46 results about "State graph" patented technology

The invention provides a data acquisition system. The data acquisition system comprises a classroom module, an acquisition module and a storage module, wherein the classroom module is used for acquiring the attendance information when a course starting command for a teacher is received, and sending the attendance information to the acquisition module, and is also used for acquiring the preset stored teaching content from the storage module, counting the information of teaching interaction and the information of students for interaction according to the teaching content, and then sending the counted information to the acquisition module; and the acquisition module is used for drawing the learning state graph for students and the explanation note for the graph according to the attendance information, the interaction information and the information of students for interaction sent from the classroom module. Teachers, students, parents and other users can timely and scientifically make corresponding training and guiding by referring to the learning state graph for students and the explanation note for the graph.

The invention discloses a method for graphically monitoring a running state of a transformer of a distribution network. The method comprises the following steps: displaying a real-time running state and data of a distribution transformer on a WEB window page in a graph manner after treating and calculating through a software system according to the running data of the monitored distribution transformer collected and sent back by an on-site measuring terminal device, wherein the graph shows the geographic information of the location of the distribution transformer and displays the current state of the distribution transformer with different colored blocks, and the colors of the colored blocks can directly reflect the high-low degree index of the load factor corresponding to the distribution transformer; and classifying and grading various distribution transformers according to the high-low degree index of the load factor and corresponding state color of each distribution transformer. By using the method, the running state of the transformer of the distribution network can be monitored in real time, so that the work loads of on-site inspection tour and long-time load measurement are greatly reduced, the hidden danger for the running of the distribution transformer is accurately and timely found out, a reforming plan can be made earlier, and the operation and maintenance levels of the device are improved.

The invention provides a vibration model establishment method applied to a fiber sensing system. The method comprises steps that a vibration signal is adjusted through a fiber vibrator into a fiber interference signal which is outputted, intensity and the period of the output signal are utilized in combination with the signal generation time and a signal generation distance, a signal state graph is established through taking a distance between the fiber position and a fiber start point as a first coordinate axis and the time as a second coordinate axis; signal state graphs under different conditions are acquired to carry out manual label marking for the data, the data information including manual marking labels and the signal state graphs is inputted to a convolutional neural network model to carry out image identification and CNN training, and a vibration model applied to the fiber sensing system is acquired; image identification and CNN training of the convolutional neural network model comprise two stages, including forward propagation and backward propagation. The method has advantages of high identification rate, good identification accuracy and strong identification capability.

The invention discloses a satellite-borne software test case generation method and device. The method comprises the steps: building a state machine model according to preset satellite-borne software demand information, and enabling the state machine model to employ a state machine graph to describe a state primitive and a transfer primitive of a function in a software system; converting the statemachine model into a directed graph, determining all path sets in the directed graph, and determining an executable path set from all path sets according to a preset path constraint condition; and determining an executable test path set from the executable path set according to a preset test case coverage strategy, and automatically generating a test case set according to the executable test pathset. According to the invention, the quality of the generated test case is improved.

The invention discloses a warehouse material in-out management method and system. The method comprises the steps of obtaining warehouse position information before material in-out and warehouse in anda warehouse position state graph under the warehouse position information; obtaining and verifying a material in-out and warehouse in identification code under the warehouse position information, anddisplaying a material picture of a to-be-in-out / warehouse; judging whether the to-be-in-out / warehouse material meets a preset condition or not; and if yes, uploading a material list of the to-be-in-out / warehouse material to update material inventory information. The purpose of accurately updating the material inventory information and the effective management of material in-out / warehouse are achieved.

The invention discloses a cutter state image classification method based on an edge mark graph neural network. The method comprises the steps that S1, a high-definition electronic measurement microscope is used for shooting a cutter abrasion image when a machine tool is shut down during machining; s2, normalization and other processing are carried out on the cutter abrasion image, the image is input into an edge mark graph neural network to extract features, then adjacent edges are established according to the existing features and initialized, a full connection graph is formed, and each edgerefers to the relation type of two nodes connected with the edge; and S3, after the graph initialization is completed, updating the node features and the edge features, further obtaining the final node category prediction from the finally updated edge features, and obtaining the category to which the test set sample belongs by using a weighted voting method in combination with the sample labels inthe training set and the prediction values of the connecting edges of the sample labels and the test sample. The method has the advantage that the wear state of the cutter can be well recognized under the condition of small sample images.

The embodiment of the invention provides a trajectory tracking control method and device, equipment and a storage medium. The method comprises the steps of obtaining a current state of a controlled object, and representing the current state by graph information; inputting the graph information into a preset graph neural network model, and determining a current optimal control sequence in combination with a preset target trajectory, wherein the preset graph neural network model is obtained after training based on a random trajectory data set, and the random trajectory data set comprises a random trajectory state graph and an output label. According to the embodiment of the invention, the graph neural network model is adopted to perform trajectory tracking control on the controlled object, so that the uncertainty of a motion model and a motion environment of the underwater controlled object can be overcome, and efficient and accurate trajectory tracking control on the controlled object is realized.

A system and method generate a graph lattice from exemplary images. At least one processor receives exemplary data graphs of the exemplary images and generates graph lattice nodes of size one from primitives. Until a termination condition is met, the at least one processor repeatedly: 1) generates candidate graph lattice nodes from accepted graph lattice nodes; 2) selects one or more candidate graph lattice nodes preferentially discriminating exemplary data graphs which are less discriminable than other exemplary data graphs using the accepted graph lattice nodes; and 3) promotes the selected graph lattice nodes to accepted status. The graph lattice is formed from the accepted graph lattice nodes and relations between the accepted graph lattice nodes.

The invention discloses an electric power information management system. The electric power information management system comprises a PC and a multi-port electric power information acquisition module, wherein the PC realizes communication through a LoRa wireless communication module; a data post-processing system is loaded in the PC. The system is composed of a data local storage module, a key data report generation module and an operation process visual playback module. The target electric power information data is stored into a local MySQL database by adopting a Mython MySQL toolkit. The key data report generation module can automatically complete analysis of target electric power information data, an analysis result and an electric power equipment working state graph line are filled into a prefabricated latex template together, and then a pdf report is compiled and generated through a latex compiler. The whole operation process of the power equipment can be visually reproduced, effective information can be quickly extracted, a report can be generated, and therefore the safety problem of the power equipment can be quickly found.

The invention discloses a network management system and network management method based on a geographic information system, and belongs to the technical field of the network management system. According to the system and the method, the problem of effectively monitoring each network device under a complex network environment and geographic condition needs to be solved. The technical scheme is that the network management system based on the geographic information system comprises a login and logout module, a system management module, a geographic information management module and a network information management module. The login and logout module is equipped with database configuration, user login and user logout functions. The system management module is equipped with affair management, working space information display and legend management functions. The geographic information management module is equipped with map browse, buffer area establishment, measurement and basic search functions. The network information management module is equipped with configuration management, port state monitoring and analysis, network performance and state graph analysis, fault diagnosis and alarm, safety management, billing management and network device management simplification functions.

The invention relates to a method for automatically identifying and correcting a touch screen. The method comprises the following step of comparing a difference between energy state graph spectrums formed by a front moment and a back moment on the touch screen with a preset threshold value to judge whether the preset threshold value is an interference value. Because the touch screen is automatically corrected by utilizing variation of the energy graph spectrums sensed by each scanning line, the method is simple and the automatic correction is not influenced even if initial environment of electrifying the touch screen changes.

The invention provides an IEC104 protocol vulnerability mining method based on protocol state graph traversing. The IEC104 protocol vulnerability mining method based on protocol state graph traversingcomprises the steps of: processing an obtained network data packet of target equipment into a de-weighted protocol base block; constructing a protocol state graph according to the de-weighted protocol base block; traversing the protocol state graph according to a pre-set rule, and generating at least one malformed data packet; and performing vulnerability testing on the at least one malformed data packet, and determining a script corresponding to the malformed data packet passing vulnerability testing as one vulnerability of the target equipment. According to the vulnerability mining method provided by the invention, vulnerability mining testing is carried out by taking state side RTU equipment as an object; security vulnerabilities in a power system and industrial control system equipment can be effectively discovered; when a test case is generated, a traversing path is relatively effective; the proportion of the generated effective test case is relatively high; and the execution time is reduced.

The invention provides a bearing early fault detection and diagnosis method and system based on singular value and graph theory feature fusion. The method comprises the steps of extracting a feature graph of an operation state of a mechanical bearing; detecting a bearing early fault; diagnosing a bearing fault; and learning fault types possibly occurring in an offline state, establishing a corresponding graph model set, classifying a feature graph and state graph set after a fault symptom point occurs, and diagnosing a type of a current fault state in real time. A symptom point at which the early fault occurs can be monitored and identified in real time online in a mechanical operation process, and moreover, the type of the fault can be detected timely. The method can be directly applied to related application of early fault detection and diagnosis of an industrial mechanical bearing.

The invention discloses a production line data preprocessing system which comprises a production line overall state reading module used for reading manufacturing process data information of to-be-machined products on a production line and working load data information of all processes on the production line; and an information preprocessing module is used for processing various types of data information input by the production line overall state reading module, establishing a production line scheduling scheme solution space state diagram and outputting the production line scheduling scheme solution space state diagram to the intelligent dispatching system. According to the invention, each process of a production line and a constraint relationship between the processes are utilized; a production line scheduling scheme solution space state graph of a directed acyclic graph structure is established; according to the technical scheme, searching can be carried out according to the product machining sequence, the solution space scale of the production line dispatching scheme is greatly reduced, a better basis is provided for finding a better production line dispatching scheme within reasonable time, and therefore the efficiency of the intelligent production line dispatching system is obviously improved. The invention further discloses a production line data preprocessing method.

The invention discloses a power system economic dispatching decision method, system and device and a medium, and the method comprises the steps: obtaining the first operation state data of a power system, and constructing a first operation state diagram according to the first operation state data; constructing a graph reinforcement learning model integrated with the graph convolutional neural network; according to a reward mechanism, training the graph reinforcement learning model by using the first operation state graph; and obtaining second operation state data of the power system, constructing a second operation state diagram according to the second operation state data, inputting the second operation state diagram into the trained diagram reinforcement learning model, and outputting an economic dispatching decision of the power system. According to the method, the operation state of the power system is converted into the graph data in the non-Euclidean space based on the graph theory, the graph convolutional network can effectively aggregate node data in the operation state graph, the graph neural network is introduced to be combined with reinforcement learning, a new economic dispatching decision scheme of the power system is formed, and the method can be widely applied to the power system.

The invention belongs to the field of data visualization analysis, and relates to a power consumption time sequence data visualization display method and system and a readable medium, and the method comprises the following steps: S1, generating a topological structure of a user in a power grid based on the historical power consumption of the user; S2, according to the topological structure, establishing a power consumption time sequence calculation model for reasonably distributing the power consumption of each user in each time period, and generating a total active power curve of the users after reasonable distribution; S3, obtaining reasonable electricity consumption of each user according to the total active power curve, and generating an operation state diagram and an electricity consumption and power comparison diagram of each user; and S4, displaying the running state diagram, the electricity consumption and the power comparison diagram, and reminding the user exceeding the electricity consumption according to the electricity consumption distribution result in the step S2. The power consumption of users in a power grid can be adjusted in advance, the probability of electric quantity instability and tripping is reduced, and meanwhile the electric energy consumption efficiency is improved.

The invention discloses a small target detection processing method for a railway cargo loading state image. The method comprises the following steps: cutting a large image by using mutually overlappedoverlay; introducing a small target annotation size variable in the process of cutting the large graph; cutting the large graph to obtain a small graph in which all original feature values are reserved; carrying out image recognition by using the maximum equal-ratio neuron number of the small image pixels; recording the change proportion and the change quantity of the weight parameters in the neural network training process; training the training data set by using a neural network structure to obtain a network weight, and completing network training; segmenting the large graph to obtain smalltarget recognition input data; carrying out small target recognition on the input data by using the network weight obtained in S6. According to the invention, image recognition is carried out on small images of all original feature values, so that small target features are prevented from being lost; and training the training data set by using a neural network structure to obtain a network weight,and carrying out small target recognition on the input data.

The invention provides a data recording method of a locomotive signal device based on a blockchain technology. The method includes a process including definition of a block data structure, configuration and connection of blockchain nodes, generation of block data, and recording of the data to a blockchain. After successful operation of the blockchain, all new block data can be browsed or historical block data can be inquired through a data full-node browser program of the locomotive signal device, and data content of data of the locomotive signal device is extracted through a block body and converted to a detailed state graph and a table mode of the locomotive signal device for display. The beneficial effects of the method are that the data of the locomotive signal device, generated by operation of a train, can be completely stored, the locomotive signal data is stored and recorded in a server of each railway administration in a blockchain mode, and the integrity and the security of the data can be guaranteed. No matter which line the train operates in, complete data records can be stored in each railway administration, data fragmentation and loss can be avoided, and the possibility that the data is tampered is fundamentally eliminated.

The invention provides a bearing early fault detection and diagnosis method and system based on singular value and graph theory feature fusion. The method comprises the steps of extracting a feature graph of an operation state of a mechanical bearing; detecting a bearing early fault; diagnosing a bearing fault; and learning fault types possibly occurring in an offline state, establishing a corresponding graph model set, classifying a feature graph and state graph set after a fault symptom point occurs, and diagnosing a type of a current fault state in real time. A symptom point at which the early fault occurs can be monitored and identified in real time online in a mechanical operation process, and moreover, the type of the fault can be detected timely. The method can be directly applied to related application of early fault detection and diagnosis of an industrial mechanical bearing.

The invention is adaptable to the technical field of automation of electronic design, and provides a method for algorithm transformation. The method includes converting a C-language program or flowchart of the C-language program into a state graph, simplifying the state graph to obtain the simplified state graph including control logic and arithmetic logic, separating the arithmetic logic from the simplified state graph, implementing the arithmetic logic through hardware and determining the implemented result as a data path, separating the control logic from the simplified state graph, implementing the control logic through hardware and determining the implemented result as a controller, and implementing the data path and the controller by hardware description language HDL. Since the C-language is converted into the state graph to construct the data path and the controller which are implemented by the HDL, poor universality in conversion from the C-language to the HDL hardware implementation is overcome.

The invention discloses a power distribution system test method and device, and aims to improve power distribution system test accuracy; the method comprises the following steps: building corresponding relations between a first area and a second area and power distribution equipment according to the first and second areas and an input power distribution equipment ID selected from a first running state graph of the power distribution system, wherein the first area displays running parameters of the power distribution equipment, and the second areas displays the running state of the power distribution equipment; setting the running parameters and / or running states of the power distribution equipment corresponding to the first and second areas, and obtaining a second running state graph of the power distribution system after the setting; determining whether the power distribution equipment correctly responses to the setting or not according to running parameters displayed in the first area of the first and second running state graphs and the running states displayed in the second area of the first and second running state graphs.

The invention discloses a finite-element-based computer numerical control bender frame analysis method, comprising the steps of S1, establishing an ideal state three-dimensional model for a computer numerical control bender frame; S2, meshing by a C3D4 mesh unit; S3, simulating on finite element analysis software, fixation-connection relational constraints of the frame on a computer numerical control bender, and setting frame local stress constraints; S4 to S8, performing cycle simulation and calculation on frame deformation; S9, comparing stressed part size in the first cycle to the size in ideal state; S10, exporting a comparison state graph and details of a table; S11 determining frame rigidity and strength limits, well as frame deformation according the table. The analysis method employs finite element analysis software to directly calculate bending and shearing tolerance rigidity and strength and deformation quantities of the computer numerical control frame at different positions, design efficiency of the frame is improved, the test stage time and cost are saved, and the design period is shortened.

The invention discloses a vector diagram display method based on an embedded human-computer interface. The method comprises the steps: loading a preset PVG graph, extracting the text information of the PVG graph, and caching all state graphs contained in the PVG graph, wherein the preset PVG graph comprises a plurality of state graphs of preset parts; according to the running state of the current equipment and the display condition information of the state graph, selecting the corresponding state graph and the text information to be drawn and displayed; receiving an operation request of a user, executing the operation request, correspondingly changing the equipment state, and according to the changed equipment state and the display condition information of the state graph, selecting the state graph and the text information corresponding to the current state of the equipment from the cache to be drawn and displayed. According to the invention, a large number of system resources are saved; and the SVG dynamic library does not need to be installed, so that the storage space of the equipment is greatly saved.

The invention relates to the technical field of software development, and discloses a software rapid programming method based on a state machine, which comprises the following steps of: constructing aresource (Res) consisting of a state graph set and an interface set; creating a graphtop instance of the graph, and initializing a point start and a point end to be in an inactive state; and creatinga state graph according to a state graph relationship specified by the resource (Res), and initializing all state points (point) to be in an inactive state. The method has the advantages that the state graph and the state point are constructed, the state value is obtained by activating the state point, and the code block is called according to the state value screened by the state point, so thata software programming mode can be effectively simplified, and a programming problem is successfully converted into a drawing problem. Therefore, a user does not need to face a large number of codes during development, and software programming can be completed only by creating several state graphs and filling several attributes and a small number of code blocks.

The present invention discloses an internal memory monitoring method. Said method includes the following steps: when said method is used, firstly, obtaining address parameter of monitored embedded system, then obtaining internal memory application information of the described monitored embedded system according to the described address parameter; then real-tim updating the obtained internal memory application information; finally placing the updated internal memory application information into historical data and utilizing the described historical data to form internal memory application state diagram.

The invention discloses an optical-communication-based traffic guidance method and apparatus. The traffic guidance method comprises: traffic data of a traffic light in a predetermined area are obtained; according to the traffic data, a traffic jam state graph in the predetermined area is generated; light scintillation coding is carried out on the traffic jam state graph and a coded optical signal is sent by the traffic light; and according to the optical signal sent by the traffic light, the traffic jam state graph is displayed on a traffic guidance display screen. With utilization of the characteristic of the small range of the visible light communication and the light suspension characteristic of the traffic light, the traffic jam state graph is coded into an optical signal and then the signal is sent by the traffic light, so that the sending pertinence is high and the reference value for the driver is high.

The invention belongs to the field of graph data intersection calculation, and proposes a privacy-protecting graph data intersection calculation method. The graph data intersection calculation is completed between the two entities, and the privacy of the graph data of both parties is protected during the calculation process; the Paillier encryption system is used in the protocol to realize homomorphic addition and homomorphic multiplication on the ciphertext; the protocol has high computational efficiency and less information leakage. The present invention can safely outsource its dense state graph structure to an untrusted cloud server without losing the ability to query it. You can make full use of the storage services provided by the cloud server, and at the same time safely hand over the query operation to the server for execution, which can ensure that the server cannot obtain effective information as much as possible during the interaction process.

The present invention is a data graph detection method for malicious data attacks in industrial control systems. The method first needs to be trained in a certain normal industrial control system to generate the relationship graph of the data in the industrial system and the status graph G at running time. The method is to generate a runtime state graph G' for the detected industrial control system of the same type. If the nodes or directed edges of the state graph G' do not exist in the state graph G, it can be judged when there is a malicious data attack. Compared with the existing intrusion detection technology, this invention does not belong to feature and behavior detection, does not need to establish feature codes, and does not need to filter data packets. It can judge the moment when malicious data attacks occur only by relying on the data relationship in the monitoring room. It has the advantage of not affecting the real-time performance of the industrial control system.

An intermodal transportation system, which obtains transportation plans that meet customer demand information through an input interface, a virtual network state diagram storage unit, a Dijkstra algorithm operation module, and a DFS algorithm operation module, and provides multiple transportation plans that meet the needs through an output interface. Provide customers with choices, and then, through the reservation interface, according to the transportation plan selected by the user, combine with multiple logistics platforms to reserve the journey of the corresponding time period. Therefore, the present invention can realize the comprehensive transportation plan planning of "five-in-one" of sea, land, air, iron and pipeline. The invention can integrate the advantages of various transportation modes, combine advantages, form a coherent transportation system, further shorten freight turnover time, simplify intermediate procedures, reduce logistics costs, and finally achieve the level of transportation standardization and rationalization.