Cross-platform data real-time monitoring and intelligent analysis method and system

Abstract

The invention relates to the technical field of data monitoring, in particular to a cross-platform data real-time monitoring and intelligent analysis method and system.The method comprises the following steps that a field structure and a protocol sequence are obtained, an offset state is calibrated, channel numbers and continuous number fragments are extracted according to offset information, and path field positions are mapped in combination with source fragments; and analyzing a field calling sequence and a processing state according to the path mapping, comparing a coverage relationship between the task field and the path field, and outputting task state information. According to the method, the offset correlation between the field number and the structure position is constructed, the field difference state is calibrated, continuous numbering sections are divided to form source fragments, the corresponding relation between the field range and the path position is established, and the coverage comparison and difference extraction of the task field and the path field are completed in combination with the state information; field adaptation elasticity and path number relevance are enhanced, path logic connection is maintained in a multi-channel and structure change scene, and dynamic judgment of a task state is supported.

Description

Technical Field

[0001] This invention relates to the field of data monitoring technology, and in particular to cross-platform real-time data monitoring and intelligent analysis methods and systems. Background Technology

[0002] The field of data monitoring technology involves real-time acquisition, unified standard conversion, high-speed transmission, and structured processing of data from diverse sources. Core aspects include multi-source data access methods, data protocol compatibility strategies, data format parsing and normalization, streaming data caching mechanisms, continuous data verification processes, and graphical presentation methods for results. This technology typically employs middleware-based data adaptation solutions. It sets rules for format mapping and field verification of incoming data, uses network transmission protocols for asynchronous data push, and uses scheduled tasks in the background service to aggregate and segment the received data. Finally, it uses a timed trigger mechanism to complete data display and alarm response. Traditional cross-platform real-time data monitoring... Monitoring and intelligent analysis methods refer to technical solutions for the unified processing and analysis of data from different operating systems or hardware architecture platforms. They mainly address technical issues such as inconsistent communication protocols between platforms, inconsistent data formats, and difficulties in coordinating data processing workflows. Traditional methods typically use fixed-format configuration files to map data structures, rely on script-driven polling mechanisms to periodically read the content of the target data source, and perform field-level data entry processing through predefined database table structures. In the analysis phase, they often use single-threaded processing logic or time-window-based batch reading methods to perform rule filtering and logical judgment on the data. They use embedded scripting languages ​​to render visual graphical interfaces to present the analysis results.

[0003] Existing technologies rely on static configuration files for field structure mapping. When field structures change dynamically or channel structures shift, it is difficult to establish a direct correspondence between fields and task paths. This leads to ambiguity in field processing order, limited path mapping capabilities, and an inability to dynamically adjust the path structure based on field status changes during execution. Furthermore, there is a lack of means to identify differences between task fields and path fields, making it difficult for processing logic to cover all task requirements. Especially when multiple channels transmit in parallel with different field orders, problems such as field mismatch, chaotic path calls, and misjudgment of task status can easily occur, restricting the accuracy and response efficiency of the overall processing. Summary of the Invention

[0004] To address the technical problems existing in the prior art, embodiments of the present invention provide a cross-platform real-time data monitoring and intelligent analysis method; To achieve the above objectives, the present invention adopts the following technical solution: a cross-platform real-time data monitoring and intelligent analysis method, comprising the following steps: S1: Obtain the field structure information and protocol identifier content from the source channel, extract the protocol field order and compare the corresponding positions of the fields in the structure, identify the field numbers of misaligned fields, locate the field status information list, and obtain the field offset status registration table. S2: Based on the field offset status registration table, extract the channel number and field sequence number corresponding to the field, analyze the consecutive numbered segments in the sequence, split the field segments according to the source number, and obtain the source field number segment information; S3: Based on the field range in the source field number fragment information, extract the task path field number, locate the path field position corresponding to the duplicate number, and map the path position to obtain the path field number corresponding information table; S4: Based on the path field number corresponding information table, read the configuration content of the path where the associated field is located in the task scheduling table, identify the calling order of the field in the path and locate the field order, and obtain the path field data processing status table. S5: Based on the path field data processing status table, compare the task field with the path field number, determine whether the path field number covers the task field number, and obtain the task status information.

[0005] As a further embodiment of the present invention, the field offset status registration table includes an offset field number set, a field order difference identifier, and a channel field status identifier; the source field number fragment information includes a fragment source identifier, a field number start and end range, and a number continuation segment feature; the path field number corresponding information table includes a path field positioning number, a cross-number mapping relationship, and a path structure field association item; the path field data processing status table includes a field processing sequence number, a field scheduling and allocation identifier, and a path participation sequence item; and the task status information includes a task field coverage status, a path execution integrity identifier, and a field difference set feature.

[0006] As a further aspect of the present invention, the protocol field order refers to the proper order in which the fields in the data structure are arranged according to the protocol definition; The field status information list refers to a table used to register the field position offset status.

[0007] As a further aspect of the present invention, the task scheduling table refers to a configuration table for the allocation and execution order of management fields in the path; The configuration content of the path refers to the structure and order information of the description fields in the task path.

[0008] As a further aspect of the present invention, the specific steps of S1 are as follows: S101: Obtain the field header information and transmission structure format identifier from the source data channel, extract the field index and field length parameters from the structure format, compare the field order with the defined order position in the structure, and obtain the field order offset comparison group; S102: Based on the offset field index and corresponding channel number in the field order offset comparison group, extract adjacent field items in the channel field set, determine whether adjacent field items have consecutive offsets, and obtain a continuous offset field mapping set; S103: Based on the field index and channel number in the continuous offset field mapping set, extract the field and channel positions that have undergone sequential offset, analyze the corresponding field number and channel information, and obtain the field offset status registration table.

[0009] As a further aspect of the present invention, the specific steps of S2 are as follows: S201: Based on the field number information in the field offset status registration table, identify the data channel number and structural position index corresponding to the field, compare the preceding and following relationships of the field numbers in the same channel, identify field groups with consecutive indices, and obtain the field consecutive numbering segment information; S202: Based on the field grouping information in the continuous numbering segment information of the field, analyze the source identifier of the field in the channel, determine the order of the differentiated source identifier fields in the structure, divide the field segment range corresponding to the source identifier, and obtain the source field sequence distribution content; S203: Based on the range of field segments in the source field sequence distribution content, analyze the start and end position range of the field segments in the channel structure, compare the structural position separation between source field segments, and obtain source field number segment information.

[0010] As a further aspect of the present invention, the specific steps of S3 are as follows: S301: Based on the field number range in the source field number fragment information, filter the appearance status of the number in the task path field list within the field range, compare whether the number range overlaps with the number in the path field, and obtain a list of number intersection segments. S302: Based on each number in the numbered cross segment list, locate the field index position in the corresponding task path structure, and map the cross number to the field position in the path structure to obtain the field path position correspondence table. S303: Based on the mapping content in the field path location correspondence table, connect the cross-information of the docking number with the field position in the task path structure, specify the position of the field in the path structure, and obtain the path field number correspondence information table.

[0011] As a further aspect of the present invention, the specific steps of S4 are as follows: S401: Based on the set of field numbers in the path field number corresponding information table and the task path index value, and filtering the belonging position of the field number under the task path from the task scheduling table, the field path belonging dataset is obtained according to the mapping relationship between the field number and the path index value. S402: Based on the path attribution information of the field numbers in the field path attribution dataset, analyze the range of the field's position in the path sequence, and compare the order of the fields appearing in the path to obtain the field path sequence relationship table. S403: Based on the field path sequence relationship table, compare the position of each field in the path sequence and verify the order, synchronize the path index information, and obtain the path field data processing status table.

[0012] As a further aspect of the present invention, the specific steps of S5 are as follows: S501: Based on the field numbers in the path field data processing status table and the task path information, extract the field numbers in the path field data processing status table, compare the status of the corresponding fields in the task path information, and obtain the path missing field number set. S502: Based on the field numbers in the path missing field number set, match them with the corresponding numbers in the task field number set, and retain the number of field numbers not covered by the path field set to obtain the path number coverage status; S503: Based on the path number coverage status, read the correspondence between the task field number set and the path field set, determine whether the path is in a completed state, and obtain the task status information.

[0013] A cross-platform real-time data monitoring and intelligent analysis system includes: The field structure extraction module obtains the field structure information and protocol identifier content from the source channel, extracts the protocol field order and compares the corresponding positions of the fields in the structure, identifies the field numbers of misaligned fields, and locates them in the field status information list to obtain the field offset status registration table. The field fragment decomposition module extracts the corresponding channel and field sequence number of the field based on the field number in the field offset status registration table, analyzes the consecutively numbered segments in the sequence, and splits the field fragments according to the source number to obtain the source field number fragment information. The path field mapping module extracts the task path field number based on the field number range in the source field number fragment information, locates the path field position corresponding to the duplicate number, and maps the path position to obtain the path field number corresponding information table. The field order positioning module reads the configuration content of the path where the associated field is located in the task scheduling table based on the field number and path identifier in the path field number corresponding information table, identifies the order of field calls in the path and locates the field order, and obtains the path field data processing status table. The task execution determination module compares the task field with the path task information based on the field number in the path field data processing status table, determines whether the path field number covers the task field number, and obtains the task status information.

[0014] Compared with the prior art, the advantages and positive effects of the present invention are as follows: In this invention, by constructing an offset association between field number and structural position, the field difference status is marked, continuous numbered segments are divided to form source fragments, and the correspondence between field range and path position is established. Combined with status information, the coverage comparison and difference extraction of task fields and path fields are completed, enhancing the field adaptation flexibility and path number association, maintaining the path logic connection in multi-channel and structural change scenarios, and supporting the dynamic judgment of task status. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a schematic diagram of the steps of the present invention; Figure 2 This is a detailed schematic diagram of S1 of the present invention; Figure 3 This is a detailed schematic diagram of S2 of the present invention; Figure 4 This is a detailed schematic diagram of S3 of the present invention; Figure 5 This is a detailed schematic diagram of S4 of the present invention; Figure 6 This is a detailed schematic diagram of S5 of the present invention; Figure 7 This is a system module diagram of the present invention. Detailed Implementation

[0017] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0018] In embodiments of the present invention, words such as "exemplarily," "for example," etc., are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one.

[0019] In the embodiments of this invention, the terms "image" and "picture" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning. Similarly, the terms "of," "corresponding (relevant)," and "corresponding" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning.

[0020] In this embodiment of the invention, sometimes a subscript such as W1 may be written in a non-subscript form such as W1. When the difference is not emphasized, the meaning they express is the same.

[0021] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0022] Please see Figure 1 This invention provides a cross-platform real-time data monitoring and intelligent analysis method, including the following steps: S1: Obtain the header information and transmission structure format identifier of the data channel from the source, extract the protocol field and source identifier field and compare their positions, determine the offset of the field content in the structure based on the difference in field order, and map the field number with the order difference to the channel field status table to obtain the field offset status registration table. S2: Based on the field number information in the field offset status registration table, extract the channel number and number sequence of the field, analyze the position between the continuous area of ​​the number arrangement and the start and end positions of the field, divide the field number segment according to the source of the field, and obtain the source field number segment information; S3: Based on the field number range in the source field number fragment information, extract the list of field numbers required for the current task path, compare the number intersection segments, point the intersection numbers to the corresponding field positions in the task path structure, and obtain the path field number corresponding information table; S4: Based on the field number and task path information in the path field number corresponding information table, read the allocation of the associated field number in the task scheduling table, parse the participation sequence of the field number in the path, align the field number with the order in the path, and obtain the path field data processing status table. S5: Based on the field numbers and task path information in the path field data processing status table, extract the difference between the task field number set and the path execution field set, analyze whether the path field set covers the numbers in the task field number set, determine whether the path is in a completed state, and obtain the task status information.

[0023] The field offset status registration table includes the offset field number set, field order difference identifier, and channel field status identifier. The source field number fragment information includes the fragment source identifier, field number start and end range, and number continuation segment characteristics. The path field number corresponding information table includes the path field location number, cross number mapping relationship, and path structure field association items. The path field data processing status table includes the field processing sequence number, field scheduling and allocation identifier, and path participation sequence item. The task status information includes the task field coverage status, path execution integrity identifier, and field difference set characteristics.

[0024] Please see Figure 2 The specific steps of S1 are as follows: S101: Obtain the field header information and transmission structure format identifier from the source data channel, extract the field index and field length parameters from the structure format, compare the field order with the defined order position in the structure, and obtain the field order offset comparison group; First, the data header area is read byte-by-byte from the data channel. The start flag and field descriptor information used to identify the field headers are extracted. The start flag is used as a marker condition for field extraction. The field descriptor is parsed into field name, field type, and unit length information. The format identifier field is read to obtain the number of fields and the encoding format and arrangement order of each field. This step can be performed using fixed-length flags. For example, in a communication message, the first 8 bytes are defined as the field header information area, the first two bytes are the flag code, and the following 6 bytes are the field definition descriptor, where each two bytes represent the field name number, field type number, and field unit length, respectively. When reading fields with this structure format... The number of fields is determined by the first two bytes. For example, if the number of fields is 4, the subsequent data reads the field information in the order defined by the fields. Each field occupies a unit length byte. If the unit length is 3 bytes, the reading step of the field in the data body is 3 bytes. By recording this information, the field index and length parameter can be obtained. Then, the offset of the field data area in the data body is calculated. By calculating whether the starting position of each field in the data is consistent with the position defined in the structure format, if the first field is defined as the first position, but is actually located in the third position in the data, its offset is recorded as +2 positions. In this way, the difference between the actual position and the standard defined position of all fields is obtained, and the field order offset comparison group is obtained.

[0025] S102: Based on the offset field index and corresponding channel number in the field order offset comparison group, extract adjacent field items in the channel field set, determine whether adjacent field items have consecutive offsets, and obtain the continuous offset field mapping set; First, it's necessary to perform a mapping process between the field index and channel number for each field item in the group. The offset information of each field is then categorized and organized according to the channel number. In this process, there are two channel numbers, 1 and 2, and the field numbers in each channel are field 1, field 2, field 3, etc., with corresponding offset values ​​of field 1: +1, field 2: +2, field 3: -1, etc. By traversing the field index, a channel field set is constructed according to the channel number. Then, the field items in the channel field set are sorted in ascending order according to their original field index. The sorted text... The segments are paired to extract adjacent field pairs, such as field 1 and field 2, field 2 and field 3, etc. For each pair of fields, the offset difference is calculated to determine whether they meet the continuous offset feature. The judgment criteria are that the absolute value of the difference is 1 or a fixed threshold. In this scenario, the continuous offset judgment threshold is set to 1. When the offset value of field 1 is +1 and field 2 is +2, the difference value is 1, which meets the condition. When field 2 is +2 and field 3 is -1, the difference value is 3, which does not meet the condition. The field pairs that meet the conditions are retained through the above judgment, and finally the continuous offset field mapping set is obtained.

[0026] S103: Based on the field index and channel number in the continuous offset field mapping set, extract the field and channel positions that have undergone sequential offset, analyze the corresponding field number and channel information, and obtain the field offset status registration table; First, the field index of each field segment group in the mapping set is decomposed. The number of each field in the segment group is extracted independently and paired with its corresponding channel number to form a field-channel pair. In this process, there is a continuous segment group with fields 5 to 7, with offset values ​​of +1, +2, and +3 respectively, and a channel number of 3. Field numbers 5, 6, and 7 are extracted and bound to channel 3 respectively, forming field-channel pairs (5, 3), (6, 3), and (7, 3). Next, the order offset confirmation operation is performed on the extracted field-channel pairs. Each pair of field number and channel number combinations is traversed. By searching the previously generated offset comparison group, the offset value of the field under the specified channel is extracted. The offset value is subtracted from the original order position of the field to obtain the actual order position. The difference between the original and the actual order is recorded. This difference is the offset value of the field. For example, if field 6 is the 6th position in the original order and is the 8th position after the offset, the offset is +2. Through this operation, the order offset information of all field-channel pairs can be completed. Then, all field numbers, channel numbers, and offset values ​​are merged and summarized to form a complete sequence. Create an offset registration record. For each record item, sequentially label the field number, channel number, original position, and current offset value. For example, if field 6 has an offset value of +2 in channel 3, an original position of 6, and a current position of 8, then the record in the registration table is: Field 6, Channel 3, Original 6, Offset +2, Current 8. If a field appears in two different channels, its offset information in each channel must be recorded separately. In this case, the field numbers are the same but the channel numbers are different. Two records should be generated in the registration table, corresponding to its offset records in different channels. A complete record of the field offset status should at least cover five parameters: field index, channel number, original sequence position, offset direction and offset value, and final sequence position. The records should be output in a standard table format. For example, if the fields in the registration table are as follows: Field number 4, Channel number 2, Original sequence position 4, Offset value -1, then the current sequence position is 3, and the record is: Field 4, Channel 2, Original 4, Offset -1, Current 3. Process all field-channel pairs in this way and organize them to obtain the field offset status registration table.

[0027] Please see Figure 3 The specific steps of S2 are as follows: S201: Based on the field number information in the field offset status registration table, identify the data channel number and structural position index corresponding to the field, compare the preceding and following relationships of the field numbers in the same channel, identify field groups with continuous indexes, and obtain the field continuous numbering segment information; First, the records in the registration table are read one by one, and the field number, channel number, and structural position index parameter corresponding to each record are extracted. During each extraction process, the field number is used as the primary key identifier, the channel number as the classification basis, and the structural position index as the sequence number parameter. All field records are grouped according to the channel number. After classifying all fields by channel, the field numbers in each channel field set are sorted in ascending order according to the structural position index value. For example, if channel 1 contains field numbers 4, 5, 6, and 7, and their corresponding structural position index values ​​are 12, 13, 14, and 15 respectively, then the sorted field sequence is field 4, field 5, field 6, and field 7. Next, the difference operation of adjacent field numbers is performed in the sorted sequence. For any two adjacent fields, the current field number is subtracted from the previous field number, and the difference is checked to see if they are equal. If the value is equal to 1, the record is part of a continuous field segment group. If the value is not equal to 1, the numbering is determined to be discontinuous and the current segment group is interrupted. A new segment group is started. In this process, the field numbering continuity determination threshold is set to 1 to ensure that the field numbers are strictly arranged in sequence. For example, in channel 2, the field numbers are 3, 4, 6, 7, and 8, and their structural position indices are 21, 22, 24, 25, and 26, respectively. After sorting by structural index, the resulting numbering sequence is 3, 4, 6, 7, and 8. The difference between field 3 and field 4 is 1, and the difference between field 4 and field 6 is 2. They do not meet the continuity determination. Therefore, field 3 and field 4 are grouped together, and field 6, 7, and 8 form another group because the differences between their field numbers are 1. This process is repeated for all channel field groups to determine the numbering differences. Finally, all field segments that meet the continuous numbering condition are merged to obtain the continuous numbering segment information.

[0028] S202: Based on the field grouping information in the continuous numbering segment information, analyze the source identifier of the field in the channel, determine the order of the differentiated source identifier fields in the structure, divide the field segment range corresponding to the source identifier, and obtain the source field sequence distribution content. First, each field in the segment is read and its starting number, ending number, and corresponding channel number are extracted. The starting number is used as the paragraph start parameter, the ending number as the paragraph end parameter, and the channel number as the source retrieval condition. During this process, a source identifier extraction operation is performed on each field number. This is done by reading the source identifier bit recorded in the registration table and using its value as the basic parameter for determining the field's source. For example, if the field segment is from field 10 to field 14 and the channel number is 2, then the source identifiers for fields 10, 11, 12, 13, and 14 are extracted item by item. The source identifier may have a value of A or B. The sequential arrangement of source identifier values ​​forms a source sequence. For example, if the source identifier for field 10 is A, field 11 is A, field 12 is B, field 13 is B, and field 14 is B, then the source sequence is A, A, B, B, B. Subsequently, a source identifier difference judgment operation is performed, comparing the current field's source identifier with the previous field's source identifier. If the identifiers are the same, it is recorded as a segment from the same source; if the identifiers are different, it is recorded as a boundary point of the source segment. For example, if the source identifiers for fields 11 and 12 are different, a source segment boundary is generated at the end of field 11, and a new source segment is started at the beginning of field 12. Based on the source identifier difference, the field group can be divided into two source segments. The first segment consists of fields 10 and 11, corresponding to source A. The second segment consists of fields 12 and 14, corresponding to source B. During the judgment process, the baseline value for determining a change in the source identifier is set to "characters are completely different." A change is determined when the current identifier value is not equal to the previous identifier value. For example, if characters A and B are not equal, a segment division is triggered. This baseline value does not need to be calculated; it only needs to be compared with the characters. Subsequently, a field range determination operation is performed on each source segment. That is, the first field number in the source segment is used as the segment start field, and the last field number in the source segment is used as the segment end field, forming a segment range record. For example, the source A segment is field 10. For field 11, the source B segment consists of fields 12 to 14. Each segment record must be labeled with both the channel number and the source identifier. For example, the segment information record is: fields 10-11, source A, channel 2; fields 12-14, source B, channel 2. If the source identifier changes alternately in the field group segment during this process, all boundary points need to be identified by item-by-item comparison and multiple segments need to be generated. For example, in the sequence A, B, A, B, B, fields 10 to 10 are segment A, fields 11 to 11 are segment B, fields 12 to 12 are segment A, and fields 13 to 14 are segment B. Through complete traversal, all source identifiers can be segmented and expressed to obtain the source field sequence distribution content.

[0029] S203: Based on the range of field segments in the source field sequence distribution content, analyze the start and end position range of the field segments in the channel structure, compare the structural position separation between source field segments, and obtain the source field number segment information;First, the starting and ending field numbers of the source field paragraphs are read segment by segment. The starting field number is used as the reference value for the beginning position of the paragraph, and the ending field number is used as the reference value for the end position of the paragraph. At the same time, the channel number to which the paragraph belongs is extracted as the basis for position retrieval. During this process, a field position retrieval operation is performed on each field paragraph, that is, the structural position index of all fields in the paragraph is searched item by item in the offset status registration record. These structural position indices are arranged in ascending order to establish the position sequence of the field paragraph in the channel structure. For example, if paragraph A consists of fields 20 to 23 and belongs to channel 4, the structural position indices of fields 20, 21, 22, and 23 in the offset status registration table are 32, 33, 34, 35, 36, 37, 38, 39 ... If the given values ​​are 7 and 38, then the paragraph's position sequence within the structure is 32, 33, 37, 38. Next, the start and end position range is confirmed. The smallest structural position value in the sequence is recorded as the paragraph's start point, and the largest structural position value is recorded as the paragraph's end point. For example, paragraph A starts at 32 and ends at 38. After confirming the start and end positions, a structural position comparison operation between paragraphs is performed. This involves selecting any two adjacent source paragraphs and calculating the difference between their structural start and end points. The difference is used to determine if a positional separation exists. The positional separation threshold is set to twice the field unit length. In this scenario, the field unit length is set to 3 bytes, so the threshold is 6. A separation is determined when the minimum structural difference between two paragraphs is greater than 6. To determine if a structural separation exists, a difference of 6 or less is considered as no significant separation. For example, if paragraph A's structural endpoint is 38 and paragraph B's structural starting point is 45, the difference is 7, which is greater than the threshold of 6. Therefore, a structural separation is determined between paragraphs A and B. Subsequently, a segmentation action is performed between the different segments, integrating each paragraph based on the continuity of its start and end positions. When two paragraphs are determined to have a structural separation, separate segment records are generated. When no structural separation exists, the two paragraphs are merged into the same segment. In this action, if the source field of paragraph B is field 24 to field 25, and its structural position sequence is 45, 46, then the difference between it and paragraph A is 7, causing segment separation and forming segment A (fields 20-23, position 32-). 38) After comparing fragment B (fields 24-25, positions 45-46), a source identifier reconfirmation action is performed on each fragment record. By reading the source identifiers of all fields in the fragment content, it is determined whether there are any changes in the source identifiers within the fragment. When all source identifiers within a fragment are consistent, the fragment source identifiers are unified. When there are multiple values ​​for the source identifiers within a fragment, it is necessary to further divide it into segments according to their positions from smallest to largest. For example, fragment C consists of fields 30 to 34, but fields 30 and 31 originate from A, while fields 32, 33, and 34 originate from C. Therefore, fragment C needs to be divided into two sub-fragments: fields 30-31 originate from A, and fields 32-34 originate from C. After completing the above division action, the numbered fragment generation action is performed.The source field number fragment information is obtained by combining the field number range, channel number, structure start and end positions, and source identifier into a single record.

[0030] Please see Figure 4 The specific steps of S3 are as follows: S301: Based on the field number range in the source field number fragment information, filter the appearance status of the number in the task path field list within the field range, compare whether the number range overlaps with the number in the path field, and obtain a list of number intersection segments. First, for each segment record, extract the start and end numbers of the fields. Use the start number as the lower bound of the numbering segment and the end number as the upper bound. Simultaneously, read all path field numbers from the task path field list, treating this list as the set of target numbers to be verified. Based on this, perform a number filtering operation on the segment numbering segment: iterate through each number within the segment and compare each iterated number with all numbers in the task path field list. If a iterated number equals a list number, record that number as present; otherwise, continue to the next item for comparison. For example, if the segment number range is field 30 to field 36, and the task path field list contains field 25, ... For segments 31, 33, and 40, during the traversal, number 30 is not equal to task path numbers 25, 31, 33, and 40, so it is not recorded as appearing. Number 31 is equal to task path number 31, so it is recorded as appearing. Number 32 is not equal to any list number, and number 33 is equal to list number 33, so it is recorded as appearing. Numbers 34 to 36 are not equal to any task path number. Through this process, the set of numbers for the appearing states within the segment range can be obtained as numbers 31 and 33. Subsequently, a number overlap judgment action is performed on the appearing numbers, that is, the difference operation is performed on two adjacent appearing numbers, and it is calculated whether the difference is equal to 1. When the difference is equal to 1, it is judged as continuous overlap; when the difference is not equal to 1, it is judged as non-continuous overlap. In this scenario, number 31 and The difference between number 33 and 1 is 2, which is not equal to 1, so it is determined to be a non-contiguous overlapping segment. Therefore, the two numbers need to be recorded as independent intersection segments. If multiple consecutive numbers appear, an intersection segment is formed according to the continuous range. For example, if the segment range is field 10 to field 20, and the task path fields are field 12, field 13, field 14, and field 18, then after traversing, numbers 12, 13, 14, and 18 are found to be present. The difference between numbers 12 and 13 is 1, and the difference between numbers 13 and 14 is 1. Numbers 12 to 14 form a continuous overlapping segment. Number 18, because its difference with number 14 is 4, does not form a continuous segment and needs to be treated as a separate segment. In this judgment process, the difference threshold is set to 1 as the continuous discrimination benchmark value. The threshold does not need to be calculated; only... The process involves checking if the difference equals 1, then performing the same action on all segment number ranges, summarizing and integrating overlapping segments within each segment. For each intersection segment, record the starting and ending field numbers, as well as its appearance status in the path field list. For example, number 31 forms segment 31 to 31, number 33 forms segment 33 to 33, and in a continuous case, numbers 12 to 14 form segment 12 to 14. During the recording process, the channel number to which the segment belongs also needs to be read and appended to the intersection segment data to distinguish overlapping numbers in different channels. For example, if segment A belongs to channel 2, then intersection segment 31-31 is recorded as channel 2, 31-31, and number 33-33 is recorded as channel 2, 33-33.If segment B belongs to channel 3, then segments 12-14 are recorded as channel 3, 12-14. After sorting, the overlapping numbered segments of all segments can be output sequentially, resulting in a list of numbered overlapping segments.

[0031] S302: Based on each number in the numbered cross segment list, locate the corresponding field index position in the task path structure, and map the cross number to the field position in the path structure to obtain the field path position correspondence table. First, each cross-segment record is read sequentially. The segment start number and segment end number are used as the number range parameters to be mapped. Simultaneously, a complete list of path fields and their corresponding field index positions are extracted from the task path structure. This list of path fields is used as the target data set for number matching, and the index positions of the path fields are used as the position values ​​required for mapping. During number positioning, each number within the segment number range is traversed sequentially. The current number is compared with each number in the path field list. When the current number equals a path field number, the matching status is recorded and the process is initiated. Using the corresponding field index position parameters, for example, if the task path field list is field 10, field 11, field 15, field 18, field 19, and field 21, and their corresponding field index positions are positions 1, 2, 3, 4, 5, and 6 respectively, and the numbered intersection segment is field 15 to field 21, then when traversing number 15, an equality comparison is performed with the six numbers in the path fields 10, 11, 15, 18, 19, and 21. When it is equal to number 15, field index 3 is recorded as its corresponding position, and this record is then stored in the mapping result temporary storage area. After traversing the numbers, the order of matching items for all numbers within the segment is sorted. The process involves arranging the data in the original numbering order to maintain the orderliness of the mapping structure. For example, when the numbering segment is from field 18 to field 19, traversing number 18 and matching the path field 18 yields index 4, and traversing number 19 and matching the path field 19 yields index 5. These two items are recorded sequentially as number 18 → index 4 and number 19 → index 5. After the numbering location action is completed, the numbering position combination action is performed to merge the correspondence between the number and the field position into a record unit. The record unit must contain the field number, the path field position, and the segment belonging information. For example, the record unit format is field 15: position 3, field 18: position 4. Field 19: Locus 5. During this process, a judgment action needs to be performed on the unmatched item numbers. That is, when a certain number has no equal value in the path field list, it is marked as unmapped but not entered into the mapping record table, so as to keep all entries in the mapping table as valid mapping numbers. For example, when the number segment is field 30 to field 32, if the path field list does not have numbers 30, 31, and 32, then all three items are marked as unmatched and do not enter the record unit generation process. Subsequently, a merging and sorting action is performed on all number mapping records of all segments, and all record units are combined according to the segment order and the number order to obtain the field path locus correspondence table.

[0032] S303: Based on the mapping content in the field path location correspondence table, connect the cross-information of the docking number with the field position in the task path structure, specify the position of the field in the path structure, and obtain the path field number correspondence information table. First, each record in the mapping table is read sequentially. The field number is used as the mapping index parameter, and the corresponding path field position is used as the path structure location parameter. Simultaneously, the number range content in the cross-numbering segment records is read, using the interval from the start to the end of the number as the filtering boundary for location matching. During the cross-numbering information matching process, the field numbers involved in each numbering segment are compared item by item with the field numbers in the mapping table. When a field number equals any number within the numbering segment, the position of that number in the path field position is retrieved, and a number position confirmation action is performed. For example, the numbering cross-numbering segment record field... Fields numbered 15 to 15, corresponding to the path location 15: position 3, are matched. Therefore, field 15 is confirmed as the 3rd position in the task path structure. The next numbered field mapping confirmation operation is then performed. When the numbered segment is fields 18 to 19, the path locations 18: position 4 and 19: position 5 are read. Both numbers are within the segment and have mapping records. Therefore, fields 18 and 19 are positioned as the 4th and 5th positions in the path structure, respectively. After completing the above positioning process for all intersecting numbered items, the field position specification operation is performed, linking the field number with the path location. The binding process is performed to generate location mapping units. The record format includes information such as field number, path structure location index, original cross-section number, and path field sequence number. For example, field 15 is bound to path location 3, field 18 is bound to path location 4, and field 19 is bound to path location 5, corresponding to section numbers 15, 18, and 19, and path field sequence numbers 3, 4, and 5. Subsequently, the integrity check of the numbering point mapping is performed. The check rules are: the path location index must be a unique value, and the field number cannot be bound to multiple locations repeatedly. If the same field number appears in multiple location index binding records, the smallest path sequence number is selected through comparison. As the final binding location, other records are deleted to ensure that the unique mapping relationship of the path field is established. If a field number exists in the intersection segment but no corresponding path position is found in the mapping table, the number is marked as unmatched and no position-specified record is generated. After completing the number mapping specification action, all successfully matched fields and their path structure positions are integrated and sorted by path structure position index from smallest to largest to form a sequence table. For example, field 15 is position 3, field 18 is position 4, and field 19 is position 5. The final combination is the sequence field 15 → field 18 → field 19, which yields the path field number corresponding information table.

[0033] Please see Figure 5 The specific steps of S4 are as follows: S401: Based on the set of field numbers in the path field number correspondence information table and the task path index value, and filtering the belonging position of the field number under the task path from the task scheduling table, the field path belonging dataset is obtained according to the mapping relationship between the field number and the path index value. First, extract the field numbers and corresponding path index values ​​from the information table one by one. Use the field number as the target item for path mapping and the path index as the reference position of the field in the path structure. Based on this, read all scheduling entries from the task scheduling table, using the field number in the scheduling table as the search key and the belonging field item in the scheduling table as the belonging value to be confirmed. Perform a filtering operation on the field numbers, traversing the path field number list one by one, comparing each field number with all field numbers in the scheduling table. When field numbers match, extract the belonging position field. This field represents the task module, task node, or path unit to which the field number belongs in the path. For example, if the path field number is field 18 and the path index value is 4, and the scheduling table records that field 18 belongs to module B, which is the 2nd unit in the task path, then mark field 18 with path index 4 and record it as belonging to module B. After completing one mapping, continue processing the next field number. If the field number... If path index 19 is 5 and belongs to module C in the scheduling table, then the mapping relationship between field 19, index 5, and module C is bound, recorded as field 19 → path 5 → module C. After traversing all path field numbers in this way, the attribution extraction operation is completed. Then, the attribution consistency confirmation action is performed. The path index value in the mapping record is compared with the order of each module in the task path structure. The position of the module to which the field number belongs is matched and verified with the order position of the task structure corresponding to the path index. The verification condition is that the module to which the field number belongs must be consistent with the module in the mapped position of the path index. When they are inconsistent, they are marked as attribution conflict field numbers, the reason for the conflict is recorded, and a conflict list is generated separately. For example, if the path index of field 20 is 7, but the attribution module is module E, while the 7th position of the path is actually module D, then field 20 is marked as an attribution conflict field. If they are consistent, they are included in the attribution dataset. After completing the mapping of all field numbers and path structures, the mapping results are sorted in ascending order of path index, and finally the field path attribution dataset is obtained.

[0034] S402: Based on the path attribution information of the field numbers in the field path attribution dataset, analyze the range of the field's position in the path sequence, and compare the order of the fields appearing in the path to obtain the field path sequence relationship table. First, each record in the field path attribution dataset is read item by item. The field number, path index value, and module name are used as core parameters. The path index value is extracted to construct a path sequence, and this index value is used as the sole sorting criterion. All field numbers are arranged in ascending order to form a path position sequence. For example, the path index values ​​for fields 11, 13, and 18 are 2, 4, and 7 respectively, so the path sequence is field 11→field 13→field 18. After sorting, the position of each field in the sequence is extracted, and a field order mapping table is established using the field number as the key and the position value as the value. Then, the module attribution information is read to generate a module path chain. For example, if field 11 belongs to module A, field 13 belongs to module B, and field 18 belongs to module C, the module chain is A→B→C. When comparing the positional relationships of adjacent fields in a field sequence, the actual order after sorting is used as the standard. The path index values ​​of the subsequent field and the preceding field are compared: if the index value of the subsequent field is greater than that of the preceding field, it is marked as ascending order; if they are equal, it is marked as parallel; if the index value of the subsequent field is less than that of the preceding field, it is marked as descending order. Since the entire sequence is sorted by index value from smallest to largest, descending order can only occur when the index values ​​are equal but the original numbering order is reversed. There will be no contradictory situation where a field with a larger index value is placed before a field with a smaller index value. For example, if the index values ​​of fields 20 and 21 are both 5, they are recorded as a pair of fields in the same position (parallel relationship). After obtaining the order identifiers of all field pairs, the minimum and maximum path index values ​​of the field number set within each module are read to construct the module path range. For example, if module A contains fields 11 and 12, with indices of 2 and 3, then the path range of module A is 2–3; if module B contains fields 13 and 15, with indices of 4 and 5, then the path range of module B is 4–5. Subsequently, a segment overlap check is performed on the path ranges of adjacent modules. When the maximum index value of the previous module is greater than the minimum index value of the current module, it is recorded as a path segment intersection. For example, if module A has a range of 2–4 and module B has a range of 3–5, then the intersection segment is 3–4. Finally, all field numbers are aggregated according to their respective modules, and the positional order of the fields in the overall path sequence is recorded, resulting in a field path sequence relationship table.

[0035] S403: Based on the field path sequence relationship table, compare the position of each field in the path sequence and verify the order, synchronize the path index information, and obtain the path field data processing status table; First, each field number and its corresponding path index position in the table are read item by item. The field number is used as the verification subject, and the path index is used as the order determination parameter. A standard path sequence is constructed in ascending order of path index values. All fields are sorted by index value to form a field sequence. When performing field position comparison, adjacent fields after sorting are used as comparison objects. The difference is obtained by subtracting the index value of the previous field from the index value of the current field: when the difference is 1, it is marked as normal order; when the difference is greater than 1, it is marked as order jump; when the difference is equal to 0, it is marked as same-position field; when the difference is less than 0, it is marked as reverse order. Since the field sequence is already arranged in ascending order of index value, reverse order can only occur when the indexes are the same and the original order is reversed. A field with a larger index will not be placed before a field with a smaller index. For example, if the index of field 25 is 3 and the index of field 26 is 4, then the difference is 1 and it is marked as normal; if the indexes of field 26 and field 29 are 4 and 7 respectively, then the difference is 3 and it is marked as jump; if the indexes of field 33 and field 34 are both 8, then the difference is 0 and it is marked as same-position field. After traversing all fields, a field order status record is generated, and the positive and negative range of the difference is used as the order verification threshold: a difference greater than 1 indicates a jump, equal to 1 indicates normal, equal to 0 indicates same position, and less than 0 indicates reverse order. After completing the order verification, a path index synchronization operation is performed on all fields, comparing each field number with the actual position of the path structure corresponding to its index: if the field number at that index position in the path structure matches the current field, the record is considered synchronized successfully; otherwise, it is considered synchronized incorrectly. For example, if the index of field 25 is 3, but the 3rd field number in the path structure is 24, then field 25 is recorded as synchronized incorrectly. After all fields are processed, the order status, synchronization status, and field number are integrated into a field path status unit. Each status unit contains the field number, index position, order status (normal, jump, reverse, same position), and synchronization status (success, incorrect). For example, field 25 is recorded as 25 → index 3 → normal → synchronized successfully; field 26 is recorded as 26 → index 4 → normal → synchronized successfully; and field 29 is recorded as 29 → index 7 → jump → synchronized successfully. Finally, all status units are sorted in ascending order by index to obtain the path field data processing status table.

[0036] Please see Figure 6 The specific steps of S5 are as follows: S501: Based on the field numbers in the path field data processing status table and the task path information, extract the field numbers in the path field data processing status table, compare the status of the corresponding fields in the task path information, and obtain the set of missing path field numbers. First, the path field data processing status table is read. The field number in each record of the table is used as the primary key for retrieval. The path index, sequence status, and synchronization status of the records in the status table are used as the processing attributes of the fields in the path. Simultaneously, the complete set of field numbers that should be included in the task path is read from the task path information. This set is used as the baseline set of complete path fields. Based on this, the field number extraction action is performed, writing the field numbers from the status table into the number temporary storage area one by one. The numbers in the number temporary storage area are arranged in the order of reading. For example, if the status table contains five fields: 11, 12, 14, 15, and 18, then the content of the temporary storage area will be 11, 12, 14, 15, and 18. Then, the task path field comparison action is performed, comparing the baseline... Each field number in the baseline path field set is read item by item and compared with all numbers in the number temporary storage area. When the baseline field number is equal to the number in the temporary storage area, the number is marked as present. If the baseline field number is not matched after traversing all numbers in the temporary storage area, the number is marked as a missing field number and added to the missing field temporary storage list. For example, if the task path field set is field 10, field 11, field 12, field 13, field 14, field 15, and field 18, then field 10 is not equal to any number in the temporary storage area and is recorded as a missing field. Field 13 is also not matched and is recorded as a missing field. Fields 11, 12, 14, 15, and 18 are recorded as present fields because they are successfully matched. During this comparison process, the threshold for determining the occurrence of field numbers is set to strict equality. Any non-complete equality is considered as not occurring, and interval inclusion or similar value mapping is not allowed. Subsequently, a field status verification action is performed, reading the synchronization and sequence status of each occurrence field. When the synchronization status is "mismatched," the field number is added to the synchronization exception field set, recording cases where the field appears but the path mapping is abnormal. For example, if the synchronization status of field 15 is "mismatched," then field 15 is added to the exception field set. When the sequence status is "jump" or "reverse," the field number is recorded as a sequence exception field for subsequent path structure integration. For example, if the sequence status of field 18 is "jump," then it is recorded as a sequence exception item during field status verification. After completion, a path integrity check is performed. The missing field set, synchronization exception set, and sequence exception set are merged using the field number as the primary key. The merged result generates a total set of missing and exception fields for the path. This total set is then sorted in ascending order by field number. For example, if the merged set contains fields 10, 13, 15, and 18, the sorting order is 10, 13, 15, and 18. Finally, the missing field set is output separately. The missing field number is recorded in the path missing field number set, along with its correct position in the baseline path field set. For example, if field 10 is in position 1 in the baseline path, it is recorded as field 10 → position 1; if field 13 is in position 4, it is recorded as field 13 → position 4.Through the above comparison, filtering, and recording actions, a set of missing path field numbers was obtained.

[0037] S502: Based on the field numbers in the path missing field number set, match them with the corresponding numbers in the task field number set, and retain the number of field numbers not covered by the path field set to obtain the path number coverage status; First, the missing field IDs are read one by one, and each field ID is written to the ID verification queue. This ID is used as the primary key in the matching operation. Simultaneously, the task field IDs set is read and used as the reference ID source. During the ID matching operation, each field ID in the queue is iterated over, and each ID is compared with all IDs in the task field IDs set. When a match is found, the field is marked as "IDs included in the task set". If no matching ID is found after the iteration is complete, the field is marked as "IDs not included in the task set". For example, the missing field IDs set includes fields 10, 13, and 22, and the task field IDs set includes fields 8, 9, 10, and 1... 1. For fields 14, 18, and 22, field 10 is equal to task field number 10 and is recorded as an included number. Field 13 is not equal to any number in the task field number set and is recorded as an unincluded number. Field 22 is equal to task field number 22 and is recorded as an included number. During this matching process, the number matching threshold is set to strict equality; any number with different characters or different digits is considered a mismatch. Range judgment, approximate value judgment, or number start / end interval judgment are not allowed to replace strict matching. Subsequently, an uncovered field filtering action is performed, writing all field numbers marked as "unincluded numbers in the task set" to the uncovered field temporary storage area. For example, field 13 is added to the temporary storage area because it is unmatched. Simultaneously, to maintain path characters... For the completeness of segment coverage calculation, coverage identifiers need to be established for all included fields. Each included field is written to the coverage field temporary storage area. For example, fields 10 and 22 are recorded as covered fields. After field filtering is completed, the coverage quantity calculation is performed. The number of elements in the uncovered field temporary storage area is counted, and the count value is used as the number of uncovered fields. For example, if only field 13 is in the temporary storage area, the number of uncovered fields is 1. When performing the counting operation, the quantity distinction interval is set as follows: a quantity of 0 indicates no missing data, a quantity of 1 to 3 indicates slight missing data, and a quantity greater than 3 indicates severe missing data. However, this distinction is only used as a quantity classification identifier and does not involve logical judgment of the path coverage structure. Subsequently, the field coverage is performed. The state generation action generates a state unit by comparing each missing field number with its corresponding task field number in the task field number set. Each state unit must include parameters such as field number, matching status (included or not included), position in the missing field set, theoretical position in the task field set, and number of uncovered fields. For example, field 10 → included → missing position 1 → task theoretical position 3 → number of uncovered fields 1; field 13 → not included → missing position 2 → task theoretical position 4 → number of uncovered fields 1; field 22 → included → missing position 3 → task theoretical position 7 → number of uncovered fields 1. After all fields have formed state units, a state structure summary action is performed, sorting all state units by field number in ascending order.A coverage state sequence is formed, for example, fields 10, 13, and 22 are arranged as 10→13→22. Finally, the number of uncovered fields and the overall coverage index are appended to this coverage state sequence to obtain the path number coverage status.

[0038] S503: Based on the path number coverage status, read the correspondence between the task field number set and the path field set, determine whether the path is in a completed state, and obtain the task status information; First, the coverage state sequence is read line by line, using field number, matching status, and number of uncovered fields as initial reference parameters. Simultaneously, a complete theoretical field sequence is constructed based on the task field number set, sorted from smallest to largest. For example, if the task field number set contains fields 10, 11, 12, 13, 14, 15, and 18, the theoretical path sequence is 10→11→12→13→14→15→18. Then, the set of path field numbers that have already appeared is extracted from the path coverage state, for example, a set containing fields 11, 12, 14, 15, and 18. During field coverage comparison, the theoretical field sequence is used as the sole benchmark. Each field number is read one by one, and a strict equality character match is performed within the path field set. Fuzzy judgments using number similarity, intervals, or offsets are not allowed: if a completely equal field number is found, it is marked as covered; otherwise, it is marked as uncovered. For example, if field 10 does not exist in the path field set, it is determined that field 10 is uncovered; if field 11 can be found in the path set, it is determined that field 11 is covered. After comparing all theoretical fields, the number of uncovered fields is directly based on the actual comparison result, no longer relying on the uncovered number carried in the original coverage status record. The method of determining the number using "the larger one" or "mixing arbitrary priorities" is also prohibited, thus ensuring the reliability of the technical determination from a single source. If the number of uncovered fields in this comparison is 2 (e.g., fields 10 and 13), then the number of uncovered fields is 2. Subsequently, a path completion determination is performed based on this number of uncovered fields: an uncovered number of 0 indicates the path is fully completed, and an uncovered number greater than 0 indicates the path is incomplete. Further auxiliary classification intervals can be set, such as an uncovered number of 0 for fully completed, 1 to 3 for partially missing, and greater than 3 for severely missing. However, these classifications are only descriptive labels and do not affect the main determination logic of "complete / incomplete". Finally, the field number, theoretical position, coverage result, missing category, and task completion marker are integrated into a task status unit. For example, field 10 is recorded as 10 → theoretical position 1 → not covered → partially missing → task not completed; field 11 is recorded as 11 → theoretical position 2 → covered → no missing → task not completed (because the overall task is still not completed). After all field information is integrated, the task is finally determined based on whether there are any uncovered fields: if any field is marked as not covered, the task status is "not completed"; if all fields are marked as covered, the task status is "completed," thus obtaining the final task status information.

[0039] Please see Figure 7 A cross-platform real-time data monitoring and intelligent analysis system, comprising: The field structure extraction module obtains the field structure information and protocol identifier content from the source channel, extracts the protocol field order and compares the corresponding positions of the fields in the structure, identifies the field numbers of misaligned fields, and locates them in the field status information list to obtain the field offset status registration table. The field fragment decomposition module extracts the corresponding channel and field sequence number of the field based on the field number in the field offset status registration table, analyzes the consecutively numbered segments in the sequence, and splits the field fragments according to the source number to obtain the source field number fragment information. The path field mapping module extracts the task path field number based on the field number range in the source field number fragment information, locates the path field position corresponding to the duplicate number, and maps the path position to obtain the path field number corresponding information table; The field order positioning module reads the configuration content of the path where the associated field is located in the task scheduling table based on the field number and path identifier in the path field number corresponding information table, identifies the order of field calls in the path and locates the field order, and obtains the path field data processing status table. The task execution determination module compares the task field with the path task information based on the field number in the path field data processing status table, determines whether the path field number covers the task field number, and obtains the task status information.

[0040] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A cross-platform real-time data monitoring and intelligent analysis method, characterized in that, Includes the following steps: S1: Obtain the field structure information and protocol identifier content from the source channel, extract the protocol field order and compare the corresponding positions of the fields in the structure, identify the field numbers of misaligned fields, locate the field status information list, and obtain the field offset status registration table. S2: Based on the field offset status registration table, extract the channel number and field sequence number corresponding to the field, analyze the consecutive numbered segments in the sequence, split the field segments according to the source number, and obtain the source field number segment information; S3: Based on the field range in the source field number fragment information, extract the task path field number, locate the path field position corresponding to the duplicate number, and map the path position to obtain the path field number corresponding information table; S4: Based on the path field number corresponding information table, read the configuration content of the path where the associated field is located in the task scheduling table, identify the calling order of the field in the path and locate the field order, and obtain the path field data processing status table. S5: Based on the path field data processing status table, compare the task field with the path field number, determine whether the path field number covers the task field number, and obtain the task status information.

2. The cross-platform real-time data monitoring and intelligent analysis method according to claim 1, characterized in that, The field offset status registration table includes an offset field number set, a field order difference identifier, and a channel field status identifier. The source field number fragment information includes a fragment source identifier, a field number start and end range, and a number continuation segment feature. The path field number corresponding information table includes a path field location number, a cross-number mapping relationship, and a path structure field association item. The path field data processing status table includes a field processing sequence number, a field scheduling and allocation identifier, and a path participation sequence item. The task status information includes a task field coverage status, a path execution integrity identifier, and a field difference set feature.

3. The cross-platform real-time data monitoring and intelligent analysis method according to claim 1, characterized in that, The protocol field order refers to the correct order in which fields in the data structure are arranged according to the protocol definition. The field status information list refers to a table used to register the field position offset status.

4. The cross-platform real-time data monitoring and intelligent analysis method according to claim 1, characterized in that, The task scheduling table refers to the configuration table that manages the allocation and execution order of fields in the path; The configuration content of the path refers to the structure and order information of the description fields in the task path.

5. The cross-platform real-time data monitoring and intelligent analysis method according to claim 1, characterized in that, The specific steps of S1 are as follows: S101: Obtain the field header information and transmission structure format identifier from the source data channel, extract the field index and field length parameters from the structure format, compare the field order with the defined order position in the structure, and obtain the field order offset comparison group; S102: Based on the offset field index and corresponding channel number in the field order offset comparison group, extract adjacent field items in the channel field set, determine whether adjacent field items have consecutive offsets, and obtain a continuous offset field mapping set; S103: Based on the field index and channel number in the continuous offset field mapping set, extract the field and channel positions that have undergone sequential offset, analyze the corresponding field number and channel information, and obtain the field offset status registration table.

6. The cross-platform real-time data monitoring and intelligent analysis method according to claim 1, characterized in that, The specific steps of S2 are as follows: S201: Based on the field number information in the field offset status registration table, identify the data channel number and structural position index corresponding to the field, compare the preceding and following relationships of the field numbers in the same channel, identify field groups with consecutive indices, and obtain the field consecutive numbering segment information; S202: Based on the field grouping information in the continuous numbering segment information of the field, analyze the source identifier of the field in the channel, determine the order of the differentiated source identifier fields in the structure, divide the field segment range corresponding to the source identifier, and obtain the source field sequence distribution content; S203: Based on the range of field segments in the source field sequence distribution content, analyze the start and end position range of the field segments in the channel structure, compare the structural position separation between source field segments, and obtain source field number segment information.

7. The cross-platform real-time data monitoring and intelligent analysis method according to claim 1, characterized in that, The specific steps for S3 are as follows: S301: Based on the field number range in the source field number fragment information, filter the appearance status of the number in the task path field list within the field range, compare whether the number range overlaps with the number in the path field, and obtain a list of number intersection segments. S302: Based on each number in the numbered cross segment list, locate the field index position in the corresponding task path structure, and map the cross number to the field position in the path structure to obtain the field path position correspondence table. S303: Based on the mapping content in the field path location correspondence table, connect the cross-information of the docking number with the field position in the task path structure, specify the position of the field in the path structure, and obtain the path field number correspondence information table.

8. The cross-platform real-time data monitoring and intelligent analysis method according to claim 1, characterized in that, The specific steps of S4 are as follows: S401: Based on the set of field numbers in the path field number corresponding information table and the task path index value, and filtering the belonging position of the field number under the task path from the task scheduling table, the field path belonging dataset is obtained according to the mapping relationship between the field number and the path index value. S402: Based on the path attribution information of the field numbers in the field path attribution dataset, analyze the range of the field's position in the path sequence, and compare the order of the fields appearing in the path to obtain the field path sequence relationship table. S403: Based on the field path sequence relationship table, compare the position of each field in the path sequence and verify the order, synchronize the path index information, and obtain the path field data processing status table.

9. The cross-platform real-time data monitoring and intelligent analysis method according to claim 1, characterized in that, The specific steps of S5 are as follows: S501: Based on the field numbers in the path field data processing status table and the task path information, extract the field numbers in the path field data processing status table, compare the status of the corresponding fields in the task path information, and obtain the path missing field number set. S502: Based on the field numbers in the path missing field number set, match them with the corresponding numbers in the task field number set, and retain the number of field numbers not covered by the path field set to obtain the path number coverage status; S503: Based on the path number coverage status, read the correspondence between the task field number set and the path field set, determine whether the path is in a completed state, and obtain the task status information.

10. A cross-platform real-time data monitoring and intelligent analysis system, characterized in that, The system is used to implement the cross-platform real-time data monitoring and intelligent analysis method according to any one of claims 1-9, and the system includes: The field structure extraction module obtains the field structure information and protocol identifier content from the source channel, extracts the protocol field order and compares the corresponding positions of the fields in the structure, identifies the field numbers of misaligned fields, and locates them in the field status information list to obtain the field offset status registration table. The field fragment decomposition module extracts the corresponding channel and field sequence number of the field based on the field number in the field offset status registration table, analyzes the consecutively numbered segments in the sequence, and splits the field fragments according to the source number to obtain the source field number fragment information. The path field mapping module extracts the task path field number based on the field number range in the source field number fragment information, locates the path field position corresponding to the duplicate number, and maps the path position to obtain the path field number corresponding information table. The field order positioning module reads the configuration content of the path where the associated field is located in the task scheduling table based on the field number and path identifier in the path field number corresponding information table, identifies the order of field calls in the path and locates the field order, and obtains the path field data processing status table. The task execution determination module compares the task field with the path task information based on the field number in the path field data processing status table, determines whether the path field number covers the task field number, and obtains the task status information.

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