A method and system for monitoring the operation of an automated robot for dye filling

Abstract

The application discloses a kind of dye filling conveying automatic robot operation monitoring method and system, it is related to robot operation monitoring technical field, comprising the following steps: S1, the state element of operation monitoring object is structured;S2, using operation state element constructs robot filling-conveying operation state expression;S3, using operation state expression set carries out robot actual operation behavior mapping;S4, using operation behavior corresponding relation set identifies operation deviation state;S5, using operation state expression set and operation deviation identification constructs robot operation monitoring result.The application is mapped by setting based on operation state expression set and carried out robot actual operation behavior, and then obtains operation behavior corresponding relation set, so that each class of actual operation behavior of robot in the whole process of dye filling conveying can be clearly attributed to the corresponding operation state expression, avoid the problem that operation monitoring only relies on isolated state or scattered behavior record.

Description

Technical Field

[0001] This invention relates to the field of robot operation monitoring technology, specifically to an automated robot operation monitoring method and system for dye dispensing and conveying. Background Technology

[0002] With the increasing demands for automation and precision control in industries such as textiles and dyeing, dye filling and conveying processes are gradually shifting from manual operation to automated robotic execution. Existing automated robots for dye filling and conveying typically integrate motion control, filling execution, and conveying scheduling functions. Their operation is characterized by frequent switching of operating conditions, strong continuity of execution behavior, and dense changes in operating status. To ensure dye filling accuracy, conveying process stability, and equipment operational safety, continuous and reliable monitoring of the robot's operation is urgently needed.

[0003] In existing technologies, operation monitoring typically treats the analysis of operation status parameters and the recording of operation behavior as independent processing objects. It either identifies status anomalies only through threshold judgment or performs post-event backtracking on behavior through operation logs. It lacks a structured processing mechanism that uses a unified expression of operation status as a benchmark and explicitly assigns actual operation behavior to the corresponding operation status. This results in an unclear correspondence between operation status and operation behavior, making it difficult to support accurate monitoring of subsequent operation deviations, behavior anomalies, and operation consistency. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides an automated robot operation monitoring method and system for dye filling and delivery, thereby solving the problems mentioned in the background section.

[0005] To achieve the above objectives, the present invention provides the following technical solution: In a first aspect, embodiments of the present invention provide a method for monitoring the operation of an automated robot for dye dispensing and conveying, comprising the following steps: S1. Construct the status elements of the running monitoring object; S2. Construct a robot refueling-delivery operational status expression using operational status elements to obtain an operational status expression set; S3. Use the running state representation set to map the robot's actual running behavior to obtain the running behavior correspondence set; S4. Use the set of operational behavior correspondences to identify operational deviation status and obtain operational deviation identifiers; S5. Use the running status expression set and running deviation identifier to construct the robot running monitoring results and obtain the running monitoring output.

[0006] To further optimize this technical solution, step S1 clarifies all key state elements involved in the operation monitoring of the automated robot for dye filling and delivery, providing basic data support for the subsequent step S2 to construct the operation state expression set; Step S1, in the process of constructing state elements, includes the following steps: Stage identification and structured decomposition; Extraction of operational elements and organization of attributes; State element integration and computational transformation; The final expression for the set of running state elements obtained in step S1 is as follows: ; in, A set of elements for a stage; A set of action state elements; A set of transport flow status elements; This is a set of interface and alignment state elements; It is a set of elements related to time and sequence.

[0007] To further optimize this technical solution, step S2, based on the structured construction and standardized output of the operating status elements of the automated robot for dye filling and delivery already completed in step S1, transforms the discrete, heterogeneous and different-sourced operating status elements into an operating status expression that can uniformly reflect the operating status of the robot throughout the filling and delivery process. Step S2, in the process of constructing the robot's refueling-delivery operation status representation, includes the following steps: Channelized mapping processing of running status elements; Scale unification and comparability processing of state elements; Construction of a single-moment runtime state representation; The continuous generation and set-based representation of runtime states.

[0008] To further optimize this technical solution, the expression set of running states obtained in step S2 is as follows: ; in, This indicates the first step in the robot's dye dispensing and delivery process. A discrete time slice; Indicates time slice The single-moment refueling-delivery operation status expression obtained from the following construction is expressed as follows: ; In the formula, Indicates the first Each operational status element in time slice State representation components after channel mapping and scale unification processing; This represents the total number of operational status elements.

[0009] To further optimize this technical solution, step S3, based on the set of operating states that has been constructed in step S2, explicitly maps the actual operating behaviors generated by the robot during the dye filling and delivery process to the corresponding operating state expressions, thus forming a structured correspondence between states and behaviors. Step S3, when mapping the robot's actual operating behavior, includes the following steps: A identifiable description of the robot's actual operating behavior; Time slice allocation for expressing operational behavior and operational status; Determining the attribution of behavior based on runtime status; The collection-based construction of the mapping relationship between runtime behaviors.

[0010] To further optimize this technical solution, in step S3, when performing the identifiable description of the robot's actual operating behavior, based on the operating records of the robot control system and actuators, the behaviors occurring during actual operation are described in an identifiable manner to form an operating behavior sequence, the expression of which is: ; in, This represents the entire sequence of the robot's actual operating behaviors, covering all time slices. ; Indicates the first Each behavioral unit is determined by the time the behavior occurs. and behavior type identifier constitute; With time slice in step S2 correspond, ; This refers to the specific type of action the robot performs at that point in time.

[0011] To further optimize this technical solution, in step S3, when assigning time slices to the expressions of running behaviors and running states, the time slice assignment process is performed on the running behaviors based on the discrete time slice division method used for the running state expression in step S2. Each running behavior is assigned to a unique time slice through timestamp truncation or control cycle synchronization technology. Thus, it is expressed in relation to the corresponding running state. Establish a defined association.

[0012] To further optimize this technical solution, in step S3, when performing behavior attribution determination based on the running state expression, actions belonging to the same running state expression are considered. The operational behavior is determined by state-behavior correspondence, forming a correspondence between state and behavior, which can be represented as: ; in, To belong to the time slice The actual operating behavior, ; Based on this, a set of operational behavior correspondences is constructed. The mapping and determination process is repeated for all time slices throughout the entire operation, resulting in a set of operational behavior correspondences covering the entire operation cycle, which can be represented as: .

[0013] To further optimize this technical solution, step S4, based on the set of corresponding operational behaviors established in step S3, performs comparative analysis on the behavioral sequences generated during the actual operation of the robot, identifies whether deviations have occurred, and outputs the deviations in a standardized and readable form. Step S5 involves aligning and mapping the structured operational status representation set obtained in step S2 with the operational deviation identifier set obtained in step S4 over time to construct a complete robot operation monitoring result matrix.

[0014] An automated robot operation monitoring system for dye filling and conveying is constructed based on the automated robot operation monitoring method for dye filling and conveying as described in any one of claims 1-9. The system is characterized by comprising the following modules: an operation status element construction module, an operation status expression construction module, an operation behavior mapping module, an operation deviation identification module, and an operation monitoring result construction module.

[0015] In a second aspect, embodiments of the present invention provide a computer device, including a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program instructions are executed by the processor, they implement the steps of the automated robot operation monitoring method and system for dye dispensing and conveying described in the first aspect of the present invention.

[0016] Thirdly, embodiments of the present invention provide a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program instructions are executed by a processor, they implement the steps of the method and system for monitoring the operation of an automated robot for dye dispensing and conveying as described in the first aspect of the present invention.

[0017] Compared with the prior art, the present invention provides an automated robot operation monitoring method and system for dye filling and delivery, which has the following beneficial effects: This automated robot operation monitoring method and system for dye filling and delivery establishes a mapping of actual robot operation behavior based on a set of operation state expressions, thereby obtaining a set of corresponding operation behavior relationships. This allows each type of actual operation behavior of the robot in the entire dye filling and delivery process to be clearly attributed to the corresponding operation state expression, thus establishing a stable and consistent correspondence between the state layer and the behavior layer. This avoids the problem of operation monitoring relying solely on isolated states or scattered behavior records, significantly improving the structural consistency, traceability, and interpretability of the monitoring results. Attached Figure Description

[0018] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a flowchart illustrating an automated robot operation monitoring method and system for dye filling and conveying proposed in this invention. Figure 2 This is a schematic diagram illustrating the process of expressing the operation status of an automated robot for dye filling and conveying, as proposed in this invention. Figure 3 This is a schematic diagram of the actual operation behavior mapping process of an automated robot operation monitoring method and system for dye filling and conveying proposed in this invention; Figure 4 This is a schematic diagram illustrating the process of monitoring the operation results of an automated robot for dye filling and conveying, as proposed in this invention. Detailed Implementation

[0020] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0021] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0022] Secondly, the term "an embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places throughout this specification does not necessarily refer to the same embodiment, nor is it a single embodiment or an embodiment selectively excluded from other embodiments.

[0023] Example 1: Reference Figures 1-4 This is the first embodiment of the present invention, which provides a method for monitoring the operation of an automated robot for dye dispensing and delivery, comprising the following steps: S1. Construct the status elements of the running monitoring object; Step S1 clarifies all key state elements involved in the operation monitoring of the automated robot for dye filling and delivery, providing basic data support for the subsequent step S2 to construct the operation state expression set; Step S1, in the process of constructing state elements, includes the following steps: Stage identification and structured decomposition: The robot's operation process is divided into stages, and key links are identified, including the refueling execution stage, the transport linkage stage, and the interface positioning stage. Using mature industrial engineering task decomposition techniques or behavior tree analysis methods, the operational actions are broken down to clarify the action sequence and time span of each stage; The determination of stage boundaries is based on changes in sensor signals (such as pump start / stop signals, changes in delivery flow rate, and feedback from end position sensors) or changes in actuator status.

[0024] Extraction and organization of operational elements: Extract key operational elements at each stage, including: Status of injection action execution: completion status of the action, duration, and injection volume; Transport flow status: medium flow rate, pressure status, and flow stability indicators; End alignment status: End filling port position, alignment accuracy, and locking status; Interface closure status: interface sealing, pressure, and contact status; Mature condition monitoring and analysis technologies (such as industrial control system signal acquisition and analysis methods) are used to clean the acquired data, remove anomalies, and format it uniformly.

[0025] State element integration and computational transformation: The state elements extracted from each stage are integrated to form a complete set of operational state elements; Numerical elements (such as injection volume, flow rate, and action duration) are transformed into standardized indicators using mature normalization techniques or interval mapping methods, which facilitates subsequent mapping and monitoring. Time series alignment technology is used to process elements involving inter-stage relationships (such as the time difference between the completion of refueling and the start of delivery) to make the stage sequence and time correspondence clear and usable.

[0026] The final expression for the set of running state elements obtained in step S1 is as follows: ; in, For the set of elements of the stage: , used to characterize the stage division results during robot operation, where: : Unique identifier for the stage; : Stage type identifier, corresponding to the annotation execution stage, delivery linkage stage, or interface positioning stage; The sequence of stages reflects the sequential structure of the operational process.

[0027] A set of action state elements: , used to describe the specific action states of the robot in each stage, where: Action type identifier, including adding action, alignment action, and separation action; Action execution status, used to indicate whether the action is in a completed state; The duration of the action is obtained after processing with a unified time reference. For the set of transport flow status elements: , used to describe the state related to dye or media delivery, where: Standardized values ​​corresponding to the transport flow rate; Is the conveyor system in effective operation? Flow stability index, used to reflect the continuity of the transportation process.

[0028] This is a set of interface and alignment state elements. ; is used to characterize the physical connection state between the end effector and the refueling interface, where: The alignment status between the end position and the target interface; Interface locked status; : Interface sealed status.

[0029] This set is acquired through position sensors and interface status detection signals, and processed by unified status encoding.

[0030] It is a set of elements related to time and sequence. ; used to describe the time and sequence relationships during operation, where: : The time stamp corresponding to each state element; The order in which actions or events occur; The time interval between adjacent operation phases.

[0031] S2. Construct a robot refueling-delivery operational status expression using operational status elements to obtain an operational status expression set; Step S2, based on the structured construction and standardized output of the operating status elements of the automated robot for dye filling and delivery completed in step S1, transforms the discrete, heterogeneous and different-origin operating status elements into an operating status expression that can uniformly reflect the robot's operating status throughout the filling and delivery process.

[0032] Step S2, in the process of constructing the robot's refueling-delivery operation status representation, includes the following steps: Channelized mapping processing of running status elements: Based on the set of operating state elements constructed in step S1, each operating state element is first mapped to a predefined state expression channel according to its physical meaning and function, thus obtaining the state elements. Among them, different channels correspond to the robot's state performance in the dye filling stage, the conveying stage, and the stage of their coordinated operation, in order to avoid the ambiguity of state semantics caused by the mixing of elements in different operational stages. This mapping process adopts the mature multi-channel state modeling concept, establishing a fixed expression position for each type of operating state element, thereby ensuring the comparability of the same type of operating state across different time slices.

[0033] Scale unification and comparability processing of state elements: The mapped state elements are scaled uniformly; through mature state standardization and normalization techniques, the numerical range of each operating state element is compressed and its distribution is reconstructed to meet the requirements of unified numerical expression. This process ensures that operational state elements from different sources and with different physical meanings can participate in subsequent calculations and analyses within the same operational state representation, without causing state bias due to scale differences.

[0034] Construction of a single-moment runtime state representation; After completing the channel mapping and scale unification, all operational state elements within the same time slice are constructed into a complete robot refueling-delivery operational state expression according to the predetermined channel order and combination rules. This state expression is used to describe the robot's overall operating state during this time slice, and can simultaneously reflect the refueling accuracy, delivery continuity, and system coordination characteristics; This process is based on a mature state vector construction method, which forms a structured state representation by orderly combination of state elements.

[0035] Continuous generation and set-based representation of runtime states: As the robot continues to operate, the above construction process is repeated for different time slices, gradually forming a set of operating state expressions arranged in chronological order.

[0036] Finally, all the completed operational state expressions are collected to obtain an operational state expression set for subsequent analysis. This set fully records the state change trajectory of the robot throughout the entire dye dispensing and delivery process.

[0037] The expression for the running state representation set obtained in step S2 is as follows: ; in, This indicates the first step in the robot's dye dispensing and delivery process. A discrete time slice; Indicates time slice The single-moment refueling-delivery operation status expression obtained from the following construction is expressed as follows: ; In the formula, Indicates the first Each operational status element in time slice State representation components after channel mapping and scale unification processing; This represents the total number of operating status elements determined in step S1. each Each element corresponds one-to-one with the specific running state element in the output set of step S1, and their arrangement order is consistent with the order of the state expression channels.

[0038] Compared to existing industrial robot operation status monitoring methods that typically rely on single-parameter monitoring or simple state splicing, making it difficult to comprehensively reflect the coordinated process of dye filling and delivery, step S2, while based on mature state vector construction, multi-channel mapping, and standardized processing concepts, strictly limits its operation status expression to the set of operation status elements clearly defined in step S1, ensuring a clear source of the state. At the same time, the state expression channels correspond one-to-one with the specific dye filling and delivery process, giving the state results a clear process orientation. The final output is not an isolated instantaneous state, but a set of operation status expressions that can directly support subsequent operation monitoring and state evolution analysis, thus better fitting the overall technical structure of the operation monitoring method for dye filling and delivery robots.

[0039] S3. Use the running state representation set to map the robot's actual running behavior to obtain the running behavior correspondence set; Step S3, based on the operational state expression set already constructed in Step S2, explicitly maps the actual operational behaviors generated by the robot during dye filling and delivery to the corresponding operational state expressions, forming a structured correspondence between states and behaviors.

[0040] Step S3, when mapping the robot's actual operating behavior, includes the following steps: A identifiable description of the robot's actual operational behavior: Based on the operation records of the robot control system and actuators, the behaviors that occur during actual operation are described in an identifiable way, forming a sequence of operation behaviors; Each operational behavior includes at least a behavior type identifier and a behavior occurrence time identifier. The behavior originates from control instruction execution records or actuator action trigger records, ensuring that the behavior object is reproducible. This sequence of running behaviors serves as the input on the behavior side and is aligned with the set of running state expressions in step S2 in the time dimension. The resulting sequence expression of the running behavior is: ; in, This represents the entire sequence of the robot's actual operating behaviors, covering all time slices. ; Indicates the first Each behavioral unit is determined by the time the behavior occurs. and behavior type identifier constitute; With time slice in step S2 correspond, ; This refers to the specific type of action the robot performs at that point in time (such as refueling, conveying linkage, or interface switching).

[0041] Time slice allocation for runtime behavior and runtime status representation: Based on the discrete time slice division method used in step S2 to express the running status, the running behavior is assigned a time attribute. By using mature timestamp capture or control cycle synchronization technologies, each running action can be assigned to a unique time slice. Thus, it is expressed in relation to the corresponding running state. Establish a defined association; This process is clearly defined as follows: Each runtime behavior can only be mapped to one runtime state representation; The smallest state unit in a state-behavior mapping is a single .

[0042] Determining the attribution of behavior based on runtime status: After assigning time slices, expressions are made for those belonging to the same running state. The operational behavior is used to determine the state-behavior correspondence; The minimum conditions for establishing a correspondence include: The time of occurrence of the running behavior falls into the running state expression Time slice range; Running behavior type and The corresponding channels represent the same operational stages; Based on this, the correspondence between states and behaviors is established, which can be expressed as: ; in, To belong to the time slice The actual operating behavior, .

[0043] Collection-based construction of mapping relationships between runtime behaviors: Repeat the above mapping and determination process for all time slices throughout the entire operation to obtain a set of operational behavior correspondences covering the entire operation cycle, which can be represented as: ; This set uses the running state as the main index to structurally categorize the actual operating behaviors of the robot.

[0044] Compared to existing mature technologies that typically employ independent judgment based on state parameter thresholds or retrospective behavior tracking based on operational logs, the analysis logic in step S3 no longer separates operational state from actual operational behavior. Instead, it uses the operational state expression constructed in step S2 as the unique and unified state benchmark, explicitly mapping and assigning the robot's actual operational behavior during dye filling and delivery to specific operational state expressions. This ultimately forms a structured set of operational behavior correspondences, thereby avoiding the output of scattered state values ​​or isolated behavior records. This results in stronger traceability and overall structural consistency of operational monitoring results at the time, state, and behavior levels.

[0045] S4. Use the set of operational behavior correspondences to identify operational deviation status and obtain operational deviation identifiers; Step S4, based on the set of corresponding operational behaviors established in Step S3, compares and analyzes the behavioral sequences generated during the actual operation of the robot to identify whether deviations have occurred, and outputs the deviations in a standardized and readable form.

[0046] Step S4, in identifying operational deviations, includes the following steps: Reading behavior matching results: Call the set of corresponding operational behaviors output in step S3, read the corresponding results of "expected operational behavior" and "actual operational behavior" at each moment or time window, and form comparable data pairs.

[0047] Construction of deviation discrimination index: Existing mature behavioral consistency analysis methods (such as threshold comparison, similarity judgment, or rule matching) are used to determine whether the actual operating behavior meets its corresponding expected behavioral constraints, and to obtain the deviation judgment results at the single behavior level.

[0048] Deviation state identification: The results of single behavioral deviation judgments within a continuous time period are summarized, and a mature state discrimination logic (such as time window statistics, continuous deviation detection, etc.) is used to identify whether the current operation is in a "normal state" or a "deviation state".

[0049] Deviation marker generation: The identified operational deviations are encoded or tagged to generate structured operational deviation identifiers that can be directly called in subsequent steps, without retaining complex intermediate analysis results.

[0050] The final operational deviation identifier obtained in step S4 is: ,in The corresponding discrimination time or time window index is represented by the following expression: ; This identifier is used to characterize whether the current robot operating state deviates from the set of operating behavior correspondences established in step S3.

[0051] S5. Use the running status expression set and running deviation identifier to construct the robot running monitoring results and obtain the running monitoring output; Step S5 involves processing the structured runtime state representation set obtained in step S2. Compared with the set of running deviation identifiers obtained in step S4 Perform time alignment and mapping to construct a complete robot operation monitoring result matrix. .

[0052] Step S5, in the process of constructing the robot operation monitoring results, includes the following steps: Status - Deviation from time alignment indicator: The state representation set for step S2 Deviation markers in step S4 By time slice Alignment.

[0053] Time alignment can be achieved using control cycle synchronization or mature mapping techniques based on timestamp indexes, ensuring that each state representation corresponds one-to-one with its corresponding deviation identifier.

[0054] State-deviation identifier pair construction: For each time slice Perform structured association construction to generate structured elements:

[0055] For data with missing states or deviations from the identifier, the matrix integrity is ensured by using default marking or interpolation methods.

[0056] Execution monitoring result matrix generation: Summarize the structured elements of all time slices in order to form a matrix: ; The matrix can be indexed by time series or running stage, enhancing readability and operability.

[0057] Running monitoring result matrix This is the final output of the robot's operation monitoring, the generated matrix. It can be directly used for monitoring system display, deviation alarm, or operational reliability analysis without further parsing or conversion.

[0058] This runtime monitoring results matrix In an automated robot operation monitoring method for dye filling and delivery, the core monitoring output, which runs through the entire operation process, is directly applied. By structurally associating the operation status at each moment with the corresponding operation deviation identifier under a unified time reference, the operation status and deviation of the robot at each stage of dye filling and delivery are continuously presented in matrix form. This allows the monitoring system to directly use it for real-time status display, abnormal deviation trigger judgment, and operation process backtracking analysis. This avoids the problem of separation between status data and abnormal judgment results in traditional methods, and improves the completeness, traceability, and usability of operation monitoring results in engineering applications.

[0059] Compared to existing mature technologies that generally employ single-point threshold judgment or discrete anomaly detection, resulting in fragmented operational status information and deviation information that fail to reflect the complete operational process, this step constructs a status-deviation identifier matrix. This method associates the operational status of each time slice with the corresponding deviation markers to form a stage-level operational monitoring result that spans the entire operational cycle. This structured output can be directly used for monitoring display, alarms, or operational reliability analysis without additional parsing, thus significantly outperforming traditional methods in terms of result completeness, readability, and engineering usability.

[0060] Example 2: This is a second embodiment of the present invention, which provides an automated robot operation monitoring system for dye dispensing and delivery, comprising the following modules: The operating state element construction module, corresponding to step S1, is used to construct a set of state elements that can represent the operating state based on the basic operating information during the robot's refueling and delivery process. The states of refueling, conveying, and coordinated operation are described in a standardized manner to form a unified structure of operational state elements, providing an input basis for the subsequent construction of state representations.

[0061] The running status expression construction module, corresponding to step S2, is used to combine and structure the running status elements according to time slices to form a continuous running status expression set. By performing channel mapping and structural unification on state elements, we obtain an expression of the operating state arranged in a time series, providing a standardized state benchmark for mapping operating behavior.

[0062] The runtime behavior mapping module, corresponding to step S3, is used to establish a correspondence between actual runtime behavior and runtime status expression; Based on the operational state representation set, the robot's behavior during dye dispensing and delivery is mapped to form a state-behavior correspondence, providing a basis for deviation identification.

[0063] Run the deviation recognition module, corresponding to step S4, to identify deviations from the predetermined behavior pattern during robot operation; Based on the correspondence of operational behaviors, the consistency of behavior is determined, and the operational deviation identifier corresponding to the time slice is output, providing deviation information input for the construction of monitoring results.

[0064] Run the monitoring results construction module, corresponding to step S5, to generate the final robot operation monitoring results; The operation status expression is time-aligned and structuredly associated with the corresponding operation deviation identifier to construct an operation monitoring result matrix, which serves as the unified monitoring output of the system for real-time monitoring, deviation prompts, and operation process backtracking.

[0065] Example 3: This embodiment provides a method and system for monitoring the operation of an automated robot used for dye dispensing and delivery, and its application in a real-world scenario: In a production workshop specializing in the automated formulation and delivery of textile dyes, multiple automated robots are deployed for dye dispensing and delivery. Each robot travels along a predetermined track between the storage area, the mixing area, and the dyeing station. An automated robot operation monitoring system for dye dispensing and delivery is introduced, and corresponding operation monitoring methods are implemented based on this system.

[0066] In actual operation, the system first uses multi-source sensing units deployed on the robot itself and in its working environment to continuously collect data on the robot's operational status during key stages such as dye dispensing, delivery, and docking. This data includes motion status, execution behavior status, and operational characteristic information related to the dye dispensing process. The collected data is then uniformly connected to the data processing module of the operation monitoring system and processed and standardized according to a preset data structure to ensure consistency and comparability in subsequent analysis.

[0067] Subsequently, based on the processed operational status data, the system comprehensively analyzes the robot's performance at each stage of operation, forming an operational monitoring result matrix that reflects its overall operational status. This result matrix is ​​used to centrally characterize the robot's operational stability, operational consistency, and abnormal deviations under different time periods and operating conditions, and serves as the core basis for subsequent judgments and decisions within the system.

[0068] When the monitoring results matrix shows that a robot's operating status fluctuates or its behavior deviates during dye dispensing, the system can promptly identify this anomaly and send alerts to maintenance personnel through the monitoring interface. Based on the monitoring results and actual production schedules, maintenance personnel can conduct targeted inspections, maintenance, or scheduling adjustments to the robot, thereby preventing problems such as uneven dye dispensing, delivery interruptions, or equipment damage.

[0069] Meanwhile, during long-term operation, the system continuously accumulates the operational monitoring results of each robot under different production batches and dye types. This data is used to summarize and analyze the robot's operational patterns, providing data support for subsequent process optimization, equipment selection, and maintenance strategy formulation. Through this method, the operational monitoring system can achieve continuous, stable, and traceable monitoring of the operational status of automated dye filling and conveying robots without disrupting normal production cycles, significantly improving the reliability of the production process and the level of management precision.

[0070] Example 4: This embodiment also provides a computer device applicable to a method and system for monitoring the operation of an automated robot for dye filling and conveying, including a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to realize the method and system for monitoring the operation of an automated robot for dye filling and conveying as proposed in the above embodiment.

[0071] This embodiment also provides a storage medium storing a computer program that, when executed by a processor, implements the automated robot operation monitoring method and system for dye dispensing and conveying as proposed in the above embodiments.

[0072] The computer device can be a terminal, comprising a processor, memory, communication interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, carrier networks, NFC (Near Field Communication), or other technologies. The display screen can be an LCD screen or an e-ink screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad on the computer device's casing, or an external keyboard, touchpad, or mouse.

[0073] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0074] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-including system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0075] More specific examples (a non-exhaustive list) of computer-readable media include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which programs can be printed, because programs can be obtained electronically, for example, by optically scanning the paper or other media, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0076] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0077] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for monitoring the operation of an automated robot used for dye dispensing and conveying, characterized in that, Includes the following steps: S1. Construct the status elements of the running monitoring object; S2. Construct a robot refueling-delivery operational status expression using operational status elements to obtain an operational status expression set; S3. Use the running state representation set to map the robot's actual running behavior to obtain the running behavior correspondence set; S4. Use the set of operational behavior correspondences to identify operational deviation status and obtain operational deviation identifiers; S5. Use the running status expression set and running deviation identifier to construct the robot running monitoring results and obtain the running monitoring output.

2. The method for monitoring the operation of an automated robot for dye dispensing and conveying according to claim 1, characterized in that, Step S1 clarifies all key state elements involved in the operation monitoring of the automated robot for dye filling and delivery, providing basic data support for the subsequent step S2 to construct the operation state expression set. Step S1, in the process of constructing state elements, includes the following steps: Stage identification and structured decomposition; Extraction of operational elements and organization of attributes; State element integration and computational transformation; The final expression for the set of running state elements obtained in step S1 is as follows: ； in, A set of elements for a stage; A set of action state elements; A set of transport flow status elements; This is a set of interface and alignment state elements; It is a set of elements related to time and sequence.

3. The method for monitoring the operation of an automated robot for dye dispensing and conveying according to claim 1, characterized in that, Step S2, based on the structured construction and standardized output of the operating status elements of the automated robot for dye filling and delivery completed in step S1, transforms the discrete, heterogeneous and different-sourced operating status elements into an operating status expression that can uniformly reflect the robot's operating status throughout the filling and delivery process. Step S2, in the process of constructing the robot's refueling-delivery operation status representation, includes the following steps: Channelized mapping processing of running status elements; Scale unification and comparability processing of state elements; Construction of a single-moment runtime state representation; The continuous generation and set-based representation of runtime states.

4. The method for monitoring the operation of an automated robot for dye dispensing and conveying according to claim 3, characterized in that, The expression set of running state representations obtained in step S2 is as follows: ； in, This indicates the first step in the robot's dye dispensing and delivery process. A discrete time slice; Indicates time slice The single-moment refueling-delivery operation status expression obtained from the following construction is expressed as follows: ； In the formula, Indicates the first Each operational status element in time slice State representation components after channel mapping and scale unification processing; This represents the total number of operational status elements.

5. The method for monitoring the operation of an automated robot for dye dispensing and conveying according to claim 1, characterized in that, Based on the set of operating states that has been constructed in step S2, step S3 explicitly maps the actual operating behaviors generated by the robot during the dye filling and delivery process to the corresponding operating state expressions, forming a structured correspondence between states and behaviors. Step S3, when mapping the robot's actual operating behavior, includes the following steps: A identifiable description of the robot's actual operating behavior; Time slice allocation for expressing operational behavior and operational status; Determining the attribution of behavior based on runtime status; The collection-based construction of the mapping relationship between runtime behaviors.

6. The method for monitoring the operation of an automated robot for dye dispensing and conveying according to claim 5, characterized in that, In step S3, when performing the identifiable description of the robot's actual operating behavior, based on the operating records of the robot's control system and actuators, the behaviors occurring during actual operation are described in an identifiable manner, forming a sequence of operating behaviors, the expression of which is: ； in, This represents the entire sequence of the robot's actual operating behaviors, covering all time slices. ; Indicates the first Each behavioral unit is determined by the time the behavior occurs. and behavior type identifier constitute; With time slice in step S2 correspond, ; This refers to the specific type of action the robot performs at that point in time.

7. The method for monitoring the operation of an automated robot for dye dispensing and conveying according to claim 5, characterized in that, In step S3, when assigning time slices to the running behavior and running state expression, the running behavior is assigned a time slice based on the discrete time slice division method used in step S2. Each running behavior is assigned to a unique time slice through timestamp truncation or control cycle synchronization techniques. Thus, it is expressed in relation to the corresponding running state. Establish a defined association.

8. The method for monitoring the operation of an automated robot for dye dispensing and conveying according to claim 5, characterized in that, In step S3, when performing behavior attribution determination based on the running state expression, behaviors belonging to the same running state expression are considered... The operational behavior is determined by state-behavior correspondence, forming a correspondence between state and behavior, which can be represented as: ； in, To belong to the time slice The actual operating behavior, ; Based on this, a set of operational behavior correspondences is constructed. The mapping and determination process is repeated for all time slices throughout the entire operation, resulting in a set of operational behavior correspondences covering the entire operation cycle, which can be represented as: 。 9. The method for monitoring the operation of an automated robot for dye dispensing and conveying according to claim 1, characterized in that, Based on the set of corresponding operational behaviors established in step S3, step S4 performs comparative analysis on the behavioral sequences generated during the actual operation of the robot to identify whether deviations have occurred, and outputs the deviations in a standardized and readable form. Step S5 involves aligning and mapping the structured operational status representation set obtained in step S2 with the operational deviation identifier set obtained in step S4 over time to construct a complete robot operation monitoring result matrix.

10. An automated robot operation monitoring system for dye filling and conveying, constructed based on the automated robot operation monitoring method for dye filling and conveying as described in any one of claims 1-9, characterized in that, The system includes the following modules: operation status element construction module, operation status expression construction module, operation behavior mapping module, operation deviation identification module, and operation monitoring result construction module.

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