104 results about "Job stream" patented technology

The invention relates to the technical field of equipment maintenance scheduling, in particular to an equipment fault repair management system, which comprises a dependency identification and modeling module, a fault state analysis module, a task priority evaluation module, a work order scheduling generation module and a resource scheduling execution module. According to the method, a multi-level dependency topology between devices is constructed through a directed graph traversal algorithm, a trigger relation between physical connection and an operation process is quantitatively analyzed, a classification marking model is established in combination with dynamic parameters such as a performance degradation rate, a fusion influence range and a dependency factor are calculated through scalar superposition, and a priority scoring matrix is dynamically generated. A task queue structure is optimized through a sorting algorithm, a data-driven maintenance decision mechanism is formed, the fault positioning precision is improved, response delay caused by manual intervention is reduced, key node equipment maintenance lag is avoided, the resource configuration efficiency is optimized, the collaboration of fault processing and a production system is strengthened, and formulation of a preventive maintenance strategy is supported.

The invention discloses an efficient intelligent warehousing system and a storage method, and relates to the technical field of warehousing management, the system comprises the following components: a virtual digital twinborn model construction module, a business scene simulation module, a potential problem prediction module and an operation process optimization module; according to the system, the virtual digital twinborn model in 1: 1 mapping with the actual storage environment is constructed, synchronous updating is carried out in combination with data collected by the sensor network in real time, the system can accurately reflect the dynamic condition of the actual storage environment, and the service scene simulation module is utilized to simulate the real storage environment. The system can simulate warehousing operation processes in different business scenes in a virtual environment, automatically adjust cargo storage positions, equipment scheduling schemes and personnel task allocation, so that the efficiency and precision of warehousing management are remarkably improved, and in addition, the operation process optimization module can predict and improve the efficiency and accuracy of warehousing management according to simulation results and potential problems. The operation process of the actual warehousing system is automatically optimized, and the overall operation efficiency is further improved.

The invention relates to the technical field of intelligent warehouse management and Internet of Things perception, in particular to a warehouse checking method and a warehouse system. The method comprises the following steps: performing inventory demand path analysis on storage to obtain an inventory path scheme; performing inventory task issuing on the robot according to the inventory path scheme to obtain a carrying task instruction; carrying out inventory article grabbing processing according to the carrying task instruction to obtain static contact characteristic data; performing dynamic interaction and multi-mode signal acquisition based on the static contact characteristic data to obtain interactive sensing data; performing sensing signal separation on the interactive sensing data to obtain a mechanical parameter characteristic table and an acoustic characteristic spectrum; and performing article type identification matching on the mechanical parameter characteristic table and the acoustic characteristic spectrum to obtain an article type judgment result. According to the invention, the inventory function is seamlessly integrated into the daily operation process, so that the dimensionality and accuracy of the inventory information are improved, and the overall efficiency of warehousing operation is greatly improved.

The invention provides a self-supervised action process anomaly detection method and system based on comparative learning, relates to the field of operation process action anomaly detection in industrial control, and is used for solving the problems of dependence on a large amount of labeled data and insufficient model generalization ability in an existing method. Through an innovative video representation learning model and a comparative learning method, the system can generate pseudo-annotation data by using an unannotated action process video, so that the annotation cost is remarkably reduced. The core technology comprises a video representation model based on ResNet, a time convolution layer and a Transform encoder, and an action label generation and mapping technology combined with a dynamic time warping algorithm. The main functions of the system are as follows: capturing camera stream data in real time, identifying and comparing action processes through a trained action detection model, and marking as abnormal if action missing, sequence error or redundant actions are detected. The method is suitable for industrial production, video monitoring, medical diagnosis and other scenes.

The invention relates to the technical field of human resource management, in particular to a labor dispatch outsourcing management and intelligent human dispatch outsourcing system, which comprises a process disassembly module, a condition check module, a capability construction module, a connection screening module and a dispatch adaptation module. According to the method, the post task is subjected to nodal sequence processing, digital expression of the post operation process is realized in combination with action labels and operation stage mapping, deviation nodes in the operation process are identified by means of device numbers and sorting verification of operation sections, and the task process precision and the quality control capability are improved; post boundary condition constraint verification is completed by fusing post equipment permission and an operation section period table, the probability of occurrence of task matching conflicts is remarkably reduced, and the coherence consistency of personnel and post actions is improved by comparing behavior tags with a post action sequence, so that accurate matching and efficient coherence deployment of tasks and personnel are realized, and the task matching efficiency is improved. And the intelligence, the matching degree and the performability of labor dispatching are enhanced.

The invention relates to the field of port energy management, and provides a bulk cargo wharf production operation process-based energy consumption prediction method and system, and the method comprises the steps: obtaining a cargo attribute information set and an equipment parameter set, and constructing a linkage database through context fusion, time sequence storage and data cleaning; based on a cargo attribute information set splitting process, performing verification and collaborative division in combination with an equipment archive and an operation emergency degree coefficient, and performing risk assessment according to theoretical and actual parking duration to generate a link list; according to the link list and the real-time working condition, a candidate device set or a compensation scheme is output in combination with the mapping table, a collaborative operation trigger signal is generated, and a device allocation list is generated through resource allocation when a collaborative scheme is started; constructing an initial energy consumption prediction model, and carrying out online iterative optimization; and calculating each operation link and a final energy consumption prediction result, and generating a final energy consumption prediction report. According to the method, dynamic planning of a collaborative operation process and adaptive prediction of energy consumption are realized, and the method is suitable for port smart energy management and automatic scheduling.

The invention provides an industrial operation area multi-view video collaborative analysis method and system based on artificial intelligence. The method comprises the following steps: firstly, acquiring multi-view video data; secondly, based on the working area and the equipment layout, deducing a semantic association relationship among the multi-view video data; according to the semantic association relationship, dynamically adjusting the analysis priority of the multi-view video data through an artificial intelligence model to determine an analysis priority sequence; and according to the determined analysis priority sequence, executing interactive co-processing of the multi-view video data, and finally generating a co-analysis result. According to the technical scheme provided by the invention, the physical layout and the workflow of the industrial site are converted into the semantic association relationship, and the dynamic scheduling analysis resources and the interactive collaborative analysis are performed according to the semantic association relationship, so that the spanning from simple monitoring of a plurality of isolated video streams to intelligent and coherent understanding of the whole operation flow is realized; and the intelligent level and decision support capability of monitoring analysis are improved.

The invention provides a dry bulk cargo port energy consumption key node identification method and system, and the method comprises the steps: collecting the energy consumption data of dry bulk cargo port loading and unloading equipment, and carrying out the multi-dimensional statistics and analysis, and obtaining the multi-dimensional energy consumption data; based on an unsupervised learning method, capturing high-energy-consumption nodes and low-energy-consumption nodes from the multi-dimensional energy consumption data; in combination with an equipment operation track and time information, a space-time law of energy consumption key nodes of the dry bulk port is excavated, the energy consumption key nodes are identified, and space-time evolution speculation is realized; an interactive digital twinborn platform is constructed based on a WebGL technology, and energy consumption distribution is presented in combination with a thermodynamic diagram; according to energy consumption key node information and port operation requirements, a loading and unloading operation strategy is made, an equipment scheduling scheme is optimized, energy conservation and operation efficiency are both considered, and intelligent scheduling decision making is achieved. Through multi-dimensional energy consumption data collection and analysis, unsupervised learning and space-time law mining are combined, the loading and unloading operation process is optimized, and the port operation efficiency and the energy-saving effect are improved.

The invention relates to the technical field of secondary equipment, in particular to a method, a device and equipment for generating a secondary operation ticket and a work ticket. The scheme comprises the following steps: acquiring substation data, and establishing a substation secondary operation library; basic data are analyzed from a secondary operation library of the transformer substation, and a correlation model is constructed through the basic data; an equipment maintenance list is formulated through the association model, so that a secondary operation ticket and a work ticket are generated; and obtaining operation records of the secondary operation ticket and the work ticket, and carrying out safety verification on the operation records. According to the generation method, the maintenance list and the operation order are automatically generated by establishing the secondary operation library and constructing the association model, a standardized operation process is realized in combination with a safety verification mechanism, and the generation method has the advantages of improving the operation order generation efficiency, reducing the safety risk and guaranteeing the maintenance normalization.

The invention provides an open pit coal mine safety management and control method and device, electronic equipment and a storage medium, and relates to the technical field of mine field safety protection. The position of a key person is obtained in real time, whether the key person enters a corresponding operation area or not is verified, associated video monitoring is automatically triggered according to the in-place state of the person, safety measure execution is verified through real-time mapping of a video stream and an operation process state, and early warning is conducted when the safety measure execution is abnormal. The problems that in the prior art, due to the fact that a'process-position-video 'triple closed-loop verification mechanism is not formed and multi-source data space-time alignment and dynamic verification are not achieved, the security measure execution rate is insufficient, supervision lags behind, positioning data staticization is caused, video coverage is not matched, approval information is delayed, and data errors exist can be solved.

On the basis of information indicated in a work log recorded for each execution of a work process flow that has been executed one or more times, a risk assessment unit (130) calculates, for each work process of the work process flow, at least one of a bottleneck index value, which is an index value regarding a bottleneck in the work process flow, an individual-dependency index value, which is an index value regarding the degree to which the work process depends on an individual, and a coordination degree index value, which is an index value regarding the coordination of workers, and calculates, for each work process of the work process flow, an evaluation value of the work process using the calculated at least one index value. A recommendation unit (140) presents a work process for which the use of a digital tool is recommended, on the basis of the evaluation value of each work process of the work process flow.

The invention relates to the technical field of digital twinning, in particular to a digital twinning management system and method applied to a petrochemical wharf, and the method comprises the steps: S1, collecting physical state parameters of a harbor district, a pipe district and a tank district in the petrochemical wharf in an operation process, constructing an asynchronous time sequence modeling network, and building a digital twinning mirror image body of the three-domain operation process, outputting a three-domain state evolution frame set; s2, generating a prediction evolution trajectory set through a dynamic compression time window and a prediction sliding evolution mechanism, and identifying evolution offset labels and linkage mismatch risk points among the three domains; and S3, combining the collected real-time state input, comparing a twinborn prediction trajectory set, triggering a difference feedback module, outputting a scheduling correction amount, reversely mapping a corrected action to a three-domain twinborn mirror image body, updating a twinborn evolution path, and forming a three-domain linkage prediction-control closed loop. According to the invention, the agility of three-domain cooperative scheduling and the steady-state operation capability of the whole system are improved.

The embodiment of the invention provides a voice dialogue job management method based on a large model, a program product, equipment and a medium, and relates to the technical field of artificial intelligence. In the outbound operation process of a user, the outbound record information of this time is input into a pre-established large model to obtain first outbound operation management information used for indicating next outbound operation or second outbound operation management information used for indicating ending of the outbound operation, and if the first outbound operation management information is obtained, the outbound record information of this time is input into the large model, and the outbound record information of this time is input into the large model. If the first outbound operation management information is obtained, next outbound operation is carried out on the user according to next outbound task information in the first outbound operation management information, and if the second outbound operation management information is obtained, the outbound operation on the user is ended. The large model is utilized to flexibly judge whether to carry out next call-out on the user or not and determine execution details of the next call-out task according to the call-out condition, so that the call-out operation process of the user is flexibly managed, and maximization of service benefits is facilitated.

The application provides a database sharding method, device and computer program product, the method comprising: obtaining a virtual account information table, the virtual account information table comprising customer information and virtual account attribute information; generating a plurality of intermediate table records according to the data of the virtual account information table, the intermediate table records comprising a type label of a job task of a batch job flow and a sharding value of the job task; obtaining the data of the virtual account information table corresponding to the sharding value of the job task of the intermediate table record, obtaining a sub-table of the virtual account information table corresponding to the intermediate table record, and determining the number of job shards corresponding to each sub-table according to the type label of the job task of the intermediate table record; and performing processing on each sub-table according to the corresponding job task by using threads of the number of job shards corresponding to each sub-table according to the flow of the batch job flow, and obtaining a processing result, thereby solving the problem of low distributed service processing efficiency caused by unbalanced data sharding of a database in the prior art.

A recording medium stores a program causing a computer to execute a process including: classifying, based on a processing content of each job in a job group which has an execution order defined in a job flow, the job group into a groups; and restarting, when an abnormality of a first job classified into a first group of the groups is detected, by referring to a memory that stores information which indicates a job in a head execution order in a group as a starting point from which the job flow is to be restarted, based on information which indicates a job in a head execution order in a second group as a starting point from which the job flow is to be restarted, and is associated with the first group, the job flow from the job in the head execution order in the second group as the starting point.

The invention discloses a subway map construction and assembly method based on dynamic configuration, and relates to the technical field of computer software. Comprising the following steps: configuring a metro map, and converting the metro map into a main process priority queue and a sub-process priority queue through a metro map construction method; assembling data into a main process priority queue and a sub-process priority queue according to a job historical record through a variant sliding window algorithm and a data assembling method; and pruning the main process priority queue and the sub-process priority queue through a dynamic jump type post pruning algorithm, and converting into a metro map of the target operation process. According to the method, metro map construction and assembly methods are packaged, metro map configuration is opened for users to use, the problem that a large number of codes need to be written for each operation process in diversified operation scenes is solved, the method supports dynamic adaptation to display requirements of different operation processes, meanwhile, the processing speed and the memory utilization efficiency are improved, and the user experience is improved. And high flexibility of configuration driving is realized.

The application relates to the technical field of artificial intelligence, and provides an interactive method, device, equipment, medium and program product of a customer service robot, the method comprising the following steps: determining a target operation process matched with a user demand indicated by a conversation context based on the conversation context; the conversation context is determined based on a user query to be replied and historical interaction data belonging to the same conversation as the user query; inputting process content corresponding to the conversation context and the target operation process into a node detection model to obtain a target process node to be executed output by the node detection model; the node detection model is used for determining a target process node most matched with the conversation context from a plurality of process nodes through semantic understanding capability; and generating reply information of the user query based on the target process node. The application solves the problem that a process execution is rigid and cannot adapt to user jump expression, realizes nonlinear and dynamic execution of an operation process, and further improves the interactive experience of the customer service robot.

A debugging system for software and hardware integration and a debugging method thereof belong to the technical field of Internet of Things, are used for solving the problems of long integration construction period and repeated debugging caused by software and hardware integration linear development, are arranged in parallel between hardware debugging and software online, and comprise an SCADA module and a PLC module, data interaction can be carried out between the two modules; the SCADA module receives the production data from the PLC module and transmits the received production data to a production management and control system to be debugged; the PLC module simulates the operation process of a production operation node through automatic programming and outputs corresponding production data for the SCADA module to collect, and simulation debugging of hardware and software needing to be integrated is achieved through data interaction of the two modules. The method is used for debugging and verifying the matching and coordination operation between the integrated software and hardware, the synchronous development of hardware debugging and hardware and software integrated debugging is realized, and the debugging period of intelligent factory construction is greatly shortened.

This invention relates to the field of equipment maintenance and scheduling technology, specifically to an equipment fault reporting and management system, comprising: a dependency identification and modeling module, a fault status analysis module, a task priority evaluation module, a work order scheduling generation module, and a resource scheduling execution module. In this invention, a multi-level dependency topology between equipment is constructed using a directed graph traversal algorithm; the triggering relationship between physical connections and work processes is quantitatively analyzed; a classification and labeling model is established using dynamic parameters such as performance degradation rate; scalar superposition calculation is used to fuse the influence range and dependency factors; a priority scoring matrix is ​​dynamically generated; and a sorting algorithm is used to optimize the task queue structure, forming a data-driven maintenance decision-making mechanism. This improves fault location accuracy, reduces response delays caused by manual intervention, avoids maintenance lags in critical node equipment, optimizes resource allocation efficiency, strengthens the synergy between fault handling and the production system, and supports the formulation of preventative maintenance strategies.

The invention discloses a new energy field operation full-process safety monitoring system and method fused with Internet of Things perception. The system comprises a perception layer, an edge layer and a cloud layer. The sensing layer, the edge layer and the cloud layer are in communication connection in sequence; the sensing layer comprises a personnel identification unit, a tool identification unit, an environment and meteorological monitoring unit and a video image identification unit; the edge layer comprises an edge controller, and the edge controller comprises a data access module, a risk scoring module, a four-state consistency interlocking module, a falling and weather composite linkage module and an interlocking execution module; the cloud layer comprises an operation process engine, a dynamic risk learning model, a digital twin tool management module, an isolation point intelligent confirmation module and a block chain evidence obtaining module. And synchronous sensing and dynamic interlocking control of personnel, tools, environments and operation processes are realized.

The present application relates to the technical field of industrial data security management, in particular to a drilling site safety operation process digitization management method and system, comprising the following steps: collecting sampling time, rotating speed, drilling pressure, standpipe pressure and writing in alignment, comparing drilling pressure with interval and checking rotating speed and pressure range, extracting difference value and checking change threshold value, writing in parallel determination label and sorting, counting abnormality and checking threshold value to generate management account book. In the present application, through the alignment and sequential writing of sampling time, rotating speed, drilling pressure, standpipe pressure, ticket number, shift and well section, discrete parameters form continuous operation link and the abnormal time and attribution are clear, combined with drilling pressure interval, rotating speed range and pressure range synchronous checking, the multi-parameter parallel constraint relationship is constructed, the composite abnormal positioning is realized, the adjacent difference value and continuous window verification are superimposed, the mutation and cumulative deviation can be identified, the interval mismatch and continuous change are determined in parallel and recorded by time, and the identification accuracy and management consistency are improved.

Methods and systems for facilitating selection of tools for one or more machine vision jobs are disclosed herein. An example method may be performed by one or more processors and includes displaying, via a display screen, an interactive graphical user interface (GUI) of an application, the application configured to generate job scripts for imaging devices to execute and the application operating in a job construction mode. The method also includes displaying an image within the GUI and detecting a selection of a portion of the image. The method further includes analyzing the portion of the image to determine a corresponding tool for processing the portion of the image and adding the corresponding tool to a job flow of the machine vision job.

The invention discloses a method for realizing data storage of law enforcement officers based on an off-line data storage technology, which is applied to a mobile operation terminal and comprises the following steps: S1, acquiring and submitting field data; s2, carrying out data localization processing based on a network state; s3, intelligent synchronization and combination of off-line data; and S4, scene data display. According to the method, the problems of data acquisition stagnation, poor safety, difficulty in synchronization and the like caused by network interruption in a complex operation environment are solved, so that the uninterrupted operation flow, safe and complete data and accurate and efficient background synchronization are ensured, and the operation flexibility and the intelligent level in a complex scene are improved.

The application discloses a kind of processing method and system of monitoring video data, main purpose is to solve the problem of low efficiency of existing monitoring video data processing. Including: obtaining the job task information of each monitoring object and the monitoring video data matched with the monitoring object;Determine the job object and the job flow node based on the job task information, and at least two groups of image data to be processed are intercepted from the monitoring video data according to the job object, the job flow node;According to the monitoring target in the preset monitoring sequence, the image data is extracted to obtain the target feature, the pointer in the preset monitoring sequence is sequentially polled to different monitoring targets and is directed;The monitoring state of the monitoring video data is obtained based on the target feature and the monitoring whitelist of the job task information, to determine the monitoring result based on the monitoring state.

The application discloses a reply text generation method and related products, and relates to the technical field of artificial intelligence. The application splices a target dialogue record and a plurality of job process names in a job process database according to a format specification of a first instruction template to generate a first instruction text; analyzes the first instruction text by using a large language model to obtain a target job process text; splices the target dialogue record and the target job process text according to a format specification of a second instruction template to generate a second instruction text; and analyzes the second instruction text by using the large language model to generate a reply text corresponding to the target dialogue record. Finally, a method with low development difficulty and good multiplicity in multiple scenarios is used to obtain a reply text that can solve user doubts, so that the reply text can efficiently answer user doubts and improve user satisfaction.

The invention discloses an automatic operation whole line comprehensive integrated control system, and relates to the technical field of automatic operation. The system comprises a maintenance station client, a server data center, a data supervision platform, a master station, a general control touch screen, a first slave station, a second slave station, a third slave station, a fourth slave station, a fifth slave station, unloading equipment, a cleaning center, an automatic loading and distributing machine, a spreading machine, a delivery machine, an I / O module and a coupler. A port of the main station is respectively communicated with ports of the maintenance station client, the server data center and the data supervision platform, and a port of the main station is communicated with a port of the master control touch screen. The equipment or time point with slow progress can be found in time, the enterprise can be helped to optimize the operation process, and the data security is improved by setting the array key.

The invention provides a job flow packet initialization method and system, electronic equipment and a computer program product, and the method comprises the steps: receiving a job flow packet initialization request comprising a target workshop identifier; obtaining workshop information and associated main assembly line configuration information based on the target workshop identifier; obtaining related node information based on the ID configured by the main pipeline, and converting a node name key value pair in the related node information into a node ID key value pair; creating a job flow packet based on the node ID key value pair, and storing the job flow packet into a database; and performing initialization processing on each node ID key value pair in the job flow packet by using a thread pool to obtain an initialized job flow packet. According to the method and the device, efficient and intelligent job flow packet initialization can be realized, batch processing of a plurality of service tasks is realized, the management efficiency and the collaboration of the job tasks are improved, and the data processing flow is optimized.

1. The name of the design product: graphical user interface for job flow control of electronic equipment. 2. The use of the design product: for an electronic device. 3. The design points of the design product: in the graphical user interface of the electronic device. 4. The picture or photo that best shows the design points: front view. 5. The use of the graphical user interface: the graphical user interface is a graphical user interface for job flow control, mainly used for interaction and display of template creation in job flow control. 6. The human-computer interaction mode of the graphical user interface: the front view is the main interface of template creation; after clicking "Template" in the upper left corner of the front view interface, the interface changes to state diagram 1, and the template creation pop-up window is displayed in the interface; after clicking "+add" in the template creation pop-up window, the interface changes to state diagram 2, and the layer creation pop-up window is displayed in the interface; after inputting the name and path of the layer to be created in the layer creation pop-up window and clicking "OK", the interface changes to state diagram 3, and the created layer is displayed in the template creation pop-up window; after clicking "History" in the layer creation pop-up window of state diagram 3, the interface changes to state diagram 4, and the version change of recipe and the corresponding time are displayed in the interface. The cross in each interface represents a character and / or a number.

The embodiment of the invention discloses an information determination method. The method comprises the following steps: determining a target grid structure corresponding to a to-be-monitored area; wherein the target grid structure represents different working areas in the to-be-monitored area and job flow information among the different working areas; after determining that the work of the to-be-monitored object of the to-be-monitored area is completed, determining the workload of each grid in the target grid structure; wherein the grids and the working area have a corresponding relation; and determining the workload of each to-be-monitored object based on the working time of the to-be-monitored object in each working area and the workload of each grid. The embodiment of the invention further discloses an information determination device and equipment and a computer storage medium.

The invention relates to a catenary equipment training system and a control method. Comprising a high-simulation hardware simulation module, an intelligent teacher machine management module, a multi-terminal student practical operation system module, a WebAPI data communication server module, an automatic evaluation system module, a central control and display system module and a data storage module in bidirectional data connection with the WebAPI data communication server module. According to the catenary equipment training system, 1: 1 high-simulation hardware is adopted to simulate a typical structure of a catenary, the operation process and mechanical feedback are truly restored, and the training immersion and the practical operation pertinence are improved; multi-terminal cooperative training is supported, multi-person and multi-project training can be carried out at the same time, and the training requirements of trainees of different levels are met in combination with switching of multiple practical training strategies; through the technical means of high-simulation hardware simulation, intelligent teacher management, multi-terminal collaborative practical operation, automatic evaluation, data visualization and the like, standardization, intelligence and safety of special repair training of the overhead line system are achieved, and the training efficiency and the talent training quality are improved.