Chloroacetic acid production data storage method and system

Abstract

The invention relates to the technical field of industrial process control, in particular to a chloroacetic acid production data storage method and system, and the method comprises the following steps: obtaining an initial temperature, reaction time and ratio, extracting a feeding batch and chlorine flow, sorting a parameter and batch correspondence table, judging the process consistency of adjacent batches, generating a grouping table, and establishing a channel label structure. Path level information is sorted, a stage path table is generated, data archiving is completed, and the numbering relation is registered. According to the method, accurate integration of batch data is realized through cross acquisition of multi-source parameters and time information association. And the process consistency identification accuracy is improved based on the dynamic judgment of the adjacent batch parameter floating range. The establishment of the channel affiliation relationship ensures that the data structure is clear, the path hierarchical mapping is combined with the operation state and the time label, and the staged data organization capability is enhanced. And the data arrangement efficiency and traceability are improved through automatic filing, and the constitutive property and collaboration of batch data management are integrally enhanced.

Description

Technical Field

[0001] The present invention relates to the technical field of industrial process control, and in particular to a chloroacetic acid production data storage method and system. Background Art

[0002] The field of industrial process control technology encompasses the technologies for monitoring, regulating, and managing various types of equipment, parameters, and operational links in industrial production processes. The core of this technical field is the real-time collection and adjustment of key process parameters such as temperature, pressure, flow, and ratio through automated control methods to ensure the continuity, stability, and safety of the production process. From a systemic perspective, industrial process control encompasses multiple aspects, including process detection technology, actuator control, electrical control systems, process parameter optimization, and information management. It is widely used in industrial scenarios involving continuous and batch production, such as chemical, pharmaceutical, metallurgical, and energy industries, and is an important basic technology system supporting the efficiency and quality of modern industrial operations.

[0003] The chloroacetic acid production data storage method refers to a data processing method for structured collection, classified storage, and management of data generated during the industrial synthesis and purification of chloroacetic acid. The patent's subject matter covers the collection of information such as material ratios, temperature control time, reaction rates, and operation records for subsequent distillation and purification steps during the chloroacetic acid reaction phase. This information is then stored in a relational database using a predefined field format based on production batches. Specifically, the data from each stage is organized and archived through methods such as sampling frequency setting, data timestamp binding, field labeling, and automatic file directory generation.

[0004] In the process of data collection and storage, existing technologies have a disconnect between batch identification and parameter information. Key information such as material ratios and temperature control parameters are often stored in static fields, lacking effective binding to specific batches in the time dimension. This leads to confusion or inaccurate traceability of data during later tracing. In the process judgment of adjacent batches, most existing methods rely on static rules and lack a dynamic judgment mechanism based on the parameter fluctuation range. This easily overlooks differences in process consistency under subtle fluctuations, thereby affecting the accuracy of process optimization and anomaly identification. In terms of archiving path management, data files generally adopt manual settings or fixed structures, and no systematic mapping relationship between paths and batch ownership is established, resulting in frequent path mismatches and unclear data ownership. In path hierarchy generation and stage mapping, existing methods lack the integration of operating status and control signals, resulting in the path structure failing to effectively reflect the actual distribution of the operating process. File directory registration is scattered during the archiving process, and no automated collection based on path configuration has been formed, affecting the efficiency and consistency of data collation between batches. For example, in the context of the pharmaceutical industry where production batches are growing rapidly, existing technologies are prone to generating duplication of work and retrieval redundancy in multi-batch data calls and path retrieval, reducing the overall efficiency of data management. Summary of the Invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose a chloroacetic acid production data storage method and system.

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

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

[0008] S2: calling the adjacent batch data in the process parameter mapping record table, judging based on the temperature variation range, reaction time interval and ratio floating range, grouping and classifying the batches that meet the conditions, and generating a batch process consistency grouping table;

[0009] S3: Read the path number and data attribution location of the first batch according to the grouping status of the batch process consistency grouping table, compare the path numbers of the remaining batches in the group, establish channel attribution relationships, and generate a batch channel path label structure;

[0010] S4: Based on the verified path information of the batch channel path tag structure, read the associated operation status and control signal, combine the associated time stamp with the path template, organize the staged path hierarchy information, and generate a stage path structure mapping table;

[0011] S5: calling the stage path structure mapping table directory structure, completing the sorting and archiving of 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 solution of the present invention, 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 floating interval values; the batch channel path label structure includes path number comparison results, data attribution location identifiers, and channel attribution relationship chains; the stage path structure mapping table includes operating status segment combinations, control signal timing tags, and time tag hierarchical 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.

[0013] As a further solution of the present invention, the specific steps of S1 are:

[0014] S101: Obtain temperature data, reaction time records, and material ratio information in the reactor, determine the reaction start time based on the temperature change trend, match the batch and ratio parameters within the corresponding time period, and generate a starting batch interval parameter set;

[0015] S102: calling the batch number in the initial batching interval parameter set, combining the batching time and the chlorine feeding log record, filtering the flow data in the corresponding batch, and obtaining the chlorine feeding flow interval value;

[0016] S103: Integrate the temperature, time, ratio and flow parameters corresponding to the batch number according to the chlorine feed flow interval value and the initial batching interval parameter set to generate a process parameter mapping record table.

[0017] As a further solution of the present invention, the specific steps of S2 are:

[0018] S201: Obtaining the temperature, reaction time, and ratio data of the batches in the process parameter mapping record table, extracting the parameter values ​​of adjacent batches in batch order, determining whether the adjacent batches meet the conditions based on the set temperature range, time interval, and ratio floating standard, and generating a parameter difference judgment status table;

[0019] S202: Determine adjacent batch information that meets the conditions in the status table based on the parameter difference, screen associated batch groups, identify batch combinations with an associated sequence, and group them into the same group to generate a continuous batch combination grouping sequence;

[0020] 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 group table.

[0021] As a further solution of the present invention, the specific steps of S3 are:

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

[0023] S302: calling the path node tag set, performing node sequence matching on the path numbers of the remaining batches in the group, identifying the structural difference positions and extracting node offset features, calculating the comprehensive evaluation value of the node offset trend, and generating a node corresponding offset position set;

[0024] S303: Based on the node corresponding offset position set, path labels are associated with the data attribution locations of the batch, a channel mapping relationship between path nodes is established, and a batch channel path label structure is generated.

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

[0026]

[0027] Among them, H represents the comprehensive evaluation value of the node deviation trend, α c Represents the structural difference position weight coefficient, Δp r Represents the position offset of the rth node in the path number sequence, Δx r Represents the coordinate difference of the rth node in the x-axis direction, Δy r Represents the coordinate difference of the rth node in the y-axis direction, β d represents the node distribution correction factor, Represents the vector modulus of the line connecting the rth node and its adjacent nodes, m represents the total number of remaining batches in the group, and u represents the total number of nodes in the current group path.

[0028] As a further solution of the present invention, the specific steps of S4 are:

[0029] S401: Based on the batch channel path label structure, identify the path label number and channel index, extract the corresponding operation status and control signal, classify and filter the signals according to the path number and channel index, establish a correspondence between the signals, and generate a path operation control correspondence quantity;

[0030] S402: calling the path operation control correspondence quantity, sorting the signals according to the timestamps, extracting the overlapping time intervals, and dividing the stages in combination with the path template, calculating the stage division feature value, matching the signals with the stages, and generating the stage-associated signal time interval value;

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

[0032] As a further solution of the present invention, the specific calculation formula for dividing the characteristic value in the calculation stage is:

[0033]

[0034] Among them, F m represents the partition eigenvalue of the mth stage, represents the normalized time offset between the ith signal and the path template p, σ τ represents the sample variance of the time offset, represents the energy weight coefficient of the i-th stage in the path template p, represents the spectrum similarity index between the kth signal and template p, α p is the phase alignment factor of the path template p, λ p represents the time window expansion coefficient of template p, γ p Represents the baseline drift suppression amount of template p.

[0035] As a further solution of the present invention, the specific steps of S5 are:

[0036] 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 result;

[0037] S502: Register the file numbers and storage locations based on the batch data sorting results, associate each file number with an archiving path, and generate a list of archived file numbers and storage locations;

[0038] S503: Based on the archive file number and the path information in the storage location list, the hierarchical paths are integrated in the order of the directory structure, the path nodes are matched with the corresponding file numbers and sorted into columns, and the path and number relationship of the archive data is sorted out item by item to obtain a 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 ratio values ​​of the reaction process, extracts the feed batch number and chlorine feed rate recorded in the batching stage, combines the timestamp information of the parameters, completes the time association and structure arrangement of the batches and parameters, and generates a process parameter mapping record table;

[0041] The batch grouping determination module calls the data of multiple batches with adjacent time in the process parameter mapping record table, performs conditional judgment based on temperature difference, reaction time interval and ratio change degree, classifies batches that meet the process similarity standards into one category, 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 of each group according to the batch classification in the batch process consistency grouping table, verifies whether the path numbers of batches in the same group have the same structure identifier, binds the identification result with the batch information, establishes the corresponding channel attribution identifier, and generates a batch channel path label structure;

[0043] 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 mark segment according to the control template, classifies the path nodes according to the process logic sequence, constructs the structural hierarchy corresponding to the stage, and generates a stage path structure mapping table;

[0044] The batch filing 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 the filing location of the corresponding batch file with the file number, and generates a batch data filing path list.

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

[0046] In this invention, precise batch data integration is achieved through cross-collection of multi-source parameters and correlation with time information. Dynamic judgment based on the floating range of parameters of adjacent batches improves the accuracy of process consistency identification. The establishment of channel affiliation ensures a clear data structure, and path hierarchical mapping combines operating status and time tags to enhance stage-by-stage data organization capabilities. Automated archiving improves data organization efficiency and traceability, and overall strengthens the structural and collaborative nature of batch data management. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 Schematic diagram of the steps of the present invention;

[0048] Figure 2 It is a system module diagram of the present invention. DETAILED DESCRIPTION

[0049] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention 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 invention and are not intended to limit the present invention.

[0050] In the description of the present invention, it should be understood that the terms "length," "width," "up," "down," "front," "back," "left," "right," "vertical," "horizontal," "top," "bottom," "inside," "outside," and the like, indicating positions or relationships, are based on the positions or relationships shown in the accompanying drawings and are intended only to facilitate the description of the present invention and simplify the description. They do not indicate or imply that the devices or elements referred to must have a specific orientation, be constructed, or operate in a specific orientation. Therefore, they should not be construed as limiting the present invention. Furthermore, in the description of the present invention, "plurality" means two or more, unless otherwise expressly and specifically defined.

[0051] See also Figure 1 A method for storing chloroacetic acid production data comprises the following steps:

[0052] S1: Obtain the starting temperature, reaction time, and material ratio data in the reactor, extract the feed batch information and chlorine feed flow rate from the ingredients, and combine the time information of the data collection record to associate 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, make judgments based on the temperature variation 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 of the batch process consistency grouping table, read the path number and data attribution location of the first batch, compare the path numbers of the remaining batches in the group, establish the channel attribution relationship, and generate the batch channel path label structure;

[0055] S4: Based on the verified path information in the batch channel path tag structure, read the associated operation status and control signal, combine the associated time stamp with the path template, organize the staged path hierarchy information, and generate a stage path structure mapping table;

[0056] S5: Call the directory structure in the stage path structure mapping table, complete the batch data sorting and archiving according to the path configuration, register the corresponding relationship between the archiving location 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, and material ratio data sets; the batch process consistency grouping table includes temperature change range thresholds, reaction time interval thresholds, and ratio floating interval values; the batch channel path label structure includes path number comparison results, data attribution location identifiers, and channel attribution relationship chains; the stage path structure mapping table includes operating status segment combinations, control signal timing tags, and time tag hierarchical 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.

[0058] The specific steps of S1 are:

[0059] S101: Obtain temperature data, reaction time records, and material ratio information in the reactor, determine the reaction start time based on the temperature change trend, match the batch and ratio parameters within the corresponding time period, and generate a starting batch interval parameter set;

[0060] The temperature data in the reactor can be recorded in real time at a frequency of one minute by the temperature sensor and connected to the data acquisition system for centralized management. The temperature change trend analysis is based on whether the temperature rise rate reaches the set threshold. If the temperature increase in unit time reaches more than 1.5 degrees Celsius per minute, it can be regarded as the time point of reaction start. At the same time, the time stamp of the time point is determined in combination with the reaction time record log. For example, if the temperature shows a clear upward trend at 10 o'clock, it is marked as the start of the reaction. The material ratio information is recorded by the ingredient control system, and each batch of ingredients will be accompanied by a time stamp. The batching interval can be set to extend 3 minutes before and after the start time, that is, the batching interval is from 9:57 to 10:03. All material addition records in this time period are screened, and the component data of the corresponding batches are summarized to form an initial batching parameter set. For example, if the batching operation numbered B20250518-01 is completed within this time interval, component A is 30 kg, component B is 20 kg, and component C is 10 kg, then the corresponding ratios are 30%, 40%, and 30%. This record will be included in the initial parameter set for subsequent analysis.

[0061] S102: Calling the batch number in the starting batching interval parameter set, combining the batching time with the chlorine feed log record, filtering the flow data in the corresponding batch, and obtaining the chlorine feed flow interval value;

[0062] For example, the batch number B20250518-01 corresponds to a batching time of 10:01. It is necessary to combine the log records of the chlorine feed system and extract all flow data records within 5 minutes before and after this time point as the analysis interval, which is from 9:56 to 10:06. The chlorine feed flow is collected by the flow meter at a frequency of one minute and recorded in the system log. 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 can be smoothed using a sliding average to form a stable flow value interval. During the calculation process, 10 sample points are taken to directly calculate the average value, and the average flow rate of the interval is approximately 21.4 standard cubic meters per hour. This value is used as the representative parameter of the chlorine feed of the batch at the initial stage of the reaction. Combined with the time period data, it can be used for synchronous correlation analysis with temperature and ratio information.

[0063] S103: Integrate the temperature, time, ratio, and flow parameters corresponding to the batch number according to the chlorine feed flow interval value and the initial batching interval parameter set to generate a process parameter mapping record table;

[0064] The chlorine feed 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 must include: batch number, material addition start time, temperature initial value, temperature maximum value, temperature change rate, group distribution ratio, chlorine average feed flow rate and reaction duration and other information. 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, and the temperature change rate is 22 degrees Celsius. The reaction rate is obtained by dividing the difference between the two by the time taken. If the time taken for the temperature to rise from 22 to 38.5 is 15 minutes, the temperature rise rate is 1.1 degrees Celsius per minute. The proportion information is recorded according to the batching system as 30% of component A, 40% of component B, and 30% of component C. The chlorine feed flow rate is 21.4 standard cubic meters per hour obtained from the above analysis. The reaction duration is defined as the time taken 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 for subsequent process standardization or comparative analysis.

[0065] The specific steps of S2 are:

[0066] S201: Obtain the temperature, reaction time, and ratio data of the batches in the process parameter mapping record table, extract the parameter values ​​of adjacent batches in batch order, determine whether the adjacent batches meet the conditions based on the set temperature range, time interval, and ratio floating standard, and generate a parameter difference judgment status table;

[0067] The temperature, reaction time, and ratio data for each batch are retrieved from the process parameter mapping table. All data is sorted by batch number or chronological order to ensure temporal continuity. Two adjacent batch combinations are extracted and the process parameter variations between them are analyzed group by group. For each batch, the temperature difference, reaction time difference, and ratio fluctuation are calculated. The temperature difference is the absolute difference between the two batches. For example, if the temperature of the previous batch is 120°C and the temperature of the next batch is 123°C, the temperature difference is 3°C. The reaction time difference is similarly calculated as its absolute value. If one batch is 90 minutes and the other is 100 minutes, the time difference is 10 minutes. For ratio fluctuation, the ratio of 3:2:5 is converted into percentages (i.e., 30%, 20%, and 50%). The differences are then compared component by component. For example, if the ratio of the next batch is 33%, 18%, and 49%, the fluctuation is estimated by square rooting the sum of the three differences. The final fluctuation is controlled within 5%. The judgment criteria are set as follows: temperature difference no more than 5°C, reaction time difference no more than 10 minutes, and ratio fluctuation no more than 5%. These comparisons are performed on all batch combinations one by one. If a batch meets all the criteria, it is marked as compliant; if any one item is out of range, it is marked as non-compliant. The results of all comparisons are summarized into a status list to determine whether each batch pair is within the allowable process deviation.

[0068] S202: Determine adjacent batch information that meets the conditions in the status table based on parameter differences, screen related batch groups, identify batch combinations with related sequences, and group them into the same group to generate a continuous batch combination grouping sequence;

[0069] According to the judgment status list, all batch combinations that meet the conditions are analyzed for continuity. Starting from the first batch combination marked as compliant, identify its first and last batches, and check whether the next group still meets the conditions. If so, continue to expand the combination until a combination that does not meet the conditions appears, thus completing the identification of a continuous batch group. In this way, all batches are traversed from beginning to end, and a set of batches that meet the conditions continuously is constructed group by group. Each set is assigned an independent number for subsequent identification and tracking. For example, the first group consists of batches numbered B001, B002, and B003, and the second group consists of B005 and B006. In this way, all batches with process continuity are divided 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 batch, mark the parameter information within the group, and summarize to form a batch process consistency group table;

[0071] Based on the generated continuous batch combination grouping sequence, the temperature, reaction time and ratio parameters of the corresponding batches are extracted from the original process records, and all batches in the same group are summarized one by one and filed in order. The data of each batch are independently labeled and classified. For example, a certain group includes three batches, and the temperature, time and ratio parameters such as 122°C, 85 minutes, and a ratio of approximately 31%, 21%, and 48% are recorded respectively. The detailed process parameters of each batch are displayed in a unified format, and the mean and standard deviation of each parameter within the group are calculated. For example, the average temperature of the group is 121°C, the time is 86 minutes, and the average ratio is approximately 30%, 20%, and 50%. The standard deviation is controlled within a reasonable range, indicating that the fluctuation of the parameters within the group is small. The collected data of all groups form a batch process consistency grouping table, which provides parameter support for subsequent process quality review and product traceability.

[0072] The specific steps of S3 are:

[0073] S301: Extract the node sequence and attribution tag information of the batch path according to the path number and data attribution position of the first batch in the batch process consistency grouping table, build the basic structure of the channel path, and generate a path node tag set;

[0074] The first record in the batch process consistency grouping table can be regarded as the initial benchmark, and its path number and data attribution position serve as the basis for the subsequent path structure construction. First, read the path number contained in the record, for example, number P001, and then find the node sequence corresponding to P001. 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 node is extracted through the process definition table or attribution configuration file, such as N1 is attributed to the "initial heating section", N2 is attributed to the "mid-section heat treatment", N3 is attributed to the "forming section", and N4 is attributed to the "cooling section". A key-value set is constructed with the node identifier as the key and the attribution position as the value, for example {N1: initial heating section} N1: heat treatment section, N2: forming section, N3: cooling section}. During the construction process, if some nodes have no attribution mark, they will be inferred according to the node naming rules. For example, if the name of N1 contains the keyword "heat", it will be classified into the heating area, or marked as "undefined area" using the default rule. The order of the path nodes retains the original definition to ensure consistency with the execution order of the path number. Through this node-attribution mapping set, the basic channel structure can be formed. If the path structure is long during the construction process, the attribution can be identified section by section through the sliding window method, which is convenient for processing 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 in the group, identify the structural difference positions and extract node offset features, calculate the comprehensive evaluation value of the node offset trend, and generate the node corresponding offset position set;

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

[0077]

[0078] Among them, H represents the comprehensive evaluation value of the node deviation trend, α c Represents the structural difference position weight coefficient, Δp r Represents the position offset of the rth node in the path number sequence, Δx r Represents the coordinate difference of the rth node in the x-axis direction, Δy r Represents the coordinate difference of the rth node in the y-axis direction, β d represents the node distribution correction factor, Represents the vector modulus length of the line connecting the rth node and its adjacent nodes, m represents the total number of remaining batches in the group, and u represents the total number of nodes in the current group path;

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

[0080] Node distribution correction factor β d The value is 1.2, referring to the commonly used correction factor value range of 1.0-1.5 in the research on node distribution optimization of wireless sensor networks;

[0081] The total number of remaining batches in the group is m = 15, which is obtained based on the batch processing data recorded in the logs of industrial IoT devices;

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

[0083] The position offset of the third node Δp3 = 2.5 mm is obtained by measuring the deviation between the actual position of the node and the standard path coordinates three times in a row with a laser rangefinder and taking the average value;

[0084] The x-axis coordinate difference Δx3 = 1.2 mm, and the y-axis coordinate difference Δy3 = 2.0 mm are obtained by collecting three-dimensional coordinate data from the displacement sensor and then processing it with the Kalman filter;

[0085] Vector modulus Calculate the Euclidean distance based on the adjacent node (2,4) coordinate data:

[0086]

[0087] Substitute the formula to calculate the third node component:

[0088]

[0089] Repeated calculation of the 8 node components and summing them up to get H = 9.632, which reflects the overall offset trend strength of the current group path nodes. When the H value exceeds the threshold of 8.0, the offset position set generation mechanism is triggered, and the system automatically records the Δp of each node. r Coordinate data >1.0 mm form a node corresponding offset position set.

[0090] S303: Associating the data attribution locations of the batch with path labels based on the node corresponding offset position set, establishing a channel mapping relationship between the path nodes, and generating a batch channel path label structure;

[0091] According to the node offset position set, the data attribution position of each batch is processed one by one, and the path node sequence of each batch is used as the primary key. The label is set in combination with the offset feature. For example, if the original node N4 is replaced by N5 in a batch, N5 is marked as "original N4 replacement node" in the current path, forming a 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 there is a new node N6 in a batch path and it is inserted into N2, it is marked as N2, N6 (newly added), N3. The offset feature combined with the path structure can generate a path label sequence. Each label record contains a node identifier, a position index, and an offset type description. A mapping relationship is established between nodes. For example, a replacement mapping is established between N5 and N4, and a relative position mapping is established between N6 and the node before insertion. The entire label structure can constitute a path label network. Each node in the network has a source description. For example, the source of N5 is marked as "N4 bit replacement in the original path." For batches with different path numbers, the final output path label structure includes node sequence, node label, attribution mark, and structural offset information, identifying the change information within the channel and ensuring the integrity of path construction and structure analysis.

[0092] The specific steps of S4 are:

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

[0094] Based on the batch channel path tag structure, the representation of path numbers and channel indices must be clarified. A unified tag format can be established, such as P plus two digits for the path number, C plus two digits for the channel index, and B plus two digits for the batch number. The tag format is P01-B05-C03. Regular expressions are then used to parse all path tag information to extract the path number and channel index. Signal data comes from the control system database or production system log. For each tag record, its associated running status field and control signal field must be retrieved. Status fields can be set as "RUNNING," "WAITING," or "FINISHED," while control signal fields can be set as "C_IN" or "C_OUT." After extraction, the signals are categorized. For example, all paths with a control signal of "C_IN" and a status of "RUNNING" are clustered. A classification structure is formed by combining the path number and channel index. The path number and channel index are then combined to form a key-value structure, such as P01 and C03, which can be combined to identify the status and control signal content. Next, based on the existing classification, path combinations with specified states are screened. For example, if the state is "WAITING" and the control signal is "C_OUT," matching path number and channel index combinations that meet the criteria are screened 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 in a data dictionary or written to a database table. Each row in the table corresponds to a path number and channel index combination, its corresponding state, and control signal. For example, if the path P02-B03-C04 corresponds to the state "WAITING" and the control signal is "C_OUT," a complete control relationship record is formed.

[0095] S402: Calling the path operation control correspondence quantity, sorting the signals according to the timestamps, extracting the overlapping time intervals, and dividing the stages in combination with the path template, calculating the stage division feature value, matching the signals with the stages, and generating the stage-related signal time interval value;

[0096] The specific calculation formula for the eigenvalue of the calculation stage is:

[0097]

[0098] Among them, F m represents the partition eigenvalue of the mth stage, represents the normalized time offset between the ith signal and the path template p, σ τ represents the sample variance of the time offset, represents the energy weight coefficient of the i-th stage in the path template p, represents the spectrum similarity index between the kth signal and template p, α p is the phase alignment factor of the path template p, λ prepresents the time window expansion coefficient of template p, γ p represents the baseline drift suppression amount of template p;

[0099] Normalized time offset By calculating the difference between the signal timestamp and the timestamp corresponding to the template p, the signal timestamp sequence in a certain monitoring data is [12.3s, 14.7s, 16.2s], and the timestamp corresponding to the template p is [12.0s, 14.5s, 16.0s].

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

[0101] Energy weight coefficient According to the signal energy ratio setting, the measured signal energy distribution is [0.4, 0.35, 0.25], and the normalized processing is

[0102] Spectral similarity index By calculating the cosine similarity between the signal spectrum and the template spectrum, a certain spectrum data is calculated. Phase alignment factor α p According to the signal phase difference setting, the measured phase difference is 0.15rad, take α p =0.9; time window expansion factor λ p According to the signal sampling rate and template matching setting, when the sampling rate matching is 95%, take λ p =1.05;

[0103] Baseline drift suppression γ p Determined according to the baseline noise level, when the noise RMS value is 0.02V, take γ p =0.1;

[0104] Substitute into the formula to calculate:

[0105] The first square root is divided into The square root value is 6.12;

[0106] The second item is

[0107] Final F m =6.12+1.38=7.50.

[0108] The results show that the stage division eigenvalue reaches the threshold of 7.0, triggering the time interval division operation. The larger the eigenvalue, the higher the match between the signal and the template. When the eigenvalue exceeds the preset threshold, a valid time interval division result is generated.

[0109] S403: Extracting path hierarchical structure information based on the time interval value of the stage-related signal, determining the ownership and order of the paths, arranging and combining the stage paths according to the time interval, establishing a multi-layer mapping relationship, and generating a stage path structure mapping table;

[0110] Based on the obtained phase-related signal time intervals, path hierarchical structure information must be further extracted. First, a hierarchical classification criteria for paths must be defined. For example, primary channels can be defined based on channel numbers, while auxiliary or branch channels can be defined as secondary paths. This classification can be based on channel number ranges or rules. The channel numbers extracted from the path labels are used to determine their hierarchical structure. Next, the temporal order of paths within each phase is analyzed. For example, the feeding phase of path P01 is from 10:00 to 10:15, while the feeding phase of path P02 is from 10:20 to 10:35. This indicates that P01 precedes P02. All path phase times are compared and arranged in temporal order to form a continuous phase path flow. The path phase structures are sequentially combined to construct a multi-layer mapping structure. Each layer represents a path hierarchy, containing multiple phases. Each phase corresponds to one or more path numbers, their time intervals, and signals. This generated phase path structure mapping table clearly defines the hierarchical structure, order, and signal associations of each phase path within the hierarchy. For example, the first-level path includes the feeding stage and the processing stage, where the feeding stage is composed of paths P01 and P02, and the processing stage is composed of path P03. The start and end time and signals of each stage are directly obtained from the time interval value of the associated signal of the previous stage, and finally a complete multi-layer path mapping structure is formed for path-level control analysis and data tracking.

[0111] The specific steps of S5 are:

[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 result;

[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 the first-level directory category, the second-level time classification field, and the third-level business number field. The path classification type field can be used to filter and select matching mapping rules for batch data. For example, in a document archiving application, if the batch data consists of contract documents for 2023, the path structure "Contract Category / Year / Project Number" should be selected. Metadata fields within the batch data must then be extracted, such as "File Type" (Contract), "Creation Time" (May 2023), and "Project Number" (PJT001). Based on this mapping, a multi-level directory structure is constructed, creating folders such as "Contract Category," "2023," and "PJT001" from the root path, and categorizing the corresponding data into the target path. During execution, a hierarchical iterative approach can be used to determine the path and generate directories. If a path node does not exist, it is created immediately. Directory names should be consistent with the metadata field contents. The archiving path of each piece of data in the batch needs to be paired and registered with its file number. The file unique identifier can be bound to the generated path and written into the archiving log. For example, the number F123456 is archived to "Archive Area / Contract Category / 2023 / PJT001", and the information is recorded in the database or text log. In the event of missing or incomplete fields in the data, such as no project number, it will be classified into the "Unspecified" directory, forming a "Contract Category / 2023 / Unspecified" structure. During the generation of the archiving path, it is necessary to avoid path duplication and non-standard naming. Special characters such as " / ", "\", ":", and "*" are prohibited in directory names, and standard character set encoding is uniformly used. After the classification and archiving is completed, each piece of data is clearly located in its corresponding directory, forming a unified organization structure, and completing the classification and archiving of batch data.

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

[0115] Based on the batch data collation results, the file number and actual archiving path of each data entry must be extracted, and a list of file number-to-storage location correspondences must be constructed. First, the unique number field for each data entry must be extracted. For example, if the file number is F123456, the corresponding archiving path is "Archiving Area / Contract Category / 2023 / PJT001." This correspondence is then recorded in the archiving list. The archiving list can be stored as simple text, a table, or a structured file. The fields include file number, file name, archiving path, and archiving time. During execution, batch processing is performed by traversing the data structure and verifying the existence of the path. Directory validation is performed using the file system's path verification function. If a path anomaly exists, such as a nonexistent path or access error, the file should be marked as abnormal and the exception 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 must be recorded for subsequent retrieval. Each file number corresponds to its path. Once the list is completed, the file number should be uniformly sorted, with the sort field in ascending order of file number, to facilitate quick querying and path tracing. The archive list can be uploaded to the management system archive module or imported into the database table to form a long-term index, which is convenient for post-archiving audit, query and export operations.

[0116] S503: Based on the archive file number and the path information in the storage location list, the hierarchical paths are integrated in the directory structure order, the path nodes are matched with the corresponding file numbers and sorted into columns, and the relationship between the paths and numbers of the archived data is sorted out item by item to obtain a batch data archive path list;

[0117] After the archive list is generated, it must be parsed and consolidated based on the archive path field information to form a complete list of the path hierarchy. During parsing, each path is segmented hierarchically, and node fields within the path, such as "Contract Category," "2023," and "PJT001," are extracted to form an array of path nodes. The path hierarchy 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 are clearly assigned within the hierarchy, and a mapping must be established within each node level. For example, from the "2023" node under the "Contract Category" node to the "PJT001" node, a list of file numbers is included in the structure of each node layer to ensure path number mapping from the root node to the leaf nodes. During the organization process, the list should be constructed sequentially according to the depth of the directory structure. Each set of path structures and their file numbers should be output and organized to form a clear and readable list of archive paths. If some data paths are incomplete or have inconsistent hierarchies, such as only reaching "Contract Category / 2023," they will be assigned to the default child node "Unspecified" to ensure the consistency and integrity of the path structure. File numbers within each directory structure can be sorted by order, creating a consistent output format. The final output is a path list of "path structure: corresponding file number set," with a clear hierarchy for easy review and auditing, forming a complete archive batch path index data set.

[0118] See also Figure 2 , a chloroacetic acid production data storage system, comprising:

[0119] The process parameter arrangement module collects the starting temperature, duration, and ratio values ​​of the reaction process, extracts the feed batch number and chlorine feed rate recorded in the batching stage, combines the timestamp information of the parameters, completes the time association and structure arrangement of the batches and parameters, and generates a process parameter mapping record table;

[0120] The batch grouping determination module calls multiple batch data with adjacent time in the process parameter mapping record table, performs conditional judgment based on temperature difference, reaction time interval and ratio change degree, and classifies batches that meet the same process standards into one category, forming a batch process attribution 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 of each group according to the batch classification in the batch process consistency grouping table, verifies whether the path numbers of batches in the same group have the same structure identifier, binds the identification result with the batch information, establishes the corresponding channel attribution 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 segment, and extracts the time-stamped segment against the control template. It then groups and classifies the path nodes according to the process logic sequence, constructs the structural hierarchy corresponding to the stage, and generates a stage path structure mapping table.

[0123] The batch filing 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 the filing location of the corresponding batch files with the file number, and generates a batch data filing path list.

[0124] The above are merely preferred embodiments of the present invention and do not limit the present invention in any other form. Any technician familiar with the profession may use the technical content disclosed above to change or modify it into an equivalent embodiment with equivalent changes and apply it to other fields. However, any simple modification, equivalent change and modification made to the above embodiment based on the technical essence of the present invention without departing from the content of the technical solution of the present invention shall still fall within the scope of protection of the technical solution of the present invention.

Claims

1. A method for storing chloroacetic acid production data, characterized in that: The following steps are involved: S1: Obtain the reactor starting temperature, reaction time and material ratio, extract the feed batch and chlorine flow data, combine the time information, correspond the parameters with the batch number, and generate a process parameter mapping record table; S2: calling the adjacent batch data in the process parameter mapping record table, judging based on the temperature variation range, reaction time interval and ratio floating range, grouping and classifying the batches that meet the conditions, and generating a batch process consistency grouping table; S3: Read the path number and data attribution location of the first batch according to the grouping status of the batch process consistency grouping table, compare the path numbers of the remaining batches in the group, establish channel attribution relationships, and generate a batch channel path label structure; S4: Based on the verified path information of the batch channel path tag structure, read the associated operation status and control signal, combine the associated time stamp with the path template, organize the staged path hierarchy information, and generate a stage path structure mapping table; S5: calling the stage path structure mapping table directory structure, completing the sorting and archiving of 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.

2. The method for storing chloroacetic acid production data according to claim 1, wherein: 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 floating interval values; the batch channel path label structure includes path number comparison results, data attribution location identifiers, and channel attribution relationship chains; the stage path structure mapping table includes operating status segment combinations, control signal timing tags, and time tag hierarchical 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, wherein: The specific steps of S1 are: S101: Obtain temperature data, reaction time records, and material ratio information in the reactor, determine the reaction start time based on the temperature change trend, match the batch and ratio parameters within the corresponding time period, and generate a starting batch interval parameter set; S102: calling the batch number in the initial batching interval parameter set, combining the batching time and the chlorine feeding log record, filtering the flow data in the corresponding batch, and obtaining the chlorine feeding flow interval value; S103: Integrate the temperature, time, ratio and flow parameters corresponding to the batch number according to the chlorine feed flow interval value and the initial batching interval parameter set to generate a process parameter mapping record table.

4. The method for storing chloroacetic acid production data according to claim 3, wherein: The specific steps of S2 are: S201: Obtaining the temperature, reaction time, and ratio data of the batches in the process parameter mapping record table, extracting the parameter values ​​of adjacent batches in batch order, determining whether the adjacent batches meet the conditions based on the set temperature range, time interval, and ratio floating standard, and generating a parameter difference judgment status table; S202: Determine adjacent batch information that meets the conditions in the status table based on the parameter difference, screen associated batch groups, identify batch combinations with an associated sequence, and group 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 group table.

5. The method for storing chloroacetic acid production data according to claim 4, wherein: The specific steps of S3 are: S301: extracting the node sequence and attribution mark information of the batch path according to the path number and data attribution position of the first batch in the batch process consistency grouping table, constructing the basic structure of the channel path, and generating a path node mark set; S302: calling the path node tag set, performing node sequence matching on the path numbers of the remaining batches in the group, identifying the structural difference positions and extracting node offset features, calculating the comprehensive evaluation value of the node offset trend, and generating a node corresponding offset position set; S303: Based on the node corresponding offset position set, path labels are associated with the data attribution locations of the batch, a channel mapping relationship between path nodes is established, and a batch channel path label structure is generated.

6. The method for storing chloroacetic acid production data according to claim 5, wherein: The specific calculation formula for the comprehensive evaluation value of the node offset trend is: Among them, H represents the comprehensive evaluation value of the node deviation trend, α c Represents the structural difference position weight coefficient, Δp r Represents the position offset of the rth node in the path number sequence, Δx r Represents the coordinate difference of the rth node in the x-axis direction, Δy r Represents the coordinate difference of the rth node in the y-axis direction, β d represents the node distribution correction factor, Represents the vector modulus of the line connecting the rth node and its adjacent nodes, m represents the total number of remaining batches in the group, and u represents the total number of nodes in the current group path.

7. The method for storing chloroacetic acid production data according to claim 5, wherein: The specific steps of S4 are: S401: Based on the batch channel path label structure, identify the path label number and channel index, extract the corresponding operation status and control signal, classify and filter the signals according to the path number and channel index, establish a correspondence between the signals, and generate a path operation control correspondence quantity; S402: calling the path operation control correspondence quantity, sorting the signals according to the timestamps, extracting the overlapping time intervals, and dividing the stages in combination with the path template, calculating the stage division feature value, matching the signals with the stages, and generating the stage-associated signal time interval value; S403: Extracting path hierarchical structure information according to the time interval value of the stage-related signal, determining the ownership and order of the paths, arranging and combining the stage paths according to the time interval, establishing a multi-layer mapping relationship, and generating a stage path structure mapping table.

8. The method for storing chloroacetic acid production data according to claim 7, wherein: The specific calculation formula for dividing the characteristic value in the calculation stage is: Among them, F m represents the partition eigenvalue of the mth stage, represents the normalized time offset between the i-th signal and the path template p, σ τ represents the sample variance of the time offset, represents the energy weight coefficient of the i-th stage in the path template p, represents the spectrum similarity index between the kth signal and template p, α p is the phase alignment factor of the path template p, λ p represents the time window expansion coefficient of template p, γ p Represents the baseline drift suppression amount of template p.

9. The method for storing chloroacetic acid production data according to claim 7, wherein: The specific steps of S5 are: S501: calling the stage path structure mapping table, arranging and archiving batch data according to the configuration, classifying and storing the data according to the directory path, and obtaining the batch data arrangement result; S502: Register the file numbers and storage locations based on the batch data sorting results, associate each file number with an archiving path, and generate a list of archived file numbers and storage locations; S503: Based on the archive file number and the path information in the storage location list, the hierarchical paths are integrated in the order of the directory structure, the path nodes are matched with the corresponding file numbers and sorted into columns, and the path and number relationship of the archive data is sorted out item by item to obtain a batch data archive 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 to 9, wherein the system comprises: The process parameter arrangement module collects the starting temperature, duration, and ratio values ​​of the reaction process, extracts the feed batch number and chlorine feed rate recorded in the batching stage, combines the timestamp information of the parameters, completes the time association and structure arrangement of the batches and parameters, and generates a process parameter mapping record table; The batch grouping determination module calls the data of multiple batches with adjacent time in the process parameter mapping record table, performs conditional judgment based on temperature difference, reaction time interval and ratio change degree, classifies batches that meet the process similarity standards into one category, forms a batch process attribution structure, and generates a batch process consistency grouping table; The path label establishment module extracts the path number and storage location of the first batch of each group according to the batch classification in the batch process consistency grouping table, verifies whether the path numbers of batches in the same group have the same structure identifier, binds the identification result with the batch information, establishes the corresponding channel attribution identifier, and generates a 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 mark segment according to the control template, classifies the path nodes according to the process logic sequence, constructs the structural hierarchy corresponding to the stage, and generates a stage path structure mapping table; The batch filing 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 the filing location of the corresponding batch file with the file number, and generates a batch data filing path list.

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