A production auxiliary platform-based job supervision system

Abstract

The application provides a production auxiliary platform-based work supervision system, comprising: a task determination module configured to determine personnel auxiliary supervision tasks and equipment auxiliary supervision tasks in a production work application integrated system based on a production auxiliary platform; a supervision module configured to perform first supervision based on the personnel auxiliary supervision tasks and second supervision based on the equipment auxiliary supervision tasks; a result acquisition module configured to acquire work supervision results of field work of the production work application integrated system based on first supervision results and second supervision results; and an information configuration module configured to configure informationized behaviors to the production work application integrated system according to the work supervision results, so as to realize intelligent work supervision. Through the first supervision on the workers and the second supervision on the production equipment, the work supervision efficiency can be effectively improved, and through the configuration of the behaviorized information, intelligent work supervision can be realized and the informationization utilization rate can be improved.

Description

Technical Field

[0001] This invention relates to the field of intelligent monitoring technology, and in particular to an operation monitoring system based on a production support platform. Background Technology

[0002] The core of a power plant's entire production work is the safe, stable, and reliable operation of its generating units. Therefore, the quality of a power plant's operation and management determines the company's business development and economic benefits.

[0003] The current level of informatization in production management is low, which affects work efficiency. This is mainly manifested in the following ways: First, current production management is mainly carried out through the factory's internal management system, internal meetings, and paper attendance records. The informatization methods for managing specific personnel are low, and there is a lack of specific management methods. Second, the daily production operation involves complex and important tasks such as equipment maintenance, usage standards, and maintenance procedures. However, the problems encountered in the work lack technical support, and the utilization rate of existing experience and informatization methods is low, which affects work efficiency.

[0004] Therefore, this invention proposes an operation monitoring system based on a production support platform. Summary of the Invention

[0005] This invention provides an operation supervision system based on a production support platform, which can effectively improve the efficiency of supervision by first supervising the staff and second supervising the production equipment. Furthermore, by configuring behavioral information, it can further realize intelligent operation supervision, improve the utilization rate of information technology, and ensure the high efficiency of supervision.

[0006] This invention provides an operation monitoring system based on a production support platform, comprising:

[0007] The task determination module is used to determine personnel auxiliary supervision tasks and equipment auxiliary supervision tasks in the integrated production work application system based on the production support platform.

[0008] The monitoring module is used to perform first monitoring of the bound staff based on the personnel-assisted monitoring task, and at the same time, to perform second monitoring of the bound production equipment based on the equipment-assisted monitoring task;

[0009] The result acquisition module is used to obtain the operation supervision results of the on-site operation of the integrated system for production work based on the first supervision result and the second supervision result.

[0010] The information configuration module is used to configure information-based behaviors to the integrated production work application system based on the operation supervision results, so as to realize intelligent operation supervision.

[0011] Preferably, the task determination module includes:

[0012] The table parsing unit is used to parse the integrated system for production work to obtain the integrated work table, personnel allocation table and equipment allocation table.

[0013] An integrated identification unit is used to configure personnel identification and equipment identification in the integrated worksheet based on the integrated identification model, and to construct a first configuration list.

[0014] The personnel identification unit is used to perform integrated identification configuration and device identification configuration on the personnel allocation table based on the personnel identification model, and to construct a second configuration list.

[0015] The equipment identification unit is used to perform integrated identification configuration and personnel identification configuration on the equipment allocation table based on the equipment identification model, and to construct a third configuration list.

[0016] The identifier filtering unit is used to filter full-match identifiers, partial-match identifiers, and non-match identifiers based on the first configuration list, the second configuration list, and the third configuration list.

[0017] The task matching unit is used to match a corresponding first supervisory task from the identifier-task database according to the full match identifier, and at the same time, match a corresponding second supervisory task from the identifier-task database according to the union of the half match identifier and the non-match identifier;

[0018] The supervision task acquisition unit is used to process tasks based on the first supervision task and the second supervision task to obtain the personnel-assisted supervision task and the equipment-assisted supervision task.

[0019] Preferably, the regulatory task acquisition unit includes:

[0020] The first setting block is used to set a first regulatory factor for each regulatory subtask corresponding to a full-match identifier according to the number of identifier matches corresponding to the full-match identifier and the first number of personnel identifiers and the second number of equipment identifiers in each full-match identifier;

[0021] The second setting block is used to determine the identifier bias of each half-matching identifier based on the half-matching identifier, and to count the total identifier bias of all half-matching identifiers corresponding to different identifiers, and to set a second regulatory factor for the regulatory subtask corresponding to each half-matching identifier.

[0022] The third setting block is used to set a third regulatory factor for each regulatory subtask corresponding to the mismatched identifier based on the frequency of the mismatched identifier's occurrence.

[0023] The task adjustment block is used to adjust the corresponding regulatory sub-tasks in the second regulatory task based on the first regulatory factor, the second regulatory factor, and the third regulatory factor.

[0024] The task expansion block is used to expand the first monitoring task based on the task adjustment result to obtain a third monitoring task;

[0025] The task splitting block is used to split the third supervision task according to the layout association of the preset personnel layout and the preset equipment layout, so as to obtain the personnel-assisted supervision task and the equipment-assisted supervision task.

[0026] Preferably, the monitoring module includes:

[0027] The task extraction unit is used to extract corresponding matching tasks from the personnel auxiliary supervision tasks according to the personnel's work attributes, extract the key points of the personnel's work content, and determine the point topology relationship of each key point.

[0028] An event setting unit is used to extract a first subtask from the matching task according to the point topology relationship, and set a task supervision event for each branch structure on the point topology relationship by performing task parsing on the first subtask, wherein the task supervision event is related to the unique execution identifier of the person and the event supervision conditions.

[0029] The first monitoring unit is used to perform first monitoring on the personnel in a monitoring manner consistent with the monitoring event when the personnel triggers the matched task monitoring event.

[0030] Preferably, the monitoring module further includes:

[0031] The equipment task extraction unit is used to extract the corresponding equipment supervision sub-task from the equipment auxiliary supervision task according to the equipment attributes of the production equipment;

[0032] A behavior weight determination unit is used to acquire the workflow of the production equipment and determine the behavior attributes and behavior weights of each work behavior in the workflow.

[0033] The ordered event setting unit is used to determine the sub-task line of each work behavior based on the behavior attributes of each work behavior, and set an ordered supervision event on the corresponding sub-task line based on the initial time point of the work behavior.

[0034] A saliency processing unit is used to perform saliency processing on the sub-task lines based on the behavior weight and behavior duration of each work behavior;

[0035] The task line processing unit is used to fill in and align all the sub-task lines with significant processing in the same workflow based on timestamps, obtain the jump time point, and set the jump event related to the jump time point on the corresponding sub-task line.

[0036] The second monitoring unit is used to perform second monitoring on the production equipment in accordance with the monitoring method consistent with the corresponding event when the production equipment triggers the corresponding ordered monitoring event and jump event.

[0037] Preferably, the taskline processing unit further includes:

[0038] A transition point event setting block is used to set a first event at the corresponding position of the device monitoring subtask according to the left salience sequence of the transition time point, and to set a second event at the corresponding position of the device monitoring subtask according to the right salience sequence of the transition event point.

[0039] The jump point event monitoring block is used to continue monitoring the production equipment in the same monitoring method as the first event and the second event when the production equipment triggers the first event corresponding to the same jump time point, and to classify the monitoring results of the same jump time point into the same memory.

[0040] Among them, the first event and the second event are the transition events.

[0041] Preferably, the result acquisition module includes:

[0042] The first supervision thread unit is used to determine the first supervision thread for each person and the first supervision task for each first supervision node in the first supervision thread based on the first supervision result.

[0043] The second monitoring thread unit is used to determine the second monitoring thread for each production device and the second monitoring operation for each second monitoring node in the second monitoring thread based on the second monitoring result.

[0044] The mapping relationship acquisition unit is used to match the first supervision thread, the second supervision thread, the first supervision job, and the second supervision job with the supervision jobs of the thread nodes, and to obtain the first mapping relationship between each person and all production equipment.

[0045] The job extraction unit is used to screen the participants and participating equipment in the on-site job selection based on the integrated production work application system, and to screen the second mapping relationship related to the participants from all first mapping relationships, and to extract the participating jobs from the second mapping relationship based on the participating equipment.

[0046] The operation supervision result acquisition unit is used to obtain the operation supervision result of the on-site operation based on the supervision result of the participating operation.

[0047] Preferably, the information configuration module includes:

[0048] The regulatory difference determination unit is used to obtain the standard regulatory results that match the on-site operation, and compare and analyze the standard regulatory results with the operation regulatory results one by one to determine the existing regulatory differences;

[0049] The difference level determination unit is used to determine the overall difference level based on all regulatory differences and the individual difference level based on each regulatory difference.

[0050] The factor determination unit is used to obtain the difference contribution factor of each individual difference level to the comprehensive difference level, and to configure difference weights to the corresponding regulatory differences based on the difference contribution factors;

[0051] The first sorting unit is used to configure information-based behaviors for the regulatory differences from the behavior database, and to sort all information-based behaviors according to the difference weights.

[0052] The difference correction unit is used to correct the existing regulatory differences according to the sorting results of the first row and the corresponding information behavior in sequence, so as to realize intelligent operation supervision.

[0053] Preferably, the information configuration module further includes:

[0054] The operation supervision and verification unit is used to re-verify the corrected supervision discrepancies after intelligent operation supervision is implemented.

[0055] If the verification passes, subsequent regulatory operations will continue according to the corrected behavior.

[0056] The re-correction unit is used to determine the dependency contribution factor of each uncorrected regulatory difference and the remaining uncorrected regulatory differences when the verification fails, and to make a re-correction to achieve intelligent operation supervision.

[0057] Preferably, the task extraction unit includes:

[0058] The branching block is used to obtain the first content associated with each content association point, and to branch the first content according to the content type of the first content;

[0059] The hierarchical partitioning block is used to hierarchically partition the first content on the corresponding branch according to the association size between the first content on each branch and the associated point of the content;

[0060] The top and bottom position setting block is used to set the top and bottom positions according to the related relationships of the first content at the same level in the same branch;

[0061] The relationship building block is used to construct point topology relationships based on branching results, hierarchical division results, and upper and lower position settings.

[0062] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the written description, claims, and drawings.

[0063] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0064] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0065] Figure 1 This is a structural diagram of an operation monitoring system based on a production support platform according to an embodiment of the present invention;

[0066] Figure 2 This is a graph showing the saliency sequence results in an embodiment of the present invention;

[0067] Figure 3 This is a point topology diagram in an embodiment of the present invention. Detailed Implementation

[0068] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0069] This invention provides an operation monitoring system based on a production support platform, such as... Figure 1 As shown, it includes:

[0070] The task determination module is used to determine personnel auxiliary supervision tasks and equipment auxiliary supervision tasks in the integrated production work application system based on the production support platform.

[0071] The monitoring module is used to perform first monitoring of the bound staff based on the personnel-assisted monitoring task, and at the same time, to perform second monitoring of the bound production equipment based on the equipment-assisted monitoring task;

[0072] The result acquisition module is used to obtain the operation supervision results of the on-site operation of the integrated system for production work based on the first supervision result and the second supervision result.

[0073] The information configuration module is used to configure information-based behaviors to the integrated production work application system based on the operation supervision results, so as to realize intelligent operation supervision.

[0074] In this embodiment, the production support platform can be implemented using a J2EE architecture, applying enterprise-level information application concepts, standards, and technologies to ensure system stability, efficiency, and robustness. It utilizes a popular and advanced three-tier architecture, constructing a data storage layer, a database layer, an application logic layer, and a web service layer. Due to the centralized data storage model, subordinate departments no longer need to configure related systems and servers. Users only need to access business information through handheld terminals and browsers, providing necessary production and operational data analysis and reporting for power plant operation and management. This improves the overall efficiency of data utilization and provides strong technical support for the scientific, standardized, and high-quality implementation of power plant operation and management.

[0075] In this embodiment, the main focus is on monitoring personnel's work status, work scope, performance evaluation, work plans, work achievements, and work statistics. It also mainly monitors the operation, maintenance, procedures, data, and spare parts of equipment.

[0076] In this embodiment, the integrated production and operation system mainly refers to the power plant system, which monitors the personnel and equipment (units, power generation equipment, power generation devices, etc.) serving the power plant to ensure the efficient operation of the power plant.

[0077] In this embodiment, personnel-assisted supervision tasks refer to supervising the tasks that personnel need to perform, while equipment-assisted supervision tasks refer to supervising the tasks that equipment needs to perform.

[0078] In this embodiment, the operation supervision result is obtained from the first supervision result and the second supervision result to obtain the results related to the on-site operation. The information behavior refers to correcting the equipment or problems in the supervision itself corresponding to the supervision differences that occur during the supervision process, so as to ensure the reliability of intelligent operation supervision.

[0079] The beneficial effects of the above technical solution are: by conducting primary supervision of personnel and secondary supervision of production equipment, the efficiency of supervision work can be effectively improved; and by configuring behavioral information, intelligent operation supervision can be further realized, improving the utilization rate of information technology and ensuring the high efficiency of supervision.

[0080] This invention provides a work monitoring system based on a production support platform, wherein the task determination module includes:

[0081] The table parsing unit is used to parse the integrated system for production work to obtain the integrated work table, personnel allocation table and equipment allocation table.

[0082] An integrated identification unit is used to configure personnel identification and equipment identification in the integrated worksheet based on the integrated identification model, and to construct a first configuration list.

[0083] The personnel identification unit is used to perform integrated identification configuration and device identification configuration on the personnel allocation table based on the personnel identification model, and to construct a second configuration list.

[0084] The equipment identification unit is used to perform integrated identification configuration and personnel identification configuration on the equipment allocation table based on the equipment identification model, and to construct a third configuration list.

[0085] The identifier filtering unit is used to filter full-match identifiers, partial-match identifiers, and non-match identifiers based on the first configuration list, the second configuration list, and the third configuration list.

[0086] The task matching unit is used to match a corresponding first supervisory task from the identifier-task database according to the full match identifier, and at the same time, match a corresponding second supervisory task from the identifier-task database according to the union of the half match identifier and the non-match identifier;

[0087] The supervision task acquisition unit is used to process tasks based on the first supervision task and the second supervision task to obtain the personnel-assisted supervision task and the equipment-assisted supervision task.

[0088] In this embodiment, the identifier-task database includes different identifier combinations and the regulatory tasks corresponding to those identifier combinations, thus enabling the acquisition of the corresponding regulatory tasks.

[0089] In this embodiment, the union matching identifier is used to obtain all different identifier combinations to obtain the second regulatory task.

[0090] In this embodiment, task processing refers to breaking down the regulatory task to obtain targeted tasks related to personnel and equipment.

[0091] In this embodiment, the integrated identification model, personnel identification model, and equipment identification model are all pre-trained, and the training samples corresponding to different identification models are different.

[0092] In this embodiment, the integrated worksheet mainly refers to the table composed of integrated production information of the integrated system, the personnel allocation table refers to the table composed of personnel involved in production, and the equipment allocation table refers to the table composed of equipment involved in production.

[0093] In this embodiment, the configuration of personnel identification and equipment identification based on the integrated identification model is mainly to enrich the integrated worksheet and determine the allocation of personnel and equipment. The personnel identification model performs integrated identification and equipment identification to determine the allocation of integrated information and equipment, and the equipment identification model performs integrated identification and personnel identification to determine the allocation of integrated information and personnel.

[0094] In this embodiment, for example, there are: integrated information 1 - personnel 1 - equipment 1, integrated information 1 - personnel 2 - equipment 2, personnel 1 - integrated information 1 - equipment 1, equipment 1 - integrated information 1 - personnel 2, personnel 2 - integrated information 1 - equipment 2, equipment 2 - integrated information 1 - personnel 2.

[0095] Integrated information 1 - personnel 1 - equipment 1, and integrated information 1 - personnel 2 - equipment 2 constitute the first configuration list.

[0096] Personnel 1 - Integrated Information 1 - Equipment 1, Personnel 2 - Integrated Information 1 - Equipment 2 constitute the second configuration list.

[0097] Equipment 1 - Integrated Information 1 - Personnel 2, Equipment 2 - Integrated Information 1 - Personnel 2, together constitute the third configuration information.

[0098] Among them, Integrated Information 1-Personnel 1-Equipment 1, Personnel 1-Integrated Information 1-Equipment 1, and Equipment 1-Integrated Information 1-Personnel 2 are the corresponding semi-matching identifiers.

[0099] The integrated information 1-personnel 2-equipment 2, personnel 2-integrated information 1-equipment 2, and equipment 2-integrated information 1-personnel 2 are the corresponding full-match identifiers.

[0100] If the corresponding information is: Integrated Information 1 - Personnel 2 - Equipment 2, Personnel 1 - Integrated Information 1 - Equipment 2, Equipment 2 - Integrated Information 2 - Personnel 2, then the corresponding mismatch identifier can be obtained.

[0101] The beneficial effects of the above technical solution are: by comprehensively determining whether the integrated information, personnel, and equipment are completely consistent through three aspects, targeted matching of tasks can be achieved, ensuring the reliability and completeness of subsequent task acquisition, thereby improving work efficiency.

[0102] This invention provides an operation monitoring system based on a production support platform, wherein the monitoring task acquisition unit includes:

[0103] The first setting block is used to set a first regulatory factor for each regulatory subtask corresponding to a full-match identifier according to the number of identifier matches corresponding to the full-match identifier and the first number of personnel identifiers and the second number of equipment identifiers in each full-match identifier;

[0104] The second setting block is used to determine the identifier bias of each half-matching identifier based on the half-matching identifier, and to count the total identifier bias of all half-matching identifiers corresponding to different identifiers, and to set a second regulatory factor for the regulatory subtask corresponding to each half-matching identifier.

[0105] The third setting block is used to set a third regulatory factor for each regulatory subtask corresponding to the mismatched identifier based on the frequency of the mismatched identifier's occurrence.

[0106] The task adjustment block is used to adjust the corresponding regulatory sub-tasks in the second regulatory task based on the first regulatory factor, the second regulatory factor, and the third regulatory factor.

[0107] The task expansion block is used to expand the first monitoring task based on the task adjustment result to obtain a third monitoring task;

[0108] The task splitting block is used to split the third supervision task according to the layout association of the preset personnel layout and the preset equipment layout, so as to obtain the personnel-assisted supervision task and the equipment-assisted supervision task.

[0109] In this embodiment, since each full-match identifier may contain multiple people or multiple devices, the number is determined to set the regulatory factor, and the larger the number, the greater the task adjustment capability of the corresponding regulatory factor.

[0110] In this embodiment, the semi-matching identifier is: integrated information 1 - personnel 2, 3, 4 - equipment 2, 4. At this time, the corresponding identifier bias is personnel, the total identifier bias of the corresponding integrated information is 1, the total identifier bias of the corresponding personnel is 3, and the total identifier bias of the corresponding equipment is 2. At this time, the second regulatory factor is determined, mainly for the purpose of supervising the identifier bias to ensure the targeting of the task.

[0111] In this embodiment, the frequency of an identifier, such as the total number of times the same identifier appears among different mismatched identifiers, indicates that the higher the frequency, the greater the task adjustment capability of the corresponding regulatory factor.

[0112] In this embodiment, the preset personnel layout and preset equipment layout are pre-set standard work distributions, which facilitates the reasonable allocation of tasks provided by the production support platform.

[0113] In this embodiment, layout association refers to the working relationship between different people and different devices.

[0114] The beneficial effects of the above technical solution are: by acquiring different regulatory factors corresponding to different identifiers, and adjusting the tasks according to the regulatory factors to expand the tasks and ensure the integrity of the tasks, and then splitting the tasks according to the layout association, the regulatory tasks for personnel and the regulatory tasks for equipment can be effectively obtained, ensuring the intelligence and efficiency of subsequent operation supervision.

[0115] This invention provides an operation monitoring system based on a production support platform, wherein the monitoring module includes:

[0116] The task extraction unit is used to extract corresponding matching tasks from the personnel auxiliary supervision tasks according to the personnel's work attributes, extract the key points of the personnel's work content, and determine the point topology relationship of each key point.

[0117] An event setting unit is used to extract a first subtask from the matching task according to the point topology relationship, and set a task supervision event for each branch structure on the point topology relationship by performing task parsing on the first subtask, wherein the task supervision event is related to the unique execution identifier of the person and the event supervision conditions.

[0118] The first monitoring unit is used to perform first monitoring on the personnel in a monitoring manner consistent with the monitoring event when the personnel triggers the matched task monitoring event.

[0119] In this embodiment, the work attribute refers to the type of work that the personnel need to perform, and the work task is based on the work type. The work content refers to the specific content to be performed, such as the content to be performed for task 1, and the work content and work task are matched one-to-one.

[0120] In this embodiment, the first subtask is aimed at point topology relationships, and the main purpose of task parsing is to determine task supervision events in order to supervise personnel.

[0121] The beneficial effects of the above technical solution are: by determining the topological relationship of points according to the key points of the content, and by setting up supervision events based on the extraction and parsing of sub-tasks, supervision of personnel can be realized when triggered, thereby achieving intelligent supervision and ensuring supervision efficiency.

[0122] This invention provides an operation monitoring system based on a production support platform, wherein the monitoring module further includes:

[0123] The equipment task extraction unit is used to extract the corresponding equipment supervision sub-task from the equipment auxiliary supervision task according to the equipment attributes of the production equipment;

[0124] A behavior weight determination unit is used to acquire the workflow of the production equipment and determine the behavior attributes and behavior weights of each work behavior in the workflow.

[0125] The ordered event setting unit is used to determine the sub-task line of each work behavior based on the behavior attributes of each work behavior, and set an ordered supervision event on the corresponding sub-task line based on the initial time point of the work behavior.

[0126] A saliency processing unit is used to perform saliency processing on the sub-task lines based on the behavior weight and behavior duration of each work behavior;

[0127] The task line processing unit is used to fill in and align all the sub-task lines with significant processing in the same workflow based on timestamps, obtain the jump time point, and set the jump event related to the jump time point on the corresponding sub-task line.

[0128] The second monitoring unit is used to perform second monitoring on the production equipment in accordance with the monitoring method consistent with the corresponding event when the production equipment triggers the corresponding ordered monitoring event and jump event.

[0129] In this embodiment, the device attribute can be the device model to extract the corresponding sub-task. The workflow of each device consists of multiple work behaviors. Therefore, the sub-task line is determined by the behavior attribute, and then an orderly supervision event is set. Since there are different places that need special supervision on each sub-task line, the places that need special supervision are obtained by salience processing and completion and alignment processing, so as to ensure the rationality and efficiency of supervision of the place.

[0130] The beneficial effects of the above technical solution are: by acquiring work behavior, sub-task lines can be determined, and then effective supervision can be carried out by setting effective supervision events. By using salience processing and completion / alignment processing, areas that require special supervision can be identified, thereby ensuring the rationality and efficiency of supervision of those areas.

[0131] This invention provides a work monitoring system based on a production support platform, a task line processing unit, and further includes:

[0132] A transition point event setting block is used to set a first event at the corresponding position of the device monitoring subtask according to the left salience sequence of the transition time point, and to set a second event at the corresponding position of the device monitoring subtask according to the right salience sequence of the transition event point.

[0133] The jump point event monitoring block is used to continue monitoring the production equipment in the same monitoring method as the first event and the second event when the production equipment triggers the first event corresponding to the same jump time point, and to classify the monitoring results of the same jump time point into the same memory.

[0134] Among them, the first event and the second event are the transition events.

[0135] Calculate the significance value of the left-hand significant sequence:

[0136]

[0137] Where n1 represents the total number of significant sequences on the left; ∝1 i This represents the line thickness of the i-th saliency sequence on the left; ∝2 i The line color represents the value of the i-th saliency sequence on the left; s1 i s2 represents the coarse and fine weight values ​​of the i-th saliency sequence on the left; i Y1 represents the color weight value of the i-th saliency sequence on the left; Y1 represents the saliency value of the saliency sequence on the left.

[0138] Similarly, the significance value of the left-hand significant sequence is calculated in a similar way to the significance value of the left-hand significant sequence mentioned above.

[0139] In this embodiment, the larger the significance value, the more reliable the regulatory capability corresponding to the setting event needs to be.

[0140] In this embodiment, the regulatory results of the first event and the second event corresponding to the same jump time point are grouped into the same content in order to better analyze the regulatory results.

[0141] Furthermore, the transition point refers to a situation where there is a significant difference between the left and right sequences, including the thickness of the lines and the intensity of the line colors.

[0142] like Figure 2 As shown, the corresponding significance sequence results.

[0143] The beneficial effects of the above technical solution are: by analyzing the left and right saliency sequences of the jump time points, events can be set, and then production equipment can be subject to specific supervision according to the corresponding supervision methods, ensuring the efficiency and rationality of supervision, and providing a foundation for intelligentization.

[0144] This invention provides an operation monitoring system based on a production support platform, wherein the result acquisition module includes:

[0145] The first supervision thread unit is used to determine the first supervision thread for each person and the first supervision task for each first supervision node in the first supervision thread based on the first supervision result.

[0146] The second monitoring thread unit is used to determine the second monitoring thread for each production device and the second monitoring operation for each second monitoring node in the second monitoring thread based on the second monitoring result.

[0147] The mapping relationship acquisition unit is used to match the first supervision thread, the second supervision thread, the first supervision job, and the second supervision job with the supervision jobs of the thread nodes, and to obtain the first mapping relationship between each person and all production equipment.

[0148] The job extraction unit is used to screen the participants and participating equipment in the on-site job selection based on the integrated production work application system, and to screen the second mapping relationship related to the participants from all first mapping relationships, and to extract the participating jobs from the second mapping relationship based on the participating equipment.

[0149] The operation supervision result acquisition unit is used to obtain the operation supervision result of the on-site operation based on the supervision result of the participating operation.

[0150] In this embodiment, each regulatory result includes both the regulatory node and the regulatory operation.

[0151] In this embodiment, the thread node refers to the supervisory node in the supervisory thread. During the matching process, the main purpose is to determine the matching relationship between personnel and equipment, and then determine the mapping relationship.

[0152] The beneficial effects of the above technical solution are: by matching regulatory operations, a mapping relationship is obtained, and personnel and equipment are screened according to on-site operations to obtain a second mapping relationship, thereby extracting the participating operations and ensuring the accuracy of the regulatory results of the matched operations.

[0153] This invention provides an operation monitoring system based on a production support platform, wherein the information configuration module includes:

[0154] The regulatory difference determination unit is used to obtain the standard regulatory results that match the on-site operation, and compare and analyze the standard regulatory results with the operation regulatory results one by one to determine the existing regulatory differences;

[0155] The difference level determination unit is used to determine the overall difference level based on all regulatory differences and the individual difference level based on each regulatory difference.

[0156] The factor determination unit is used to obtain the difference contribution factor of each individual difference level to the comprehensive difference level, and to configure difference weights to the corresponding regulatory differences based on the difference contribution factors;

[0157] The first sorting unit is used to configure information-based behaviors for the regulatory differences from the behavior database, and to sort all information-based behaviors according to the difference weights.

[0158] The difference correction unit is used to correct the existing regulatory differences according to the sorting results of the first row and the corresponding information behavior in sequence, so as to realize intelligent operation supervision.

[0159] In this embodiment, the standard supervision result is the result obtained when the on-site operation is carried out under the pre-set standard conditions and is supervised. As a reference, comparing and analyzing this result with the operation supervision result can effectively identify the existing supervision differences.

[0160] In this embodiment, the comprehensive difference level and the individual difference level are obtained based on the regulatory difference level model, which is trained using different regulatory differences and various combinations of regulatory differences as samples, thereby determining the corresponding difference level.

[0161] In this embodiment, the difference contribution factor refers to the proportion of the contribution of a single difference level to the overall difference level; the larger the proportion, the greater the corresponding difference weight.

[0162] In this embodiment, the behavior database is pre-set and includes various different information-based behaviors.

[0163] The beneficial effects of the above technical solution are: by conducting comparative analysis between standards and reality, the existing regulatory differences are identified, and then by determining the individual difference level and the comprehensive difference level, the difference contribution factor is determined, thereby ranking the information-based behaviors, ensuring the orderly correction of regulatory differences, and ensuring the high efficiency of intelligent operation supervision.

[0164] This invention provides an operation monitoring system based on a production support platform, wherein the information configuration module further includes:

[0165] The operation supervision and verification unit is used to re-verify the corrected supervision discrepancies after intelligent operation supervision is implemented.

[0166] If the verification passes, subsequent regulatory operations will continue according to the corrected behavior.

[0167] The re-correction unit is used to determine the dependency contribution factor of each uncorrected regulatory difference and the remaining uncorrected regulatory differences when the verification fails, and to make a re-correction to achieve intelligent operation supervision.

[0168] In this embodiment, the dependency contribution factor refers to the impact of one regulatory difference on the remaining regulatory differences.

[0169] The beneficial effects of the above technical solution are: by verifying the corrected regulatory differences, the dependency contribution factor can be determined, thereby achieving intelligent operation supervision.

[0170] This invention provides a work monitoring system based on a production support platform, wherein the task extraction unit includes:

[0171] The branching block is used to obtain the first content associated with each content association point, and to branch the first content according to the content type of the first content;

[0172] The hierarchical partitioning block is used to hierarchically partition the first content on the corresponding branch according to the association size between the first content on each branch and the associated point of the content;

[0173] The top and bottom position setting block is used to set the top and bottom positions according to the related relationships of the first content at the same level in the same branch;

[0174] The relationship building block is used to construct point topology relationships based on branching results, hierarchical division results, and upper and lower position settings.

[0175] In this embodiment, such as Figure 3 As shown, this represents the topological relationship between points, where 1 indicates a branch, 2 indicates a level, and 3 indicates the vertical position.

[0176] The beneficial effects of the above technical solution are: by analyzing and dividing according to content, dividing into levels and setting up and down positions, it is easy to construct point topology relationships, providing an effective basis for primary supervision.

[0177] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. An operation monitoring system based on a production support platform, characterized in that, include: The task determination module is used to determine personnel auxiliary supervision tasks and equipment auxiliary supervision tasks in the integrated production work application system based on the production support platform. The monitoring module is used to perform first monitoring of the bound staff based on the personnel-assisted monitoring task, and at the same time, to perform second monitoring of the bound production equipment based on the equipment-assisted monitoring task; The result acquisition module is used to obtain the operation supervision results of the on-site operation of the integrated system for production work based on the first supervision result and the second supervision result. The information configuration module is used to configure information-based behaviors to the integrated production work application system based on the operation supervision results, so as to realize intelligent operation supervision. The task determination module includes: The table parsing unit is used to parse the integrated system for production work to obtain the integrated work table, personnel allocation table and equipment allocation table. An integrated identification unit is used to configure personnel identification and equipment identification in the integrated worksheet based on the integrated identification model, and to construct a first configuration list. The personnel identification unit is used to perform integrated identification configuration and device identification configuration on the personnel allocation table based on the personnel identification model, and to construct a second configuration list. The equipment identification unit is used to perform integrated identification configuration and personnel identification configuration on the equipment allocation table based on the equipment identification model, and to construct a third configuration list. The identifier filtering unit is used to filter full-match identifiers, partial-match identifiers, and non-match identifiers based on the first configuration list, the second configuration list, and the third configuration list. The task matching unit is used to match a corresponding first supervisory task from the identifier-task database according to the full match identifier, and at the same time, match a corresponding second supervisory task from the identifier-task database according to the union of the half match identifier and the non-match identifier; The supervision task acquisition unit is used to process tasks based on the first supervision task and the second supervision task to obtain the personnel-assisted supervision task and the equipment-assisted supervision task.

2. The operation monitoring system based on a production support platform as described in claim 1, characterized in that, The regulatory task acquisition unit includes: The first setting block is used to set a first regulatory factor for each regulatory subtask corresponding to a full-match identifier according to the number of identifier matches corresponding to the full-match identifier and the first number of personnel identifiers and the second number of equipment identifiers in each full-match identifier; The second setting block is used to determine the identifier bias of each half-matching identifier based on the half-matching identifier, and to count the total identifier bias of all half-matching identifiers corresponding to different identifiers, and to set a second regulatory factor for the regulatory subtask corresponding to each half-matching identifier. The third setting block is used to set a third regulatory factor for each regulatory subtask corresponding to the mismatched identifier based on the frequency of the mismatched identifier's occurrence. The task adjustment block is used to adjust the corresponding regulatory sub-tasks in the second regulatory task based on the first regulatory factor, the second regulatory factor, and the third regulatory factor. The task expansion block is used to expand the first monitoring task based on the task adjustment result to obtain a third monitoring task; The task splitting block is used to split the third supervision task according to the layout association of the preset personnel layout and the preset equipment layout, so as to obtain the personnel-assisted supervision task and the equipment-assisted supervision task.

3. The operation monitoring system based on a production support platform as described in claim 1, characterized in that, The monitoring module includes: The task extraction unit is used to extract corresponding matching tasks from the personnel auxiliary supervision tasks according to the personnel's work attributes, extract the key points of the personnel's work content, and determine the point topology relationship of each key point. An event setting unit is used to extract a first subtask from the matching task according to the point topology relationship, and set a task supervision event for each branch structure on the point topology relationship by performing task parsing on the first subtask, wherein the task supervision event is related to the unique execution identifier of the person and the event supervision conditions. The first monitoring unit is used to perform first monitoring on the personnel in a monitoring manner consistent with the monitoring event when the personnel triggers the matched task monitoring event.

4. The operation monitoring system based on a production support platform as described in claim 1, characterized in that, The monitoring module also includes: The equipment task extraction unit is used to extract the corresponding equipment supervision sub-task from the equipment auxiliary supervision task according to the equipment attributes of the production equipment; A behavior weight determination unit is used to acquire the workflow of the production equipment and determine the behavior attributes and behavior weights of each work behavior in the workflow. The ordered event setting unit is used to determine the sub-task line of each work behavior based on the behavior attributes of each work behavior, and set an ordered supervision event on the corresponding sub-task line based on the initial time point of the work behavior. A saliency processing unit is used to perform saliency processing on the sub-task lines based on the behavior weight and behavior duration of each work behavior; The task line processing unit is used to fill in and align all the sub-task lines with significant processing in the same workflow based on timestamps, obtain the jump time point, and set the jump event related to the jump time point on the corresponding sub-task line. The second monitoring unit is used to perform second monitoring on the production equipment in accordance with the monitoring method consistent with the corresponding event when the production equipment triggers the corresponding ordered monitoring event and jump event.

5. The operation monitoring system based on a production support platform as described in claim 4, characterized in that, The taskline processing unit also includes: A transition point event setting block is used to set a first event at the corresponding position of the device monitoring subtask according to the left salience sequence of the transition time point, and to set a second event at the corresponding position of the device monitoring subtask according to the right salience sequence of the transition event point. The jump point event monitoring block is used to continue monitoring the production equipment in the same monitoring method as the first event and the second event when the production equipment triggers the first event corresponding to the same jump time point, and to classify the monitoring results of the same jump time point into the same memory. Among them, the first event and the second event are the transition events.

6. The operation monitoring system based on a production support platform as described in claim 1, characterized in that, The result acquisition module includes: The first supervision thread unit is used to determine the first supervision thread for each person and the first supervision task for each first supervision node in the first supervision thread based on the first supervision result. The second monitoring thread unit is used to determine the second monitoring thread for each production device and the second monitoring operation for each second monitoring node in the second monitoring thread based on the second monitoring result. The mapping relationship acquisition unit is used to match the first supervision thread, the second supervision thread, the first supervision job, and the second supervision job with the supervision jobs of the thread nodes, and to obtain the first mapping relationship between each person and all production equipment. The job extraction unit is used to screen the participants and participating equipment in the on-site job selection based on the integrated production work application system, and to screen the second mapping relationship related to the participants from all first mapping relationships, and to extract the participating jobs from the second mapping relationship based on the participating equipment. The operation supervision result acquisition unit is used to obtain the operation supervision result of the on-site operation based on the supervision result of the participating operation.

7. The operation monitoring system based on a production support platform as described in claim 1, characterized in that, The information configuration module includes: The regulatory difference determination unit is used to obtain the standard regulatory results that match the on-site operation, and compare and analyze the standard regulatory results with the operation regulatory results one by one to determine the existing regulatory differences; The difference level determination unit is used to determine the overall difference level based on all regulatory differences and the individual difference level based on each regulatory difference. The factor determination unit is used to obtain the difference contribution factor of each individual difference level to the comprehensive difference level, and to configure difference weights to the corresponding regulatory differences based on the difference contribution factors; The first sorting unit is used to configure information-based behaviors for the regulatory differences from the behavior database, and to sort all information-based behaviors according to the difference weights. The difference correction unit is used to correct the existing regulatory differences according to the sorting results of the first row and the corresponding information behavior in sequence, so as to realize intelligent operation supervision.

8. The operation monitoring system based on a production support platform as described in claim 7, characterized in that, The information configuration module further includes: The operation supervision and verification unit is used to re-verify the corrected supervision discrepancies after intelligent operation supervision is implemented. If the verification passes, subsequent regulatory operations will continue according to the corrected behavior. The re-correction unit is used to determine the dependency contribution factor of each uncorrected regulatory difference and the remaining uncorrected regulatory differences when the verification fails, and to make a re-correction to achieve intelligent operation supervision.

9. The operation monitoring system based on a production support platform as described in claim 3, characterized in that, The task extraction unit includes: The branching block is used to obtain the first content associated with each content association point, and to branch the first content according to the content type of the first content; The hierarchical partitioning block is used to hierarchically partition the first content on the corresponding branch according to the association size between the first content on each branch and the associated point of the content; The top and bottom position setting block is used to set the top and bottom positions according to the related relationships of the first content at the same level in the same branch; The relationship building block is used to construct point topology relationships based on branching results, hierarchical division results, and upper and lower position settings.

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