Multi-stage parameter collaborative driving method for nasal saline salt bagging process

Abstract

The application discloses a method for multi-stage parameter collaborative driving in a nasal saline bag making process, and relates to the technical field of nasal saline bag making. The method comprises the following steps: in the case of a collaborative driving path interruption, the interruption position, semantic offset direction and semantic fracture degree in the path semantic identification sequence are fused and calculated to generate a path semantic state mapping quantity; the path semantic state mapping quantity is introduced into a multi-stage parameter collaborative driving relationship, the inter-stage parameter association order, association strength and action direction are reorganized according to the path semantic state mapping quantity, and a replacement association input is generated based on the path semantic state mapping quantity to form a corresponding association evolution sequence. The application solves the problem of control disconnection caused by the missing input of the subsequent stage due to the collaborative driving path interruption in the nasal saline bag making process, and realizes the dynamic reconstruction and adaptive adjustment effect of the multi-stage parameter collaborative driving relationship based on the path semantic state.

Description

Technical Field

[0001] This invention relates to the field of nasal wash bag making technology, specifically to a multi-stage parameter coordinated driving method for the nasal wash bag making process. Background Technology

[0002] The multi-stage parameter coordinated drive of the nasal wash salt bag making process refers to dividing the entire bag making process into several interconnected stages according to function during the continuous production process of nasal wash salt powder packaging bags. The key process parameters of each stage are established in relation to each other, and the temperature, pressure, speed, tension and time are uniformly scheduled and coordinated through the control system to achieve coordinated control and stable operation of the entire bag making process. In existing technologies, bag-making equipment is typically managed programmatically based on industrial control systems. This involves pre-setting process stages, such as film conveying and tension control, bag forming, powder metering and filling, heat sealing, and cutting / output. Corresponding sensors and actuators are configured in each stage to collect and adjust parameters such as temperature, feeding speed, sealing pressure, and time. Simultaneously, a controller establishes parameter transmission and constraint relationships between different stages, allowing the output state of the previous stage to serve as the input for the next, achieving coordinated parameter control across multiple stages. This enables continuous and automated operation of nasal wash bag making. The process generally includes parameter acquisition, status recognition, control command generation, actuator response, and result feedback, thus forming a closed-loop, multi-stage coordinated control system.

[0003] The existing technology has the following shortcomings: In the process of making nasal wash bags, multi-stage parameter collaborative drive relies on continuous parameter transmission paths between stages to maintain the integrity of the collaborative relationship. When a stage in the operation of a single bag fails to generate an effective output or the output status is not correctly transmitted, the collaborative drive path will be interrupted. Since multi-stage parameter collaborative drive establishes a linkage relationship based on the output of the previous stage as the input of the next stage, once the path is interrupted at a certain node, the subsequent stages will not be able to obtain the corresponding collaborative parameter input. Existing technology cannot adjust the multi-stage parameter collaborative drive relationship according to the path status of the nasal wash bag making process when the collaborative drive path is interrupted. This will cause the subsequent stages to still execute control according to the original collaborative relationship or default parameters, which will lead to the problem of control disconnect between stages. This will cause local control failure in the subsequent processing of a single bag, thereby affecting the stability and consistency of the overall bag making process.

[0004] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0005] The purpose of this invention is to provide a multi-stage parameter coordinated driving method for the nasal wash bag making process, so as to solve the problems in the background art mentioned above.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a multi-stage parameter coordinated driving method for the nasal wash salt bag making process, specifically including the following steps: S1. Sequentially associate and encode the output parameters of each stage in the nasal saline bag making process to generate the corresponding path semantic identifier sequence, and perform continuity verification on the path semantic identifier sequence to determine whether a collaborative driving path interruption has occurred. S2. In the event of a collaborative drive path interruption, the interruption position, semantic offset direction and semantic breakage degree in the path semantic identifier sequence are fused and calculated to generate a path semantic state mapping quantity. S3. Introduce the path semantic state mapping quantity into the multi-stage parameter collaborative driving relationship, reorganize the parameter association order, association strength and action direction between stages according to the path semantic state mapping quantity, and generate alternative association inputs based on the path semantic state mapping quantity to form a corresponding association evolution sequence. S4. Continuously track the path semantic state mapping quantity and update the associated evolution sequence based on the changes in the path semantic state mapping quantity to complete the adjustment of the multi-stage parameter collaborative driving relationship.

[0007] Preferably, S1 specifically includes the following steps: S101. The output parameters of each stage in the nasal rinse salt bag making process are sequentially associated and encoded according to the stage execution order. Each stage output parameter is bound to the corresponding stage execution order identifier, and the current stage execution order identifier is associated and combined with the previous stage execution order identifier to form a sequential association code containing stage execution order information and previous association information. S102. Based on the sequential association coding, the execution order of each stage is arranged in the order of execution. The execution order information, the preceding association information and the output parameter information in each sequential association coding are combined and embedded to construct the corresponding path semantic identifier sequence. S103. Perform continuity verification on the path semantic identifier sequence. Compare the stage execution order information and the preceding association information in the adjacent path semantic identifiers level by level. When there is a discontinuity in the stage execution order or a mismatch in the preceding association information between adjacent path semantic identifiers, it is determined that a collaborative driving path interruption has occurred.

[0008] Preferably, S103 is as follows: For each adjacent path semantic identifier pair in the path semantic identifier sequence, extract the stage execution order information and the preceding association information in each path semantic identifier to form the corresponding adjacent comparison data group. Based on the adjacent comparison data group, the execution order information of the stage in the semantic identifier of the adjacent path is subjected to sequential difference calculation to obtain the difference between the execution order value of the current stage and the execution order value of the previous stage. At the same time, the preceding association information is subjected to item-by-item matching processing to obtain the corresponding association matching tag. The determination is made based on the sequential difference calculation result and the associated matching mark. When the sequential difference calculation result is not equal to the preset step size value or the associated matching mark is mismatched, it is determined that there is a discontinuity in the stage execution order or a mismatch in the preceding associated information between the semantic identifiers of the corresponding adjacent paths, and the collaborative driving path is interrupted accordingly.

[0009] Preferably, S2 specifically includes the following steps: S201. In the event of a collaborative drive path interruption, perform location processing on the path semantic identifier sequence, extract the corresponding path semantic identifier and its adjacent path semantic identifiers based on the interruption determination position in the path semantic identifier sequence, and determine the interruption position by combining the stage execution order information and the preceding association information. S202. Around the interruption position, perform directional difference analysis on the stage execution order information of adjacent path semantic identifiers in the path semantic identifier sequence. Determine the semantic offset direction by comparing the trend of stage execution order changes before and after the interruption position. At the same time, perform association deviation calculation on the preceding association information. Determine the degree of semantic break by statistically analyzing the deviation between the preceding association information and the corresponding stage execution order information. S203. The interruption position, semantic offset direction and semantic breakage degree are fused and calculated. The path semantic identifier corresponding to the interruption position is used as the position reference, the semantic offset direction is used as the direction parameter, and the semantic breakage degree is used as the degree parameter. These are combined and embedded to generate the path semantic state mapping quantity.

[0010] Preferably, S202 specifically refers to: Around the interruption location, the semantic identifiers of adjacent paths before and after the interruption location in the path semantic identifier sequence are extracted, and the stage execution order information in the corresponding path semantic identifiers is parsed to form the forward stage execution order sequence and the backward stage execution order sequence. Based on the difference analysis of the execution direction between the forward stage execution sequence and the backward stage execution sequence, the change trend of the stage execution order is determined by comparing the change direction of the forward stage execution sequence and the backward stage execution sequence, and the semantic offset direction is obtained. After determining the semantic offset direction, the preceding association information of the corresponding interruption position in the path semantic identifier sequence is extracted, and the preceding association information is aligned with the execution order information of the corresponding stage item by item to form an association comparison sequence. Based on the correlation comparison sequence, correlation deviation calculation is performed. By statistically analyzing the deviation between the preceding correlation information and the corresponding stage execution order information, the degree of semantic breakage is obtained.

[0011] Preferably, S3 specifically includes the following steps: S301. Introduce the path semantic state mapping quantity into the multi-stage parameter collaborative driving relationship, insert the position benchmark corresponding to the stage in the path semantic state mapping quantity into the inter-stage parameter association relationship, and bind the direction parameter and degree parameter in the path semantic state mapping quantity to the association direction and association strength in the inter-stage parameter association relationship respectively, forming a multi-stage parameter collaborative driving relationship in which the path semantic state mapping quantity participates. S302. Based on the path semantic state mapping quantity, rearrange the inter-stage parameter association order in the multi-stage parameter collaborative driving relationship in which the path semantic state mapping quantity participates, adjust the inter-stage parameter action direction according to the direction parameter in the path semantic state mapping quantity, and adjust the inter-stage parameter association strength according to the degree parameter in the path semantic state mapping quantity, thereby completing the reorganization of the inter-stage parameter association order, association strength and action direction. S303. Generate alternative associated inputs based on path semantic state mapping. Use the position reference in the path semantic state mapping as the input positioning parameter, the direction parameter in the path semantic state mapping as the input action direction parameter, and the degree parameter in the path semantic state mapping as the input action intensity parameter. Combine the input positioning parameter, the input action direction parameter, and the input action intensity parameter to generate alternative associated inputs. Embed the alternative associated inputs into the reorganized multi-stage parameter collaborative driving relationship according to the position reference in the path semantic state mapping. Arrange the reorganized multi-stage parameter collaborative driving relationship continuously according to the stage execution order to form a corresponding associated evolution sequence.

[0012] Preferably, S302 is as follows: Based on the position reference in the path semantic state mapping, the corresponding stage node is located in the multi-stage parameter collaborative driving relationship in which the path semantic state mapping participates, and the inter-stage parameter association relationship between the adjacent stages before and after the node is extracted to form a set of inter-stage parameter association order rearrangement. Based on the set of inter-stage parameter association order rearrangement, the direction determination of the parameter association relationship between adjacent stages is performed according to the direction parameter in the path semantic state mapping. By aligning and matching the original inter-stage parameter action direction with the direction parameter, the adjustment of the inter-stage parameter action direction is completed. After adjusting the direction of action of inter-stage parameters, the association strength in the inter-stage parameter association relationship is classified according to the degree parameter in the path semantic state mapping. By mapping the association strength to the degree parameter and reassigning the value, and rearranging the order of inter-stage parameter association according to the adjusted direction of action of inter-stage parameters, the reorganization of the inter-stage parameter association order, association strength and direction of action is completed.

[0013] Preferably, S4 is as follows: The path semantic state mapping quantity is continuously tracked, and the path semantic state mapping quantity is arranged in order according to the stage execution order. The position reference, direction parameter and degree parameter in the adjacent path semantic state mapping quantity are compared item by item to obtain the change information of the path semantic state mapping quantity. The association evolution sequence is updated based on the changes in the path semantic state mapping quantity. The change information of the path semantic state mapping quantity is mapped to the corresponding stage nodes in the association evolution sequence. The association order, association strength and direction of action of the inter-stage parameters in the association evolution sequence are adjusted synchronously. The updated association evolution sequence is then arranged continuously according to the stage execution order to complete the adjustment of the multi-stage parameter collaborative driving relationship.

[0014] The technical effects and advantages provided by the present invention in the above technical solution are as follows: 1. This invention introduces path semantic identifier sequences and path semantic state mapping quantities to structurally express and dynamically characterize the multi-stage parameter collaborative driving path in the nasal wash bag making process. When a path interruption occurs, it can accurately identify the interruption location, semantic offset direction, and semantic breakage degree, and reorganize the original multi-stage parameter collaborative driving relationship based on this information, thereby avoiding the collaborative failure problem caused by relying on fixed parameter transmission paths in traditional technologies. By combining sequential association coding and continuity verification, the output parameters of each stage not only have numerical meaning but also stage-related semantic information, thus enabling traceable analysis of the parameter transmission link. At the same time, by constructing a path semantic state mapping quantity, path interruption is transformed from a discrete abnormal event into a continuous state variable that can participate in calculation, changing the multi-stage parameter collaborative driving from static relationship control to dynamic control based on path state, improving the response capability to abnormal working conditions.

[0015] 2. This invention introduces path semantic state mapping into the multi-stage parameter collaborative driving relationship and generates alternative associated inputs based on position references, direction parameters, and degree parameters. This enables the construction of new parameter input sources even when the path is interrupted, fundamentally solving the control failure problem caused by missing inputs in subsequent stages. Simultaneously, through continuous updating of the associated evolution sequence, the multi-stage parameter collaborative driving relationship can be adjusted in real time according to changes in the path semantic state, achieving adaptive evolutionary control of the collaborative relationship. This technical solution not only restores the continuity of the parameter transmission link but also maintains the stability and consistency of multi-stage collaborative driving under complex operating conditions, reducing the risk of local control failures caused by path interruptions, thereby improving the overall operational reliability and product quality consistency of the bag-making process. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0017] Figure 1 This is a schematic diagram of the process of the present invention. Detailed Implementation

[0018] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, they are provided so that the description of this disclosure will be more complete and fully convey the concept of the exemplary embodiments to those skilled in the art.

[0019] This invention provides, for example Figure 1 The multi-stage parameter collaborative driving method for the nasal rinse salt bag making process shown includes the following steps: S1. Sequentially associate and encode the output parameters of each stage in the nasal saline bag making process to generate the corresponding path semantic identifier sequence, and perform continuity verification on the path semantic identifier sequence to determine whether a collaborative driving path interruption has occurred. In this embodiment, S1 specifically includes the following steps: S101. The output parameters of each stage in the nasal rinse salt bag making process are sequentially associated and encoded according to the stage execution order. Each stage output parameter is bound to the corresponding stage execution order identifier, and the current stage execution order identifier is associated and combined with the previous stage execution order identifier to form a sequential association code containing stage execution order information and previous association information. In the process of making nasal wash bags, the entire production line can be divided into continuous stages such as conveying, forming, filling, sealing, and cutting. Output parameters for each stage are collected, such as the output speed value during the conveying stage, the output tension value during the forming stage, the output metering value during the filling stage, and the output temperature and pressure values ​​during the sealing stage. In implementation, a unique stage execution sequence identifier can be assigned to each stage, for example, by assigning incremental numbers according to the process sequence. Upon completion of each stage, the output parameters are bound to the current stage execution sequence identifier. Simultaneously, the execution sequence identifier of the previous stage is read and associated with the current stage execution sequence identifier to form a sequential association code. This can be specifically implemented through data structures in the control program, storing the stage number, the previous sequence number, and the corresponding parameter values ​​in the same record unit. Taking experimental production data as an example, data from 100 bags produced continuously on a nasal wash bag production line were collected. The conveying speed was recorded as a certain number of meters per second, the filling measurement as a certain number of grams, and the sealing temperature as a certain number of degrees Celsius. After combining these parameters with the stage number, a coding sequence such as "stage number - previous sequence number - parameter value" can be formed. By comparing bag by bag, it was found that when the previous sequence number of a certain bag jumps or is missing, the corresponding path is interrupted. This verifies that the sequential association coding can accurately reflect the stage transmission relationship and be used for subsequent analysis.

[0020] The nasal rinse salt bag-making process refers to the entire process of processing nasal rinse salt raw materials into individually packaged products through continuous equipment. The output parameters of each stage refer to the numerical information reflecting the state of each stage at the end of each processing step, such as speed, pressure, or measurement values. The stage execution sequence indicates the temporal relationship between each processing step. The sequence association code represents the structured data identifier formed by combining the stage execution sequence information with the output parameters. The corresponding stage execution sequence identifier is used to indicate the processing step position from which the current data originates. The association combination refers to pairing and connecting the current stage execution sequence identifier with the previous stage execution sequence identifier. The sequence association code containing stage execution sequence information and prior association information indicates that the current stage position and the source stage position are recorded simultaneously in the same data unit. The stage execution sequence information is used to describe the current processing position, and the prior association information is used to describe which previous stage the data comes from. Through the coexistence of these two types of information, the transmission relationship between multi-stage parameters can be completely described, providing a basis for subsequent determination of path continuity.

[0021] S102. Based on the sequential association coding, the execution order of each stage is arranged in the order of execution. The execution order information, the preceding association information and the output parameter information in each sequential association coding are combined and embedded to construct the corresponding path semantic identifier sequence. After completing the sequential association coding, the sequential association codes generated in each stage need to be arranged according to the stage execution order. The stage execution order information, preceding association information, and output parameter information from each sequential association code are then combined and embedded to construct a path semantic identifier sequence. Specifically, a data queue arranged chronologically can be established in the control program. The sequential association codes generated in each stage are written into the queue sequentially according to their entry time. During the writing process, the stage execution order information is used as the primary sequence field, the preceding association information is used as the association field, and the output parameter information is embedded into the same data unit to form a complete record. For example, in actual production experiments, data on a batch of continuously running nasal wash bag making processes are collected, recording the conveying speed, filling metering value, and sealing temperature. These data are then stored as multiple consecutive records in the processing order. By combining the stage execution sequence information with the preceding association information, a continuous chain-like data sequence can be obtained. During analysis, it was found that when the preceding association information in the sequence is inconsistent with the stage execution sequence information of the previous record, it can be identified as a link anomaly. Therefore, by combining, embedding, and arranging in sequence, a complete expression of the multi-stage parameter transmission relationship can be achieved, providing basic data for subsequent continuity verification.

[0022] Sequential association coding represents the coded data containing stage relationships and parameter information formed in each processing stage. Stage execution sequence information is used to describe the position of the current data's processing stage in the overall process. Precedence association information is used to identify the correspondence between the current stage and the previous stage. Output parameter information is used to record the specific process parameter values ​​generated in this stage. Combination embedding means integrating stage execution sequence information, precedence association information, and output parameter information into the same data unit to form a complete data expression. Path semantic identifier sequence represents the overall data sequence formed by arranging multiple sequential association codes continuously according to the stage execution order. This sequence can simultaneously reflect the processing flow sequence, inter-stage relationships, and parameter changes, thus forming a structured description basis for the multi-stage parameter collaborative driving relationship in the nasal wash salt bag making process.

[0023] S103. Perform continuity verification on the path semantic identifier sequence. Compare the stage execution order information and the preceding association information in the adjacent path semantic identifiers level by level. When there is a discontinuity in the stage execution order or a mismatch in the preceding association information between adjacent path semantic identifiers, it is determined that a collaborative driving path interruption has occurred.

[0024] In this embodiment, S103 specifically refers to: For each adjacent path semantic identifier pair in the path semantic identifier sequence, extract the stage execution order information and the preceding association information in each path semantic identifier to form the corresponding adjacent comparison data group. Based on the adjacent comparison data group, the execution order information of the stage in the semantic identifier of the adjacent path is subjected to sequential difference calculation to obtain the difference between the execution order value of the current stage and the execution order value of the previous stage. At the same time, the preceding association information is subjected to item-by-item matching processing to obtain the corresponding association matching tag. The determination is made based on the sequential difference calculation result and the associated matching mark. When the sequential difference calculation result is not equal to the preset step size value or the associated matching mark is mismatched, it is determined that there is a discontinuity in the stage execution order or a mismatch in the preceding associated information between the semantic identifiers of the corresponding adjacent paths, and the collaborative driving path is interrupted accordingly.

[0025] When performing continuous analysis on a path semantic identifier sequence, it is first necessary to extract each adjacent path semantic identifier pair in the sequence and parse the stage execution order information and preceding association information in each path semantic identifier to form a corresponding adjacent comparison data group. In practice, the program can read the path semantic identifiers one by one according to the sequence order, combine the data at the current position with the data at the previous position into a comparison unit, and extract the stage execution order information and preceding association information as core fields. For example, in a set of actually collected data on nasal wash salt bag production, recording a batch of continuously produced products, the stage number and source number in each record are extracted to form adjacent pairs. This method can construct a continuous comparison data group for subsequent judgment of whether the transmission relationship between stages remains consistent. The purpose of this is to decompose the originally continuous path relationship into local relationship units that can be analyzed item by item.

[0026] After constructing the adjacent comparison data set, it is necessary to perform sequential difference calculation on the stage execution order information in the semantic identifier of adjacent paths based on the adjacent comparison data set. This yields the difference between the current stage execution order value and the previous stage execution order value. Simultaneously, item-by-item matching processing is performed on the preceding association information to obtain the corresponding association matching markers. Specifically, the difference between the stage number in the current record and the stage number in the previous record can be calculated. At the same time, the preceding association information in the current record is compared item-by-item with the stage execution order information in the previous record. If they match, it is marked as a match; otherwise, it is marked as a mismatch. In actual experimental data, for example, when multiple production stage numbers are continuously recorded, the difference remains stable when the numbers increase sequentially, but becomes significantly abnormal when there is a jump. Combining this with the correspondence of the preceding association information provides a dual verification basis, thus avoiding misjudgment problems caused by a single judgment.

[0027] After obtaining the sequential difference calculation result and the associated matching mark, a judgment needs to be made based on the sequential difference calculation result and the associated matching mark. When the sequential difference calculation result is not equal to the preset step size value or the associated matching mark is mismatched, it is determined that there is a discontinuity in the stage execution order or a mismatch in the preceding associated information between the semantic identifiers of the corresponding adjacent paths, and a collaborative driving path interruption is determined accordingly. In specific implementation, a normal step size value between stages can be set as the judgment benchmark. When the calculated difference value deviates from the benchmark, or the associated matching mark is mismatched, it is considered that the path relationship is abnormal. In actual testing, when the signal input of a certain stage is manually disconnected during the production process, the abnormal difference value and inconsistent associated information at the corresponding position in the sequence can be observed, thereby accurately locating the path interruption position. This joint judgment method can consider both sequential and associated information at the same time.

[0028] The path semantic identifier sequence represents a structured data set arranged according to the execution order of the stages. Each adjacent path semantic identifier refers to the comparison unit formed by two adjacent records in the sequence. The stage execution order information and the preceding association information are used to describe the current stage position and the relationship with the source stage, respectively. The adjacent comparison data set is a data set extracted from two adjacent records for analysis. The sequential difference calculation refers to the difference calculation of consecutive stage numbers to reflect the change in order. The difference between the execution order value of the current stage and the execution order value of the previous stage is used to determine whether the stage is continuous. The item-by-item matching process refers to the comparison of the preceding association information with the corresponding source information one by one. The association matching mark is used to identify the matching result. The preset step size value is used to limit the range of order change between normal stages. When the association matching mark is mismatched or the difference is abnormal, it indicates that the stage execution order is not continuous or the preceding association information is mismatched, so it can be determined that the collaborative driving path is interrupted. These elements together constitute the basis for accurately characterizing the continuity of the multi-stage parameter collaborative driving path.

[0029] S2. In the event of a collaborative drive path interruption, the interruption position, semantic offset direction and semantic breakage degree in the path semantic identifier sequence are fused and calculated to generate a path semantic state mapping quantity. In this embodiment, S2 specifically includes the following steps: S201. In the event of a collaborative drive path interruption, perform location processing on the path semantic identifier sequence, extract the corresponding path semantic identifier and its adjacent path semantic identifiers based on the interruption determination position in the path semantic identifier sequence, and determine the interruption position by combining the stage execution order information and the preceding association information. When a collaborative drive path interruption is determined, location processing needs to be performed on the path semantic identifier sequence to pinpoint the interruption location. Specifically, this can be achieved by sequentially traversing the path semantic identifier sequence, comparing each path semantic identifier with its predecessor, and reading the stage execution order information and preceding association information. When a jump in stage execution order is detected, or the preceding association information is inconsistent with the stage execution order information in the previous path semantic identifier, that location can be marked as the interruption determination location. The corresponding path semantic identifier and the semantic identifiers of adjacent paths at that location can then be extracted as analysis objects. For example, in actual production data acquisition, when recording data for a continuously running batch of nasal wash bag making, if the preceding association information of a certain record does not point to the stage execution order information of the previous record, it indicates a transmission break at that location. By comparing the records before and after that location, the interruption location can be precisely located. This processing refines the path interruption from an overall anomaly to a specific location, providing a foundation for subsequent analysis.

[0030] The path semantic identifier sequence represents a structured data set arranged according to the execution order of the stages. Each path semantic identifier contains stage execution order information and preceding association information. The location positioning process refers to analyzing each position in the path semantic identifier sequence one by one to determine the point of anomaly occurrence. The interruption judgment position represents the position identified as having a path break during the continuity verification process. The path semantic identifier and its adjacent path semantic identifiers refer to the data corresponding to the interruption judgment position and the data records immediately before and after it. The stage execution order information is used to describe the position of the current processing stage in the overall process. The preceding association information is used to identify the previous stage from which the data of the current stage comes. By combining the stage execution order information and the preceding association information, the specific location of the interruption position and its preceding and following relationships can be determined, thereby providing accurate input for the subsequent calculation of semantic offset direction and semantic break degree.

[0031] S202. Around the interruption position, perform directional difference analysis on the stage execution order information of adjacent path semantic identifiers in the path semantic identifier sequence. Determine the semantic offset direction by comparing the trend of stage execution order changes before and after the interruption position. At the same time, perform association deviation calculation on the preceding association information. Determine the degree of semantic break by statistically analyzing the deviation between the preceding association information and the corresponding stage execution order information. S203. The interruption position, semantic offset direction and semantic breakage degree are fused and calculated. The path semantic identifier corresponding to the interruption position is used as the position reference, the semantic offset direction is used as the direction parameter, and the semantic breakage degree is used as the degree parameter. These are combined and embedded to generate the path semantic state mapping quantity.

[0032] After obtaining the interruption location, semantic offset direction, and semantic breakage degree, these three elements need to be fused and calculated to generate a path semantic state mapping. Specifically, the path semantic identifier corresponding to the interruption location can be used as the core index unit. The position of this location in the path semantic identifier sequence can be used as the position reference. Simultaneously, the semantic offset direction is converted into a direction parameter identifier, and the semantic breakage degree is converted into a quantifiable degree parameter. Then, the three types of information are combined and embedded according to a unified data structure. For example, a composite data record containing location, direction, and degree fields can be constructed and written sequentially into the state record set in the control program. In actual production experiments, data from a batch of continuously produced nasal wash bag making processes can be analyzed. When a path interruption occurs at a certain location, the index position of that location in the sequence is recorded, the stage execution direction change is marked, and the correlation deviation degree is statistically analyzed. Combining these three elements forms a state record. By comparing multiple batches of data, it can be found that different interruption situations correspond to different combination results, thus achieving a unified expression of abnormal path states. The purpose of this processing is to integrate scattered interruption information into a unified data form that can participate in subsequent control.

[0033] The interruption location represents the specific index of the break in the path semantic identifier sequence. The semantic offset direction describes the direction of change in the execution order of the path before and after the interruption point. The semantic breakage degree reflects the magnitude of the deviation between the preceding associated information and the stage execution order information. The fusion calculation refers to the unified processing of the interruption location, semantic offset direction, and semantic breakage degree to form an integrated data representation. The path semantic identifier corresponding to the interruption location serves as a location benchmark to determine the position of this state in the overall sequence. The direction parameter is used to characterize the path change trend, and the degree parameter is used to characterize the path breakage intensity. The combined embedding refers to the integration of the location benchmark, direction parameter, and degree parameter into the same data structure. The path semantic state mapping quantity represents the integrated state data after fusion. This data can simultaneously reflect the location characteristics, change direction, and breakage degree of the path interruption, thereby providing a unified input basis for the adjustment of the subsequent multi-stage parameter collaborative driving relationship.

[0034] In this embodiment, S202 specifically refers to: Around the interruption location, the semantic identifiers of adjacent paths before and after the interruption location in the path semantic identifier sequence are extracted, and the stage execution order information in the corresponding path semantic identifiers is parsed to form the forward stage execution order sequence and the backward stage execution order sequence. Based on the difference analysis of the execution direction between the forward stage execution sequence and the backward stage execution sequence, the change trend of the stage execution order is determined by comparing the change direction of the forward stage execution sequence and the backward stage execution sequence, and the semantic offset direction is obtained. After determining the semantic offset direction, the preceding association information of the corresponding interruption position in the path semantic identifier sequence is extracted, and the preceding association information is aligned with the execution order information of the corresponding stage item by item to form an association comparison sequence. Based on the correlation comparison sequence, correlation deviation calculation is performed. By statistically analyzing the deviation between the preceding correlation information and the corresponding stage execution order information, the degree of semantic breakage is obtained.

[0035] To address the interruption point, it's necessary to extract the semantic identifiers of adjacent paths before and after the interruption point from the path semantic identifier sequence and parse their stage execution order information to form a forward stage execution order sequence and a backward stage execution order sequence. Specifically, using the interruption point as the central window, several path semantic identifiers can be extracted forward to form a forward sequence, and several path semantic identifiers can be extracted backward to form a backward sequence. The stage execution order information is then read from each path semantic identifier and arranged accordingly. For example, in a set of actual collected data on nasal wash salt bag production, after detecting an interruption point, the consecutive stage number sequences before and after that point can be extracted. This method splits the execution trajectory before and after the interruption point into two independent sequences, providing a basic data structure for subsequent analysis.

[0036] After obtaining the forward and backward execution sequences, directional difference analysis is needed. By comparing the changing directions of the two sequences, the trend of the stage execution order change is determined, thus obtaining the semantic offset direction. Specifically, this can be achieved by observing the changing trends of the stage numbers in both the forward and backward sequences, such as determining whether they are continuously increasing, reversing, or jumping. In experimental data, if the forward sequence shows normal increasing, while the backward sequence shows reversing or discontinuous changes, it indicates that the execution direction of the stage after the interruption point has shifted. This shift direction can then be used as the semantic offset direction, further refining path anomalies from simple interruptions to directional changes.

[0037] After determining the semantic offset direction, it is necessary to extract the preceding association information corresponding to the interruption position in the path semantic identifier sequence, and then align the preceding association information with the corresponding stage execution order information item by item to form an association comparison sequence. In specific implementation, the preceding association information in each path semantic identifier can be matched one-to-one with the stage execution order information in the adjacent records, and the two can be arranged in order to form aligned data. For example, in actual production data, aligning the preceding association field in the records near the interruption position with the corresponding stage number can form a set of one-to-one corresponding data pairs. This processing can make the originally implicit association relationship explicit, which is convenient for subsequent deviation analysis.

[0038] After forming the association comparison sequence, association deviation calculation needs to be performed. By statistically analyzing the deviation between preceding association information and the corresponding stage execution order information, the degree of semantic breakage can be obtained. In specific implementation, each item of preceding association information can be checked to see if it equals the corresponding stage execution order information, and the number or distribution of inconsistencies can be counted to reflect the degree of deviation of the association relationship. In actual testing, when stage signal missing is artificially introduced, it can be observed that the preceding association information cannot correspond to the correct stage number. By counting the number of deviation items, the severity of the path breakage can be quantified, thus expanding the path interruption from a single event to a measurable degree of information.

[0039] The interruption position indicates the specific location where an abnormal break occurs in the path semantic identifier sequence. The semantic identifiers of adjacent paths before and after the interruption position are used to construct before-and-after comparison data. The stage execution order information is used to describe the sequential relationship of each stage in the process. The forward stage execution order sequence and the backward stage execution order sequence represent the stage execution trajectories before and after the interruption position, respectively. The directional difference analysis is used to identify the difference in the direction of change between the two sequences. The stage execution order change trend reflects the change law of stage number. The semantic offset direction indicates the directional change of the path after the interruption. The preceding association information corresponding to the interruption position is used to describe the data source relationship. The item-by-item alignment processing is used to establish a correspondence between the preceding association information and the stage execution order information. The association comparison sequence represents the aligned data set. The association deviation calculation is used to measure the degree of difference between the two types of information. By statistically analyzing the deviation between the preceding association information and the corresponding stage execution order information, the degree of semantic breakage can be obtained, thereby providing a complete characterization of the abnormal state of the collaboratively driven path.

[0040] S3. Introduce the path semantic state mapping quantity into the multi-stage parameter collaborative driving relationship, reorganize the parameter association order, association strength and action direction between stages according to the path semantic state mapping quantity, and generate alternative association inputs based on the path semantic state mapping quantity to form a corresponding association evolution sequence. In this embodiment, S3 specifically includes the following steps: S301. Introduce the path semantic state mapping quantity into the multi-stage parameter collaborative driving relationship, insert the position benchmark corresponding to the stage in the path semantic state mapping quantity into the inter-stage parameter association relationship, and bind the direction parameter and degree parameter in the path semantic state mapping quantity to the association direction and association strength in the inter-stage parameter association relationship respectively, forming a multi-stage parameter collaborative driving relationship in which the path semantic state mapping quantity participates. Once the path semantic state mapping has been generated, it needs to be introduced into the multi-stage parameter collaborative driving relationship to adjust the original inter-stage parameter transmission logic. Specifically, the stage corresponding to the position reference in the path semantic state mapping can be used as an insertion node. The inter-stage parameter association relationship is reconstructed in the control program, and this node is embedded into the original stage connection structure. Simultaneously, the direction and degree parameters in the path semantic state mapping are read. The direction parameter is mapped as the basis for adjusting the inter-stage parameter action direction, and the degree parameter is mapped as the basis for adjusting the inter-stage parameter association strength. Both are then bound to the corresponding stage association edges. For example, in actual production experiments, data is collected from a continuously operating nasal wash bag production line. When a path interruption is detected in a certain stage, the path semantic state mapping determines that stage as the position reference, inserts it into the original parameter transmission link, and adjusts the parameter transmission direction of subsequent stages based on the recorded direction changes. The parameter action strength is reassigned based on the degree of interruption. In multiple batches of data verification, it can be observed that this introduction and binding process can form a new stage association structure, thereby replacing the original failed transmission path.

[0041] The path semantic state mapping quantity represents the comprehensive state data formed by fusing interruption location, semantic offset direction, and semantic breakage degree. The multi-stage parameter collaborative driving relationship represents the set of parameter transmission and interaction relationships between each processing stage. The position reference corresponding stage represents the key stage node used for positioning in the path semantic state mapping quantity. The inter-stage parameter association relationship represents the connection relationship of parameter transmission between different stages. The association direction in the inter-stage parameter association relationship is used to describe the direction of parameter transmission from one stage to another. The association strength is used to describe the weight or degree of influence of the parameter. By binding the direction parameter and degree parameter in the path semantic state mapping quantity to the association direction and association strength respectively, it means that the abnormal state of the path is mapped to the specific parameter interaction relationship. The multi-stage parameter collaborative driving relationship in which the path semantic state mapping quantity participates represents a new association structure after introducing path state information on the basis of the original stage association. This structure can simultaneously reflect the stage sequence relationship and the influence of abnormal path state on parameter transmission.

[0042] S302. Based on the path semantic state mapping quantity, rearrange the inter-stage parameter association order in the multi-stage parameter collaborative driving relationship in which the path semantic state mapping quantity participates, adjust the inter-stage parameter action direction according to the direction parameter in the path semantic state mapping quantity, and adjust the inter-stage parameter association strength according to the degree parameter in the path semantic state mapping quantity, thereby completing the reorganization of the inter-stage parameter association order, association strength and action direction. S303. Generate alternative associated inputs based on path semantic state mapping. Use the position reference in the path semantic state mapping as the input positioning parameter, the direction parameter in the path semantic state mapping as the input action direction parameter, and the degree parameter in the path semantic state mapping as the input action intensity parameter. Combine the input positioning parameter, the input action direction parameter, and the input action intensity parameter to generate alternative associated inputs. Embed the alternative associated inputs into the reorganized multi-stage parameter collaborative driving relationship according to the position reference in the path semantic state mapping. Arrange the reorganized multi-stage parameter collaborative driving relationship continuously according to the stage execution order to form a corresponding associated evolution sequence.

[0043] After the path semantic state mapping has participated in the reorganization of multi-stage parameter collaborative driving relationships, it is necessary to further generate alternative related inputs based on the path semantic state mapping and embed them into the reorganized multi-stage parameter collaborative driving relationships to form a new association structure. Specifically, the position reference in the path semantic state mapping can be used as the starting point for input generation. The direction and degree parameters in the path semantic state mapping can be combined to generate a new set of parameter transmission data as alternative related inputs. This alternative related input is then inserted into the stage node corresponding to the position reference, replacing the input relationship at the original interruption position. Simultaneously, the reorganized multi-stage parameter collaborative driving relationships are rearranged according to the stage execution order to form a continuous link. For example, in actual production experiments, analyzing the data of a batch of continuously produced nasal wash salt bag making, when a path interruption occurs at a certain stage, new input data is generated based on the recorded path semantic state mapping and inserted into the stage node, enabling subsequent stages to continue receiving parameter inputs. By comparing multiple batches of data, it can be observed that after the insertion of alternative related inputs, the parameter transmission relationship between stages is restored to continuity, thus forming a new association evolution sequence.

[0044] Alternative associated inputs represent the data set generated after a path interruption to replace the original stage inputs. The input position is determined by the positional reference in the path semantic state mapping, the direction of input action is determined by the direction parameter, and the intensity of input action is determined by the degree parameter. These are combined to generate corresponding alternative associated inputs. The positional reference in the path semantic state mapping is used to determine the insertion position of the alternative associated inputs. The reorganized multi-stage parameter collaborative driving relationship represents the stage connection structure after adjustments to the inter-stage parameter association order, association intensity, and action direction. Embedding alternative associated inputs into this structure represents the introduction of new input connections based on the original stage associations. The association evolution sequence represents the continuous stage association data sequence formed after introducing alternative associated inputs and rearranging them. This sequence reflects the new parameter transmission path after a path interruption, ensuring that the multi-stage parameter collaborative driving relationship maintains a continuous evolutionary state even after an anomaly occurs.

[0045] In this embodiment, S302 specifically refers to: Based on the position reference in the path semantic state mapping, the corresponding stage node is located in the multi-stage parameter collaborative driving relationship in which the path semantic state mapping participates, and the inter-stage parameter association relationship between the adjacent stages before and after the node is extracted to form a set of inter-stage parameter association order rearrangement. Based on the set of inter-stage parameter association order rearrangement, the direction determination of the parameter association relationship between adjacent stages is performed according to the direction parameter in the path semantic state mapping. By aligning and matching the original inter-stage parameter action direction with the direction parameter, the adjustment of the inter-stage parameter action direction is completed. After adjusting the direction of action of inter-stage parameters, the association strength in the inter-stage parameter association relationship is classified according to the degree parameter in the path semantic state mapping. By mapping the association strength to the degree parameter and reassigning the value, and rearranging the order of inter-stage parameter association according to the adjusted direction of action of inter-stage parameters, the reorganization of the inter-stage parameter association order, association strength and direction of action is completed.

[0046] To establish a rearrangement set based on the location benchmark in the path semantic state mapping, it is necessary to locate the corresponding stage node within the multi-stage parameter collaborative driving relationship involving the path semantic state mapping, and extract the inter-stage parameter association relationships between adjacent stages before and after that node. Specifically, a stage node index table can be established in the control program, using the stage number corresponding to the location benchmark as the location entry point. The position of that stage in the collaborative driving relationship can be found, and the parameter transmission relationships between adjacent stages before and after that node can be extracted as the basis for rearrangement. For example, in a set of actual collected production data, once a stage is marked as a location benchmark, the parameter connection relationships between its preceding and following stages can be read from the data structure, and these relationships can be aggregated to form a rearrangement set for subsequent adjustments.

[0047] After obtaining the set of rearranged parameter associations between stages, it is necessary to perform directional determination processing on the parameter associations between adjacent stages based on the direction parameters in the path semantic state mapping. Specifically, the original inter-stage parameter action direction can be used as the basic direction identifier, and compared item by item with the direction parameters. Alignment matching is then performed; when the direction parameter matches the original direction, the original direction is maintained; when there is a difference, the action direction is adjusted. For example, in experimental data, when a path offset direction is detected to be opposite to the original transmission direction, the parameter transmission direction of subsequent stages can be adjusted in the opposite direction to ensure that the new transmission relationship conforms to the current path state.

[0048] After adjusting the direction of action of parameters between stages, it is necessary to classify the association strength in the parameter relationships between stages according to the degree parameter in the path semantic state mapping. Specifically, the original association strength can be divided into multiple level intervals, and the association strength can be reassigned according to the degree parameter, mapping the degree parameter to the corresponding level, thereby changing the weight of action between parameters. For example, in actual testing, when the path breakage degree is high, the association strength can be reduced to a lower level, and when the breakage degree is low, a higher strength can be maintained. This hierarchical processing allows for differentiated control over different breakage conditions.

[0049] After adjusting the association strength, the association order between stage parameters needs to be rearranged based on the adjusted direction of action of the stage parameters. Specifically, the connection order between stages can be redefined based on the adjusted direction information, and the new order can be written into the data structure to form the updated association relationship. For example, during experiments, by comparing and analyzing multiple batches of data, it can be observed that rearranging the association order after direction adjustment can form new stage connection paths, thus replacing the connection methods after the original path was interrupted.

[0050] The location benchmark in the path semantic state mapping represents the reference point used to locate key stages. The multi-stage parameter collaborative driving relationship involved in the path semantic state mapping represents the stage association set after introducing path state. The stage node represents the specific stage position in the set. The inter-stage parameter association relationship between adjacent stages before and after the node is used to describe the connection between the nodes. The set of reordered inter-stage parameter association order represents the set of connection relationships to be adjusted. The direction parameter in the path semantic state mapping is used to indicate the change in parameter transmission direction. The direction determination processing is used to analyze and determine the direction. The alignment and matching of the original inter-stage parameter action direction and the direction parameter is used to complete the direction adjustment. The degree parameter in the path semantic state mapping is used to describe the degree of breakage. The association strength in the inter-stage parameter association relationship represents the parameter action weight. The hierarchical division processing is used to classify the strength into levels. Mapping the association strength to the degree parameter and reassigning it is used to achieve strength adjustment. The adjusted inter-stage parameter action direction and inter-stage parameter association order together constitute the reorganized multi-stage parameter collaborative driving relationship.

[0051] S4. Continuously track the path semantic state mapping quantity and update the associated evolution sequence based on the changes in the path semantic state mapping quantity to complete the adjustment of the multi-stage parameter collaborative driving relationship.

[0052] In this embodiment, S4 specifically refers to: The path semantic state mapping quantity is continuously tracked, and the path semantic state mapping quantity is arranged in order according to the stage execution order. The position reference, direction parameter and degree parameter in the adjacent path semantic state mapping quantity are compared item by item to obtain the change information of the path semantic state mapping quantity. Continuous tracking of path semantic state mapping quantities can be achieved by establishing a state record sequence arranged according to the execution order of each stage in the control program. Each generated path semantic state mapping quantity is sequentially written into the data sequence according to the corresponding stage. When a new path semantic state mapping quantity is written, it is extracted and compared item by item with the previous one. The position reference is indexed and compared, the direction parameter is judged for consistency or variability, and the degree parameter is analyzed for numerical differences, thus obtaining information on changes in the path semantic state mapping quantity. For example, in actual production experiments, data on a batch of continuously produced nasal wash salt bags is collected. When a path interruption occurs at a certain stage, multiple path semantic state mapping quantity records are continuously generated. By statistically analyzing the changes in position references in adjacent records, it is possible to identify whether the interruption location has shifted. By analyzing changes in direction parameters, it is possible to identify path offset trends. By statistically analyzing changes in degree parameters, it is possible to reflect the magnitude of changes in the degree of breakage. This continuous tracking and item-by-item comparison can transform path state from single-point information into dynamic change information, thus providing a basis for subsequent updates to the correlation.

[0053] The path semantic state mapping quantity represents a comprehensive data record formed by fusing the interruption location, semantic offset direction, and semantic breakage degree. Continuous tracking represents the continuous collection and recording of this type of data in time or stage sequence. Stage execution order is used to determine the arrangement relationship between each path semantic state mapping quantity. Sequential arrangement means that the path semantic state mapping quantities are organized into a continuous sequence according to the stage sequence. Adjacent path semantic state mapping quantities refer to two records that are adjacent to each other in the sequence. The position reference is used to identify the location of the stage where the path interruption occurs. The direction parameter is used to describe the directional characteristics of the path change. The degree parameter is used to describe the intensity characteristics of the path breakage. Item-by-item comparison processing means that the corresponding fields in adjacent records are compared one by one. The change information of the path semantic state mapping quantity represents the state change result obtained by analyzing the changes in the position reference, direction parameter, and degree parameter. This change information can reflect the evolution of the abnormal state of the path in continuous stages.

[0054] The association evolution sequence is updated based on the changes in the path semantic state mapping quantity. The change information of the path semantic state mapping quantity is mapped to the corresponding stage nodes in the association evolution sequence. The association order, association strength and direction of action of the inter-stage parameters in the association evolution sequence are adjusted synchronously. The updated association evolution sequence is then arranged continuously according to the stage execution order to complete the adjustment of the multi-stage parameter collaborative driving relationship.

[0055] After obtaining the change information of the path semantic state mapping quantity, it is necessary to map this change information to the corresponding stage node in the associated evolution sequence, thereby updating the associated evolution sequence. Specifically, an index correspondence between stage nodes and path semantic state mapping quantities can be established in the control program. When a change in the path semantic state mapping quantity is detected, the position reference in the change information is mapped to the specific stage node in the associated evolution sequence, and the parameter association relationship between that node and its adjacent stages is adjusted. This includes correcting the parameter transmission direction based on changes in direction parameters, reassigning the parameter association strength based on changes in degree parameters, and adjusting the parameter association order between stages. Finally, the updated stage nodes are rearranged according to the stage execution order to form a continuous sequence. For example, in an actual production experiment, data from a batch of continuously running nasal wash bag making processes is recorded. When the path semantic state mapping quantity changes at a certain stage, this change information is mapped to the corresponding stage node, and the parameter transmission direction and strength of subsequent stages are adjusted. By comparing multiple batches of data, it can be observed that after this update process, the parameter transmission relationship between stages can continuously adapt to changes in path state, thus forming a dynamically updated associated evolution sequence.

[0056] The change in path semantic state mapping represents the changes in position reference, direction parameters, and degree parameters in continuous stages. The associated evolution sequence represents a continuous data sequence formed by the multi-stage parameter collaborative driving relationship after reorganization, according to the stage execution order. Mapping the change information of path semantic state mapping to the corresponding stage node in the associated evolution sequence means determining the specific adjustment position based on the position reference. The corresponding stage node refers to the specific stage position in the associated evolution sequence. The parameter association order between stages represents the sequential relationship of parameter transmission between stages. The association strength represents the weight of the interaction between parameters. The direction of action represents the directional relationship of parameter transmission. Synchronous adjustment means that the order, strength, and direction are jointly modified in the same update process. Continuous arrangement according to the stage execution order means that the updated stage relationship is reordered to form a continuous structure. The adjustment of the multi-stage parameter collaborative driving relationship means that the entire stage parameter collaborative relationship is dynamically adjusted through the above update process.

[0057] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. A computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions according to the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. Computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired or wireless means (e.g., infrared, wireless, microwave, etc.). A computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. Available media can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media. Semiconductor media can be solid-state drives.

[0058] It should be understood that in the various embodiments of this application, the order of the above-mentioned processes does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0059] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0060] In the several embodiments provided in this application, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0061] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0062] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0063] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A multi-stage parameter coordinated driving method for the nasal rinse salt bag making process, characterized in that, Specifically, the following steps are included: S1. Sequentially associate and encode the output parameters of each stage in the nasal saline bag making process to generate the corresponding path semantic identifier sequence, and perform continuity verification on the path semantic identifier sequence to determine whether a collaborative driving path interruption has occurred. S2. In the event of a collaborative drive path interruption, the interruption position, semantic offset direction and semantic breakage degree in the path semantic identifier sequence are fused and calculated to generate a path semantic state mapping quantity. S3. Introduce the path semantic state mapping quantity into the multi-stage parameter collaborative driving relationship, reorganize the parameter association order, association strength and action direction between stages according to the path semantic state mapping quantity, and generate alternative association inputs based on the path semantic state mapping quantity to form a corresponding association evolution sequence. S4. Continuously track the path semantic state mapping quantity and update the associated evolution sequence based on the changes in the path semantic state mapping quantity to complete the adjustment of the multi-stage parameter collaborative driving relationship.

2. The multi-stage parameter coordinated driving method for the nasal wash salt bag making process according to claim 1, characterized in that, S1 specifically includes the following steps: S101. The output parameters of each stage in the nasal rinse salt bag making process are sequentially associated and encoded according to the stage execution order. Each stage output parameter is bound to the corresponding stage execution order identifier, and the current stage execution order identifier is associated and combined with the previous stage execution order identifier to form a sequential association code containing stage execution order information and previous association information. S102. Based on the sequential association coding, the execution order of each stage is arranged in the order of execution. The execution order information, the preceding association information and the output parameter information in each sequential association coding are combined and embedded to construct the corresponding path semantic identifier sequence. S103. Perform continuity verification on the path semantic identifier sequence. Compare the stage execution order information and the preceding association information in the adjacent path semantic identifiers level by level. When there is a discontinuity in the stage execution order or a mismatch in the preceding association information between adjacent path semantic identifiers, it is determined that a collaborative driving path interruption has occurred.

3. The multi-stage parameter coordinated driving method for the nasal wash salt bag making process according to claim 2, characterized in that, S103 specifically refers to: For each adjacent path semantic identifier pair in the path semantic identifier sequence, extract the stage execution order information and the preceding association information in each path semantic identifier to form the corresponding adjacent comparison data group. Based on the adjacent comparison data group, the execution order information of the stage in the semantic identifier of the adjacent path is subjected to sequential difference calculation to obtain the difference between the execution order value of the current stage and the execution order value of the previous stage. At the same time, the preceding association information is subjected to item-by-item matching processing to obtain the corresponding association matching tag. The determination is made based on the sequential difference calculation result and the associated matching mark. When the sequential difference calculation result is not equal to the preset step size value or the associated matching mark is mismatched, it is determined that there is a discontinuity in the stage execution order or a mismatch in the preceding associated information between the semantic identifiers of the corresponding adjacent paths, and the collaborative driving path is interrupted accordingly.

4. The multi-stage parameter coordinated driving method for the nasal wash salt bag making process according to claim 1, characterized in that, S2 specifically includes the following steps: S201. In the event of a collaborative drive path interruption, perform location processing on the path semantic identifier sequence, extract the corresponding path semantic identifier and its adjacent path semantic identifiers based on the interruption determination position in the path semantic identifier sequence, and determine the interruption position by combining the stage execution order information and the preceding association information. S202. Around the interruption position, perform directional difference analysis on the stage execution order information of adjacent path semantic identifiers in the path semantic identifier sequence. Determine the semantic offset direction by comparing the trend of stage execution order changes before and after the interruption position. At the same time, perform association deviation calculation on the preceding association information. Determine the degree of semantic break by statistically analyzing the deviation between the preceding association information and the corresponding stage execution order information. S203. The interruption position, semantic offset direction and semantic breakage degree are fused and calculated. The path semantic identifier corresponding to the interruption position is used as the position reference, the semantic offset direction is used as the direction parameter, and the semantic breakage degree is used as the degree parameter. These are combined and embedded to generate the path semantic state mapping quantity.

5. The multi-stage parameter coordinated driving method for the nasal wash salt bag making process according to claim 4, characterized in that, S202 specifically refers to: Around the interruption location, the semantic identifiers of adjacent paths before and after the interruption location in the path semantic identifier sequence are extracted, and the stage execution order information in the corresponding path semantic identifiers is parsed to form the forward stage execution order sequence and the backward stage execution order sequence. Based on the difference analysis of the execution direction between the forward stage execution sequence and the backward stage execution sequence, the change trend of the stage execution order is determined by comparing the change direction of the forward stage execution sequence and the backward stage execution sequence, and the semantic offset direction is obtained. After determining the semantic offset direction, the preceding association information of the corresponding interruption position in the path semantic identifier sequence is extracted, and the preceding association information is aligned with the execution order information of the corresponding stage item by item to form an association comparison sequence. Based on the correlation comparison sequence, correlation deviation calculation is performed. By statistically analyzing the deviation between the preceding correlation information and the corresponding stage execution order information, the degree of semantic breakage is obtained.

6. The multi-stage parameter coordinated driving method for the nasal wash salt bag making process according to claim 1, characterized in that, S3 specifically includes the following steps: S301. Introduce the path semantic state mapping quantity into the multi-stage parameter collaborative driving relationship, insert the position benchmark corresponding to the stage in the path semantic state mapping quantity into the inter-stage parameter association relationship, and bind the direction parameter and degree parameter in the path semantic state mapping quantity to the association direction and association strength in the inter-stage parameter association relationship respectively, forming a multi-stage parameter collaborative driving relationship in which the path semantic state mapping quantity participates. S302. Based on the path semantic state mapping quantity, rearrange the inter-stage parameter association order in the multi-stage parameter collaborative driving relationship in which the path semantic state mapping quantity participates, adjust the inter-stage parameter action direction according to the direction parameter in the path semantic state mapping quantity, and adjust the inter-stage parameter association strength according to the degree parameter in the path semantic state mapping quantity, thereby completing the reorganization of the inter-stage parameter association order, association strength and action direction. S303. Generate alternative associated inputs based on path semantic state mapping. Use the position reference in the path semantic state mapping as the input positioning parameter, the direction parameter in the path semantic state mapping as the input action direction parameter, and the degree parameter in the path semantic state mapping as the input action intensity parameter. Combine the input positioning parameter, the input action direction parameter, and the input action intensity parameter to generate alternative associated inputs. Embed the alternative associated inputs into the reorganized multi-stage parameter collaborative driving relationship according to the position reference in the path semantic state mapping. Arrange the reorganized multi-stage parameter collaborative driving relationship continuously according to the stage execution order to form a corresponding associated evolution sequence.

7. The multi-stage parameter coordinated driving method for the nasal wash salt bag making process according to claim 6, characterized in that, S302 specifically refers to: Based on the position reference in the path semantic state mapping, the corresponding stage node is located in the multi-stage parameter collaborative driving relationship in which the path semantic state mapping participates, and the inter-stage parameter association relationship between the adjacent stages before and after the node is extracted to form a set of inter-stage parameter association order rearrangement. Based on the set of inter-stage parameter association order rearrangement, the direction determination of the parameter association relationship between adjacent stages is performed according to the direction parameter in the path semantic state mapping. By aligning and matching the original inter-stage parameter action direction with the direction parameter, the adjustment of the inter-stage parameter action direction is completed. After adjusting the direction of action of inter-stage parameters, the association strength in the inter-stage parameter association relationship is classified according to the degree parameter in the path semantic state mapping. By mapping the association strength to the degree parameter and reassigning the value, and rearranging the order of inter-stage parameter association according to the adjusted direction of action of inter-stage parameters, the reorganization of the inter-stage parameter association order, association strength and direction of action is completed.

8. The multi-stage parameter coordinated driving method for the nasal wash salt bag making process according to claim 1, characterized in that, S4 specifically refers to: The path semantic state mapping quantity is continuously tracked, and the path semantic state mapping quantity is arranged in order according to the stage execution order. The position reference, direction parameter and degree parameter in the adjacent path semantic state mapping quantity are compared item by item to obtain the change information of the path semantic state mapping quantity. The association evolution sequence is updated based on the changes in the path semantic state mapping quantity. The change information of the path semantic state mapping quantity is mapped to the corresponding stage nodes in the association evolution sequence. The association order, association strength and direction of action of the inter-stage parameters in the association evolution sequence are adjusted synchronously. The updated association evolution sequence is then arranged continuously according to the stage execution order to complete the adjustment of the multi-stage parameter collaborative driving relationship.

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