A method and system for storing data of chloroacetic acid production

Abstract

The present application relates to the technical field of industrial process control, in particular to a chloroacetic acid production data storage method and system, comprising the following steps: obtaining starting temperature, reaction time and ratio, extracting feed batch and chlorine flow, arranging parameter and batch corresponding table, judging adjacent batch process consistency, generating grouping table, establishing channel label structure, arranging path level information, generating stage path table, completing data archiving and registering number relationship. In the present application, through cross collection of multiple source parameters and time information association, accurate integration of batch data is realized. Dynamic judgment based on adjacent batch parameter floating range improves process consistency recognition accuracy. Establishment of channel attribution relationship ensures clear data structure, path level mapping combined with running state and time label enhances stage data organization ability. Automatic archiving improves data arrangement efficiency and traceability, and overall strengthens the structure and synergy of batch data management.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of industrial process control, and particularly relates to a chloroacetic acid production data storage method and system. BACKGROUND

[0002] The technical field of industrial process control includes the technical content of monitoring, adjusting and managing various types of equipment, parameters and operation links in industrial production processes. The core content of this technical field is to collect and adjust key process parameters such as temperature, pressure, flow rate and ratio in real time through automatic control means, to ensure the continuity, stability and safety of the production process. Systematically, industrial process control covers process detection technology, actuator control, electrical control system, process parameter optimization and information management, and is widely used in continuous and batch production industrial scenes such as chemical industry, pharmaceutical industry, metallurgy and energy, and is an important basic technology system to support the operation efficiency and quality of modern industry.

[0003] Among them, the chloroacetic acid production data storage method refers to a data processing method for structurally collecting, classifying storing and managing the data generated in the key process links in the industrial synthesis and refining process of chloroacetic acid. The technical matter targeted by the patent subject covers the collection of information such as material ratio, temperature control time, reaction rate in the chloroacetic acid reaction stage and operation records in the subsequent rectification and purification links, and based on the production batch, the data is stored in a relational database through a set field format. Specifically, through means such as sampling frequency setting, data timestamp binding, field label arrangement and file directory automatic generation, the organization and archiving of data in each stage are completed.

[0004] Existing technologies suffer from a disconnect between batch identification and parameter information during data acquisition and storage. Key information such as material ratios and temperature control parameters are often stored as static fields, lacking effective binding with specific batches over time. This leads to confusion and inaccurate traceability during later stages. In process judgment between adjacent batches, current methods mostly rely on static rules, lacking dynamic judgment mechanisms based on parameter fluctuation ranges. This easily overlooks subtle differences in process consistency under minor fluctuations, affecting the accuracy of process optimization and anomaly identification. Data file archiving path management generally uses manual settings or fixed structures, failing to establish a systematic mapping relationship between paths and batch affiliation, resulting in frequent path mismatches and unclear data attribution. In path hierarchy generation and stage mapping, existing methods lack integration of operating status and control signals, causing the path structure to fail to effectively reflect the true distribution of the operation process. During archiving, file directory registration is scattered, failing to form automated aggregation based on path configuration, affecting the efficiency and consistency of data processing between batches. For example, in the pharmaceutical industry where production batches are growing rapidly, existing technologies are prone to generating repetitive work and retrieval redundancy in multi-batch data retrieval and path searching, reducing the overall efficiency of data management. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of the existing technology and to propose a method and system for storing chloroacetic acid production data.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: a method for storing chloroacetic acid production data, comprising the following steps:

[0007] S1: Obtain the initial temperature, reaction time, and material ratio of the reactor; extract the feed batch and chlorine flow rate data; combine the time information; map the parameters to the batch numbers; and generate a process parameter mapping record table.

[0008] S2: Call the adjacent batch data of the process parameter mapping record table, judge according to the temperature change range, reaction time interval and ratio fluctuation range, group and classify the batches that meet the conditions, and generate a batch process consistency grouping table;

[0009] S3: Based on the grouping situation of the batch process consistency grouping table, read the path number and data location of the first batch, compare the path numbers of the remaining batches in the group, establish the channel ownership relationship, and generate the batch channel path label structure.

[0010] S4: Based on the verified path information of the batch channel path label structure, read the associated running status and control signals, combine the associated time stamp with the path template, organize the staged path hierarchy information, and generate a staged path structure mapping table.

[0011] S5: calling the stage path structure mapping table directory structure, completing the arrangement and archiving of the batch data according to the path configuration, registering the corresponding relationship between the archiving position and the file number, and generating a batch data archiving path list.

[0012] As a further scheme of the present application, the process parameter mapping record table comprises batch number associated parameters, timestamp records, and material proportioning data sets, the batch process consistency grouping table comprises temperature variation range threshold values, reaction time interval threshold values, and proportioning floating interval values, the batch channel path label structure comprises path number comparison results, data attribution location identifiers, and channel attribution relationship chains, and the stage path structure mapping table comprises running state segmented combinations, control signal time sequence markers, and time marker hierarchical templates.

[0013] As a further scheme of the present application, the specific steps of S1 are as follows:

[0014] S101: acquiring temperature data in a reaction kettle, reaction time records, and material proportioning information, determining a reaction starting time according to a temperature variation trend, matching a proportioning batch and proportioning parameters in a corresponding time period, and generating a starting proportioning interval parameter set;

[0015] S102: calling batch numbers in the starting proportioning interval parameter set, combining proportioning time and chlorine gas feeding log records, screening flow data in a corresponding batch, and obtaining a chlorine gas feeding flow interval value;

[0016] S103: integrating temperature, time, proportioning, and flow parameters corresponding to batch numbers according to the chlorine gas feeding flow interval value and the starting proportioning interval parameter set, and generating a process parameter mapping record table.

[0017] As a further scheme of the present application, the specific steps of S2 are as follows:

[0018] S201: acquiring temperature, reaction time, and proportioning data of batches in the process parameter mapping record table, extracting parameter values of adjacent batches in batch order, judging whether the adjacent batches meet conditions according to a set temperature range, time interval, and proportioning floating standard, and generating a parameter difference judgment state table;

[0019] S202: screening batch groups having correlations according to adjacent batch information meeting conditions in the parameter difference judgment state table, identifying batch combinations having correlation orders, and classifying the batch combinations into the same group, and generating a continuous batch combination grouping sequence;

[0020] S203: Call the grouping number in the continuous batch combination grouping sequence, collect the temperature, reaction time and ratio data of the corresponding batch, mark the parameter information in the group, and form a batch process consistency grouping table.

[0021] As a further scheme of the present application, the specific steps of S3 are:

[0022] S301: According to the path number and data attribution position of the first batch in the batch process consistency grouping table, extract the node sequence and attribution mark information of the batch path, construct the basic structure of the channel path, and generate a path node mark set;

[0023] S302: Call the path node mark set, match the node sequence of the path number of the remaining batches in the group, identify the structural difference position and extract the node offset feature, calculate the comprehensive evaluation value of the node offset trend, and generate a node corresponding offset position set;

[0024] S303: According to the node corresponding offset position set, associate the data attribution position of the batch with the path label, establish the channel mapping relationship between the path nodes, and generate a batch channel path label structure.

[0025] As a further scheme of the present application, the specific calculation formula of the comprehensive evaluation value of the node offset trend is:

[0026] ;

[0027] Wherein, H represents the comprehensive evaluation value of the node offset trend, represents the structural difference position weight coefficient, represents the position offset of the rth node in the path number sequence, Δ represents the coordinate difference value of the rth node in the x-axis direction, Δ represents the coordinate difference value of the rth node in the y-axis direction, represents the node distribution correction factor, ‖ ‖ represents the vector module length of the rth node and its adjacent node, m represents the total number of the remaining batches in the group, and u represents the total number of the path nodes in the current group.

[0028] As a further scheme of the present application, the specific steps of S4 are:

[0029] S401: Based on the batch channel path label structure, identify the number and channel index of the path label, extract the corresponding running state and control signal, complete the classification and screening of the signals according to the path number and channel index, establish the corresponding relationship between the signals, and generate a path running control corresponding relationship quantity;

[0030] S402: calling the path running control corresponding relationship quantity, extracting the overlapping time interval according to the timestamp order signal, combining the path template for stage division, calculating the stage division characteristic value, matching the signal with the stage, and generating the stage associated signal time interval value;

[0031] S403: according to the stage associated signal time interval value, extracting the path hierarchical structure information, determining the belonging and order between paths, arranging and combining the stage path according to the time interval, establishing a multi-layer mapping relationship, and generating a stage path structure mapping table.

[0032] As a further scheme of the application, the specific calculation formula of the calculated stage division characteristic value is:

[0033] ;

[0034] Among them, The division characteristic value of the mth stage, The standardized time offset of the ith signal and the path template p, Indicates the sample variance of the time offset, Indicates the energy weight coefficient of the ith stage in the path template p, Indicates the spectral similarity index of the kth signal and the template p, The phase alignment factor of the path template p, Indicates the time window stretching coefficient of the template p, The baseline drift suppression amount of the template p.

[0035] As a further scheme of the application, the specific steps of S5 are:

[0036] S501: calling the stage path structure mapping table, arranging and archiving the batch data according to the configuration, storing the data according to the directory path, and obtaining the batch data arrangement result;

[0037] S502: according to the batch data arrangement result, registering the file number and storage location, corresponding each file number with the archive path, and generating the archive file number and storage location list;

[0038] S503: according to the path information in the archive file number and storage location list, integrating the hierarchical path according to the directory structure order, matching and arranging the path nodes with the corresponding file numbers into a list, and combing the path and number relationship of the archived data item by item, to obtain the batch data archive path list.

[0039] A chloroacetic acid production data storage system, comprising:

[0040] The process parameter arrangement module collects the starting temperature, duration and proportioning value of the reaction process, extracts the feeding batch number and chlorine feeding rate recorded in the batching stage, combines the timestamp information of the parameters, completes the time correlation and structure arrangement of the batch and parameters, and generates a process parameter mapping record table;

[0041] The batch grouping determination module calls a plurality of batch data adjacent in time in the process parameter mapping record table, performs conditional judgment according to a temperature difference, a reaction time interval and a proportioning change degree, classifies batches meeting process similar standards into a class, forms a batch process attribution structure, and generates a batch process consistency grouping table;

[0042] The path label establishment module extracts the path number and storage location of the first batch in each group according to the batch classification in the batch process consistency grouping table, checks whether the path numbers of the batches in the same group have the same structure identifier, binds the identification result with the batch information, establishes a corresponding channel attribution identifier, and generates a batch channel path label structure;

[0043] The stage path mapping module reads the corresponding control signal state and system running identifier based on the batch channel path label structure, identifies the signal change section and extracts the time marker segment by contrasting the control template, classifies according to the process logic order of the path nodes, constructs the structure level corresponding to the stage, and generates a stage path structure mapping table;

[0044] The batch archiving registration module calls the path number directory provided by the stage path structure mapping table, configures the path structure by stage, completes the storage and collection of batch data, records the archiving position and file number of the corresponding batch file, and generates a batch data archiving path list.

[0045] Compared with the prior art, the advantages and positive effects of the present application are that:

[0046] In the present application, the precise integration of batch data is realized through the cross collection of multiple source parameters and the association with time information. The dynamic judgment of the floating range of adjacent batch parameters improves the accuracy of process consistency identification. The establishment of channel attribution relationship ensures clear data structure, and the path level mapping combined with running state and time label enhances the stage data organization ability. Automatic archiving improves the data arrangement efficiency and traceability, and overall strengthens the structure and synergy of batch data management. BRIEF DESCRIPTION OF DRAWINGS

[0047] Figure 1 The figure is a step flowchart of the present application;

[0048] Figure 2 The figure is a system module diagram of the present application. DETAILED DESCRIPTION

[0049] In order to make the objects, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and not intended to limit the present application.

[0050] In the description of the present application, it should be understood that the terms "length", "width", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer" and the like indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, and are only used to facilitate the description of the present application and simplify the description, and therefore cannot be understood as indicating or implying that the device or element referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as limiting the present application. In addition, in the description of the present application, the meaning of "a plurality of" is two or more, unless otherwise explicitly and specifically limited.

[0051] Please refer to Figure 1 A method for storing data of chloroacetic acid production, comprising the following steps:

[0052] S1: Obtain the initial temperature, reaction time and material ratio data in the reaction kettle, extract the feed batch information and chlorine feed flow in the batching, and at the same time, combine the time information recorded by the data acquisition, associate and arrange the parameters with the batch number, and generate a process parameter mapping record table;

[0053] S2: Call the adjacent batch data in the process parameter mapping record table, judge according to the temperature change range, reaction time interval and ratio floating range, group and classify the batches that meet the parameter conditions, and generate a batch process consistency grouping table;

[0054] S3: According to the grouping situation of the batch process consistency grouping table, read the path number and data attribution position of the first batch, compare the path numbers of the remaining batches in the group, and establish the channel attribution relationship, and generate a batch channel path label structure;

[0055] S4: Based on the verified path information in the batch channel path label structure, read the associated running state and control signal, combine the associated time mark with the path template, arrange the path level information in stages, and generate a stage path structure mapping table;

[0056] S5: Call the directory structure in the stage path structure mapping table, complete the arrangement and archiving of batch data according to the path configuration, and register the corresponding relationship between the archiving position and the file number, and generate a batch data archiving path list.

[0057] The process parameter mapping record table includes batch number associated parameters, timestamp records, material ratio data set, the batch process consistency grouping table includes temperature change range threshold, reaction time interval threshold, ratio floating interval value, the batch channel path label structure includes path number comparison result, data attribution location identification, channel attribution relationship chain, the stage path structure mapping table includes running state segmented combination, control signal time sequence marker, time marker level template, the batch data archiving path list includes archiving directory structure tree, file number mapping relationship table, data storage location index.

[0058] The specific steps of S1 are:

[0059] S101: Obtain the temperature data in the reaction kettle, reaction time records and material ratio information, determine the reaction start time according to the temperature change trend, match the batch and ratio parameters in the corresponding time period, and generate the start batching interval parameter set;

[0060] The temperature data in the reaction kettle can be recorded in real time by a temperature sensor at a frequency of every minute and input into a data acquisition system for centralized management. The temperature change trend analysis takes whether the temperature rise rate reaches the set threshold as the basis for judgment. If the temperature increase in unit time reaches 1.5 degrees Celsius per minute or more, it can be considered as the time point of the start of the reaction. At the same time, the time stamp of this time point is determined by combining the reaction time record log. For example, if the temperature shows a clear upward trend at 10 o'clock, this time is marked as the start of the reaction. The material ratio information is recorded by the batching control system. Each batch of batching will be accompanied by time, batch number and the mass and proportion of each component. The batching interval can be set to extend 3 minutes before and after the start time, i.e. 9:57 to 10:03. From this time period, all material feeding records are selected, the component data of the corresponding batch is summarized to form the initial batching parameter set. For example, in this time interval, the batching operation numbered B20250518-01 is completed, component A is 30 kg, component B is 20 kg, and component C is 10 kg. The corresponding ratio is 30%, 40% and 30%. This record will be included in the initial parameter set for subsequent analysis.

[0061] S102: Call the batch number in the start batching interval parameter set, combine the batching time and chlorine gas feeding log records, and select the flow data in the corresponding batch to obtain the chlorine gas feeding flow interval value;

[0062] The batching time corresponding to batch number B20250518-01 is 10:01, and the flow data records within 5 minutes before and after this time point are extracted as the analysis interval by combining the log records of the chlorine feeding system. The interval is from 9:56 to 10:06, the chlorine feeding flow is collected by the flow meter at a frequency of every minute, and the sampling values such as 20.0, 22.5, 21.3, 20.8, 23.1, 22.2, 21.9, 20.6, 19.8, and 22.0 are recorded in the system log. The sliding average method can be used for smoothing processing to form a stable flow value interval. In the calculation process, 10 sample points are directly averaged to obtain an interval average flow of about 21.4 standard cubic meters per hour. This value is used as the representative parameter of chlorine feeding at the initial stage of the batching batch, and can be used for synchronous correlation analysis with temperature, batching information, etc.

[0063] S103: According to the chlorine feeding flow interval value and the initial batching interval parameter set, the temperature, time, batching and flow parameters corresponding to the batch number are integrated to generate a process parameter mapping record table;

[0064] The chlorine feeding flow data of batch number B20250518-01 is integrated with the corresponding initial batching parameter set to construct a mapping record table containing multiple key process fields. The record table needs to include: batch number, material feeding start time, temperature initial value, temperature maximum value, temperature change rate, batching ratio of each component, average chlorine feeding flow, and reaction duration, etc. The temperature initial value can be obtained by looking up the sensor record corresponding to the start time, such as 22 degrees Celsius. The temperature peak value is obtained by scanning the temperature curve of the corresponding batch, such as 38.5 degrees Celsius. The temperature change rate is obtained by dividing the difference between the two values by the time used. If the temperature rises from 22 to 38.5 in 15 minutes, the temperature rise rate is 1.1 degrees Celsius per minute. The batching information is displayed according to the batching system record as A component 30%, B component 40%, and C component 30%. The chlorine feeding flow is 21.4 standard cubic meters per hour obtained by the above analysis. The reaction duration is defined as the time used for the temperature to drop to 30% of the peak value after reaching the peak value. If it is 30 minutes, the above contents are summarized to form the process parameter record of the batch, which is used for subsequent process standardization or comparison analysis.

[0065] The specific steps of S2 are:

[0066] S201: Obtain the temperature, reaction time and batching ratio data of the batch in the process parameter mapping record table. Extract the parameter values of adjacent batches in batch order. According to the set temperature range, time interval and batching ratio floating standard, it is judged whether the adjacent batches meet the conditions, and a parameter difference judgment state table is generated;

[0067] Read the temperature, reaction time and ratio data of each batch from the process parameter mapping record table, sort all the data according to batch number or time sequence first, and ensure that the batch arrangement has time continuity. Extract the combination of two adjacent batches, and analyze the process parameter changes between them one by one. For each batch, calculate the temperature difference, reaction time difference and ratio floating value one by one. The temperature difference is the absolute difference between the two batches, for example, the temperature of the previous batch is 120℃, and the temperature of the next batch is 123℃, the temperature difference is 3℃; the reaction time difference is also calculated as the absolute value, for example, one batch is 90 minutes, and the other is 100 minutes, then the time difference is 10 minutes; the ratio floating is converted into percentage form, that is, 30%, 20%, 50%, and then compared with the difference value of each component, for example, the ratio of the next batch is 33%, 18%, 49%, then the floating value is estimated by adding the square of the difference value of the three components and then taking the square root, and the final floating value is controlled within 5%. Set the judgment standard: the temperature difference does not exceed 5℃, the reaction time difference does not exceed 10 minutes, and the ratio floating does not exceed 5%. Execute the above comparison one by one for all batch combinations, if a batch meets all the conditions, it is marked as conforming, if one of them exceeds the range, it is marked as not conforming. The comparison results of all combinations are summarized into a state list to determine whether each pair of batches is within the allowed process deviation.

[0068] S202: According to the parameter difference judgment state table, the information of the adjacent batches that meet the conditions is judged, the batch groups with correlation are screened, the batch combination with correlation sequence is identified, and the same group is classified, and the continuous batch combination grouping sequence is generated;

[0069] According to the judgment state list, all batch combinations that meet the conditions are analyzed for continuity. Starting from the first batch combination marked as conforming, the first and last batches are identified, and it is checked whether the next group still meets the conditions, if it meets the conditions, the combination is continued to expand, until a combination that does not meet the conditions appears, that is, the identification of a continuous batch group is completed. In this way, all batches are traversed from head to tail, and a batch set that continuously meets the conditions is constructed one by one. Each set is assigned an independent number for subsequent identification and tracking. For example, the first group is composed of batches B001, B002 and B003, and the second group is B005 and B006. In this way, all batches with process continuity are classified into groups, providing a basis for subsequent consistency analysis.

[0070] S203: Call the group number in the continuous batch combination grouping sequence, collect the temperature, reaction time and ratio data of the corresponding batches, mark the parameter information in the group, and form a batch process consistency grouping table;

[0071] Based on the generated consecutive batch combination grouping sequence, the temperature, reaction time, and proportion parameters of the corresponding batches are extracted from the original process records. All batches within the same group are summarized and archived sequentially. Data for each batch is independently labeled and categorized. For example, a group may include three batches, recording temperature, time, and proportion parameters such as 122℃, 85 minutes, and proportions of approximately 31%, 21%, and 48%, respectively. Detailed process parameters for each batch are displayed in a unified format. Simultaneously, the mean and standard deviation of each parameter within the group are calculated. For instance, if the average temperature for this group is 121℃, the average time is 86 minutes, and the average proportions are approximately 30%, 20%, and 50%, with the standard deviation controlled within a reasonable range, it indicates minimal parameter fluctuation within the group. The aggregated data for all groups forms a batch process consistency grouping table, providing parameter support for subsequent process quality verification and product traceability.

[0072] The specific steps for S3 are as follows:

[0073] S301: Based on the path number and data location of the first batch in the batch process consistency grouping table, extract the node sequence and attribution marker information of the path of that batch, construct the basic structure of the channel path, and generate a set of path node markers;

[0074] The first record in the batch process consistency grouping table can be considered the initial baseline. Its path number and data location serve as the basis for subsequent path structure construction. First, the path number contained in this record is read, for example, number P001. Then, the node sequence corresponding to P001 is found. The nodes may be N1, N2, N3, N4, etc. Each node has a unique identifier in the path table. Further, the attribution information corresponding to the nodes is extracted through the process definition table or attribution configuration file. For example, N1 belongs to "initial heating section", N2 belongs to "intermediate heat treatment", N3 belongs to "forming section", and N4 belongs to "cooling section". A key-value set is constructed with the node identifier as the key and the attribution location as the value, for example, {N1: initial heating section, N2: intermediate heat treatment, N3: forming section, N4:}. In the cooling section, if some nodes are not assigned affiliations during the construction process, they are inferred based on the node naming rules. For example, if the name N1 contains the keyword "heat", it is classified as a heating area, or it is marked as an "undefined area" using the default rules. The order of path nodes retains the original definition to ensure consistency with the execution order of path numbers. The basic channel structure can be formed through this node-affiliation mapping set. If the path structure is long during the construction process, the affiliation can be identified segment by segment using a sliding window method, which is convenient for handling a large number of node paths. If the path has more than 10 nodes, the window width can be set to 3, and the local structure can be processed and constructed in sequence, and finally summarized into a complete node set.

[0075] S302: Call the path node tag set, perform node sequence matching on the path numbers of the remaining batches within the group, identify the structural difference positions and extract the node offset features, calculate the comprehensive evaluation value of the node offset trend, and generate the set of offset positions corresponding to the nodes.

[0076] The specific formula for calculating the comprehensive evaluation value of node offset trend is as follows:

[0077] ;

[0078] Where H represents the comprehensive evaluation value of the node offset trend, The positional weighting coefficients represent structural differences. Δ represents the offset of the r-th node in the path number sequence. Δ represents the coordinate difference of the r-th node in the x-axis direction. This represents the difference in coordinates of the r-th node along the y-axis. Represents the node distribution correction factor, || ‖ represents the vector magnitude of the line connecting the r-th node to its adjacent nodes, m represents the total number of remaining batches within the group, and u represents the total number of path nodes in the current group.

[0079] Structural difference location weighting coefficient The value is 0.85, selected based on the empirical coefficient range of 0.8-0.9 in the path loss model of the IEEE 802.11 standard;

[0080] Node distribution correction factor The value is set to 1.2, referencing the commonly used correction factor range of 1.0-1.5 in wireless sensor network node distribution optimization research.

[0081] The total number of remaining batches within the group is m=15, which is calculated based on the batch processing data recorded in the industrial IoT device logs.

[0082] The current total number of path nodes in the group is u=8, which is obtained from real-time monitoring data by the path planning system.

[0083] The offset of the third node position Δp3 = 2.5mm was obtained by taking the average of three consecutive measurements of the deviation between the actual position of the node and the standard path coordinates using a laser rangefinder.

[0084] The x-axis coordinate difference Δx3 = 1.2 mm and the y-axis coordinate difference Δy3 = 2.0 mm are obtained by processing the three-dimensional coordinate data collected by the displacement sensor through Kalman filtering.

[0085] Vector Magnitude || 3‖=3.5mm, calculate the Euclidean distance based on the coordinate data of the adjacent node (2,4):

[0086] ;

[0087] Substitute into the formula to calculate the component at the 3rd node:

[0088] ;

[0089] Repeatedly calculating the components of all 8 nodes and summing them yields H = 9.632. This value reflects the overall offset trend strength of the current group path nodes. When the H value exceeds the threshold of 8.0, the offset location set generation mechanism is triggered, and the system automatically records each node. Coordinate data greater than 1.0 mm form a set of offset positions corresponding to nodes.

[0090] S303: Based on the offset position set corresponding to the node, the path label is associated with the data location of the batch, the channel mapping relationship between the path nodes is established, and the batch channel path label structure is generated.

[0091] Based on the node offset position set, the location of each batch of data is processed one by one. The path node sequence of each batch is used as the primary key, and labels are set according to the offset features. For example, if the original node N4 is replaced by N5 in a certain batch, then N5 is marked as "original N4 replacement node" in the current path, forming the labeled path sequence N1, N2, N3, N5 (original N4 replacement). If there is a missing node, it is marked as "missing" in the label. For example, if the path is N1, N2, N3, then "original N4 missing" is marked in the 4th position. If a new node N6 is added to the path after N2 in a certain batch, it is marked as N2, N6 (new), N3. Offset features combined with path structure can generate a path label sequence. Each label record contains a node identifier, position index, and offset type description. Mapping relationships are built between nodes, such as establishing a replacement mapping between N5 and N4, and establishing a relative position mapping between N6 and the node before insertion. The entire label structure can form a path label network. Each node in the network has a source description, such as N5 being labeled as "original path N4 position replacement". For batches with different path numbers, the final output path label structure includes a node sequence, node label, attribution mark, and structural offset information, identifying changes within the channel and ensuring the integrity of path construction and structure resolution.

[0092] The specific steps of S4 are as follows:

[0093] S401: Based on the batch channel path label structure, identify the path label number and channel index, extract the corresponding running status and control signal, classify and filter the signal according to the path number and channel index, establish the correspondence between the signals, and generate the path running control correspondence quantity.

[0094] Based on the batch channel path label structure, the expression methods for path numbers and channel indices must first be clarified. A unified label format can be set, such as path number as P followed by two digits, channel index as C followed by two digits, batch number as B followed by two digits, and label format as P01-B05-C03. All path label information is parsed using regular expressions to extract path numbers and channel indices. Signal data comes from the control system database or production system logs. For each label record, its associated running status field and control signal field need to be called. Status fields can be set to "RUNNING", "WAITING", "FINISHED", etc., and control signal fields to "C_IN", "C_OUT", etc. After extraction, the signals are classified. For example, all paths with control signals of "C_IN" and status of "RUNNING" are clustered, forming a classification structure by combining path numbers and channel indices. Then, a key-value structure is formed using path numbers and channel indices, such as P01 and C03, pointing to the status and control signal content. Next, based on the existing classification, path combinations with specified states are filtered, such as a state defined as "WAITING" and a control signal as "C_OUT". The path number and channel index combinations that meet the criteria are compared and filtered one by one. Finally, a mapping structure is constructed, combining the path number, channel index, state, and control signal to form a path operation control correspondence. This structure can be stored using a data dictionary or written to a database table. Each row in the table corresponds to a path number and channel index combination and its corresponding state and control signal. For example, if a path P02-B03-C04 corresponds to the state "WAITING" and the control signal "C_OUT", then a complete control relationship record is formed.

[0095] S402: Call the path operation control corresponding relationship quantity, sort the signals according to the timestamp, extract the overlapping time interval, and divide the path into stages in combination with the path template. Calculate the stage division feature value, match the signal with the stage, and generate the stage-related signal time interval value.

[0096] The specific formula for calculating the feature values ​​in the computation stage is as follows:

[0097] ;

[0098] in, This represents the partitioning feature value of the m-th stage. This represents the normalized time offset between the i-th signal and the path template p. The sample variance representing the time offset. Let represent the energy weight coefficient of the i-th stage in the path template p, and q represent the phase alignment factor of the path template p. This represents the spectral similarity index between the k-th signal and template p. Let p be the phase alignment factor of the path template. This represents the time window scaling factor for template p. The amount of baseline drift suppression represented by template p;

[0099] Standardized time offset The difference between the signal timestamp and the corresponding timestamp of template p is used to calculate the difference. In a certain monitoring data, the signal timestamp sequence is [12.3s, 14.7s, 16.2s], and the corresponding timestamp of template p is [12.0s, 14.5s, 16.0s]. The calculation yields... , , ;

[0100] Sample variance Based on the above offset calculation , where 0.23s is the average offset;

[0101] Energy weighting coefficient Based on the signal energy ratio setting, the measured signal energy distribution is [0.4, 0.35, 0.25], which is then normalized to obtain... , , ;

[0102] Spectral similarity index The cosine similarity between the signal spectrum and the template spectrum is calculated to obtain the following from a certain spectrum data. , Phase alignment factor Based on the signal phase difference setting, the measured phase difference is 0.15 rad. Time window scaling factor Based on the signal sampling rate and template matching degree settings, when the sampling rate matching degree is 95%, take... ;

[0103] Baseline drift suppression Based on the baseline noise level, a noise RMS value of 0.02V is taken as... ;

[0104] Substitute into the formula to calculate:

[0105] The first term's square root is divided into... The square root value is 6.12;

[0106] The second item is ;

[0107] final .

[0108] The results show that when the stage division feature value reaches the threshold of 7.0, the time interval division operation is triggered. The larger the feature value, the higher the matching degree between the signal and the template. When the feature value exceeds the preset threshold, a valid time interval division result is generated.

[0109] S403: Based on the time interval values ​​of the stage-related signals, extract the path hierarchy information, determine the attribution and order between paths, arrange and combine stage paths according to the time interval, establish multi-level mapping relationships, and generate a stage path structure mapping table.

[0110] Based on the obtained time interval values ​​of the stage-related signals, further extraction of path hierarchy information is required. First, the path hierarchy classification criteria need to be defined. For example, based on channel number, the main channel can be defined as a first-level path, and auxiliary or branch channels as second-level paths. The classification criteria can be based on the range or rules of the channel number. The channel number extracted from the path label is used to determine its hierarchical structure. Then, the temporal order relationship between different paths in each stage is analyzed. For example, the feeding stage time of path P01 is from 10:00 to 10:15, and the feeding stage time of path P02 is from 10:20 to 10:35, thus determining that P01 precedes P02. Comparing the time of all path stages, they are arranged and combined according to their temporal order to form a continuous stage path flow. The path stage structures are combined sequentially to construct a multi-layer mapping structure. Each layer represents a path hierarchy, containing multiple stages, and each stage corresponds to one or more path numbers, their time intervals, and signals. The stage path structure mapping table generated in this way clarifies the affiliation, order, and signal association relationships of each stage path in different hierarchical structures. For example, a primary path includes a feeding stage and a processing stage. The feeding stage consists of paths P01 and P02, and the processing stage consists of path P03. The start and end times and signals of each stage are directly obtained from the time interval values ​​of the associated signals of the previous stage, thus forming a complete multi-layer path mapping structure for path-level control analysis and data tracking.

[0111] The specific steps of S5 are as follows:

[0112] S501: Call the stage path structure mapping table, organize and archive batch data according to the configuration, classify and store the data according to the directory path, and obtain the batch data organization results;

[0113] When calling the stage path structure mapping table, the path structure configuration set in the archiving system must be loaded first. This configuration includes multiple hierarchical fields, such as first-level directory category, second-level time category, and third-level business number. The path category type field can be used to filter the batch data and select the matching mapping rule. For example, in a document archiving application, if the batch data consists of 2023 contract files, the path structure "Contract Type / Year / Project Number" should be selected. Then, the metadata fields in the batch data need to be extracted, such as "File Type" as "Contract," "Creation Time" as "May 2023," and "Project Number" as "PJT001." A multi-level directory structure is constructed based on the mapping relationship, creating folders named "Contract Type," "2023," and "PJT001" sequentially from the root path, and classifying the corresponding data under the target path. During execution, a hierarchical iteration method can be used to complete path judgment and directory generation. If a path node does not exist, it is created immediately. The directory name should be consistent with the metadata field content. Each data entry in a batch must have its archiving path paired with its file number. A unique file identifier can be bound to the generated path and written to the archiving log. For example, file number F123456 should be archived to "Archived Area / Contracts / 2023 / PJT001," and this information should be recorded in the database or text log. If data fields are missing or incomplete, such as without a project number, it should be placed in the "Unspecified" directory, forming a structure like "Contracts / 2023 / Unspecified." During the archiving path generation process, duplicate paths and non-standard naming should be avoided. Special characters such as " / ", "\", ":", and "*" are prohibited in directory names, and standard character set encoding should be used consistently. After classification and archiving are completed, each data entry will be clearly located in its corresponding directory, forming a unified organizational structure, thus completing the classification and archiving of the batch data.

[0114] S502: Based on the batch data processing results, register the file number and storage location, associate each file number with the archive path, and generate a list of archive file numbers and storage locations;

[0115] Based on the batch data processing results, the file number and actual archiving path of each data entry need to be extracted to construct a list of correspondences between file numbers and storage locations. First, the unique ID field of each data entry is extracted. For example, if the ID is F123456, the corresponding archiving path is "Archive Area / Contracts / 2023 / PJT001". This correspondence is recorded in the archiving list. The archiving list can be stored as simple text, a table, or a structured file. The field structure includes file number, file name, archiving path, archiving time, etc. During execution, batch processing is performed by traversing the data structure in batches, while simultaneously verifying the existence of the path using a file system path verification function to perform directory verification. If the path is abnormal, such as non-existent or access error, the file should be marked as abnormal, and its abnormality description field should be recorded in the archiving list. If the archiving path involves multiple nested server directories, such as a path containing "host identifier: root path / intermediate path / target path", the complete path needs to be recorded for subsequent retrieval. Each file number corresponds one-to-one with its path. After the list is completed, the file numbers should be uniformly sorted in ascending order for easy subsequent quick querying and path tracing. The archive list can be uploaded to the management system's archive module or imported into a database table to form a long-term index, facilitating auditing, querying, and exporting operations after archiving.

[0116] S503: Based on the archived file number and the path information in the storage location list, integrate the hierarchical paths according to the directory structure order, match the path nodes with the corresponding file numbers and organize them into the list, sort out the path and number relationship of the archived data item by item, and obtain the batch data archived path list.

[0117] Once the archive list is generated, it needs to be parsed and integrated line by line based on the archive path field information to form a complete hierarchical path structure list. During parsing, each path is segmented hierarchically, and node fields such as "Contract Category," "2023," and "PJT001" are extracted to form a path node array. The hierarchical path structure can be constructed using nested data structures to create a tree-like mapping, with each node associated with its corresponding set of file numbers. File numbers have a clear affiliation within the hierarchical structure, requiring mapping to be established at each level of node. For example, the "2023" node under the "Contract Category" node, and then the "PJT001" node, with a file number list added to the structure of each level of node to achieve path-to-file number location from the root node to the leaf node. During the organization process, the list content should be constructed according to the depth of the directory structure, outputting and organizing each set of path structures and their file numbers to form a clear and readable archive path list. If some data paths are incomplete or have inconsistent hierarchies, such as only reaching "Contract Category / 2023," they are categorized under the default child node "Unspecified" to ensure the consistency and completeness of the path structure. Files within each directory structure can be sorted by their numerical order, resulting in a consistent output format. The final output is a list of paths in the format of "path structure: corresponding file number set," with a clear hierarchical structure that facilitates review and auditing, forming a complete archive batch path index dataset.

[0118] Please see Figure 2 A chloroacetic acid production data storage system, comprising:

[0119] The process parameter processing module collects the initial temperature, duration, and ratio values ​​of the reaction process, extracts the batch number and chlorine feed rate recorded during the batching stage, and combines the timestamp information of the parameters to complete the time association and structure processing of batches and parameters, generating a process parameter mapping record table.

[0120] The batch grouping and determination module calls up data from multiple batches that are adjacent in time in the process parameter mapping record table, and makes conditional judgments based on temperature difference, reaction time interval and the degree of change in ratio. Batches that meet the same process standard are grouped into one category, forming a batch process affiliation structure and generating a batch process consistency grouping table.

[0121] The path label establishment module extracts the path number and storage location of the first batch in each group based on the batch classification in the batch process consistency grouping table, verifies whether the path numbers of batches in the same group have the same structural identifier, binds the identification results with the batch information, establishes the corresponding channel belonging identifier, and generates the batch channel path label structure.

[0122] The stage path mapping module reads the corresponding control signal status and system operation identifier based on the batch data associated with the path number in the batch channel path label structure, identifies the signal change section and extracts the time stamp segment by referring to the control template, collects and classifies according to the process logic order of the path node, constructs the structural hierarchy corresponding to the stage, and generates a stage path structure mapping table.

[0123] The batch archiving registration module calls the path number directory provided by the stage path structure mapping table, configures the path structure hierarchically by stage, completes the storage and collection of batch data, pairs and records the archiving location and file number of the corresponding batch file, and generates a list of batch data archiving paths.

[0124] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments that can be applied to other fields. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A method for storing chloroacetic acid production data, characterized in that, Includes the following steps: S1: Obtain the initial temperature of the reactor, reaction time and material ratio, extract the feed batch and chlorine flow rate data, combine with time information, organize the parameters with batch numbers, and generate a process parameter mapping record table. S2: Call the adjacent batch data of the process parameter mapping record table, judge according to the temperature change range, reaction time interval and ratio fluctuation range, group and classify the batches that meet the conditions, and generate a batch process consistency grouping table; S3: Based on the grouping situation of the batch process consistency grouping table, read the path number and data location of the first batch, compare the path numbers of the remaining batches in the group, establish the channel ownership relationship, and generate the batch channel path label structure. S4: Based on the verified path information of the batch channel path label structure, read the associated running status and control signals, combine the associated time stamp with the path template, organize the staged path hierarchy information, and generate a staged path structure mapping table. S5: Call the stage path structure mapping table directory structure, complete the sorting and archiving of batch data according to the path configuration, register the correspondence between the archiving location and the file number, and generate a batch data archiving path list.

2. The method for storing chloroacetic acid production data according to claim 1, characterized in that, The process parameter mapping record table includes batch number associated parameters, timestamp records, and material ratio data sets. The batch process consistency grouping table includes temperature change range thresholds, reaction time interval thresholds, and ratio fluctuation range values. The batch channel path label structure includes path number comparison results, data location identifiers, and channel ownership relationship chains. The stage path structure mapping table includes operating status segment combinations, control signal timing markers, and time marker hierarchy templates. The batch data archiving path list includes an archiving directory structure tree, a file number mapping relationship table, and a data storage location index.

3. The method for storing chloroacetic acid production data according to claim 1, characterized in that, The specific steps of S1 are as follows: S101: Acquire temperature data, reaction time records and material ratio information inside the reactor, determine the reaction start time based on the temperature change trend, match the batch and ratio parameters of the corresponding time period, and generate the parameter set of the initial batching interval. S102: Call the batch number in the initial batching interval parameter set, combine the batching time and chlorine feed log record, filter the flow data in the corresponding batch, and obtain the chlorine feed flow interval value; S103: Based on the chlorine feed flow rate range and the initial batching range parameter set, integrate the temperature, time, ratio and flow rate parameters corresponding to the batch number to generate a process parameter mapping record table.

4. The method for storing chloroacetic acid production data according to claim 3, characterized in that, The specific steps of S2 are as follows: S201: Obtain the temperature, reaction time and ratio data of each batch in the process parameter mapping record table, extract the parameter values ​​of adjacent batches according to the batch order, and determine whether adjacent batches meet the conditions based on the set temperature range, time interval and ratio fluctuation standard, and generate a parameter difference judgment status table. S202: Based on the parameter differences, determine the adjacent batch information that meets the conditions in the status table, filter the batch groups with correlation, identify the batch combinations with correlation order, and classify them into the same group to generate a continuous batch combination grouping sequence. S203: Call the group number in the continuous batch combination grouping sequence, collect the temperature, reaction time and ratio data of the corresponding batch, mark the parameter information within the group, and summarize to form a batch process consistency grouping table.

5. The method for storing chloroacetic acid production data according to claim 4, characterized in that, The specific steps for S3 are as follows: S301: Based on the path number and data location of the first batch in the batch process consistency grouping table, extract the node sequence and attribution marker information of the path of that batch, construct the basic structure of the channel path, and generate a set of path node markers; S302: Call the path node tag set, perform node sequence matching on the path numbers of the remaining batches within the group, identify the structural difference positions and extract the node offset features, calculate the comprehensive evaluation value of the node offset trend, and generate the node corresponding offset position set; S303: Based on the offset position set corresponding to the node, the data location of the batch is associated with path labels, the channel mapping relationship between path nodes is established, and the batch channel path label structure is generated.

6. The method for storing chloroacetic acid production data according to claim 5, characterized in that, The specific formula for calculating the comprehensive evaluation value of the offset trend of the computing nodes is as follows: ； Where H represents the comprehensive evaluation value of the node offset trend, The positional weighting coefficients represent structural differences. Δ represents the offset of the r-th node in the path number sequence. Δ represents the coordinate difference of the r-th node in the x-axis direction. This represents the difference in coordinates of the r-th node along the y-axis. Represents the node distribution correction factor, || ‖ represents the vector magnitude of the line connecting the r-th node to its adjacent nodes, m represents the total number of remaining batches within the group, and u represents the total number of path nodes in the current group.

7. The method for storing chloroacetic acid production data according to claim 5, characterized in that, The specific steps of S4 are as follows: S401: Based on the batch channel path label structure, identify the path label number and channel index, extract the corresponding running status and control signal, classify and filter the signal according to the path number and channel index, establish the correspondence between the signals, and generate the path running control correspondence quantity. S402: Call the path operation control corresponding relationship quantity, sort the signal according to the timestamp, extract the overlapping time interval, and divide the path into stages in combination with the path template, calculate the stage division feature value, match the signal with the stage, and generate the stage-related signal time interval value. S403: Based on the time interval values ​​of the stage-related signals, extract the path hierarchy information, determine the attribution and order between paths, arrange and combine stage paths according to the time interval, establish multi-level mapping relationships, and generate a stage path structure mapping table.

8. The method for storing chloroacetic acid production data according to claim 7, characterized in that, The specific calculation formula for the feature values ​​in the calculation stage is as follows: ； in, This represents the partitioning feature value of the m-th stage. This represents the normalized time offset between the i-th signal and the path template p. The sample variance representing the time offset. Let represent the energy weight coefficient of the i-th stage in the path template p, and q represent the phase alignment factor of the path template p. This represents the spectral similarity index between the k-th signal and template p. Let p be the phase alignment factor of the path template. This represents the time window scaling factor for template p. This represents the amount of baseline drift suppression for template p.

9. The method for storing chloroacetic acid production data according to claim 7, characterized in that, The specific steps of S5 are as follows: S501: Call the stage path structure mapping table, organize and archive the batch data according to the configuration, classify and store the data according to the directory path, and obtain the batch data organization result; S502: Based on the batch data processing results, register the file number and storage location, associate each file number with the archive path, and generate a list of archived file numbers and storage locations; S503: Based on the archived file number and the path information in the storage location list, integrate the hierarchical paths according to the directory structure order, match the path nodes with the corresponding file numbers and organize them into the list, sort out the path and number relationship of the archived data item by item, and obtain the batch data archived path list.

10. A chloroacetic acid production data storage system, characterized in that, A method for storing chloroacetic acid production data according to any one of claims 1-9, wherein the system comprises: The process parameter processing module collects the initial temperature, duration, and ratio values ​​of the reaction process, extracts the batch number and chlorine feed rate recorded during the batching stage, and combines the timestamp information of the parameters to complete the time association and structure processing of batches and parameters, generating a process parameter mapping record table. The batch grouping determination module calls up multiple batches of data that are adjacent in time in the process parameter mapping record table, and makes conditional judgments based on temperature difference, reaction time interval and the degree of change in ratio. Batches that meet the same process standard are grouped into one category to form a batch process affiliation structure and generate a batch process consistency grouping table. The path label establishment module extracts the path number and storage location of the first batch in each group based on the batch classification in the batch process consistency grouping table, verifies whether the path numbers of batches in the same group have the same structural identifier, binds the identification results with the batch information, establishes the corresponding channel belonging identifier, and generates the batch channel path label structure. The stage path mapping module reads the corresponding control signal status and system operation identifier based on the batch data associated with the path number in the batch channel path label structure, identifies the signal change segment and extracts the time stamp segment by referring to the control template, collects and classifies according to the process logic order of the path node, constructs the structural hierarchy corresponding to the stage, and generates a stage path structure mapping table. The batch archiving registration module calls the path number directory provided by the stage path structure mapping table, configures the path structure hierarchically according to the stage, completes the storage and collection of batch data, pairs and records the archiving location and file number of the corresponding batch file, and generates a batch data archiving path list.

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