embodiment of the present invention, the transmission path identification includes the following steps:

[0105] Collect data logs, network configuration information, and application configuration information of the industrial data to be analyzed based on the communication path framework network;

[0106] Determine the path nodes of the transmission path of the industrial data to be parsed based on the data log;

[0107] Determine the routing path, network interface configuration information, and DNS records of the industrial data to be parsed based on the network configuration information, and determine the configuration parameters of the transmission path based on the communication transmission nodes;

[0108] Based on the application configuration information and configuration parameters, determine the proxy settings, port mapping, and protocol selection for the industrial data to be parsed, and determine the transmission path.

[0109] The principle of the above technical solution is:

[0110] In the specific implementation process, in the transmission path identification stage, the existing communication path framework network is used to obtain and analyze relevant data logs, network configuration information and application configuration information.

[0111] Next, data logs are used to identify the nodes along the transmission path of the industrial data to be parsed. This involves identifying all nodes that the data passes through during transmission and recording their locations and order. The specific locations of the nodes along the industrial data transmission path are represented using methods such as network topology diagrams. Furthermore, network configuration information is used to determine the routing path, network interface configuration information, and DNS records for the industrial data to be parsed. The configuration parameters of the transmission path are determined based on the communication transmission nodes. Configuration parameters typically include network addresses, port numbers, encryption algorithms, cache settings, and other factors, which influence the behavior and characteristics of the data during transmission.

[0112] Finally, the application configuration information and configuration parameters are used to determine the proxy settings, port mapping, and protocol selection for the industrial data to be parsed, and ultimately determine the transmission path.

[0113] The beneficial effects of the above technical solution are:

[0114] In the process of transmission path identification, the present invention can more quickly and accurately parse the corresponding data to be transmitted by obtaining configuration parameters such as network configuration information and application configuration information.

[0115] As an embodiment of the present invention, the feature recognition includes the following steps:

[0116] Based on the data log, determine the set of behavioral events of the industrial data to be analyzed in the transmission path;

[0117] According to the preset industrial equipment behavior catalog, determine whether the target behavior event in the behavior event set is in the industrial equipment behavior catalog;

[0118] When a target behavior event exists in the industrial equipment behavior directory, event information of the target behavior event is obtained;

[0119] Extract behavioral features based on event information.

[0120] The principle of the above technical solution is:

[0121] In the specific implementation process of the present invention, in the feature recognition stage, existing data logs are used to determine the set of behavioral events in the transmission path of the industrial data to be analyzed. It is necessary to find the behavioral events that occur during the data transmission process, classify them, and organize them.

[0122] Based on a preset industrial equipment behavior catalog, the system determines whether the target behavior event exists within the set of behavior events. This allows the system to quickly locate the target behavior event within the industrial data being analyzed, reducing the workload for subsequent feature extraction. If the behavior event already exists in the behavior catalog, its relevant information can be directly retrieved; otherwise, it must be re-extracted and recalculated.

[0123] Once a behavioral event has been identified, behavioral features can be extracted based on the event information. Behavioral features describe the behavior and status of industrial equipment and can be obtained through analysis and processing of event information. For example, behavioral features can be extracted based on factors such as the duration, frequency, and intensity of an industrial event. They can also be extracted based on the event's context, such as the time, location, and participants involved in the event.

[0124] The beneficial effects of the above technical solution are:

[0125] In the process of identifying the behavioral characteristics of industrial equipment, the present invention can identify event information of industrial data with analysis during transmission and determine the behavioral characteristics, so as to more accurately configure the analysis strategy corresponding to the behavioral characteristics.

[0126] As an embodiment of the present invention, determining the protocol type to which the industrial data to be parsed belongs according to the data transmission mode includes:

[0127] Determine the transmission protocol of the industrial data to be parsed based on the data transmission mode;

[0128] Determine the corresponding data feature interval according to the transmission protocol; wherein the data feature interval is not unique, and each data feature interval corresponds to a unique industrial data type;

[0129] According to the data feature value, traverse all data packets of the industrial data to be parsed in the target industrial equipment and determine the industrial data type corresponding to each data packet;

[0130] Determine the protocol type of the industrial data to be parsed based on the industrial data type.

[0131] The principle of the above technical solution is:

[0132] In the actual implementation of the present invention, the transmission protocol refers to the protocol type followed by data transmission in the network. Different transmission protocols have different data feature intervals and feature value ranges. Therefore, the transmission protocol of the industrial data to be analyzed needs to be determined based on the transmission mode.

[0133] That is, if it is determined that the data is transmitted over a specific network, such as the HTTP or MQTT protocol, the transmission protocol can be determined based on the characteristics of the network. For example, the HTTP protocol is commonly used for request responses in web browsers, while the MQTT protocol is often used for data transmission in IoT applications. The data feature interval refers to the range of values ​​of data feature values, which is closely related to the transmission protocol. Different transmission protocols correspond to different data feature intervals, so the corresponding data feature interval needs to be determined based on the transmission protocol. For example, if the data to be parsed is transmitted via the HTTP protocol, the data feature interval may include the request header, response header, body, and other content. For data transmitted via the MQTT protocol, the data feature interval may only include the Topic and Payload features of the message.

[0134] Then, all data packets in the target industrial device are traversed, and the industrial data type to which they belong is determined based on the data feature values ​​of each data packet. This process can be achieved by pre-configuring a traversal listener, which reads all data packets from the target industrial device, then processes each data packet, extracts its data feature values, and compares them with the parsing database. If a matching data feature value is found, it indicates that the corresponding data packet belongs to the corresponding industrial data type. After determining the transmission protocol and data feature interval of the industrial data to be parsed, the protocol type to which the industrial data to be parsed belongs is determined based on its corresponding feature value range. For example, if the feature interval of the industrial data to be parsed is only related to the HTTP protocol, then it belongs to the HTTP protocol type data. Conversely, if the feature interval of the industrial data to be parsed is associated with multiple protocols, then it belongs to the general protocol type data.

[0135] The beneficial effects of the above technical solution are:

[0136] The present invention can perform different parsing processes on different industrial data to be parsed by determining the protocol type of the industrial data to be parsed.

[0137] As an embodiment of the present invention: the target parsing strategy is determined in a preset parsing database according to the protocol type and behavior characteristics;

[0138] Determine, based on the protocol type, a first parsing strategy list associated with the preset parsing database; wherein the sorting order of the first parsing strategy list is sorted according to a first priority, the first priority sorting being based on a degree of association between the protocol type and different parsing strategies in the first parsing strategy list;

[0139] Determine, based on the behavioral characteristics, a second parsing strategy list associated with the preset parsing database; wherein the sorting order of the second parsing strategy list corresponds to the alternative setting according to the first priority sorting, and the parsing strategy at each sorting position in the first priority sorting has an alternative association with the same position in the second parsing strategy list;

[0140] Constructing a dual parsing strategy for the industrial data to be parsed according to the first parsing strategy list and the second parsing strategy list;

[0141] According to the dual parsing strategy and the preset parsing database, the parsing efficiency of the same sorting position in the first parsing strategy list and the second parsing strategy list is determined, and a second priority sorting is generated;

[0142] According to the second priority sorting, the target resolution strategy is determined.

[0143] The principle of the above technical solution is:

[0144] like Figure 3 As shown, in actual implementation, the corresponding target parsing strategy is found in a pre-set parsing database based on the protocol type and behavioral characteristics. The parsing database contains information on various parsing strategies for different protocol types and behavioral characteristics. Based on the protocol type, the associated first parsing strategy list is found in the parsing database and then sorted. The sorting principle is typically based on the first priority level, meaning that the higher the parsing strategy, the higher the priority. Furthermore, the parsing strategy at each ranking position in the first priority ranking has an alternative relationship with the same position in the second parsing strategy list. Based on the behavioral characteristics, the associated second parsing strategy list in the pre-set parsing database is then determined. Similarly, the list is sorted, typically based on the first priority ranking corresponding to the alternative setting, meaning that the parsing strategy at each ranking position in the first priority ranking has an alternative relationship with the same position in the second parsing strategy list. With the first and second parsing strategy lists, a dual parsing strategy can be established for the industrial data to be parsed. This dual parsing strategy allows the same data to be analyzed using different parsing methods based on data type and event characteristics, resulting in parsing results, when the first parsing strategy is unresponsive or ineffective.

[0145] The beneficial effects of the above technical solution are:

[0146] The present invention can use a dual parsing strategy to automatically switch the parsing strategy corresponding to the protocol type or the parsing strategy corresponding to the event feature according to adaptability and priority for the industrial data to be parsed.

[0147] As an embodiment of the present invention, the parsing process includes the following steps:

[0148] According to the target parsing strategy, the data attribute code of the industrial data to be parsed is obtained;

[0149] According to the data attribute code, determine the data information field of each industrial data after parsing;

[0150] According to the data field information, the parsing result data is mapped to determine the parsing content.

[0151] The principle of the above technical solution is:

[0152] During implementation, the parsing strategy is associated with the data, encoding the information described by the parsing strategy into the data. For example, if the parsing strategy specifies a specific data format, this format must be encoded into the data. The data attribute encodings are then mapped back to the fields in the industrial data to ensure that all data can be parsed correctly. Finally, the parsed data is matched with the corresponding industrial data fields to obtain the final parsing results. This process typically includes operations such as data conversion, cleaning, and summarization.

[0153] As an embodiment of the present invention, the parsing process is a visualization data set, including:

[0154] Obtain the data analysis results of the industrial data to be analyzed; wherein the data analysis results are connected to the corresponding visualization chart in the form of a data set;

[0155] According to the visualization chart, the data analysis results are loaded through the preset calculation strategy to generate the corresponding visualization content.

[0156] The principle of the above technical solution is:

[0157] In practice, data analysis results typically require processing the raw data according to the target analysis strategy to produce more readable results. The results are presented in the form of tables, graphs, or text. This process organizes the data into a logically connected, easy-to-understand set. Visualization conversion is then achieved using a pre-defined calculation strategy, which is a set of pre-defined algorithms or rules used to transform the data analysis results into visual charts.

[0158] The beneficial effects of the above technical solution are:

[0159] The above methods improve the readability and comprehensibility of data analysis results. Because all results are organized and displayed according to unified specifications and standards, manual intervention can also be reduced.

[0160] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. A multi-protocol compatible multi-data parsing method, characterized in that: include: Determine the industrial data to be parsed of the target industrial equipment through the industrial server; Determine the data transmission mode and behavior characteristics of the industrial data to be analyzed through transmission path identification and behavior feature identification; wherein, transmission path identification includes a preset communication path framework network, and behavior feature identification includes a preset industrial equipment behavior catalog; Determine the protocol type to which the industrial data to be parsed belongs based on the data transmission mode; Determine the target parsing strategy in the preset parsing database based on the protocol type and behavior characteristics; According to the target parsing strategy, the industrial data to be parsed is converted into a target format and parsed into a visual data set; wherein, the target parsing strategy is determined in a preset parsing database according to the protocol type and behavior characteristics, including: Determine, based on the protocol type, a first parsing strategy list associated with the preset parsing database; wherein the sorting order of the first parsing strategy list is sorted according to a first priority, the first priority sorting being based on a degree of association between the protocol type and different parsing strategies in the first parsing strategy list; Determine, based on the behavioral characteristics, a second parsing strategy list associated with the preset parsing database; wherein the sorting order of the second parsing strategy list corresponds to the alternative setting according to the first priority sorting, and the parsing strategy at each sorting position in the first priority sorting has an alternative association with the same position in the second parsing strategy list; Constructing a dual parsing strategy for the industrial data to be parsed according to the first parsing strategy list and the second parsing strategy list; According to the dual parsing strategy and the preset parsing database, the parsing efficiency of the same sorting position in the first parsing strategy list and the second parsing strategy list is determined, and a second priority sorting is generated; According to the second priority sorting, the target resolution strategy is determined.

2. The multi-protocol compatible multi-data parsing method according to claim 1, wherein: The industrial server includes a first parsing and processing server and a second parsing and processing server; The first parsing processing server is used to receive the monitoring results of the target industrial equipment, and when the monitoring results meet the preset parsing behavior, determine the target industrial equipment for the industrial data to be parsed, and generate a first parsing work order for the target industrial equipment; The second parsing processing server is used to receive the parsing request from the management end, determine the target industrial equipment in the parsing request, and generate a second parsing work order for the target industrial equipment.

3. The multi-protocol compatible multi-data parsing method according to claim 2, characterized in that: The first parsing processing server determines the target industrial device for the industrial data to be parsed, including the following steps: Receive monitoring results of industrial equipment by a monitoring mechanism preset in the industrial server, determine the data behavior entropy value of each industrial equipment, and determine the behavior trend change point corresponding to the data behavior entropy value of each industrial equipment; According to the behavioral trend change points of each industrial equipment, determine the corresponding trend change maximum and minimum values ​​of each industrial equipment; According to the maximum and minimum trend changes corresponding to each industrial equipment, the data behavior entropy value corresponding to each industrial equipment is evaluated for distribution status and a distribution status map is determined; According to the distribution situation map, it is judged whether each industrial equipment meets the distribution area of ​​the preset analytical behavior entropy value, and the industrial equipment that meets the distribution area of ​​the preset analytical behavior entropy value is taken as the target industrial equipment.

4. The multi-protocol compatible multi-data parsing method according to claim 2, wherein: The second parsing processing server determines the target industrial device in the parsing request, including the following steps: A list of industrial devices capable of data parsing is pre-set; the list of industrial devices includes a pre-loaded list of Class I industrial devices and a list of Class II industrial devices whose data complexity attributes fall within a preset data complexity attribute range during self-checking. Industrial devices in the Class I industrial devices list generate parsing requests through an active approval mode, while industrial devices in the Class II industrial devices list generate parsing requests through an automatic approval mode. A target industrial device in a category of industrial device list is used to initiate a first network request; When there is a request exception in the first network request, the target industrial equipment in the first category industrial equipment list is automatically classified into the second category industrial equipment list, and a second network request is initiated.

5. The multi-protocol compatible multi-data parsing method according to claim 1, wherein: The transmission path identification comprises the following steps: Collect data logs, network configuration information, and application configuration information of the industrial data to be analyzed based on the communication path framework network; Determine the path nodes of the transmission path of the industrial data to be parsed based on the data log; Determine the routing path, network interface configuration information, and DNS records of the industrial data to be parsed based on the network configuration information, and determine the configuration parameters of the transmission path based on the communication transmission nodes; Based on the application configuration information and configuration parameters, determine the proxy settings, port mapping, and protocol selection for the industrial data to be parsed, and determine the transmission path.

6. The multi-protocol compatible multi-data parsing method according to claim 5, characterized in that: The behavioral feature recognition includes the following steps: Based on the data log, determine the set of behavioral events of the industrial data to be analyzed in the transmission path; According to the preset industrial equipment behavior catalog, determine whether the target behavior event in the behavior event set is in the industrial equipment behavior catalog; When a target behavior event exists in the industrial equipment behavior directory, event information of the target behavior event is obtained; Extract behavioral features based on event information.

7. The multi-protocol compatible multi-data parsing method according to claim 1, wherein: Determining the protocol type to which the industrial data to be parsed belongs based on the data transmission mode includes: Determine the transmission protocol of the industrial data to be parsed based on the data transmission mode; Determine the corresponding data feature interval according to the transmission protocol; wherein the data feature interval is not unique, and each data feature interval corresponds to a unique industrial data type; According to the data feature value, traverse all data packets of the industrial data to be parsed in the target industrial equipment and determine the industrial data type corresponding to each data packet; According to the industrial data type, determine the protocol type to which the industrial data to be parsed belongs.

8. The multi-protocol compatible multi-data parsing method according to claim 1, wherein: The analysis process includes the following steps: According to the target parsing strategy, the data attribute code of the industrial data to be parsed is obtained; According to the data attribute code, determine the data information field of each industrial data after parsing; According to the data field information, the parsing result data is mapped to determine the parsing content.

9. The multi-protocol compatible multi-data parsing method according to claim 1, wherein: The analysis process is to visualize the data set, including: Obtain the data analysis results of the industrial data to be analyzed; wherein the data analysis results are connected to the corresponding visualization chart in the form of a data set; According to the visualization chart, the data analysis results are loaded through the preset calculation strategy to generate the corresponding visualization content.

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