Online Cycle Reconstruction Method for Multi-Process Linkage Equipment Based on Digital Twin

Abstract

This invention discloses an online cycle time reconstruction method for multi-process linkage equipment based on digital twins, specifically relating to the field of industrial automation control technology. The controller initializes the acquisition channel and performs anti-jitter screening, marking low-confidence events. Events such as material feeding, material discharge, cutter dead point, and weighing are solidified as odometer anchor point events. Anchor point segments are divided, and the quality of these events is evaluated. During material feeding, a workpiece identifier is generated and written to the work-in-process queue, and a twin workpiece instance is established and bound on the twin side. A displacement odometer is established, and anchor point predictions are compared with actual triggers to identify drift. Multi-source evidence is fused to obtain a comprehensive odometer drift correction quantity, outputting the displacement correction quantity and position uncertainty. The position is cumulatively corrected, and a comprehensive virtual workstation misalignment trigger gating quantity is generated by combining the virtual workstation window and the actuator readiness factor. The triggering strategy is adaptively adjusted to achieve cycle time reconstruction, thereby improving position tracking accuracy and reducing the risk of misalignment triggering.

Description

Technical Field

[0001] This invention relates to the field of industrial automation control technology, and more specifically, to a method for online cycle time reconstruction of multi-process linkage equipment based on digital twins. Background Technology

[0002] Multi-process linkage processing and virtual workstation trigger control technology is mainly used for automated collaborative control of continuous processing equipment primarily based on conveyor belt transportation. This allows processes such as material input documentation, peeling, slicing, and weighing to be sequentially connected under a unified cycle time. By maintaining the binding relationship between workpiece identifiers and spatial positions, the work-in-process queue is updated, thereby generating trigger windows for each workstation in the virtual workstation model and driving the actuators to move. This technology is widely used in agricultural and food processing, continuous sorting and packaging, and light industrial material handling. Among these applications, virtual workstation triggering schemes that use encoder counting and photoelectric event signals as the main sensing inputs are often used for online cycle time control and workstation motion scheduling of multi-process linkage equipment due to their lower deployment costs and simpler engineering implementation.

[0003] The existing technology has the following shortcomings:

[0004] Previously, multi-process linkage equipment relied heavily on fixed delays and encoder counting to calculate workpiece positions and trigger virtual workstations. This approach excessively depended on single displacement odometers and lacked online correction for conveyor belt slippage, elongation, and rebound. In conditions with high levels of cinnamon dust, fluctuating moisture content, or oily residue, photoelectric sensors are easily obstructed or interfered with by reflections. Furthermore, vibrations during peeling and slicing can cause event signal jitter and missed detections, leading to gradual drift of the workpiece marker's position in the work queue. This misalignment between the virtual workstation trigger window and the actual arrival point results in incomplete peeling, material damage, uncontrolled slice thickness, and even material jamming. It also causes confusion in weighing objects and breaks in the traceability chain. Therefore, it is crucial to conduct reliability assessment and dynamic correction of workpiece markers and spatial positions. This involves utilizing anchor events such as material infeed, material discharge, cutter top or bottom dead points, and weighing completion, combined with multi-source fusion to update the position confidence interval. When confidence decreases, adaptive window expansion and speed reduction are implemented to ensure quality and safety.

[0005] To address the above problems, this invention proposes a solution. Summary of the Invention

[0006] In order to overcome the above-mentioned defects of the prior art, embodiments of the present invention provide an online cycle reconstruction method for multi-process linkage equipment based on digital twins to solve the problems mentioned in the background art.

[0007] To achieve the above objectives, the present invention provides the following technical solution:

[0008] The online cycle time reconstruction method for multi-process linkage equipment based on digital twins includes the following steps:

[0009] Step 1: The controller initializes and verifies the connectivity of the equipment operation signal and event signal acquisition channels; performs anti-jitter and validity screening on the event signals and marks low-confidence events; solidifies events strongly correlated with the workpiece's passing position as odometer anchor point events, uses the time interval formed by two adjacent odometer anchor point events as anchor point segments, evaluates the quality of odometer anchor point events within the anchor point segment to obtain the anchor point segment event quality, and marks the corresponding anchor segment as a low-confidence anchor segment when the anchor segment event quality is lower than a preset threshold;

[0010] Step 2: When a workpiece is detected to have arrived at the feed end, a unique workpiece identifier is generated and written into the in-process queue. On the digital twin side, a twin workpiece instance corresponding to the workpiece identifier is generated one-to-one and a binding relationship is established. The odometer anchor point event is associated with the workpiece identifier in the in-process queue and the data is organized with the anchor point segment as the basic unit.

[0011] Step 3: Establish a displacement odometer to predict the workpiece marker position, compare the actual trigger time of the odometer anchor point event with the predicted trigger time of the displacement odometer to identify suspicious drift states; generate multi-source evidence characterizing displacement drift for the anchor point segment and fuse it to obtain a comprehensive odometer drift correction quantity, and output the anchor point segment displacement correction quantity and anchor point segment position uncertainty based on the comprehensive odometer drift correction quantity.

[0012] Step 4: For workpieces in a suspected drift state or whose associated anchor segments are marked as low-confidence anchor segments, the cumulative correction amount and cumulative uncertainty of the subsequent anchor segment displacement are accumulated based on the most recent reliable odometer anchor event. The cumulative correction amount is then used to correct the position estimate given by the displacement odometer to obtain the corrected position. Based on the corrected position, cumulative uncertainty, and pre-set virtual station window, a misalignment tendency amount is formed. Combined with the actuator's ready state, a ready factor is generated, thereby obtaining the virtual station misalignment trigger gating comprehensive amount. The virtual station triggering strategy is adaptively adjusted according to the virtual station misalignment trigger gating comprehensive amount to achieve online cycle time reconstruction.

[0013] In a preferred embodiment, the equipment operation signals and event signals include at least one or more of the following: encoder pulse acquisition signal, feed end photoelectric or proximity switch signal, peeling zone discharge detection signal, slicing mechanism cutter top dead point signal and bottom dead point signal, weighing arrival signal, and weighing module weight data reporting signal.

[0014] In a preferred embodiment, the anti-jitter and effectiveness screening in step one includes filtering out short pulse width spikes, suppressing repeated triggering of the same event within a short period of time, and marking missing detections for events that do not trigger for a long time or have abnormal triggering intervals, and marking events that are still abnormal after processing as low confidence events.

[0015] In a preferred embodiment, the anchor segment event quality in step one is determined by a combination of the missing status of odometer anchor events within the anchor segment, the repeated triggering status, and the jitter intensity at the triggering time. When the anchor segment event quality is lower than a preset threshold, the corresponding anchor segment is marked as a low-confidence anchor segment.

[0016] In a preferred embodiment, the twin workpiece instance in step two includes at least an initial timestamp, an initial position, an initial position uncertainty, and a process link identifier. The process link identifier is used to solidify the process sequence constraints of the workpiece identifier in a multi-process linkage device.

[0017] In a preferred embodiment, the identification conditions for the suspicious drift state in step three include the difference between the actual trigger time and the predicted trigger time of the anchor point event showing a cumulative shift in the same direction within a continuous anchor point segment, a significant amplification of the difference fluctuation amplitude, or the occurrence of inconsistent order phenomena such as the event not arriving when it should have arrived or arriving early.

[0018] In a preferred embodiment, the multi-source evidence in step three includes evidence of displacement inconsistency and load-induced slippage formed by one or more of encoder pulse count, anchor segment time interval, average transmission speed and average drive current, and combined with anchor segment event quality to form evidence of anchor segment event quality degradation; the mileage drift correction comprehensive quantity is the result obtained by fusing and normalizing the evidence according to preset weights.

[0019] In a preferred embodiment, in step three, when both encoder pulse counting and motor speed feedback are available, the direction of the anchor segment displacement correction is determined based on the difference between the encoder displacement and the speed integral displacement based on motor speed feedback, so that the segment-level correction of the displacement odometer is directed in the direction of reducing the difference.

[0020] In a preferred embodiment, the misalignment tendency in step four is determined based on the window boundary safety margin. The window boundary safety margin is based on the minimum distance from the corrected position to both sides of the virtual workstation window and is obtained by subtracting from the cumulative uncertainty. The virtual workstation misalignment triggering gating comprehensive quantity is calculated by combining the misalignment tendency with the readiness factor. The higher the readiness factor, the lower the virtual workstation misalignment triggering gating comprehensive quantity.

[0021] In a preferred embodiment, the adaptive adjustment of the virtual workstation triggering strategy in step four includes setting a first threshold, a second threshold, and a third threshold, wherein the first threshold is less than the second threshold and the second threshold is less than the third threshold; when the virtual workstation misalignment triggering gated comprehensive amount is lower than the first threshold, it is triggered according to the standard virtual workstation triggering window; when the virtual workstation misalignment triggering gated comprehensive amount is not lower than the first threshold and is lower than the second threshold, the triggering window is expanded and the triggering condition is upgraded to a linkage triggering of the position arrival and odometer anchor point event or the workstation readiness confirmation event; when the virtual workstation misalignment triggering gated comprehensive amount is not lower than the second threshold and is lower than the third threshold, the transmission speed is reduced and the number of confirmations for the linkage triggering is increased; when the virtual workstation misalignment triggering gated comprehensive amount is not lower than the third threshold, flow limiting or freezing processing is performed on the in-process queue and the addition of new workpiece identifiers is suspended.

[0022] The technical effects and advantages of this invention are as follows:

[0023] This invention initializes and verifies the equipment operation signal and event signal acquisition channels, and performs anti-jitter and validity screening on event signals to mark low-confidence events. Furthermore, it solidifies events strongly correlated with workpiece position, such as material feeding, material discharge from the peeling zone, the top or bottom dead point of the slicing mechanism cutter, and weighing, into odometer anchor point events. Anchor point segments are formed by adjacent anchor point events, and the quality of these segments is quantified. This allows for explicit management of anchor point segment reliability under conditions such as dust obstruction, vibration, and missed detections, avoiding the gradual drift of the work queue position caused by relying solely on displacement odometers. Based on evidence of inconsistent displacement, load-induced slippage, and deterioration of anchor point segment event quality, a comprehensive odometer drift correction is obtained. The output includes the anchor segment displacement correction and anchor segment position uncertainty, thereby transforming unobservable cumulative deviations of slippage, elongation, and springback into executable segment-level corrections and conservative uncertainty boundaries. This improves the accuracy of workpiece identification position prediction and the consistency of process link mapping, and reduces the probability of station trigger window misalignment.

[0024] At the cycle time control level, this invention targets workpieces in a state of suspected drift or whose associated anchor segments are marked as low-confidence anchor segments. Using the most recent reliable odometer anchor event as the alignment benchmark, it accumulates the anchor segment displacement correction and the anchor segment position uncertainty to obtain the cumulative correction amount and cumulative uncertainty, and then obtains the corrected position. Furthermore, it combines a preset virtual workstation window to form a misalignment tendency quantity, and introduces the actuator's ready state to generate a ready factor, resulting in a comprehensive virtual workstation misalignment trigger gating quantity. This drives adaptive adjustment of the virtual workstation triggering strategy, which includes window expansion, linkage confirmation, speed reduction, and in-process queue flow limiting / freezing. This allows multi-process linked equipment to proactively switch to conservative triggering and cycle time reconstruction when uncertainty increases, thereby reducing risks such as peeling damage, uncontrolled slice thickness, material jamming, and weighing mismatch, and improving continuous production stability. Simultaneously, key decision quantities are stored in association with workpiece identifiers, facilitating data chain traceability before and after misalignment, enhancing process interpretability and quality traceability capabilities. Attached Figure Description

[0025] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings;

[0026] Figure 1 This is a flowchart illustrating the online cycle time reconstruction method for multi-process linkage equipment based on digital twins according to the present invention.

[0027] Figure 2 This is a schematic diagram of the closed loop of virtual workstation triggering and online cycle reconstructing of multi-process linkage equipment based on digital twins according to the present invention. Detailed Implementation

[0028] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0029] Example 1, such as Figure 2 As shown, this embodiment includes a physical device side, a controller, and a digital twin side. The controller generates a virtual workstation window trigger strategy based on event signals and operation signals and drives the actuator to move. Based on this, the present invention provides a method for online cycle time reconstruction of multi-process linkage equipment based on digital twins, as follows: Figure 1 As shown, it includes the following steps:

[0030] Step 1: After the equipment is powered on, the controller first initializes and verifies the connectivity of the encoder pulse acquisition channel, the photoelectric or proximity switch at the feed end, the material discharge detection signal in the peeling area, the top and bottom dead center signals of the slicing mechanism cutter, the weighing arrival signal, and the weight data reporting channel of the weighing module. This ensures that all signals are collected uniformly under the same sampling cycle and a unified timestamp is attached, thereby forming a basic dataset that can be used for subsequent workpiece identification and spatial position binding. To avoid false triggering or missed triggering caused by dust obstruction, reflective interference, and mechanical vibration on site, the controller performs anti-jitter and validity screening processing on the above event signals, including filtering out short pulse width glitch, suppressing repeated triggering of the same event in a short period of time, and marking missing detections for events that are not triggered for a long time or have abnormal triggering intervals. At the same time, events judged to be suspicious for obstruction, abnormal for jitter, or missing are recorded as low-confidence events for subsequent quantitative expression of event quality in the anchor point segment. Among these, events strongly correlated with the workpiece's position include material feeding, material discharge from the peeling zone, the top and bottom dead centers of the slicing mechanism's cutter, and weighing completion. In this embodiment, these events are used as odometer anchor point events to provide verifiable timing anchor points for subsequent anchor point segmentation and drift correction. Furthermore, the controller uses the time interval formed by two adjacent odometer anchor point events as the anchor point segment. The reliability of events within the anchor segment is evaluated to obtain the event quality of the anchor segment. The closer the value is to 1, the more stable and consistent the triggering of anchor point events such as material feeding, material discharge from the peeling zone, cutting at the top or bottom dead center, and weighing at the anchor point segment. The closer the value is to 0, the more obvious the absence, repetition, or jitter. This is to facilitate the subsequent calculation of the overall mileage drift correction amount. When used uniformly, the event quality of the anchor segment is... It can be determined by combining the missing rate, repeated trigger rate, and time jitter intensity within the anchor segment, for example, in the following form:

[0031] ;

[0032] in, This means restricting the result to between 0 and 1, that is, taking 0 when x < 0, taking 1 when x > 1, and otherwise taking x itself; This represents the missing rate of anchor events within an anchor segment, reflecting the proportion of events that should have been triggered but were not. Defined as the ratio of the number of anchor events that should have been triggered but were not, to the total number of events that should have been triggered; This represents the recurrence rate of anchor events within an anchor segment, reflecting the proportion of abnormal recurrences of the same anchor point within a short period of time. Defined as the ratio of the number of times the same anchor point event is abnormally triggered repeatedly within a short period of time to the total number of events that should be triggered; This indicates the jitter intensity at the moment the anchor event is triggered within the anchor segment, reflecting the degree of temporal instability that still exists after anti-jitter processing. Defined as the coefficient of variation (the ratio of standard deviation to mean) of the time interval between anchor event triggering, it is used to quantify temporal instability; , , This is a weighting coefficient used to balance the impact of missing, duplicate, and jitter on the event quality of the anchor segment. Its value range is [0,1], and it satisfies... The specific values ​​can be determined through experiments or simulations based on actual working conditions; for example, a value can be taken as... , , .

[0033] Through the above processing, the controller can obtain a unified timing reference, along with event reliability flags and anchor segment event quality at the initial stage of system operation. The event sequence provides a reliable input for subsequent segment-level drift correction and virtual workstation trigger gating based on odometer anchor point events, thereby reducing the probability of gradual drift in the in-process queue position and misalignment of the workstation trigger window caused by relying solely on a single encoder count or fixed delay.

[0034] Step Two: When the photoelectric or proximity switch at the feed end detects the arrival of cinnamon bark, the controller determines this arrival as a valid feed event and generates a unique workpiece identifier. This ensures that each piece of cinnamon bark entering the equipment has a traceable identification index during subsequent transportation, peeling, slicing, and weighing processes. The workpiece identifier can be generated using an incremental sequence number or a combination of batch number and sequence number to associate it with production batch, shift, or recipe version. Simultaneously with generating the workpiece identifier, the controller writes it into the work-in-progress queue and registers the timestamp of the feed event and the feed end reference position as the initial state of the workpiece identifier, giving it a clear starting point and spatiotemporal reference. To ensure consistent mapping for subsequent linkage control based on digital twins, the controller synchronously generates twin workpiece instances that correspond one-to-one with workpiece identifiers on the digital twin side, and establishes a binding relationship between the twin workpiece instances and workpiece identifiers in the in-process queue. The twin workpiece instances include at least an initial timestamp, an initial position, an initial position uncertainty, and a process link identifier. The process link identifier is used to solidify the processing order in which the workpiece needs to pass through the peeling virtual station, the slicing virtual station, and the weighing virtual station in sequence, thereby providing a consistent sequence constraint for subsequent virtual station triggering and gating.

[0035] After completing the enqueue and twin instance generation, the controller solidifies events strongly related to the workpiece's position, such as material feeding, material discharge from the peeling zone, the top and bottom dead centers of the slicing mechanism's cutter, and weighing, into odometer anchor point events. It also establishes the expected sequence and arrival constraints for these anchor point events within the system, enabling the sequence of anchor point events corresponding to the same workpiece identifier during operation to be used to verify the cumulative deviation of the displacement odometer. To facilitate subsequent segment-level correction of displacement drift caused by slippage, elongation, or springback, the controller defines the time interval between any two adjacent anchor point events as an anchor point segment. ,in and These represent the event types and trigger times of the previous and subsequent anchor point events, respectively. For each anchor point segment, the controller registers the start and end timestamps of the anchor point segment in the work-in-process queue for the corresponding workpiece identifier, and establishes a correlation between the anchor point segment and the encoder pulse accumulation, transmission speed feedback, and drive current sampling sequence of the transport device, making the anchor point segment a comprehensive quantity for subsequent calculation of mileage drift correction. The basic statistical window. Furthermore, to avoid introducing new drift errors due to uncertainties in the anchor segment boundaries under sensor occlusion or jitter conditions, the controller also incorporates the anchor segment event quality formed in step one when establishing the anchor segment. Mark the validity of the anchor segment when When the value falls below a preset threshold, the anchor point segment is marked as a low-confidence anchor point segment, and its constraint strength is reduced or a conservative strategy is enabled in subsequent correction and gating calculations. This ensures that the position update of the workpiece identifier in the in-process queue and the virtual workstation mapping are always driven by verifiable anchor point events. Through the above steps, the workpiece identifier, the in-process queue, the twin workpiece instance, and the odometer anchor point event are uniformly organized into the same closed-loop data structure, providing a directly callable input basis for subsequent drift correction and virtual workstation trigger gating based on anchor point segments.

[0036] Step 3: After the transport and conveying device enters the operating state, the controller establishes a displacement odometer based on encoder pulse count or motor speed feedback. This odometer continuously predicts the current position of each workpiece marker in the in-process queue and calculates the expected arrival time window for the workpiece marker to enter the peeling virtual station, slicing virtual station, and weighing virtual station, thus providing a priori reference for subsequent station triggering. During operation, the controller continuously monitors the actual trigger time of the odometer anchor point event and compares the actual trigger time with the anchor point arrival time predicted based on the displacement odometer, forming an anchor point arrival time residual. When the residual shows a cumulative offset in the same direction within a continuous anchor point segment, a significantly amplified fluctuation amplitude, or inconsistencies such as failure to arrive as expected or early arrival, the controller marks the corresponding workpiece marker as a drift suspect state. This prevents subsequent position updates from relying on a single displacement odometer and instead switches to segment-level correction and gating strategies.

[0037] To achieve quantifiable assessment and executable correction of drift, the controller uses an anchor point segment consisting of any two adjacent odometer anchor point events. As a statistical window, the number of encoder pulses is collected within this anchor point segment. Anchor point segment time interval Average transmission speed within the segment and the average driving current within the segment .in, and These represent the anchor event types and their trigger times corresponding to the start and end points of the anchor segment, respectively. , The timestamp of the starting anchor event. The timestamp of the endpoint anchor event; This represents the cumulative number of pulses accumulated by the encoder within the anchor point segment. The average transmission speed within the anchor segment can be obtained from the statistical values ​​of speed feedback or speed commands within that anchor segment; The average drive current within the anchor point segment is used to characterize the transmission load and friction state. The controller is based on the encoder pulse conversion coefficient. Calculate encoder displacement And calculate the velocity integral displacement based on velocity and time interval. ,in This represents the equivalent displacement corresponding to each encoder pulse.

[0038] Based on this, the controller constructs displacement inconsistency evidence to characterize mileage drift. Its definition is:

[0039] ;

[0040] in, This represents the absolute value operation. This means taking the larger of the two values ​​to complete the normalization, making The value is between 0 and 1. A larger value indicates a more significant difference between the encoder displacement and the speed integral displacement, and a greater likelihood of mileage drift caused by slippage, elongation, or springback. Meanwhile, the controller uses a reference current under the same speed and formula conditions. Evidence of load-induced slippage Its definition is

[0041] ;

[0042] in, The reference load level used to characterize the stable operating condition can be statistically obtained from anchor segments that have not been marked as potentially drifting in the recent period and updated in a sliding manner. Specifically, it can be dynamically updated using a moving average method: for example, taking the average drive current of the most recent N (N≥10) anchor segments that have not been marked as potentially drifting as the reference load level. ; This means limiting the results to between 0 and 1 to avoid excessive amplification caused by abnormal peaks. The controller further incorporates evidence of quality degradation in anchor segment events. Its quality is derived from the anchor segment event obtained in step one. Given, defined as ,in The smaller the value, the less reliable the anchor point segment boundary is, and the more conservative the handling needs to be in the correction and triggering strategy.

[0043] The controller will provide evidence of displacement inconsistency. Evidence of load-induced slippage Evidence of quality degradation in anchor segment events By combining the results, the total mileage drift correction amount corresponding to the anchor point segment is obtained. Its definition is:

[0044] ;

[0045] in, , , The weighting coefficients are satisfied. This is used to balance the contributions of inconsistent displacement, load-induced slippage, and anchor point segment event mass to drift judgment, for example... , , Based on the comprehensive mileage drift correction, the controller outputs the anchor point segment displacement correction. Uncertainty of anchor point position The anchor point segment displacement correction is used to perform segment-level correction on the displacement odometer, and the anchor point segment position uncertainty is used to provide a conservative margin for subsequent virtual workstation gating; wherein It can be represented as

[0046] ;

[0047] This is a sign function; it outputs 1 if the independent variable is greater than 0, -1 if it is less than 0, and 0 if it is equal to 0; it is used to determine the value of the independent variable based on the given condition. The positive and negative values ​​determine the correction direction, so that when the encoder displacement is too large relative to the velocity integral displacement, the odometer position is corrected backward, and vice versa; the uncertainty of the anchor point segment position... It can be represented as

[0048] ;

[0049] in This is the minimum uncertainty constant, which is usually set based on the sensor accuracy and mechanical installation errors, and can be taken as... =0.2; This is a proportionality coefficient used to amplify the contribution of the drift correction composite to the uncertainty. It can be set according to the system's fault tolerance requirements, for example, by taking... =1.0. Through the above segment-level statistical and comprehensive analysis, the controller transforms the cumulative deviation caused by factors such as dust obstruction, conveyor belt slippage, and vibration into calculable drift correction and uncertainty outputs, laying the foundation for the virtual workstation trigger gating based on the corrected position in the next step.

[0050] Step 4: Obtain the comprehensive mileage drift correction amount for the anchor point segment. Anchor point segment displacement correction amount and the uncertainty of the anchor point position Subsequently, the controller performs segment-level cumulative correction on workpiece identifiers in a suspected drift state or with degraded anchor segment event quality, ensuring that the position update of the workpiece identifier in the work queue no longer relies solely on the cumulative count of a single displacement odometer. Specifically, the controller uses the most recently confirmed reliable odometer anchor event for that workpiece identifier as the alignment reference point; where a reliable odometer anchor event is defined as an anchor event that meets the following conditions: the event quality of its respective anchor segment... Furthermore, the anchor event was not marked as a low-confidence event within two consecutive anchor segments, and the set of anchor segments experienced after the reference point up to the current time is denoted as... The controller controls the set. The cumulative correction amount is obtained by summing the displacement correction amounts of each anchor point segment within the segment. and for the set The cumulative uncertainty is obtained by summing the positional uncertainties of each anchor point segment within the segment. Their expressions are as follows:

[0051] ;

[0052] in, The anchor point segment displacement correction amount output in step three is used to correct the directionality of the displacement odometer estimate. The anchor point segment position uncertainty output in step three is used to quantify the conservative error that may exist in the position estimation within the anchor point segment; This is the set of anchor point segments from the most recent reliable anchor point to the current moment. Based on the cumulative correction, the controller estimates the current position from the original displacement odometer reading. Corrected to the corrected position Its expression is:

[0053] ;

[0054] in, The uncorrected position is calculated based on encoder counts or motor feedback. The corrected position is obtained after taking into account factors such as slippage, elongation, or springback. Through the above processing, the controller explicitly feeds back the drift information within the anchor point segment into the position estimation without changing the continuous tracking mechanism of the workpiece marking, thus avoiding the continuous accumulation of misalignment during long-distance transmission and multi-process linkage.

[0055] After correction With cumulative uncertainty Subsequently, the controller further utilizes this technology for trigger gating of the peeling, slicing, and weighing virtual workstations, transforming workstation triggering from a single location arrival to a controllable triggering that arrives at a corrected location while meeting safety margins. To this end, the controller pre-sets a corresponding virtual workstation window for each virtual workstation. ,in and These are the entry and exit boundaries of the j-th virtual workstation window, respectively; the controller constructs a conservative position range for the workpiece identifier based on the corrected position and cumulative uncertainty. And calculate the window boundary safety margin accordingly. Its expression is:

[0056] ;

[0057] in, This indicates that the smaller value is taken to reflect the minimum margin from the correction position to the two edges of the window, minus... This yields a safety margin that ensures the product falls within the window while considering uncertainty; when This indicates that even with accumulated uncertainty, the actual position corresponding to the workpiece identifier still has sufficient margin to fall into the virtual workstation window, thus triggering a low risk of misalignment; when This indicates that the uncertainty has covered the window boundary or that there is a possibility of exceeding the boundary, requiring a more conservative triggering method; safety margin This indicates that cumulative uncertainty is being considered. Then, correct the position. Go to the virtual workstation window The minimum residual distance to the boundary. When When, it indicates that the actual position of the workpiece mark has sufficient margin to fall within the window; when When this value is reached, it indicates that the uncertainty has covered or exceeded the window boundary, triggering a high risk of misalignment. To facilitate unified gating decisions, the controller further normalizes the safety margin to obtain a misalignment tendency. Its expression is:

[0058] ;

[0059] in, The length of the virtual workstation window. Used to limit the result to between 0 and 1, A larger value indicates a greater tendency for misalignment triggering.

[0060] In addition to position-related misalignment tendencies, the controller also incorporates the actuator readiness status into the gating calculation to avoid malfunctions caused by the actuator not being ready when the position is met. The controller generates the readiness factor of the slicing virtual station based on the readiness status of the slicing mechanism's cutter top dead center and safety interlock conditions. The readiness factor of the virtual weighing station is generated based on the stability of the weighing arrival signal and the availability of the weighing module. Among them, the ready factor The values ​​are calculated based on the status signals of the actuator and the system safety conditions, and range from [0,1]. Taking the slicing virtual station as an example, when the cutter is at top dead center, the safety interlock conditions are met, and there is no alarm, If any condition is not met, the value will decrease according to a preset rule, for example, 0.3 will be deducted for each missing ready condition. (This applies to the virtual weighing station.) It can be determined based on the stability signal and communication status of the weighing module. Furthermore, a larger value indicates a more ready workstation. Based on this, the controller generates a comprehensive virtual workstation misalignment trigger gating quantity. Its expression is:

[0061] ;

[0062] in, A higher value indicates a higher risk of misalignment triggering under the combined effects of current position uncertainty and workstation insecurity. The controller adaptively adjusts the virtual workstation triggering strategy based on the aforementioned gating comprehensive value: when At that time, the corresponding process is triggered according to the standard virtual workstation window; when At that time, the virtual workstation trigger window is expanded, and the trigger condition is upgraded from a single location arrival to a linked triggering of location arrival and anchor point event or status confirmation, in order to improve trigger consistency; when When uncertainty increases, the controller reduces the operating speed of the conveyor and increases the number of repeated confirmations, so that the system actively slows down the cycle time to avoid material jamming and tool impact caused by slice misalignment or measurement distortion caused by weighing mismatch; when When the controller is in operation, it applies flow control or freezes the in-process queue and suspends the addition of new workpiece identifiers. It prioritizes realigning the current workpiece identifiers and confirming the workstation. If necessary, it triggers a safety stop and prompts the system to clear sensor obstructions or address conveyor belt slippage. The aforementioned 0.3 is the first threshold, 0.7 is the second threshold, and 0.9 is the third threshold, all of which are preset. Simultaneously, the controller will process the anchor point segment statistics... and Output results, cumulative correction amount Cumulative uncertainty and gate control comprehensive quantity The judgment record is associated with the workpiece identification and stored, enabling subsequent traceability of the data chain before and after the misalignment, thereby forming a closed-loop control basis for multi-process linkage.

[0063] 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.

[0064] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus 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. The above descriptions are merely specific embodiments of this application, but the protection scope of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the protection scope of this application. Therefore, the protection scope of this application should be determined by the protection scope of the claims.

Claims

1. A method for online cycle time reconstruction of multi-process linkage equipment based on digital twins, characterized in that, Includes the following steps: Step 1: The controller initializes and verifies the connectivity of the equipment operation signal and event signal acquisition channels; Perform anti-jitter and validity screening on event signals and mark low-confidence events; solidify events strongly correlated with workpiece passing position into odometer anchor point events, take the time interval formed by two adjacent odometer anchor point events as anchor point segments, evaluate the quality of odometer anchor point events within the anchor point segment to obtain the anchor point segment event quality, and mark the corresponding anchor segment as a low-confidence anchor segment when the anchor segment event quality is lower than a preset threshold. Step 2: When a workpiece is detected to have arrived at the feed end, a unique workpiece identifier is generated and written into the in-process queue. On the digital twin side, a twin workpiece instance corresponding to the workpiece identifier is generated one-to-one and a binding relationship is established. The odometer anchor point event is associated with the workpiece identifier in the in-process queue and the data is organized with the anchor point segment as the basic unit. Step 3: Establish a displacement odometer to predict the workpiece marker position, compare the actual trigger time of the odometer anchor point event with the predicted trigger time of the displacement odometer to identify suspicious drift states; generate multi-source evidence characterizing displacement drift for the anchor point segment and fuse it to obtain a comprehensive odometer drift correction quantity, and output the anchor point segment displacement correction quantity and anchor point segment position uncertainty based on the comprehensive odometer drift correction quantity. Step 4: For workpieces in a suspected drift state or whose associated anchor segments are marked as low-confidence anchor segments, the cumulative correction amount and cumulative uncertainty of the subsequent anchor segment displacement are accumulated based on the most recent reliable odometer anchor event. The cumulative correction amount is then used to correct the position estimate given by the displacement odometer to obtain the corrected position. Based on the corrected position, cumulative uncertainty, and pre-set virtual station window, a misalignment tendency amount is formed. Combined with the actuator's ready state, a ready factor is generated, thereby obtaining the virtual station misalignment trigger gating comprehensive amount. The virtual station triggering strategy is adaptively adjusted according to the virtual station misalignment trigger gating comprehensive amount to achieve online cycle time reconstruction.

2. The online cycle time reconstruction method for multi-process linkage equipment based on digital twins according to claim 1, characterized in that: The equipment operation signals and event signals include at least one or more of the following: encoder pulse acquisition signal, feed end photoelectric or proximity switch signal, peeling zone discharge detection signal, slicing mechanism cutter top dead point signal and bottom dead point signal, weighing arrival signal, and weighing module weight data reporting signal.

3. The online cycle time reconstruction method for multi-process linkage equipment based on digital twins according to claim 2, characterized in that: Step one, the anti-jitter and effectiveness screening, includes filtering out short pulse width spikes, suppressing repeated triggering of the same event within a short period of time, and marking missing detections for events that do not trigger for a long time or have abnormal triggering intervals. Events that are still abnormal after processing are marked as low confidence events.

4. The online cycle time reconstruction method for multi-process linkage equipment based on digital twins according to claim 3, characterized in that: The quality of the anchor segment events in step one is determined by a combination of the missing status of the odometer anchor events within the anchor segment, the repeated triggering status, and the jitter intensity at the triggering time. When the quality of the anchor segment events is lower than a preset threshold, the corresponding anchor segment is marked as a low-confidence anchor segment.

5. The online cycle time reconstruction method for multi-process linkage equipment based on digital twins according to claim 1, characterized in that: The twin workpiece instance in step two includes at least an initial timestamp, an initial position, an initial position uncertainty, and a process link identifier. The process link identifier is used to solidify the process sequence constraints of the workpiece identifier in a multi-process linkage device.

6. The online cycle time reconstruction method for multi-process linkage equipment based on digital twins according to claim 1, characterized in that: The identification conditions for suspicious drift states in step three include the difference between the actual trigger time and the predicted trigger time of the anchor point event showing a cumulative shift in the same direction within a continuous anchor point segment, a significant amplification of the difference fluctuation amplitude, or the inconsistency in the order of events that should have arrived but did not, or arrived ahead of time.

7. The online cycle time reconstruction method for multi-process linkage equipment based on digital twins according to claim 6, characterized in that: The multi-source evidence in step three includes evidence of displacement inconsistency and load-induced slippage formed by one or more of the encoder pulse count, anchor segment time interval, average transmission speed and average drive current, and combined with the anchor segment event quality to form evidence of anchor segment event quality degradation; the mileage drift correction comprehensive quantity is the result obtained by fusing and normalizing the evidence according to preset weights.

8. The online cycle time reconstruction method for multi-process linkage equipment based on digital twins according to claim 7, characterized in that: In step three, when both encoder pulse counting and motor speed feedback are available, the direction of the anchor point segment displacement correction is determined based on the difference between the encoder displacement and the speed integral displacement based on motor speed feedback, so that the segment-level correction of the displacement odometer is directed in the direction of reducing the difference.

9. The online cycle time reconstruction method for multi-process linkage equipment based on digital twins according to claim 1, characterized in that: In step four, the misalignment tendency is determined based on the window boundary safety margin. The window boundary safety margin is based on the minimum distance from the corrected position to the two sides of the virtual workstation window, and is obtained by subtracting from the cumulative uncertainty. The virtual workstation misalignment trigger gated comprehensive quantity is calculated by combining the misalignment tendency with the readiness factor. The higher the readiness factor, the lower the virtual workstation misalignment trigger gated comprehensive quantity.

10. The online cycle time reconstruction method for multi-process linkage equipment based on digital twins according to claim 9, characterized in that: Step four involves an adaptive adjustment strategy for virtual workstation triggering, which includes setting a first threshold, a second threshold, and a third threshold, where the first threshold is less than the second threshold and the second threshold is less than the third threshold. When the overall threshold for virtual workstation misalignment triggering is lower than the first threshold, the system triggers the system using the standard virtual workstation triggering window. When the overall threshold for virtual workstation misalignment triggering is not lower than the first threshold but is lower than the second threshold, the system expands the triggering window and upgrades the triggering condition to a linkage triggering event involving location arrival and odometer anchor point events or workstation readiness confirmation events. When the overall threshold for virtual workstation misalignment triggering is not lower than the second threshold but is lower than the third threshold, the system reduces the transmission speed and increases the number of confirmations for the linkage triggering event. When the overall threshold for virtual workstation misalignment triggering is not lower than the third threshold, the system performs flow limiting or freezing on the in-process queue and suspends the addition of new workpiece identifiers to the queue.

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