Method and system for optimizing performance of signal acquisition and processing module of dcs system

Abstract

The present application relates to the technical field of data processing optimization, in particular to a DCS system signal acquisition and processing module performance optimization method and system, comprising the following steps: analyzing the relationship between the main clock scanning boundary and the trigger drop point to determine the period segmentation distribution, calculating the adjacent record difference trend, combining the previous valid record to adjust the reverse concentration position to replace the sequence, comparing the increasing state of the whole sequence trigger time, and constructing the sampling time sequence continuous structure. The present application defines the cache distribution by comprehensively analyzing the attribution relationship between the main clock scanning start and end positions and the trigger drop point, deeply excavates the difference trend switching law and reverse symbol aggregation characteristics between adjacent entries, establishes a previous effective value freezing replacement mechanism for the abnormal fluctuation extreme value concentration section, effectively blocks the path of the surface distortion value penetrating into the subsequent processing flow, and strictly checks the increasing constraint condition of the adjacent action time when reconstructing the whole sequence, completely avoiding the time sequence inversion and misplacement caused by external interference and blind acceptance.

Description

Technical Field

[0001] This invention relates to the field of data processing optimization technology, and in particular to a method and system for optimizing the performance of signal acquisition and processing modules in a DCS system. Background Technology

[0002] The field of data processing optimization technology involves the acquisition, conversion, verification, sorting, storage, and transmission of continuous and discrete data generated during industrial operations. This typically includes the access methods for field measurements, numerical conversion rules for different types of electrical signals, sampling period settings, time sequence maintenance, outlier detection, historical data retention, and data exchange mechanisms between the controller and the operator station. Among these, the performance optimization methods for traditional DCS system signal acquisition and processing modules refer to the processing methods employed in the reception, conversion, processing, and transmission of field signals after they enter the control station in a distributed control system. These methods primarily address issues such as inconsistent sampling order of signals from different measurement points after entering the control system, inconsistent range conversion criteria, instantaneous jumps in raw values, mismatch between communication cycles and refresh rates, and disordered order of historical data writing.

[0003] Existing technologies process field signals by mechanically receiving and passively storing them according to a fixed rhythm. This operating mode makes it difficult to accurately define the misalignment triggering action that crosses the scanning cycle boundary, which easily induces timing misalignment when multiple channels are accessed in parallel. At the same time, when dealing with external interference, it relies on surface numerical reception and lacks in-depth analysis of the evolution trend of continuous data and the aggregation state of differential changes. It is difficult to accurately separate transient distortion records mixed in with normal fluctuations, causing abnormal differential data to flow directly into subsequent processing stages, resulting in serious negative impacts such as damage to the underlying timing continuity and mis-issuance of control commands. Summary of the Invention

[0004] To address the technical problems existing in the prior art, embodiments of the present invention provide a method and system for optimizing the performance of a DCS system signal acquisition and processing module. The technical solution is as follows: On the one hand, a method for optimizing the performance of the signal acquisition and processing module of a DCS system is provided, including the following steps: S1: Based on the DCS control station, analyze the start time of the scanning cycle, compare the trigger landing point with the boundary position, determine the buffer status of the record belonging to the cycle, and combine the sequence number to count the distribution of records within the cycle to obtain the cycle segment distribution characteristics. S2: Based on the periodic segment distribution characteristics, obtain the channel buffer arrangement status, compare the registration sequence number order, calculate the direction of difference change of adjacent records, determine the direction structure of continuous difference symbols, and obtain the channel difference direction characteristics; S3: Based on the channel differential direction features, obtain the symbol sequence distribution state, compare the switching positions of adjacent symbols, determine the reverse switching clustering relationship, and combine the symbol continuation state to organize the distribution structure to obtain symbol reverse clustering data; S4: Based on the symbol inversion aggregated data, call the sequence position relationship, determine the record status corresponding to the inverted set position, compare the previous valid record with the current record, adjust the replacement order, and obtain the abnormal frozen replacement sequence; S5: Based on the abnormal frozen replacement sequence, obtain the state of the sequence record, compare the order of adjacent trigger times, determine the state of the increasing arrangement of trigger times, calculate the continuous distribution of time, and obtain the continuous structure of the sampling time sequence.

[0005] On the other hand, the periodic segmentation distribution features include periodic sampling density level, sampling time period division identifier, and periodic data distribution category; the channel differential direction features include differential direction symbol sequence identifier, differential trend category identifier, and change segment division label; the symbol inversion aggregated data includes symbol inversion position set, reverse change distribution area, and symbol switching concentration area identifier; the abnormal frozen replacement sequence includes frozen sampling record set, replacement sampling source record, and abnormal replacement position index; and the sampling time sequence continuity structure includes sampling time sequence identifier, time interval distribution type, and time sequence continuity identifier.

[0006] On the other hand, the specific steps for obtaining the periodic segment distribution characteristics are as follows: S101: Based on the DCS control station, obtain the start time series of the master clock scan cycle, verify the connection relationship between adjacent cycles, retrieve the landing point of the sampling record trigger time in the cycle limit interval, determine the scanning cycle of the sampling record, and obtain the scanning cycle belonging index. S102: Based on the scanning cycle attribution index, obtain the sampling cache registration sequence number order relationship, check the corresponding position of the cache area type identifier, organize the sampling record arrangement order within the same scanning cycle, and obtain the cycle record distribution structure; S103: Based on the periodic record distribution structure, analyze the positional relationship of the sampling records within the scanning period, divide the time period identifiers of the sampling records, determine the clustering status of the records in each time period, and obtain the periodic segment distribution characteristics.

[0007] On the other hand, the specific steps for obtaining the channel differential orientation features are as follows: S201: Based on the periodic segment distribution characteristics, locate the sampling record corresponding to the periodic buffer of the input channel, verify the order of sampling trigger times, check the order of the sampling buffer registration number, associate the trigger time with the registration number, and obtain the sampling time sequence arrangement. S202: Based on the sampling time sequence, compare the changes in the sampling values ​​of adjacent sampling records before and after, determine the differential sign direction of adjacent records, associate the sampling buffer registration sequence number order relationship, and obtain the differential direction sign sequence; S203: Based on the differential direction symbol sequence, analyze the connection relationship of continuous differential symbols, determine the arrangement status of the same-direction continuous segment and the reverse switching segment, adjust the position of the changing segment boundary, and obtain the channel differential direction characteristics.

[0008] On the other hand, the specific steps for obtaining the symbol-inverted aggregated data are as follows: S301: Based on the channel differential direction characteristics, check the order of continuous differential symbols, compare the positions of symbol pointing changes, mark the sequence number corresponding to the direction change, and associate the positions of adjacent symbols to obtain a set of symbol switching positions; S302: Based on the set of symbol switching positions, check the interval arrangement of adjacent switching positions, compare the adjacent states before and after the switching positions, filter the combination of consecutive adjacent switching positions, optimize the correspondence of segment boundaries, and obtain the reverse change distribution area; S303: Based on the reverse change distribution area, analyze the continuation state of the preceding symbols of the segment, compare the continuation state of the following symbols of the segment, determine the arrangement relationship of the reverse switching concentration positions, organize the reverse distribution structure, and obtain the symbol reversal clustered data.

[0009] On the other hand, the specific steps for obtaining the abnormal frozen replacement sequence are as follows: S401: Based on the symbol inversion aggregated data, obtain the sequence number corresponding to the reverse switching position, compare the adjacency relationship of adjacent sequence numbers, determine the continuous reverse switching landing point segment, associate the position relationship of the sampling sequence, organize the corresponding order of the positions, and obtain the reverse switching segment index. S402: Based on the reverse switching segment index, analyze the arrangement status of the corresponding sampling records, compare the change trend of the current position record with the previous record, determine the classification of the current position record status, filter the previous valid records, and obtain the set of valid sampling positions. S403: Based on the set of valid sampling positions, check the order of the sampling sequence positions, compare the correspondence between the previous valid records and the current position records, adjust the current position replacement order mapping, associate the reverse switching landing position, and obtain the abnormal frozen replacement sequence.

[0010] On the other hand, the specific steps for obtaining the sampling time-series continuous structure are as follows: S501: Based on the abnormal freeze replacement sequence, obtain the correlation relationship of sampling sequence position numbers, compare the order of trigger times of adjacent position numbers, determine the record position of the reverse landing point of the trigger time, and obtain the whole sequence of sampling records; S502: Based on the ordered sampling record sequence, analyze the connection relationship between the trigger times of adjacent sampling records, compare the order of the trigger times of the preceding and following records, determine the boundary position of the continuously increasing segment, and obtain the time sequence segment set. S503: Based on the set of time sequence segments, analyze the connection status of trigger times within the segments, compare the arrangement relationship of trigger times before and after the segment boundary, determine the continuous distribution status of the sampling sequence time, and obtain the continuous structure of the sampling time sequence.

[0011] On the other hand, the DCS control station refers to the control computing node in the process industry control system, the trigger landing point refers to the time position of a single sampling record in the time axis of the DCS system master clock scan cycle, and the boundary position refers to the time boundary formed by the start time of the master clock scan cycle and the end time of the scan cycle.

[0012] On the other hand, the arrangement state refers to the arrangement relationship of all sampling records in the periodic buffer of the same input channel after sorting according to the sampling buffer registration number or sampling trigger time, and the direction structure refers to the change sequence structure formed by connecting multiple continuous differential change directions in chronological order.

[0013] On the other hand, a performance optimization system for DCS system signal acquisition and processing modules is provided. This system is applied to the performance optimization methods for DCS system signal acquisition and processing modules, including: The periodic segmentation module is based on the DCS control station. It analyzes the start time of the scanning cycle, compares the trigger landing point with the boundary position, determines the buffer status of the record belonging to the cycle, and combines the sequence number to count the distribution of records within the cycle to obtain the periodic segmentation distribution characteristics. Based on the periodic segment distribution characteristics, the differential direction module obtains the channel buffer arrangement status, compares the registration sequence number order, calculates the differential change direction of adjacent records, determines the direction of continuous differential symbols, and obtains the channel differential direction characteristics. The symbol inversion module obtains the symbol sequence distribution state based on the channel differential direction characteristics, compares the switching positions of adjacent symbols, determines the reverse switching clustering relationship, and combines the symbol continuation state to organize the distribution structure to obtain symbol inversion clustering data. The freeze replacement module, based on the symbol inversion aggregated data, calls the sequence position relationship, determines the record status corresponding to the inverted set position, compares the previous valid record with the current record, adjusts the replacement order, and obtains the abnormal freeze replacement sequence. The timing verification module obtains the state of the sequence record based on the abnormal frozen replacement sequence, compares the order of adjacent trigger times, determines the state of the trigger times in ascending order, calculates the continuous distribution of time, and obtains the continuous structure of the sampled timing sequence.

[0014] The beneficial effects of the technical solutions provided in the embodiments of the present invention include at least the following: By defining the cache distribution through the relationship between the start and end points of the master clock scan and the trigger landing point, and by deeply exploring the switching patterns of differential directions between adjacent entries and the clustering characteristics of reverse symbols, a mechanism for freezing and replacing the preceding valid values ​​in the concentrated areas of abnormal fluctuations is established. This effectively blocks the path of surface distortion values ​​penetrating into the subsequent processing flow. Furthermore, when reconstructing the sequence, the incremental constraints of the timing of adjacent actions are strictly examined to completely avoid timing inversion and misalignment caused by external interference and blind acceptance. This results in the construction of a low-level data link with strong anti-interference capabilities and a stable and coherent structure. 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 flowchart of the main steps of the present invention; Figure 2 This is a flowchart of steps S1 of the present invention; Figure 3 This is a flowchart of steps S2 of the present invention; Figure 4 This is a flowchart of steps S3 of the present invention; Figure 5 This is a flowchart of step S4 of the present invention; Figure 6 This is a flowchart of steps S5 of the present invention; Figure 7 This is a system block 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] 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.

[0019] This invention provides a method for optimizing the performance of a DCS system signal acquisition and processing module, such as... Figure 1 As shown, it includes the following steps: S1: Based on the DCS control station, analyze the start time of the master clock scan cycle, compare the landing point of the sampling trigger time with the boundary position of the scan cycle, determine the buffer status of the sampling record belonging to the cycle, and combine the sampling buffer registration number to statistically analyze the distribution of records within the cycle and obtain the cycle segment distribution characteristics. S2: Based on the periodic segment distribution characteristics, obtain the sampling record arrangement status of the corresponding input channel periodic buffer area, compare the order relationship of the sampling buffer registration number, calculate the direction of change of the numerical difference between adjacent sampling records, determine the direction structure of the continuous difference sign, and obtain the channel difference direction characteristics. S3: Based on the channel differential direction characteristics, obtain the distribution state of the continuous differential symbol sequence, compare the direction switching positions of adjacent differential symbols, determine the clustering relationship of the reverse switching positions, combine the continuation state of the preceding and following differential symbols, organize the reverse distribution structure, and obtain the symbol reversal clustering data. S4: Based on the symbol inversion clustered data, call the sampling sequence position relationship, determine the sampling record status corresponding to the differential symbol inversion cluster position, compare the previous valid sampling record with the current position sampling record, adjust the current position replacement order, and obtain the abnormal frozen replacement sequence. S5: Based on the abnormal frozen replacement sequence, obtain the record status of the ordered sampling sequence, compare the sequential relationship of adjacent sampling trigger times, determine the incremental arrangement of sampling trigger times, calculate the continuous distribution of sampling sequence time, and obtain the continuous structure of sampling time sequence.

[0020] The periodic segmentation distribution characteristics include periodic sampling density level, sampling time period division identifier, and periodic data distribution category; the channel differential direction characteristics include differential direction symbol sequence identifier, differential trend category identifier, and change segment division label; the symbol inversion clustered data includes symbol inversion position set, reverse change distribution area, and symbol switching concentration area identifier; the abnormal frozen replacement sequence includes frozen sampling record set, replacement sampling source record, and abnormal replacement position index; and the sampling time sequence continuity structure includes sampling time sequence identifier, time interval distribution type, and time sequence continuity identifier.

[0021] In S1, the DCS control station refers to the control computing node in the process industry control system, used to receive sampling data uploaded by the signal acquisition card and perform sampling data periodic segmentation processing according to the system master clock; the sampling trigger moment refers to the time position of a single sampling record on the time axis of the DCS system master clock scan cycle, used to indicate the relative time position of the sampling action in the current scan cycle; the scan cycle boundary position refers to the time limit formed by the start time and end time of the master clock scan cycle, used to determine the scan cycle range to which the sampling trigger moment belongs; the buffer status refers to the buffer category status of the sampling records categorized and stored between the signal acquisition module and the signal processing module, used to indicate the data buffer area type to which the sampling record currently belongs; the registration number refers to the record sequence number assigned to the sampling record when the signal acquisition card generates sampling data, used to identify the generation order relationship of the sampling records in the acquisition process; the record distribution within the cycle refers to the distribution of all sampling records on the time axis within the same scan cycle time interval, used to describe the distribution of the location and quantity of sampling data within that cycle.

[0022] In S2, the sampling record arrangement state refers to the arrangement relationship of all sampling records in the periodic buffer of the same input channel after being sorted according to the sampling buffer registration number or the sampling trigger time, which is used to represent the sequential structure of the sampling records; the numerical difference change direction refers to the change direction corresponding to the difference result obtained after subtracting the sampling values ​​of two adjacent sampling records, which is used to represent the upward or downward change trend of the sampling signal in the time series; the trend structure refers to the change sequence structure formed by connecting multiple continuous difference change directions in time order, which is used to describe the combination of change directions of the sampling signal over a period of time.

[0023] In S3, the differential symbol sequence refers to the sequence of symbols arranged in chronological order of the differential change direction of continuous sampling records, used to represent the continuous expression of the change direction of the sampled signal in the time dimension; the direction switching position refers to the position where the direction of adjacent differential symbols in the differential symbol sequence changes, used to identify the position point where the change direction of the sampled signal changes; the clustering relationship refers to the spatial proximity of multiple direction switching positions in the differential symbol sequence, used to indicate whether the reverse change of differential symbols is concentrated in a local area; the reverse distribution structure refers to the arrangement of the reverse change symbols in the differential symbol sequence in the overall sequence, used to represent the reverse distribution state of the change direction of the sampled signal.

[0024] In S4, the sampling record status refers to the data status category of the sampling record during the anomaly identification and reordering process performed by the signal processing module, which is used to distinguish between valid sampling records and abnormal sampling records; the current position substitution order refers to the priority order rule used to determine the source of the substitution sampling value after the abnormal sampling record is identified, which is used to determine whether to use the preceding valid sampling record to perform substitution processing on the abnormal sampling record.

[0025] In S5, the ordered sampling sequence refers to the sequence of sampling records arranged in chronological order after abnormal sampling identification and freeze replacement processing, used to represent the set of sampling data after the ordered processing is completed; the ascending arrangement state refers to the order relationship formed by arranging adjacent sampling trigger times in the sampling sequence according to the chronological order, used to represent the chronological relationship of the sampling records; the temporal continuous distribution refers to the distribution state of the time interval between each sampling trigger time in the ordered sampling sequence, used to represent the continuity of the temporal distribution of the sampling records; the sampling temporal continuous structure refers to the overall temporal arrangement structure formed by the ordered sampling sequence in the time dimension, used to describe the combination relationship between the temporal order and temporal distribution of the sampling records.

[0026] like Figure 2 As shown, the specific steps for obtaining the periodic segment distribution characteristics are as follows: S101: Based on the DCS control station, obtain the start time series of the master clock scan cycle, verify the connection relationship between adjacent cycles, retrieve the landing point of the sampling record trigger time in the cycle limit interval, determine the scanning cycle of the sampling record, and obtain the scanning cycle belonging index. In the DCS control station's operating state, the cycle start time data in the master clock cycle record buffer is read. The preset scan cycle length is 100 milliseconds, and multiple cycle start points are continuously read from the cycle buffer table, for example, recorded as 0 milliseconds, 100 milliseconds, 200 milliseconds, 300 milliseconds, 400 milliseconds, and 500 milliseconds. The time difference is calculated for each adjacent cycle start point: 100 minus 0 equals 100 milliseconds, 200 minus 100 equals 100 milliseconds, 300 minus 200 equals 100 milliseconds, 400 minus 300 equals 100 milliseconds, and 500 minus 400 equals 100 milliseconds. Each calculation result is compared with the scan cycle baseline value of 100 milliseconds. When the time difference is within the closed interval of 98 milliseconds to 102 milliseconds, it is marked as a normal cycle connection; when the calculated value is less than 98 milliseconds or greater than 102 milliseconds, it is marked as a cycle anomaly. In this example, all five calculation results are 100 milliseconds, therefore, it is recorded as a normal connection state. Then, the sampling trigger time data is read one by one from the sampling record table, such as 35 milliseconds, 82 milliseconds, 118 milliseconds, 165 milliseconds, 214 milliseconds, and 287 milliseconds. Period assignment is performed according to the rule that 'the trigger time is greater than or equal to the start of the period and less than the start of the next period': 35 milliseconds and 82 milliseconds satisfy 0 ≤ t < 100, and are assigned to period 1; 118 milliseconds and 165 milliseconds satisfy 100 ≤ t < 200, and are assigned to period 2; 214 milliseconds and 287 milliseconds satisfy 200 ≤ t < 300, and are assigned to period 3. Finally, the period numbers 1, 1, 2, 2, 3, and 3 are written into the index field of the corresponding sampling record, generating a scan period assignment index for each sampling record.

[0027] S102: Based on the scan cycle attribution index, obtain the order relationship of the sampling cache registration number, verify the corresponding position of the cache type identifier, organize the sampling record arrangement order within the same scan cycle, and obtain the period record distribution structure; The process retrieves the cycle number from the scan cycle index field and uses this number to search for the corresponding registration number in the sampling cache record table. The sampling registration number is generated by the sampling card in an incrementing manner. For example, if the consecutive record numbers for a certain input channel are 101, 102, 103, 104, 105, and 106, the sampling records are first grouped according to the cycle number. The first cycle corresponds to registration numbers 101 and 102, the second cycle to 103 and 104, and the third cycle to 105 and 106. Then, the cache type identifier corresponding to each record is read one by one. The cache type is limited to three integers: 1, 2, and 3. 1 represents a real-time cache, 2 represents a transitional cache, and 3 represents a delayed cache. For example, record 101 corresponds to type 1, 102 corresponds to type 1, and 103 corresponds to type 1. For each type, 104 corresponds to type 2, 105 corresponds to type 1, and 106 corresponds to type 1. The read cache type is checked against the registration sequence number position item by item. When the registration sequence number in the same period meets the increasing relationship, the original arrangement order is maintained. If a record with a larger registration sequence number is located at the front, a swap process is performed. For example, if 104 is located before 103, the position is swapped. In this example, the registration sequence number in each period is kept in an increasing state, so the arrangement order is maintained as 101 before 102, 103 before 104, and 105 before 106. Then, the number of records in each period is counted. For example, there are 2 records in period 1, 2 records in period 2, and 2 records in period 3. The period number, registration sequence number order, and number of records are written into the period record distribution table to obtain the period record distribution structure.

[0028] S103: Based on the periodic record distribution structure, analyze the positional relationship of the sampling records within the scanning period, divide the time period of the sampling records, determine the clustering status of the records in each time period, and obtain the periodic segment distribution characteristics. The system retrieves the cycle number and its corresponding registration number from the cycle record distribution table and synchronously reads the sampling trigger time data for each record. The scan cycle length is set to 100 milliseconds, and the relative time interval within each cycle is divided into three fixed time periods: the first time period is greater than or equal to 0 milliseconds and less than 33 milliseconds; the second time period is greater than or equal to 33 milliseconds and less than 66 milliseconds; and the third time period is greater than or equal to 66 milliseconds and less than 100 milliseconds. Subsequently, the sampling trigger time within each cycle is read one by one and converted to a time value relative to the cycle start point. In cycle 1, 35 milliseconds minus the cycle start point of 0 milliseconds equals 35 milliseconds, satisfying 33 ≤ t < 66, and is assigned to the second time period; 82 milliseconds minus the cycle start point of 0 milliseconds equals 82 milliseconds, satisfying 66 ≤ t < 100, and is assigned to the third time period. In cycle 2, 118 milliseconds minus the cycle start point of 100 milliseconds equals 18 milliseconds, assigned to the first time period; 165 milliseconds minus the cycle start point of 100 milliseconds equals 65 milliseconds, assigned to the second time period. In period 3, 214 milliseconds minus the period start of 200 milliseconds equals 14 milliseconds, which is assigned to time segment 1; 287 milliseconds minus the period start of 200 milliseconds equals 87 milliseconds, which is assigned to time segment 3. The number of records for each period within the three time segments is then counted: period 1: 0, 1, 1; period 2: 1, 1, 0; period 3: 1, 0, 1. The total number of records for each period is then counted, with 2 records for all three periods. Following the rule that 0 to 1 records are marked as density level 1, 2 to 3 records as density level 2, and more than 3 records as density level 3, in this example, each period is marked as density level 2. Finally, the period number, the number of records in time segments 1 to 3, the total number of records for the period, and the density level are entered into the period segmentation record table to obtain the period segmentation distribution characteristics.

[0029] like Figure 3 As shown, the specific steps for obtaining the channel differential orientation features are as follows: S201: Based on the periodic segment distribution characteristics, locate the sampling record corresponding to the periodic buffer of the input channel, check the order of sampling trigger times, verify the order of the sampling buffer registration number, associate the trigger time with the registration number, and obtain the sampling time sequence. The DCS control station reads the set of sampling records for the channel within the target scan cycle from the buffer area and extracts the sampling trigger time and sampling buffer registration number for each record. Suppose a temperature input channel retrieves 5 records within one scan cycle, with trigger times of 112 ms, 126 ms, 151 ms, 168 ms, and 189 ms, corresponding to registration numbers 2201, 2202, 2203, 2204, and 2205. The system reads adjacent trigger times one by one and performs a time comparison: 126 is greater than 112 (if true); 151 is greater than 126 (if true); 168 is greater than 151 (if true); and 189 is greater than 168 (if true). If a later time is less than a previous time, the record is adjusted to the correct time position. Then, the same incremental judgment is performed on the registration sequence number: 2202 is compared to 2201, and the result is true; 2203 is compared to 2202, and the result is true; 2204 is compared to 2203, and the result is true; 2205 is compared to 2204, and the result is true. If a larger registration sequence number precedes a smaller registration sequence number, the record is adjusted to the correct position. After completing the two sets of sequence checks, the trigger time is bound one-to-one with the registration sequence number: 112 milliseconds corresponds to 2201, 126 milliseconds corresponds to 2202, 151 milliseconds corresponds to 2203, 168 milliseconds corresponds to 2204, and 189 milliseconds corresponds to 2205, and each record is written to the time-series association cache table. Then, it is checked again whether the ascending position of the trigger time sequence corresponds one-to-one with the ascending position of the registration sequence number sequence. If all positions match, it is marked as a consistent state, and a sampling time sequence is generated in chronological order.

[0030] S202: Based on the sampling time sequence, compare the changes in the sampling values ​​of adjacent sampling records before and after, determine the differential sign direction of adjacent records, associate the order relationship of the sampling buffer registration numbers, and obtain the differential direction sign sequence; The sampling values ​​of adjacent sampling records are read in chronological order, and the difference is calculated by subtracting the previous sampling value from the subsequent sampling value. For example, if an input channel receives sampling values ​​50.2, 50.8, 50.5, 51.1, 51.1, and 50.7 in sequence, then 50.8 minus 50.2 gives a difference of 0.6; 50.5 minus 50.8 gives a difference of -0.3; 51.1 minus 50.5 gives a difference of 0.6; 51.1 minus 51.1 gives a difference of 0; and 50.7 minus 51.1 gives a difference of -0.4. The direction is determined based on the difference range: a difference greater than 0.05 is considered a positive change; a difference greater than or equal to -0.05 and less than or equal to 0.05 is considered a horizontal change; and a difference less than -0.05 is considered a negative change. Therefore, the resulting direction sequence is: positive, negative, positive, horizontal, negative. Each difference result is then associated with its corresponding sampling buffer registration number interval: 2201 to 2202 correspond to the forward direction, 2202 to 2203 to the reverse direction, 2203 to 2204 to the forward direction, 2204 to 2205 to the horizontal direction, and 2205 to 2206 to the reverse direction. The registration numbers are then checked to ensure they remain continuously increasing. If a number jump occurs, the buffer is first searched for missing number records. If found, the record is inserted and the difference calculation is re-executed. If not found, a breakpoint is marked at the corresponding number interval, ultimately forming a sequence of difference direction symbols arranged according to the registered number intervals.

[0031] S203: Based on the differential direction symbol sequence, analyze the connection relationship of continuous differential symbols, determine the arrangement status of the same-direction continuous segment and the reverse switching segment, adjust the boundary position of the changing segment, and obtain the channel differential direction characteristics; The symbols are read sequentially and their continuity is checked. For example, if the direction sequence is positive, negative, positive, neutral, negative, then adjacent symbols are compared in turn: the first positive symbol is different from the second negative symbol, so a direction switching boundary is recorded between 1 and 2; the second negative symbol is different from the third positive symbol, so a second switching boundary is recorded between 2 and 3; the third positive symbol is different from the fourth neutral symbol, where the neutral direction is recorded separately as a transitional state and not immediately merged into the previous direction segment; the fourth neutral symbol is different from the fifth negative symbol, so a new switching boundary is recorded between 4 and 5. Then, statistics are performed on the change segments formed by consecutive identical symbols. When the number of consecutive symbols satisfies 1 ≤ n ≤ 2, it is marked as a short change segment; when it satisfies 3 ≤ n ≤ 4, it is marked as a medium change segment; and when it is greater than 4, it is marked as a long change segment. In the current example, the formed consecutive change segments are positive, negative, positive, neutral, negative, and each segment has a consecutive number of 1, so they are all recorded as short segments. Then, paragraph boundary trimming is performed: if a horizontal symbol is located between two symbols of the same direction and there is only one horizontal symbol, it is merged into that direction segment. For example, "positive, positive, horizontal, positive" can be trimmed into four consecutive positive segments. If a horizontal symbol is located between two different directions, it remains an independent segment. In this example, "horizontal forward" is positive and "horizontal backward" is negative, so it remains an independent segment. Finally, the start position, end position, direction identifier, and number of consecutive segments of each segment are written into the channel segment record table to obtain the channel differential direction characteristics.

[0032] like Figure 4 As shown, the specific steps for obtaining sign-reversed aggregated data are as follows: S301: Based on the channel differential direction characteristics, check the order of continuous differential symbols, compare the positions of symbol pointing changes, mark the corresponding sequence number of the direction change, and associate the positions of adjacent symbols to obtain the symbol switching position set; Retrieve continuous symbol data according to the differential symbol arrangement order of the same input channel. Assume the symbol sequence corresponding to a pressure channel in one scan cycle is positive, positive, negative, negative, positive, neutral, negative. Starting from the 1st and 2nd bits, perform a forward and backward direction check. If positive matches, do not register a change position. Then read the 2nd and 3rd bits. If positive and negative do not match, record the position after the 2nd bit as the 1st directional change position and number it 2. Then read the 3rd and 4th bits. If negative matches, maintain the current state and do not write a number. Continue reading the 4th and 5th bits. If negative and positive do not match, register the 2nd directional change position after the 4th bit and number it 4. Then read the 5th and 6th bits. If positive and neutral do not match... The third directional change position is recorded after the 5th position and marked as 5. Then, the 6th and 7th positions are read, and it is determined that flat and reversed are inconsistent. The fourth directional change position is recorded after the 6th position and marked as 6. Then, each directional change position is bound to the positions of the adjacent symbols before and after it. For example, number 2 corresponds to the 2nd position being positive and the 3rd position being reversed, number 4 corresponds to the 4th position being reversed and the 5th position being positive, number 5 corresponds to the 5th position being positive and the 6th position being flat, and number 6 corresponds to the 6th position being flat and the 7th position being reversed. The positions with an adjacent position difference of 1 are marked as directly adjacent. If the position difference is greater than 1, it is marked as an interval switch. In this example, all four change positions come from continuous scanning, so they are all retained and written into the switch position record table in ascending order of number to obtain the symbol switch position set.

[0033] S302: Based on the set of symbol switching positions, check the interval arrangement of adjacent switching positions, compare the adjacent states before and after the switching positions, filter the combination of consecutive adjacent switching positions, optimize the correspondence of segment boundaries, and obtain the reverse change distribution area. Read all handover numbers in order of position. Let's say the current handover numbers for a channel are 2, 4, 5, 6, and 9. First, read 2 and 4 and calculate the interval, resulting in an interval of 2. An interval of 1 is considered an adjacent handover, an interval of 2 is considered a near-adjacent handover, and an interval greater than 2 is considered a separated handover. Therefore, 2 and 4 are recorded as near-adjacent. Next, read 4 and 5, obtaining an interval of 1, and record it as adjacent. Then read 5 and 6, obtaining an interval of 1, and again record it as adjacent. Continue reading 6 and 9, obtaining an interval of 3, and record it as separated. Then, check the adjacency of each handover position before and after it. For example, position 4 is preceded by position 2 and followed by position 5, so position 4 is marked as bilaterally adjacent. Position 5 is preceded by position 4 and followed by position 6, so position 5 is also marked. Since the two sides are adjacent, position 2 is only adjacent to position 4 and there is no switching point in front of it, so it is recorded as a one-sided adjacency. The interval between position 9 and position 6 is 3, so it is listed separately as far away from the switching point. Then, the continuous adjacency combination filtering is performed. Starting from position 4, positions 5 and 6 are searched backward. Since 4 and 5, and 5 and 6 both meet the condition that the interval is no greater than 1, 4, 5, and 6 are merged into the same combination segment. Then, it is checked that although the interval between position 2 and position 4 is 2, there is no other switching point in between. It is retained as an adjacent reference point and not merged into the combination segment. Then, the boundary of the combination segment is adjusted accordingly. The starting boundary is placed in front of position 4, and the ending boundary is placed behind position 6. The individual position 9 is recorded as another independent segment, forming a reverse change distribution area divided by position.

[0034] S303: Based on the reverse change distribution area, analyze the continuation state of the preceding symbols of the segment, compare the continuation state of the following symbols of the segment, determine the arrangement relationship of the reverse switching concentration positions, organize the reverse distribution structure, and obtain the symbol reversal clustered data; The symbol continuation state before and after a segment is read segment by segment. Assume a channel has two segments: segment 1 covers switching positions 4 to 6, and segment 2 covers switching position 9. First, process segment 1 by reading its preceding symbol sequence. Assume positions 1 to 3 correspond to positive, positive, and negative symbols, respectively. Count the consecutive lengths in the same direction preceding the segment. Positions 1 and 2 are both positive, so the consecutive length is recorded as 2. Stop counting the preceding sequence when position 3 turns negative. Next, read the symbols following segment 1. Assume positions 7 to 10 correspond to negative, negative, positive, and positive symbols, respectively. Determine if positions 7 and 8 are both negative, so the consecutive length is recorded as 2. Stop counting the following sequence when position 9 turns positive. Then compare the consecutive lengths before and after the segment. If the current preceding length is 2 and the following length is 2, record a consecutive length of 1 as weak continuation, and a consecutive length of 2 to 3 as weak continuation. For medium continuation, a value greater than 3 is considered long continuation. Therefore, both sides of this segment are considered medium continuation. Then, the concentration of switching points is checked. The switching numbers within the first segment are 4, 5, and 6. The difference between the maximum and minimum values ​​of the three numbers is 2. A difference of no more than 2 is considered a concentrated arrangement, a difference of 3 to 4 is considered a dispersed arrangement, and a difference greater than 4 is considered a discrete arrangement. Therefore, this segment is marked as a concentrated position. The second segment contains only position 9. The preceding symbol is read as reversed, and the following symbol is read as positive. The continuous length of the preceding symbol is 2, and the continuous length of the following symbol is 1. The single-point segment is marked as a single switching position. Finally, the switching number set, preceding continuation state, following continuation state, and concentration category of each segment are written into the inversion record table in sequence to obtain the symbol inversion clustered data.

[0035] like Figure 5 As shown, the specific steps for obtaining the abnormally frozen replacement sequence are as follows: S401: Based on the symbol inversion aggregated data, obtain the sequence number corresponding to the reverse switching position, compare the adjacency relationship of adjacent sequence numbers, determine the continuous reverse switching landing point segment, associate the position relationship of the sampling sequence, organize the corresponding order of the positions, and obtain the reverse switching segment index. Read the reverse switching position numbers within the same input channel and arrange them in ascending order. Let the currently acquired switching numbers for a certain channel be 4, 5, 6, 10, and 11. Compare the differences between adjacent numbers one by one. The difference between 4 and 5 is 1, so they are directly adjacent. The difference between 5 and 6 is also 1, so they are directly adjacent. The difference between 6 and 10 is 4, so they are disconnected. The difference between 10 and 11 is 1, so they are directly adjacent. Switching positions with a difference of 1 are grouped into the same segment, while those with a difference greater than 1 are placed in a new segment. Therefore, 4, 5, and 6 are grouped into the first reverse switching segment, and 10 and 11 are grouped into the second reverse switching segment. Then, the switching numbers are matched one by one with the sampling sequence positions. Therefore, number 4 corresponds to the area between the 4th and 5th sampling records, number 5 corresponds to the area between the 5th and 6th sampling records, and number 6 corresponds to the area between the 6th and 7th sampling records. Thus, segment 1 corresponds to positions 4 to 7 in the sampling sequence, and numbers 10 and 11 correspond to positions 10 to 12 in the sampling sequence. Next, the size pattern of the start and end positions of each segment is checked. If the start number is less than the end number, the current order is maintained. If an inversion occurs, the smaller number is rewritten as the start number and the larger number is rewritten as the end number. In this example, the segment positions are all incremented. Therefore, segment 1 is registered as 4 to 7, segment 2 is registered as 10 to 12, and written into the segment index table to obtain the reverse switching segment index.

[0036] S402: Based on the reverse switching segment index, analyze the arrangement status of the corresponding sampling records, compare the change trend of the current position record with the previous record, determine the classification of the current position record status, filter the previous valid records, and obtain the set of valid sampling positions. Retrieve the sampling record and its preceding record within the corresponding segment from the sampling cache table. Assume the first segment covers positions 4 to 7 of the sampling sequence, with relevant sampling values ​​of 60.5, 60.4, 60.6, and 60.3 respectively. The third record at the previous position of the segment has a value of 60.7. Comparing the fourth position (60.5) with the third position (60.7), we find a decrease of 0.2, recorded as a downward change. Next, comparing the fifth position (60.4) with the fourth position (60.5), we find a decrease of 0.1, again recorded as a downward change. Then, comparing the sixth position (60.6) with the fifth position (60.4), we find an increase of 0.2, recorded as an upward change. Finally, comparing the seventh position (60.3) with the sixth position (60.6), we find a decrease of 0.3, recorded as a downward change. Then, based on the previous... The execution state is then categorized. When the direction of change of the current position is consistent with the direction of the preceding continuous position, it is recorded as a valid continuation record. When the direction of change of the current position is opposite to that of the previous position and then reverses again, it is recorded as an abnormal candidate record. Therefore, positions 4 and 5 remain downward and are recorded as valid continuations. Position 6 changes from descending to ascending and is recorded as an abnormal candidate. Position 7 changes to descending again and is still in the switching zone, so it is recorded as an abnormal candidate. Then, valid records are screened forward from the starting point of the segment, prioritizing the position that is closest and not marked as abnormal. In this example, position 3 (60.7) is selected as the first-choice valid position through screening, and position 2 (60.9) is selected as the second-choice valid position through screening. These positions are written into the valid position table in the order of nearest to farthest, resulting in a set of valid sampling positions.

[0037] S403: Based on the set of valid sampling positions, check the order of the sampling sequence positions, compare the correspondence between the previous valid record and the current position record, adjust the current position replacement order mapping, associate the reverse switching landing position, and obtain the abnormal frozen replacement sequence. Read the valid position number and the current position number within the reverse switching segment. Assume the valid sampling positions are position 3 and position 2. The reverse switching segment covers positions 4 to 7. Verify the position order, confirming that position 3 precedes position 4 and position 2 precedes position 3. Then process the substitution mapping for each position within the segment. First, check position 4. Since position 4 has been classified as a valid continuation record, keep the original value 60.5 unchanged. Next, check position 5. Since position 5 is also a valid continuation record, keep the original value 60.4 unchanged. Then check position 6, read the record value 60.7 from the preferred valid position 3, and verify that position 6 has been marked as an anomaly. If selected, the 3rd position is written to the alternative source field of the 6th position. Then, the 7th position is checked to determine whether the preferred valid position has been occupied by the previous abnormal position. If it has been occupied, the record value 60.9 of the second-selected valid position 2 is read and written to the alternative source field of the 7th position. In this example, the 6th position calls the 3rd position and the 7th position calls the 2nd position. Then, the abnormal position number, the corresponding alternative source position number, the segment number, and the corresponding switching landing point number are written to the alternative mapping table. The 6th position is associated with the 1st segment and the 5th to 6th switching positions, and the 7th position is associated with the 1st segment and the 6th to 7th switching positions, forming an abnormal frozen alternative sequence arranged in the order of the sampling sequence.

[0038] like Figure 6 As shown, the specific steps for obtaining the sampling time-series continuous structure are as follows: S501: Based on the abnormal freeze replacement sequence, obtain the correlation between the sampling sequence position numbers, compare the order of the trigger times of adjacent position numbers, determine the record position of the reverse landing point of the trigger time, and obtain the whole sequence of sampling records. To obtain the correspondence between the position numbers and trigger times in the sampling sequence, let the current sequence positions of a certain input channel be 1, 2, 3, 4, 5, 6, and the corresponding trigger times be 105 milliseconds, 118 milliseconds, 132 milliseconds, 129 milliseconds, 146 milliseconds, and 159 milliseconds, respectively. Position 4 is a record position retained after abnormal freeze replacement. The trigger times of adjacent position numbers are read item by item and compared. First, 105 and 118 are compared; 118 is greater than 105 and recorded as having a normal sequence. Then, 118 and 132 are compared; 132 is greater than 118 and recorded as having a normal sequence. Finally, 132 and 129 are compared; 129 is less than 132. The position is recorded as the reverse landing point, and the 4th position is written into the reverse position record table. Then, 129 and 146 are compared. It is determined that 146 is greater than 129 and recorded as the order is restored. Then, 146 and 159 are compared. It is determined that 159 is greater than 146 and recorded as the order is normal. Then, the position numbers before and after the reverse position are adjusted. The 4th position record is moved to before the 3rd position, and the trigger time order is rearranged to 105, 118, 129, 132, 146, 159. At the same time, the position numbers are updated synchronously. The adjacent trigger times are compared again to confirm that all meet the condition that the later order is greater than the earlier order. Finally, the sorted record order is written into the whole sequence record table to obtain the whole sequence sampling record sequence.

[0039] S502: Based on the sequence of sampling records, analyze the connection relationship between the trigger times of adjacent sampling records, compare the order of the trigger times of the preceding and following records, determine the boundary position of the continuously increasing segments, and obtain the set of time sequence segments. Read the trigger time of each record sequentially, assuming the trigger times are 105 milliseconds, 118 milliseconds, 129 milliseconds, 132 milliseconds, 146 milliseconds, 159 milliseconds, 157 milliseconds, and 171 milliseconds respectively. Starting from the first and second records, compare the trigger times one by one to determine the pattern. If 118 is greater than 105, group the two records into the same increasing segment. Then compare 129 with 118; if 129 is greater than 118, keep them in the same segment. Next, compare 132 with 129; if 132 is greater than 129, extend the segment. Then compare 146 with 132; if 146 is greater than 132, extend the segment. Finally, compare 159 with 146; if 159 is greater than 146, extend the segment. When reading 157 and 159, it is determined that 157 is less than 159, so it is recorded as the increment interrupt position and a segment boundary is set after the 6th record. The 1st to 6th records are registered as the first increment segment. Then, 157 and 171 are read, and it is determined that 171 is greater than 157. The 7th and 8th records are registered as the new increment segment. Then, the number of records in each segment is marked. The number of records is 1 to 2, which is recorded as a short segment, 3 to 5 as a medium segment, and more than 5 as a long segment. In this example, the 1st segment has 6 records and is recorded as a long segment, and the 2nd segment has 2 records and is recorded as a short segment. The start position, end position and number of records of the segment are written into the time sequence segment table to obtain the time sequence segment set.

[0040] S503: Based on the time sequence segment set, analyze the connection state of triggering times within the segment, compare the arrangement relationship of triggering time intervals before and after the segment boundary, determine the time continuous distribution state of the sampling sequence, and obtain the sampling time sequence continuous structure. The trigger times within each segment are read segment by segment, and the adjacent time intervals are calculated. Let the trigger times of segment 1 be 105 ms, 118 ms, 129 ms, 132 ms, 146 ms, and 159 ms, and the trigger times of segment 2 be 157 ms and 171 ms. First, within segment 1, the adjacent intervals are calculated item by item: 118 minus 105 equals 13 ms, 129 minus 118 equals 11 ms, 132 minus 129 equals 3 ms, 146 minus 132 equals 14 ms, and 159 minus 146 equals 13 ms. Then, time intervals of 0 to 15 ms are marked as tightly connected, 16 to 30 ms as generally connected, and greater than 30 ms as loosely connected. Next, in this example, all intervals in the first segment are within the range of 0 to 15 milliseconds, so it is marked as a tightly continuous segment. Then, the time interval within the second segment is read, 171 minus 157 equals 14 milliseconds, which is also marked as tightly connected. Then, the segment boundary position is read and the last 159 milliseconds of the first segment are compared with the starting 157 milliseconds of the second segment. The difference is calculated as negative 2 milliseconds and recorded as a reverse boundary. If the time after the boundary is greater than the time before the boundary and the interval is within 0 to 15 milliseconds, it is marked as a continuous boundary. In this example, this boundary is recorded as a reverse boundary. Finally, the interval status, boundary type, and segment position relationship within each segment are written into the timing structure record table to obtain the sampled timing continuous structure.

[0041] like Figure 7 As shown, the DCS system signal acquisition and processing module performance optimization system includes: The periodic segmentation module is based on the DCS control station. It analyzes the start time of the scanning cycle, compares the trigger landing point with the boundary position, determines the buffer status of the record belonging to the cycle, and combines the sequence number to count the distribution of records within the cycle to obtain the periodic segmentation distribution characteristics. The differential direction module obtains the channel buffer arrangement status based on the periodic segment distribution characteristics, compares the registration sequence number order, calculates the differential change direction of adjacent records, determines the direction of continuous differential symbols, and obtains the channel differential direction characteristics. The symbol inversion module obtains the symbol sequence distribution state based on the channel differential direction characteristics, compares the switching positions of adjacent symbols, determines the reverse switching clustering relationship, and combines the symbol continuation state to organize the distribution structure to obtain symbol inversion clustered data. The freeze replacement module is based on the sign-reversed aggregated data. It calls the sequence position relationship, determines the record status corresponding to the reverse set position, compares the previous valid record with the current record, adjusts the replacement order, and obtains the abnormal freeze replacement sequence. The timing verification module obtains the state of the sequence record based on the abnormal freeze replacement sequence, compares the order of adjacent trigger times, determines the state of the trigger times in ascending order, calculates the continuous distribution of time, and obtains the continuous structure of the sampled timing sequence.

[0042] 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 method for optimizing the performance of a DCS system signal acquisition and processing module, characterized in that, The method includes: S1: Based on the DCS control station, analyze the start time of the scanning cycle, compare the trigger landing point with the boundary position, determine the buffer status of the record belonging to the cycle, and combine the sequence number to count the distribution of records within the cycle to obtain the cycle segment distribution characteristics. S2: Based on the periodic segment distribution characteristics, obtain the channel buffer arrangement status, compare the registration sequence number order, calculate the direction of difference change of adjacent records, determine the direction structure of continuous difference symbols, and obtain the channel difference direction characteristics. S3: Based on the channel differential direction features, obtain the symbol sequence distribution state, compare the switching positions of adjacent symbols, determine the reverse switching clustering relationship, and combine the symbol continuation state to organize the distribution structure to obtain symbol reverse clustering data; S4: Based on the symbol inversion aggregated data, call the sequence position relationship, determine the record status corresponding to the inverted set position, compare the previous valid record with the current record, adjust the replacement order, and obtain the abnormal frozen replacement sequence; S5: Based on the abnormal frozen replacement sequence, obtain the state of the sequence record, compare the order of adjacent trigger times, determine the state of the trigger times in ascending order, calculate the continuous distribution of time, and obtain the continuous structure of the sampling time sequence.

2. The method for optimizing the performance of the DCS system signal acquisition and processing module according to claim 1, characterized in that, The periodic segmentation distribution features include periodic sampling density level, sampling time period division identifier, and periodic data distribution category; the channel differential direction features include differential direction symbol sequence identifier, differential trend category identifier, and change segment division label; the symbol inversion clustered data includes symbol inversion position set, reverse change distribution area, and symbol switching concentration area identifier; the abnormal freeze replacement sequence includes frozen sampling record set, replacement sampling source record, and abnormal replacement position index; and the sampling time sequence continuity structure includes sampling time sequence identifier, time interval distribution type, and time sequence continuity identifier.

3. The method for optimizing the performance of the DCS system signal acquisition and processing module according to claim 1, characterized in that, The specific steps for obtaining the periodic segment distribution characteristics are as follows: S101: Based on the DCS control station, obtain the start time series of the master clock scan cycle, verify the connection relationship between adjacent cycles, retrieve the landing point of the sampling record trigger time in the cycle limit interval, determine the scanning cycle of the sampling record, and obtain the scanning cycle belonging index. S102: Based on the scanning cycle attribution index, obtain the sampling cache registration sequence number order relationship, check the corresponding position of the cache area type identifier, organize the sampling record arrangement order within the same scanning cycle, and obtain the cycle record distribution structure; S103: Based on the periodic record distribution structure, analyze the positional relationship of the sampling records within the scanning period, divide the time period identifiers of the sampling records, determine the clustering status of the records in each time period, and obtain the periodic segment distribution characteristics.

4. The method for optimizing the performance of the DCS system signal acquisition and processing module according to claim 1, characterized in that, The specific steps for obtaining the channel differential orientation features are as follows: S201: Based on the periodic segment distribution characteristics, locate the sampling record corresponding to the periodic buffer of the input channel, verify the order of sampling trigger times, check the order of the sampling buffer registration number, associate the trigger time with the registration number, and obtain the sampling time sequence arrangement. S202: Based on the sampling time sequence, compare the changes in the sampling values ​​of adjacent sampling records before and after, determine the differential sign direction of adjacent records, associate the sampling buffer registration sequence number order relationship, and obtain the differential direction sign sequence; S203: Based on the differential direction symbol sequence, analyze the connection relationship of continuous differential symbols, determine the arrangement status of the same-direction continuous segment and the reverse switching segment, adjust the position of the changing segment boundary, and obtain the channel differential direction characteristics.

5. The method for optimizing the performance of the DCS system signal acquisition and processing module according to claim 1, characterized in that, The specific steps for obtaining the symbol-reversed aggregated data are as follows: S301: Based on the channel differential direction characteristics, check the order of continuous differential symbols, compare the positions of symbol pointing changes, mark the sequence number corresponding to the direction change, and associate the positions of adjacent symbols to obtain a set of symbol switching positions; S302: Based on the set of symbol switching positions, check the interval arrangement of adjacent switching positions, compare the adjacent states before and after the switching positions, filter the combination of consecutive adjacent switching positions, optimize the correspondence of segment boundaries, and obtain the reverse change distribution area. S303: Based on the reverse change distribution area, analyze the continuation state of the preceding symbols of the segment, compare the continuation state of the following symbols of the segment, determine the arrangement relationship of the reverse switching concentration positions, organize the reverse distribution structure, and obtain the symbol reversal clustered data.

6. The method for optimizing the performance of the DCS system signal acquisition and processing module according to claim 1, characterized in that, The specific steps for obtaining the abnormal frozen replacement sequence are as follows: S401: Based on the symbol inversion aggregated data, obtain the sequence number corresponding to the reverse switching position, compare the adjacency relationship of adjacent sequence numbers, determine the continuous reverse switching landing point segment, associate the position relationship of the sampling sequence, organize the corresponding order of the positions, and obtain the reverse switching segment index. S402: Based on the reverse switching segment index, analyze the arrangement status of the corresponding sampling records, compare the change trend of the current position record with the previous record, determine the classification of the current position record status, filter the previous valid records, and obtain the set of valid sampling positions. S403: Based on the set of valid sampling positions, check the order of the sampling sequence positions, compare the correspondence between the previous valid records and the current position records, adjust the current position replacement order mapping, associate the reverse switching landing position, and obtain the abnormal frozen replacement sequence.

7. The method for optimizing the performance of the DCS system signal acquisition and processing module according to claim 1, characterized in that, The specific steps for obtaining the sampling time-series continuous structure are as follows: S501: Based on the abnormal freeze replacement sequence, obtain the correlation relationship of sampling sequence position numbers, compare the order of trigger times of adjacent position numbers, determine the record position of the reverse landing point of the trigger time, and obtain the whole sequence of sampling records; S502: Based on the ordered sampling record sequence, analyze the connection relationship between the trigger times of adjacent sampling records, compare the order of the trigger times of the preceding and following records, determine the boundary position of the continuously increasing segment, and obtain the time sequence segment set. S503: Based on the set of time sequence segments, analyze the connection status of trigger times within the segments, compare the arrangement relationship of trigger times before and after the segment boundary, determine the continuous distribution status of the sampling sequence time, and obtain the continuous structure of the sampling time sequence.

8. The method for optimizing the performance of the DCS system signal acquisition and processing module according to claim 1, characterized in that, The DCS control station refers to the control computing node in the process industry control system. The trigger landing point refers to the time position of a single sampling record in the time axis of the DCS system master clock scan cycle. The boundary position refers to the time boundary formed by the start time of the master clock scan cycle and the end time of the scan cycle.

9. The method for optimizing the performance of the DCS system signal acquisition and processing module according to claim 1, characterized in that, The arrangement state refers to the arrangement relationship of all sampling records in the periodic buffer of the same input channel after sorting according to the sampling buffer registration number or sampling trigger time. The direction structure refers to the change sequence structure formed by connecting multiple continuous differential change directions in chronological order.

10. A DCS system signal acquisition and processing module performance optimization system, said system being used to implement the DCS system signal acquisition and processing module performance optimization method as described in any one of claims 1-9, characterized in that, The system includes: The periodic segmentation module is based on the DCS control station. It analyzes the start time of the scanning cycle, compares the trigger landing point with the boundary position, determines the buffer status of the record belonging to the cycle, and combines the sequence number to count the distribution of records within the cycle to obtain the periodic segmentation distribution characteristics. Based on the periodic segment distribution characteristics, the differential direction module obtains the channel cache arrangement status, compares the registration sequence number order, calculates the differential change direction of adjacent records, determines the direction of continuous differential symbols, and obtains the channel differential direction characteristics. The symbol inversion module obtains the symbol sequence distribution state based on the channel differential direction characteristics, compares the switching positions of adjacent symbols, determines the reverse switching clustering relationship, and combines the symbol continuation state to organize the distribution structure to obtain symbol inversion clustering data. The freeze replacement module, based on the symbol inversion aggregated data, calls the sequence position relationship, determines the record status corresponding to the inverted set position, compares the previous valid record with the current record, adjusts the replacement order, and obtains the abnormal freeze replacement sequence. The timing verification module obtains the state of the sequence record based on the abnormal frozen replacement sequence, compares the order of adjacent trigger times, determines the state of the trigger times in ascending order, calculates the continuous distribution of time, and obtains the continuous structure of the sampled timing sequence.

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