Method and system for controlling printing progress of thermal printer

Abstract

The invention discloses a control method and system for the printing progress of a thermal printer, and the method comprises the steps: defining a plurality of abnormal dimensions according to printing data, a corresponding tracing mechanism and a multi-dimensional detection model, achieving the deep interaction of the printing data, the corresponding tracing mechanism and the multi-dimensional detection model, and guaranteeing the precision of the plurality of abnormal dimensions. Further, a corresponding optimization learning model is matched based on the abnormal event, the model of the thermal printer and a to-be-printed task of the thermal printer; defining a primary optimization logic based on an optimization learning model and the abnormal event; the second-level optimization logic is defined based on the printing effect level and the preset printing effect level threshold value, and the dynamic balance mechanism is constructed based on the second-level optimization progress, the first-level optimization progress and the printing progress of the thermal printer, so that multiple optimization of the abnormal event and normal execution of the optimized abnormal event are ensured; the control effect of the printing progress of the thermal printer is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of thermal printers, and in particular to a method and system for controlling the printing progress of a thermal printer. Background Art

[0002] With the development of science and technology, thermal printers are gradually used in people's lives. Thermal printers receive printing tasks and collect printing data. Based on the printing data, the thermal printer is triggered to print the printing paper. In the existing technology, the thermal printer detects the printing data and traces the printing data along a single node. It is impossible to control the anomalies in different dimensions, which affects the control effect of the printing progress of the thermal printer. Summary of the invention

[0003] The purpose of the present invention is to overcome the shortcomings of the prior art. The present invention provides a method and system for controlling the printing progress of a thermal printer. The method and system collect corresponding data space based on the positioning detection of the thermal printer, and define printing data according to the traversal of the data space; define a tracing mechanism for printing data based on the detection of printing data; define multiple abnormal dimensions according to the printing data, the corresponding tracing mechanism and the multi-dimensional detection model, and are compatible with the overall consideration of the printing data, the corresponding tracing mechanism and the multi-dimensional detection model, thereby realizing the deep interaction of the printing data, the corresponding tracing mechanism and the multi-dimensional detection model, and ensuring the accuracy of multiple abnormal dimensions.

[0004] Furthermore, an exception set is defined based on multiple exception dimensions and the interactive process of printing data; multiple exception features are defined based on the exception set and the model of the thermal printer; corresponding exception events are constructed based on the multiple exception features and the printing process of the thermal printer; a corresponding optimization learning model is matched based on the exception event, the model of the thermal printer and the task to be printed of the thermal printer; a first-level optimization logic is defined based on the optimization learning model and the exception event; a second-level optimization logic is defined based on the printing effect level and a preset printing effect level threshold, and a dynamic balance mechanism is constructed based on the second-level optimization progress, the first-level optimization progress and the printing progress of the thermal printer, thereby ensuring multiple optimizations of exception events and the normal execution of optimized exception events, being compatible with the overall consideration of the second-level optimization progress, the first-level optimization progress and the printing progress of the thermal printer, ensuring multi-dimensional control of the second-level optimization progress, the first-level optimization progress and the printing progress of the thermal printer, and achieving the management and control effect of the printing progress of the thermal printer.

[0005] An embodiment of the present invention provides a method for controlling the printing progress of a thermal printer, which is applied to a scenario of controlling the printing progress of a thermal printer; The method for controlling the printing progress of the thermal printer comprises: Based on the positioning detection of the thermal printer, the corresponding data space is collected, and the printing data is defined according to the traversal of the data space; Defining a traceability mechanism for print data based on the detection of print data; Define multiple anomaly dimensions based on the printed data, the corresponding traceability mechanism, and the multi-dimensional detection model; An exception set is defined based on multiple exception dimensions and an interactive process of print data; multiple exception features are defined according to the exception set and the model of the thermal printer; Constructing a corresponding abnormal event according to a plurality of abnormal features and the printing process of the thermal printer; matching a corresponding optimization learning model based on the abnormal event, the model of the thermal printer and the task to be printed of the thermal printer; A first-level optimization logic is defined based on the optimization learning model and the abnormal event; a second-level optimization logic is defined based on the printing effect level and a preset printing effect level threshold, and a dynamic balance mechanism is constructed based on the second-level optimization progress, the first-level optimization progress and the printing progress of the thermal printer.

[0006] Optionally, the collecting of the corresponding data space based on the positioning detection of the thermal printer and defining the printing data according to the traversal of the data space include: Collect the location of thermal printer; A corresponding scene space is defined based on the location of the thermal printer, a plurality of scene parameters are defined according to the traversal of the scene space, and a working scene of the thermal printer is defined according to the plurality of scene parameters; Associating the location of the thermal printer with the corresponding working scene, defining a corresponding detection method according to the location of the thermal printer and the corresponding working scene, and triggering the positioning detection of the thermal printer along the detection method; Based on the positioning detection of the thermal printer, the corresponding data space is collected and dynamically monitored to control the real-time interaction of the data space; The data space is traversed, and the printing data is defined according to the traversal of the data space.

[0007] Optionally, the step of defining a print data tracing mechanism based on the detection of the print data includes: Freeze-frame print data; Define the corresponding data volume according to the print data; triggering detection of the print data according to the amount of data and the distribution mode of the print data; Based on the detection of printing data, a corresponding data chain is defined, and based on the division of the data chain, corresponding printing nodes, encryption nodes and overall verification nodes are defined; Associate the printing node, encryption node, and overall verification node; A traceability mechanism for printed data is constructed based on printing nodes, encryption nodes, and overall verification nodes.

[0008] Optionally, the method of defining multiple abnormal dimensions according to the printing data, the corresponding tracing mechanism and the multi-dimensional detection model includes: Freeze-print data and corresponding traceability mechanism; Associate printing data and corresponding traceability mechanism; Trigger multi-dimensional traceability based on printing data and corresponding traceability mechanism; Define the abnormal parts of the printed data under the traceability of various dimensions; Associating multiple abnormal parts; constructing corresponding abnormal combinations according to the multiple abnormal parts, and matching corresponding multi-dimensional detection models along the abnormal combinations and the models of thermal printers; Multiple abnormal dimensions are defined based on the abnormal part and the multi-dimensional detection model. At this time, the multi-dimensional detection model is trained based on previous dimensional data, and is further upgraded autonomously based on online training of the abnormal part and the working scenario.

[0009] Optionally, the interactive process based on multiple abnormal dimensions and print data defines an abnormal set; and multiple abnormal features are defined according to the abnormal set and the model of the thermal printer, including: Freeze multiple abnormal dimensions; Correlate multiple abnormal dimensions, the data volume corresponding to the printed data, and the interactive process of the printed data; An exception set is defined based on multiple exception dimensions, the data volume corresponding to the print data, and the interactive process of the print data; Associate an exception set, the age of the thermal printer, and the model of the thermal printer, define a first feature set based on the exception set and the age of the thermal printer, define a second feature set based on the exception set and the model of the thermal printer, and define multiple exception features based on the first feature set and the second feature set.

[0010] Optionally, the step of constructing a corresponding abnormal event according to a plurality of abnormal features and the printing process of the thermal printer; and matching a corresponding optimization learning model based on the abnormal event, the model of the thermal printer, and the task to be printed of the thermal printer, includes: Freeze multiple abnormal features; Collect the printing process of the thermal printer, define multiple printing tasks based on the printing process of the thermal printer, and associate the multiple printing tasks with multiple abnormal features; Corresponding abnormal events are constructed based on multiple printing tasks and multiple abnormal features.

[0011] Optionally, the constructing a corresponding abnormal event according to a plurality of abnormal features and the printing process of the thermal printer; matching a corresponding optimization learning model based on the abnormal event, the model of the thermal printer and the task to be printed of the thermal printer, further includes: Defining the tasks to be printed by the thermal printer according to the progress control of multiple printing tasks; Associating the abnormal event, the model of the thermal printer, and the pending printing tasks of the thermal printer; A first model coefficient is defined according to the abnormal event and the model of the thermal printer, a second model coefficient is defined according to the abnormal event and the task to be printed of the thermal printer, and a corresponding optimization learning model is matched based on the first model coefficient, the second model coefficient and the control model of the thermal printer. At this time, the optimization learning model is trained based on previous optimization data.

[0012] Optionally, the first-level optimization logic is defined based on the optimization learning model and the abnormal event; the second-level optimization logic is defined based on the printing effect level and a preset printing effect level threshold, and a dynamic balance mechanism is constructed based on the second-level optimization progress, the first-level optimization progress and the printing progress of the thermal printer, including: Dynamically interact with the optimized learning model and the abnormal event, and define the corresponding interaction coefficient; Associating the optimization learning model, the abnormal event and the corresponding interaction coefficient, and defining a primary optimization logic according to the optimization learning model, the abnormal event and the corresponding interaction coefficient; Trigger the first-level optimization of abnormal events based on the first-level optimization logic, control the first-level optimization progress of abnormal events, and conduct online management and control of the first-level optimization progress and the printing progress of the thermal printer.

[0013] Optionally, the first-level optimization logic is defined based on the optimization learning model and the abnormal event; the second-level optimization logic is defined based on the printing effect level and the preset printing effect level threshold, and a dynamic balance mechanism is constructed based on the second-level optimization progress, the first-level optimization progress and the printing progress of the thermal printer, and further includes: Monitor the printing effect coefficient of the thermal printer on the printing paper in real time, and define the printing effect level of the thermal printer on the printing paper based on the printing effect coefficient and the printing area; Compare the printing effect level with the preset printing effect level threshold, and output the level difference, and define the secondary optimization logic according to the level difference, the printing effect level and the service life of the thermal printer; Trigger the secondary optimization of abnormal events based on the secondary optimization logic, control the secondary optimization progress of abnormal events, associate the secondary optimization progress, the primary optimization progress and the printing progress of the thermal printer, and build a dynamic balance mechanism based on the secondary optimization progress, the primary optimization progress and the printing progress of the thermal printer to ensure multiple optimizations of abnormal events and the normal execution of the optimized abnormal events.

[0014] In addition, an embodiment of the present invention further provides a printing progress control system of a thermal printer, the printing progress control system of the thermal printer comprising: A positioning detection module, used to collect corresponding data space based on positioning detection of the thermal printer, and define printing data according to the traversal of the data space; A tracing module, used to define a tracing mechanism for printing data based on the detection of printing data; The abnormal dimension module is used to define multiple abnormal dimensions according to the printing data, the corresponding traceability mechanism and the multi-dimensional detection model; An abnormal feature module is used to define an abnormal set based on multiple abnormal dimensions and an interactive process of printing data; and define multiple abnormal features according to the abnormal set and the model of the thermal printer; An optimization module, used to construct a corresponding abnormal event according to a plurality of abnormal features and the printing process of the thermal printer; and to match a corresponding optimization learning model based on the abnormal event, the model of the thermal printer and the printing task to be printed by the thermal printer; The progress control module is used to define the first-level optimization logic based on the optimization learning model and the abnormal event; define the second-level optimization logic based on the printing effect level and the preset printing effect level threshold, and build a dynamic balance mechanism based on the second-level optimization progress, the first-level optimization progress and the printing progress of the thermal printer.

[0015] In an embodiment of the present invention, through the method in the embodiment of the present invention, the corresponding data space is collected based on the positioning detection of the thermal printer, and the printing data is defined according to the traversal of the data space; the tracing mechanism of the printing data is defined based on the detection of the printing data; and multiple abnormal dimensions are defined according to the printing data, the corresponding tracing mechanism and the multi-dimensional detection model, which is compatible with the overall consideration of the printing data, the corresponding tracing mechanism and the multi-dimensional detection model, realizes the deep interaction of the printing data, the corresponding tracing mechanism and the multi-dimensional detection model, and ensures the accuracy of multiple abnormal dimensions.

[0016] Furthermore, an exception set is defined based on multiple exception dimensions and the interactive process of printing data; multiple exception features are defined based on the exception set and the model of the thermal printer; corresponding exception events are constructed based on the multiple exception features and the printing process of the thermal printer; a corresponding optimization learning model is matched based on the exception event, the model of the thermal printer and the task to be printed of the thermal printer; a first-level optimization logic is defined based on the optimization learning model and the exception event; a second-level optimization logic is defined based on the printing effect level and a preset printing effect level threshold, and a dynamic balance mechanism is constructed based on the second-level optimization progress, the first-level optimization progress and the printing progress of the thermal printer, thereby ensuring multiple optimizations of exception events and the normal execution of optimized exception events, being compatible with the overall consideration of the second-level optimization progress, the first-level optimization progress and the printing progress of the thermal printer, ensuring multi-dimensional control of the second-level optimization progress, the first-level optimization progress and the printing progress of the thermal printer, and achieving the management and control effect of the printing progress of the thermal printer. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0018] Figure 1 It is a flow chart of a method for controlling the printing progress of a thermal printer in an embodiment of the present invention; Figure 2 is a flow chart of S11 in the method for controlling the printing progress of a thermal printer in an embodiment of the present invention; Figure 3 is a flow chart of S12 in the method for controlling the printing progress of a thermal printer in an embodiment of the present invention; Figure 4 is a flow chart of S13 in the method for controlling the printing progress of a thermal printer in an embodiment of the present invention; Figure 5 is a flow chart of S14 in the method for controlling the printing progress of a thermal printer in an embodiment of the present invention; Figure 6 is a flow chart of S15 in the method for controlling the printing progress of a thermal printer in an embodiment of the present invention; Figure 7 is a flow chart of S16 in the method for controlling the printing progress of a thermal printer in an embodiment of the present invention; Figure 8It is a schematic diagram of the structure of the printing progress control system of the thermal printer in an embodiment of the present invention; Fig. 9 The figure is a hardware diagram of an electronic device according to an exemplary embodiment. DETAILED DESCRIPTION

[0019] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0020] See also Figures 1 to 9 A method for controlling the printing progress of a thermal printer is applied to a scenario of controlling the printing progress of a thermal printer; the method for controlling the printing progress of a thermal printer includes: Step S11: collecting corresponding data space based on positioning detection of the thermal printer, and defining printing data according to traversal of the data space; Step S12: defining a print data tracing mechanism based on the detection of the print data; Step S13: defining multiple abnormal dimensions according to the printing data, the corresponding tracing mechanism and the multi-dimensional detection model; Step S14: defining an abnormality set based on multiple abnormality dimensions and the interactive process of printing data; defining multiple abnormality features according to the abnormality set and the model of the thermal printer; Step S15: constructing a corresponding abnormal event according to the multiple abnormal features and the printing process of the thermal printer; matching a corresponding optimization learning model based on the abnormal event, the model of the thermal printer and the task to be printed of the thermal printer; Step S16: Define the primary optimization logic based on the optimization learning model and the abnormal event; define the secondary optimization logic based on the printing effect level and the preset printing effect level threshold, and build a dynamic balance mechanism based on the secondary optimization progress, the primary optimization progress and the printing progress of the thermal printer.

[0021] In an embodiment of the present invention, through the method in the embodiment of the present invention, the corresponding data space is collected based on the positioning detection of the thermal printer, and the printing data is defined according to the traversal of the data space; the tracing mechanism of the printing data is defined based on the detection of the printing data; and multiple abnormal dimensions are defined according to the printing data, the corresponding tracing mechanism and the multi-dimensional detection model, which is compatible with the overall consideration of the printing data, the corresponding tracing mechanism and the multi-dimensional detection model, realizes the deep interaction of the printing data, the corresponding tracing mechanism and the multi-dimensional detection model, and ensures the accuracy of multiple abnormal dimensions.

[0022] Furthermore, an exception set is defined based on multiple exception dimensions and the interactive process of printing data; multiple exception features are defined based on the exception set and the model of the thermal printer; corresponding exception events are constructed based on the multiple exception features and the printing process of the thermal printer; a corresponding optimization learning model is matched based on the exception event, the model of the thermal printer and the task to be printed of the thermal printer; a first-level optimization logic is defined based on the optimization learning model and the exception event; a second-level optimization logic is defined based on the printing effect level and a preset printing effect level threshold, and a dynamic balance mechanism is constructed based on the second-level optimization progress, the first-level optimization progress and the printing progress of the thermal printer, thereby ensuring multiple optimizations of exception events and the normal execution of optimized exception events, being compatible with the overall consideration of the second-level optimization progress, the first-level optimization progress and the printing progress of the thermal printer, ensuring multi-dimensional control of the second-level optimization progress, the first-level optimization progress and the printing progress of the thermal printer, and achieving the management and control effect of the printing progress of the thermal printer.

[0023] refer to Figure 2 , in step S11, the corresponding data space is collected based on the positioning detection of the thermal printer, and the printing data is defined according to the traversal of the data space; In the specific implementation process of the present invention, the specific steps may be: S111: collecting the location of the thermal printer; S112: defining a corresponding scene space based on the location of the thermal printer, defining a plurality of scene parameters according to the traversal of the scene space, and defining a working scene of the thermal printer according to the plurality of scene parameters; S113: Associating the location of the thermal printer with the corresponding working scene, defining a corresponding detection method according to the location of the thermal printer and the corresponding working scene, and triggering positioning detection of the thermal printer according to the detection method; S114: collecting corresponding data space based on the positioning detection of the thermal printer, and dynamically monitoring the data space to control the real-time interaction of the data space; S115: Traverse the data space, and define the printing data according to the traversal of the data space.

[0024] In an embodiment of the present application, the location of the thermal printer is collected and controlled, so as to define a corresponding scene space based on the location of the thermal printer, define multiple scene parameters based on the traversal of the scene space, and define the working scene of the thermal printer based on the multiple scene parameters. Multiple scene parameters are introduced to achieve deep interaction of multiple scene parameters, so as to ensure the accuracy of the working scene of the thermal printer.

[0025] Furthermore, the location of the thermal printer and the corresponding working scene are associated, a corresponding detection method is defined according to the location of the thermal printer and the corresponding working scene, and the positioning detection of the thermal printer is triggered along the detection method, so as to realize the positioning detection of the thermal printer, which is compatible with the overall consideration of the location of the thermal printer and the corresponding working scene.

[0026] Therefore, the corresponding data space is collected based on the positioning detection of the thermal printer, and the data space is dynamically monitored to control the real-time interaction of the data space; the data space is traversed, and the printing data is defined according to the traversal of the data space, and each printing data is further controlled, and a comprehensive traversal of the data space is achieved.

[0027] refer to Figure 3 , in step S12, a print data tracing mechanism is defined based on the detection of the print data; In the specific implementation process of the present invention, the specific steps may be: S121: freeze-frame printing data; S122: defining the corresponding data volume according to the print data; S123: triggering detection of print data according to the data volume and the distribution mode of the print data; S124: defining a corresponding data chain based on the detection of the printing data, and defining a corresponding printing node, an encryption node, and an overall verification node based on the division of the data chain; S125: Associating the printing node, the encryption node and the overall verification node; S126: Construct a traceability mechanism for printing data based on the printing node, encryption node and overall verification node.

[0028] In the embodiments of the present application, the print data is frozen, the print data is introduced, and the print data is controlled, so that the corresponding data volume is defined according to the print data, and the overall load of the print data is presented through the data volume.

[0029] At the same time, the detection of the printing data is triggered according to the data volume and the distribution mode of the printing data, so that the corresponding data chain is defined based on the detection of the printing data, and the corresponding printing nodes, encryption nodes and overall verification nodes are defined based on the division of the data chain, so as to facilitate the reasonable division of the data chain, introduce printing nodes, encryption nodes and overall verification nodes, so as to perform separate detection on the printing nodes, encryption nodes and overall verification nodes, ensure the overall interaction of the printing nodes, encryption nodes and overall verification nodes, and realize the overall control of the data chain.

[0030] Therefore, the printing node, encryption node and overall verification node are associated; a traceability mechanism for printing data is constructed based on the printing node, encryption node and overall verification node, which is compatible with the overall consideration of the printing node, encryption node and overall verification node, realizes multi-dimensional control of the printing node, encryption node and overall verification node, and ensures the accuracy of the traceability mechanism for printing data.

[0031] refer to Figure 4 , in step S13, in the floor cleaning space, multiple abnormal dimensions are defined according to the printing data, the corresponding traceability mechanism and the multi-dimensional detection model; In the specific implementation process of the present invention, the specific steps may be: S131: freeze-frame printing data and corresponding traceability mechanism; S132: Associating printing data with corresponding tracing mechanism; S133: triggering multi-dimensional tracing based on the printing data and the corresponding tracing mechanism; S134: defining abnormal parts of the print data under the traceability of each dimension; S135: Associating multiple abnormal parts; constructing corresponding abnormal combinations according to the multiple abnormal parts, and matching corresponding multi-dimensional detection models along the abnormal combinations and the models of thermal printers; S136: Define multiple abnormal dimensions according to the abnormal part and the multi-dimensional detection model. At this time, the multi-dimensional detection model is trained based on previous dimensional data and is further upgraded autonomously according to the online training of the abnormal part and the working scenario.

[0032] In an embodiment of the present application, a corresponding data space is collected based on the positioning detection of a thermal printer, and printing data is defined according to the traversal of the data space; a tracing mechanism for printing data is defined based on the detection of printing data; and multiple abnormal dimensions are defined according to the printing data, the corresponding tracing mechanism, and a multi-dimensional detection model. This is compatible with the overall consideration of printing data, the corresponding tracing mechanism, and the multi-dimensional detection model, realizes the deep interaction of printing data, the corresponding tracing mechanism, and the multi-dimensional detection model, and ensures the accuracy of multiple abnormal dimensions.

[0033] At this time, the printing data and the corresponding traceability mechanism are frozen and associated with each other, thereby triggering multi-dimensional traceability based on the printing data and the corresponding traceability mechanism, which is compatible with the overall consideration of the printing data and the corresponding traceability mechanism and realizes multi-dimensional traceability of the printing data.

[0034] Therefore, the abnormal parts of the printing data are defined under the traceability of each dimension, so that the corresponding abnormal parts are introduced in each dimension, thereby associating multiple abnormal parts; the corresponding abnormal combination is constructed according to the multiple abnormal parts, and the corresponding multi-dimensional detection model is matched along the abnormal combination and the model of the thermal printer, thereby ensuring the accuracy of the multi-dimensional detection model.

[0035] Furthermore, multiple abnormal dimensions are defined according to the abnormal part and the multidimensional detection model, and the abnormal part and the multidimensional detection model are introduced to achieve overall control of the abnormal part and the multidimensional detection model, thereby ensuring multidimensional control of the abnormal part and the multidimensional detection model and improving the accuracy of multiple abnormal dimensions. At this time, the multidimensional detection model is trained based on previous dimensional data and is further upgraded autonomously according to online training of the abnormal part and the working scenario.

[0036] refer to Figure 5 , S14: defining an anomaly set based on multiple anomaly dimensions and an interactive process of printing data; defining multiple anomaly features according to the anomaly set and the model of the thermal printer; In the specific implementation process of the present invention, the specific steps may be: S141: Freeze multiple abnormal dimensions; S142: Associating multiple abnormal dimensions, the data volume corresponding to the print data, and the interactive process of the print data; S143: defining an exception set based on multiple exception dimensions, the data volume corresponding to the print data, and the interactive process of the print data; S144: Associating an exception set, the age of the thermal printer, and the model of the thermal printer, defining a first feature set according to the exception set and the age of the thermal printer, defining a second feature set according to the exception set and the model of the thermal printer, and defining multiple exception features based on the first feature set and the second feature set.

[0037] In an embodiment of the present application, multiple abnormal dimensions are frozen to associate the multiple abnormal dimensions, the data volume corresponding to the printing data, and the interactive process of the printing data. Multiple abnormal dimensions, the data volume corresponding to the printing data, and the interactive process of the printing data are introduced, and the multiple abnormal dimensions, the data volume corresponding to the printing data, and the interactive process of the printing data are controlled as a whole. Then, an abnormal set is defined based on the multiple abnormal dimensions, the data volume corresponding to the printing data, and the interactive process of the printing data, thereby ensuring the comprehensiveness of the abnormal set.

[0038] Therefore, the exception set, the age of the thermal printer, and the model of the thermal printer are associated, a first feature set is defined according to the exception set and the age of the thermal printer, a second feature set is defined according to the exception set and the model of the thermal printer, and multiple exception features are defined based on the first feature set and the second feature set, which are compatible with the overall consideration of the first feature set and the second feature set, achieve multi-dimensional control of the exception set, the age of the thermal printer, and the model of the thermal printer, and ensure the accuracy of multiple exception features.

[0039] refer to Figure 6 , S15: constructing a corresponding abnormal event according to a plurality of abnormal features and the printing process of the thermal printer; matching a corresponding optimization learning model based on the abnormal event, the model of the thermal printer and the task to be printed of the thermal printer; In the specific implementation process of the present invention, the specific steps may be: S151: Freeze multiple abnormal features; S152: collecting the printing process of the thermal printer, defining multiple printing tasks based on the printing process of the thermal printer, and associating the multiple printing tasks with multiple abnormal features; S153: constructing corresponding abnormal events based on the multiple printing tasks and the multiple abnormal features; S154: defining the tasks to be printed by the thermal printer according to the progress control of the plurality of printing tasks; S155: Associating the abnormal event, the model of the thermal printer, and the pending printing task of the thermal printer; S156: Define a first model coefficient according to the abnormal event and the model of the thermal printer, define a second model coefficient according to the abnormal event and the task to be printed of the thermal printer, and match the corresponding optimization learning model based on the first model coefficient, the second model coefficient and the control model of the thermal printer. At this time, the optimization learning model is trained based on previous optimization data.

[0040] In an embodiment of the present application, multiple abnormal features are frozen and overall control is performed on the multiple abnormal features. At the same time, the printing process of the thermal printer is collected, multiple printing tasks are defined based on the printing process of the thermal printer, and the multiple printing tasks and multiple abnormal features are associated to facilitate overall control of the multiple printing tasks and multiple abnormal features.

[0041] Furthermore, corresponding abnormal events are constructed based on multiple printing tasks and multiple abnormal features, and overall control is performed based on the multiple printing tasks and multiple abnormal features to ensure the accuracy of the abnormal time. At the same time, the tasks to be printed of the thermal printer are defined based on the progress control of multiple printing tasks.

[0042] Therefore, the abnormal event, the model of the thermal printer and the task to be printed of the thermal printer are associated; the first model coefficient is defined according to the abnormal event and the model of the thermal printer, and the second model coefficient is defined according to the abnormal event and the task to be printed of the thermal printer; the corresponding optimization learning model is matched based on the first model coefficient, the second model coefficient and the control model of the thermal printer. At this time, the optimization learning model is trained based on previous optimization data.

[0043] refer to Figure 7 , S16: defining a primary optimization logic based on the optimization learning model and the abnormal event; defining a secondary optimization logic based on the printing effect level and a preset printing effect level threshold, and building a dynamic balance mechanism based on the secondary optimization progress, the primary optimization progress and the printing progress of the thermal printer; In the specific implementation process of the present invention, the specific steps may be: S161: dynamically interacting the optimized learning model and the abnormal event, and defining a corresponding interaction coefficient; S162: Associating the optimization learning model, the abnormal event, and the corresponding interaction coefficient, and defining a primary optimization logic according to the optimization learning model, the abnormal event, and the corresponding interaction coefficient; S163: triggering the first-level optimization of the abnormal event based on the first-level optimization logic, controlling the first-level optimization progress of the abnormal event, and performing online management and control of the first-level optimization progress and the printing progress of the thermal printer; S164: real-time monitoring of the printing effect coefficient of the thermal printer on the printing paper, and defining the printing effect level of the thermal printer on the printing paper based on the printing effect coefficient and the printing area; S165: Compare the printing effect level with a preset printing effect level threshold, output the level difference, and define a secondary optimization logic according to the level difference, the printing effect level, and the service life of the thermal printer; S166: Trigger the secondary optimization of abnormal events based on the secondary optimization logic, control the secondary optimization progress of abnormal events, associate the secondary optimization progress, the primary optimization progress and the printing progress of the thermal printer, and build a dynamic balance mechanism based on the secondary optimization progress, the primary optimization progress and the printing progress of the thermal printer to ensure multiple optimizations of abnormal events and the normal execution of the optimized abnormal events.

[0044] In the specific implementation process of the present invention, an exception set is defined based on multiple exception dimensions and the interactive process of printing data; multiple exception features are defined according to the exception set and the model of the thermal printer; corresponding exception events are constructed according to the multiple exception features and the printing process of the thermal printer; a corresponding optimization learning model is matched based on the exception event, the model of the thermal printer and the task to be printed of the thermal printer; a first-level optimization logic is defined based on the optimization learning model and the exception event; a second-level optimization logic is defined based on the printing effect level and a preset printing effect level threshold, and a dynamic balance mechanism is constructed based on the second-level optimization progress, the first-level optimization progress and the printing progress of the thermal printer, thereby ensuring multiple optimizations of exception events and the normal execution of optimized exception events, being compatible with the overall consideration of the second-level optimization progress, the first-level optimization progress and the printing progress of the thermal printer, ensuring multi-dimensional control of the second-level optimization progress, the first-level optimization progress and the printing progress of the thermal printer, and achieving the management and control effect of the printing progress of the thermal printer.

[0045] At this point, the optimized learning model and the abnormal event dynamically interact, and the corresponding interaction coefficient is defined. The interaction coefficient is introduced to associate the optimized learning model, the abnormal event and the corresponding interaction coefficient. The first-level optimization logic is defined according to the optimized learning model, the abnormal event and the corresponding interaction coefficient. At this point, the first-level optimization of the abnormal event is controlled according to the first-level optimization logic, and the abnormal nodes and abnormal contents in the abnormal event are initially controlled to control each abnormal content.

[0046] Therefore, based on the first-level optimization logic, the first-level optimization of the abnormal event is triggered, the first-level optimization progress of the abnormal event is controlled, and the first-level optimization progress and the printing progress of the thermal printer are managed online, thereby realizing dynamic interaction between the first-level optimization progress and the printing progress of the thermal printer, so as to facilitate dynamic management and control of the first-level optimization progress and the printing progress of the thermal printer, ensuring that the first-level optimization progress is higher than the printing progress of the thermal printer, and realizing subsequent normal printing of the abnormal content after the first-level optimization.

[0047] At the same time, the printing effect coefficient of the thermal printer on the printing paper is monitored in real time, and the printing effect level of the thermal printer on the printing paper is defined based on the printing effect coefficient and the printing area; the printing effect level and the preset printing effect level threshold are compared, and the level difference is output, and the secondary optimization logic is defined according to the level difference, the printing effect level and the service life of the thermal printer; based on the secondary optimization logic, the printed content is optimized, and the corresponding printing parameters are dynamically adjusted, and the thermal printer is optimized in different dimensions based on the secondary optimization logic and the primary optimization logic, and is compatible with the overall control of abnormal events and printed content, realizing multi-dimensional control of abnormal events and printed content, and ensuring the printing effect of the printed content.

[0048] Therefore, based on the secondary optimization logic, the secondary optimization of abnormal events is triggered, the secondary optimization progress of abnormal events is controlled, the secondary optimization progress, the primary optimization progress and the printing progress of the thermal printer are associated, and a dynamic balance mechanism is constructed based on the secondary optimization progress, the primary optimization progress and the printing progress of the thermal printer to ensure multiple optimizations of abnormal events and the normal execution of the optimized abnormal events. It is compatible with the overall consideration of the secondary optimization progress, the primary optimization progress and the printing progress of the thermal printer, ensures multi-dimensional control of the secondary optimization progress, the primary optimization progress and the printing progress of the thermal printer, and realizes the management and control effect of the printing progress of the thermal printer.

[0049] In an embodiment of the present invention, through the method in the embodiment of the present invention, the corresponding data space is collected based on the positioning detection of the thermal printer, and the printing data is defined according to the traversal of the data space; the tracing mechanism of the printing data is defined based on the detection of the printing data; and multiple abnormal dimensions are defined according to the printing data, the corresponding tracing mechanism and the multi-dimensional detection model, which is compatible with the overall consideration of the printing data, the corresponding tracing mechanism and the multi-dimensional detection model, realizes the deep interaction of the printing data, the corresponding tracing mechanism and the multi-dimensional detection model, and ensures the accuracy of multiple abnormal dimensions.

[0050] Furthermore, an exception set is defined based on multiple exception dimensions and the interactive process of printing data; multiple exception features are defined based on the exception set and the model of the thermal printer; corresponding exception events are constructed based on the multiple exception features and the printing process of the thermal printer; a corresponding optimization learning model is matched based on the exception event, the model of the thermal printer and the task to be printed of the thermal printer; a first-level optimization logic is defined based on the optimization learning model and the exception event; a second-level optimization logic is defined based on the printing effect level and a preset printing effect level threshold, and a dynamic balance mechanism is constructed based on the second-level optimization progress, the first-level optimization progress and the printing progress of the thermal printer, thereby ensuring multiple optimizations of exception events and the normal execution of optimized exception events, being compatible with the overall consideration of the second-level optimization progress, the first-level optimization progress and the printing progress of the thermal printer, ensuring multi-dimensional control of the second-level optimization progress, the first-level optimization progress and the printing progress of the thermal printer, and achieving the management and control effect of the printing progress of the thermal printer.

[0051] See also Figure 8 , Figure 8 It is a schematic diagram of the structure of the printing progress control system of the thermal printer in an embodiment of the present invention.

[0052] like Figure 8 As shown, a printing progress control system of a thermal printer, the printing progress control system of the thermal printer comprises: A positioning detection module 21, used to collect corresponding data space based on positioning detection of the thermal printer, and define printing data according to the traversal of the data space; A tracing module 22, for defining a tracing mechanism for printing data based on the detection of printing data; Anomaly dimension module 23, used to define multiple anomaly dimensions according to printing data, corresponding tracing mechanism and multi-dimensional detection model; The abnormality feature module 24 is used to define an abnormality set based on multiple abnormality dimensions and the interactive process of printing data; and define multiple abnormality features according to the abnormality set and the model of the thermal printer; The optimization module 25 is used to construct a corresponding abnormal event according to a plurality of abnormal features and the printing process of the thermal printer; and to match a corresponding optimization learning model based on the abnormal event, the model of the thermal printer and the task to be printed of the thermal printer; The progress control module 26 is used to define the primary optimization logic based on the optimization learning model and the abnormal event; define the secondary optimization logic based on the printing effect level and the preset printing effect level threshold, and build a dynamic balance mechanism based on the secondary optimization progress, the primary optimization progress and the printing progress of the thermal printer.

[0053] See also Fig. 9 , refer to the following Fig. 9 The electronic device 40 according to this embodiment of the present invention will be described. Fig. 9 The electronic device 40 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0054] like Fig. 9 As shown, the electronic device 40 is in the form of a general computing device. The components of the electronic device 40 may include but are not limited to: at least one processing unit 41, at least one storage unit 42, and a bus 43 connecting different system components (including the storage unit 42 and the processing unit 41).

[0055] The storage unit stores program codes, which can be executed by the processing unit 41, so that the processing unit 41 executes the steps according to various exemplary embodiments of the present invention described in the above “Embodiment Method” section of this specification.

[0056] The storage unit 42 may include a readable medium in the form of a volatile storage unit, such as a random access memory unit (RAM) 421 and / or a cache memory unit 422 , and may further include a read-only memory unit (ROM) 423 .

[0057] The storage unit 42 may also include a program / utility 424 having a set (at least one) of program modules 425, such program modules 425 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0058] Bus 43 may represent one or more of several types of bus structures, including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

[0059] The electronic device 40 may also communicate with one or more external devices (e.g., keyboards, pointing devices, Bluetooth devices, etc.), one or more devices that enable a user to interact with the electronic device 40, and / or any device that enables the electronic device 40 to communicate with one or more other computing devices (e.g., routers, modems, etc.). Such communication may be performed via an input / output (I / O) interface 44. Furthermore, the electronic device 40 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) via a network adapter 45. Fig. 9 As shown, the network adapter 45 communicates with other modules of the electronic device 40 via the bus 43. It should be understood that although Fig. 9 Not shown, other hardware and / or software modules may be used in conjunction with the electronic device 40, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup planning systems.

[0060] Through the description of the above implementation, it is easy for those skilled in the art to understand that the example implementation described here can be implemented by software, or by software combined with necessary hardware. Therefore, the technical solution according to the implementation of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, including several instructions to enable a computing device (which can be a personal computer, a server, a multi-parameter sensor device, or a network device, etc.) to execute the method according to the implementation of the present disclosure.

[0061] Those skilled in the art can understand that all or some of the steps in the various methods of the above embodiments can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium, and the storage medium can include: a read-only memory (ROM), a random access memory (RAM), a disk or an optical disk, etc. In addition, it stores computer program instructions, and when the computer program instructions are executed by a computer, the computer executes the above method.

[0062] In addition, the above describes in detail the printing progress control method and system of the thermal printer provided in the embodiment of the present invention. Specific examples are used herein to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. For those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. A method for controlling the printing progress of a thermal printer, characterized in that: Applicable to the control scenario of printing progress of thermal printers; The method for controlling the printing progress of the thermal printer comprises: Based on the positioning detection of the thermal printer, the corresponding data space is collected, and the printing data is defined according to the traversal of the data space; Defining a traceability mechanism for print data based on the detection of print data; Define multiple anomaly dimensions based on the printed data, the corresponding traceability mechanism, and the multi-dimensional detection model; An exception set is defined based on multiple exception dimensions and an interactive process of print data; multiple exception features are defined according to the exception set and the model of the thermal printer; Constructing a corresponding abnormal event according to a plurality of abnormal features and the printing process of the thermal printer; matching a corresponding optimization learning model based on the abnormal event, the model of the thermal printer and the task to be printed of the thermal printer; A first-level optimization logic is defined based on the optimization learning model and the abnormal event; a second-level optimization logic is defined based on the printing effect level and a preset printing effect level threshold, and a dynamic balance mechanism is constructed based on the second-level optimization progress, the first-level optimization progress and the printing progress of the thermal printer.

2. The method for controlling the printing progress of a thermal printer according to claim 1, characterized in that: The method of collecting the corresponding data space based on the positioning detection of the thermal printer and defining the printing data according to the traversal of the data space includes: Collect the location of thermal printer; A corresponding scene space is defined based on the location of the thermal printer, a plurality of scene parameters are defined according to the traversal of the scene space, and a working scene of the thermal printer is defined according to the plurality of scene parameters; Associating the location of the thermal printer with the corresponding working scene, defining a corresponding detection method according to the location of the thermal printer and the corresponding working scene, and triggering the positioning detection of the thermal printer along the detection method; Based on the positioning detection of the thermal printer, the corresponding data space is collected and dynamically monitored to control the real-time interaction of the data space; The data space is traversed, and the printing data is defined according to the traversal of the data space.

3. The method for controlling the printing progress of a thermal printer according to claim 2, characterized in that: The tracing mechanism for printing data is defined based on the detection of printing data, including: Freeze-frame print data; Define the corresponding data volume according to the print data; triggering detection of the print data according to the amount of data and the distribution mode of the print data; Based on the detection of printing data, a corresponding data chain is defined, and based on the division of the data chain, corresponding printing nodes, encryption nodes and overall verification nodes are defined; Associate the printing node, encryption node, and overall verification node; A traceability mechanism for printed data is constructed based on printing nodes, encryption nodes, and overall verification nodes.

4. The method for controlling the printing progress of a thermal printer according to claim 3, characterized in that: Defining multiple abnormal dimensions according to the printing data, the corresponding tracing mechanism and the multi-dimensional detection model includes: Freeze-print data and corresponding traceability mechanism; Associate printing data and corresponding traceability mechanism; Trigger multi-dimensional traceability based on printing data and corresponding traceability mechanism; Define the abnormal parts of the printed data under the traceability of various dimensions; Associating multiple abnormal parts; constructing corresponding abnormal combinations according to the multiple abnormal parts, and matching corresponding multi-dimensional detection models along the abnormal combinations and the models of thermal printers; Multiple abnormal dimensions are defined based on the abnormal part and the multi-dimensional detection model. At this time, the multi-dimensional detection model is trained based on previous dimensional data, and is further upgraded autonomously based on online training of the abnormal part and the working scenario.

5. The method for controlling the printing progress of a thermal printer according to claim 4, characterized in that: The interactive process based on multiple abnormal dimensions and print data defines an abnormal set; and defines multiple abnormal features according to the abnormal set and the model of the thermal printer, including: Freeze multiple abnormal dimensions; Correlate multiple abnormal dimensions, the data volume corresponding to the printed data, and the interactive process of the printed data; An exception set is defined based on multiple exception dimensions, the data volume corresponding to the print data, and the interactive process of the print data; Associate an exception set, the age of the thermal printer, and the model of the thermal printer, define a first feature set based on the exception set and the age of the thermal printer, define a second feature set based on the exception set and the model of the thermal printer, and define multiple exception features based on the first feature set and the second feature set.

6. The method for controlling the printing progress of a thermal printer according to claim 5, characterized in that: The corresponding abnormal event is constructed according to the plurality of abnormal features and the printing process of the thermal printer; Based on the abnormal event, the model of the thermal printer and the printing task to be printed by the thermal printer, a corresponding optimization learning model is matched, including: Freeze multiple abnormal features; Collect the printing process of the thermal printer, define multiple printing tasks based on the printing process of the thermal printer, and associate the multiple printing tasks with multiple abnormal features; Corresponding abnormal events are constructed based on multiple printing tasks and multiple abnormal features.

7. The method for controlling the printing progress of a thermal printer according to claim 6, characterized in that: The corresponding abnormal event is constructed according to the plurality of abnormal features and the printing process of the thermal printer; Based on the abnormal event, the model of the thermal printer and the task to be printed of the thermal printer, a corresponding optimization learning model is matched, which also includes: Defining the tasks to be printed by the thermal printer according to the progress control of multiple printing tasks; Associating the abnormal event, the model of the thermal printer, and the pending printing tasks of the thermal printer; A first model coefficient is defined according to the abnormal event and the model of the thermal printer, a second model coefficient is defined according to the abnormal event and the task to be printed of the thermal printer, and a corresponding optimization learning model is matched based on the first model coefficient, the second model coefficient and the control model of the thermal printer. At this time, the optimization learning model is trained based on previous optimization data.

8. The method for controlling the printing progress of a thermal printer according to claim 7, characterized in that: The first-level optimization logic is defined based on the optimization learning model and the abnormal event; The secondary optimization logic is defined based on the printing effect level and the preset printing effect level threshold, and a dynamic balance mechanism is constructed based on the secondary optimization progress, the primary optimization progress and the printing progress of the thermal printer, including: Dynamically interact with the optimized learning model and the abnormal event, and define the corresponding interaction coefficient; Associating the optimization learning model, the abnormal event and the corresponding interaction coefficient, and defining a primary optimization logic according to the optimization learning model, the abnormal event and the corresponding interaction coefficient; Trigger the first-level optimization of abnormal events based on the first-level optimization logic, control the first-level optimization progress of abnormal events, and conduct online management and control of the first-level optimization progress and the printing progress of the thermal printer.

9. The method for controlling the printing progress of a thermal printer according to claim 8, characterized in that: The first-level optimization logic is defined based on the optimization learning model and the abnormal event; The secondary optimization logic is defined based on the printing effect level and the preset printing effect level threshold, and a dynamic balance mechanism is constructed based on the secondary optimization progress, the primary optimization progress and the printing progress of the thermal printer, and also includes: Monitor the printing effect coefficient of the thermal printer on the printing paper in real time, and define the printing effect level of the thermal printer on the printing paper based on the printing effect coefficient and the printing area; Compare the printing effect level with the preset printing effect level threshold, and output the level difference, and define the secondary optimization logic according to the level difference, the printing effect level and the service life of the thermal printer; Trigger the secondary optimization of abnormal events based on the secondary optimization logic, control the secondary optimization progress of abnormal events, associate the secondary optimization progress, the primary optimization progress and the printing progress of the thermal printer, and build a dynamic balance mechanism based on the secondary optimization progress, the primary optimization progress and the printing progress of the thermal printer to ensure multiple optimizations of abnormal events and the normal execution of the optimized abnormal events.

10. A thermal printer printing progress control system, characterized in that: The printing progress control system of the thermal printer is applied to the printing progress control method of the thermal printer as claimed in any one of claims 1 to 9, and the printing progress control system of the thermal printer includes: A positioning detection module, used to collect corresponding data space based on positioning detection of the thermal printer, and define printing data according to the traversal of the data space; A tracing module, used to define a tracing mechanism for printing data based on the detection of printing data; The abnormal dimension module is used to define multiple abnormal dimensions according to the printing data, the corresponding traceability mechanism and the multi-dimensional detection model; An abnormal feature module is used to define an abnormal set based on multiple abnormal dimensions and an interactive process of printing data; and define multiple abnormal features according to the abnormal set and the model of the thermal printer; An optimization module, used to construct a corresponding abnormal event according to a plurality of abnormal features and the printing process of the thermal printer; and to match a corresponding optimization learning model based on the abnormal event, the model of the thermal printer and the printing task to be printed by the thermal printer; The progress control module is used to define the first-level optimization logic based on the optimization learning model and the abnormal event; define the second-level optimization logic based on the printing effect level and the preset printing effect level threshold, and build a dynamic balance mechanism based on the second-level optimization progress, the first-level optimization progress and the printing progress of the thermal printer.

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