2835results about How to "Easy to understand" patented technology

The invention discloses an intelligent tooling for paving a photovoltaic module and a control method thereof, the method is suitable for a robot end effector, and the method comprises the following steps: collecting three-dimensional space point cloud data of the photovoltaic module to generate pose information of the photovoltaic module, and controlling the end effector to carry out adaptive pose adjustment according to the pose information; the tooling is controlled to press down, and after it is judged that fitting is in place by monitoring the compression stroke of the suction cup, a vacuum adsorption instruction is started; the adsorption state is judged based on vacuum pressure change curve parallel monitoring and a dynamic balance algorithm, and a carrying permission signal is generated after a preset adsorption success condition is met; continuously carrying out anomaly detection in the carrying process, and if an anomaly is found, triggering a fault processing strategy; and releasing the negative pressure to place the photovoltaic module after the target position is reached, and rechecking the placement pose. Intelligent and self-adaptive picking and placing of the photovoltaic module by the tooling are realized, and the reliability, the safety and the automation level in the carrying process are improved.

The invention discloses a shale oil geological engineering dessert evaluation method and device based on geological modeling, and the method comprises the steps: determining a shale oil facies classification scheme and shale oil dessert evaluation key parameter values according to the shale oil geological engineering logging interpretation data, determining the corresponding scores of different shale rocks, and obtaining the shale oil dessert evaluation key parameter values of the shale oil facies classification scheme and the shale oil dessert evaluation key parameter values of the shale oil facies classification scheme; and determining a target sweet spot evaluation parameter weight based on sweet spot evaluation attributes of the lithofacies three-dimensional model and actual well drilling productivity data, establishing a shale oil geological engineering integrated comprehensive sweet spot factor, and determining a shale oil geological engineering comprehensive sweet spot evaluation result based on the sweet spot factor and the target sweet spot evaluation parameter value. Through the technical scheme of the embodiment of the invention, comprehensive evaluation of shale oil geological engineering desserts is realized, complexity of shale oil geological features can be adapted, correlation between geological and engineering dessert evaluation parameters is improved, and fine evaluation of shale oil dessert space distribution is ensured.

The invention discloses an automatic compiling method and device for a test case, electronic equipment and a storage medium, and relates to the technical field of computers, and the method comprises the steps: carrying out the structural analysis of a demand document for creative and creative transformation, and extracting the demand information of the demand document; the code warehouse is connected to obtain the source code and performs static analysis to generate code logic; establishing a semantic association mapping table of the demand information and the code logic, generating a test scene library according to the semantic association mapping table, and automatically generating a test case according to the parameter type and the constraint rule; and performing multi-dimensional verification on the generated test case to generate a verification result, and adjusting the priority of the test case according to the verification result. The method has the technical effects of improving marginal scene coverage depth and breadth, improving test case writing efficiency and accuracy, reducing manual dependence, and optimizing test case quality and execution pertinence.

The invention provides a multi-process-mode intelligent switching method and system for vehicle-mounted sludge treatment, and the method comprises the steps: carrying out the time-space alignment and standardization of multi-dimensional sensing data such as sludge characteristics, environmental parameters and equipment states, carrying out the real-time reasoning of a process switching critical value through combining with a lightweight incremental regression model, generating a self-adaptive threshold value band with a confidence interval, and carrying out the real-time reasoning of the process switching critical value. Dynamic monitoring and mode switching pre-judgment of actual operation parameters are realized; in the switching process, a weighted fusion progressive transition control strategy is adopted, the transfer rate is adaptively adjusted according to real-time feedback, the operation stability is guaranteed, and the intelligence, reliability and switching smoothness of process switching of the vehicle-mounted sludge treatment system are remarkably improved.

The invention relates to the technical field of risk early warning, and provides an operation risk early warning method, device and system for substation operation and maintenance personnel and a medium. According to the implementation scheme, the method comprises the steps of training a behavior recognition model based on multi-modal historical data to obtain a target recognition model; based on the current operation data of the operation and maintenance personnel, performing risk identification on the current operation behavior represented by the current operation data through a target identification model to obtain an identification result; if the identification result is that the current operation behavior belongs to the dangerous behavior, triggering a multi-dimensional risk assessment mechanism to perform risk assessment on the current operation behavior to obtain a risk assessment result; and generating risk early warning information based on the risk assessment result. According to the embodiment of the invention, the intelligent early warning of the operation risk of the operation and maintenance personnel of the transformer substation can be realized, and the safety guarantee level of the operation and maintenance personnel during operation is improved.

The embodiment of the invention discloses a malignant load identification method, device and equipment, a medium and a program product, and relates to the technical field of power load monitoring. The method comprises the following steps: performing modal decomposition on an original power utilization sequential sequence to obtain a plurality of intrinsic mode components, and reconstructing intrinsic mode components which do not belong to noise components to obtain a target power utilization sequential sequence; performing feature extraction on the target power consumption time sequence to obtain target power consumption features, and inputting the target power consumption features into a pre-trained malignant load identification model for identification to obtain an identification result; the malignant load identification model is obtained by updating model parameters of a weak learner based on a natural gradient descent method and performing training optimization. The lightweight malignant load learning model obtained through training in the scheme can be deployed and operated on the intelligent electric meter, high-quality input features are obtained through multi-mode decomposition and reconstruction, the accuracy of malignant load recognition is improved, and accurate recognition of the malignant load based on the lightweight model is achieved.

The embodiment of the invention discloses a process template generation method and device, electronic equipment and a storage medium. The method comprises the steps of obtaining a process generation demand of a user, and determining structured process logic description information based on the process generation demand, a preset process design cue word and a preset large language model; generating cue words and a preset large language model based on the process logic description information, a preset process template, and determining a first process template required by the user; performing rule verification on the first process template based on a preset verification plug-in, and determining a verification result; and if the verification result is that the verification is not passed, adjusting the first process template by utilizing a preset large language model, and determining a second process template required by the user. Through the technical scheme of the embodiment of the invention, the executable process template can be directly generated according to the demand described by the natural language, the node attribute and the logic relationship do not need to be manually configured, and the generality, the efficiency and the accuracy of the process template generation are improved.

The invention discloses an extractor hood and a control method and a control device thereof.The extractor hood comprises at least two independently-lifting smoke gathering cavities, and the control method comprises the steps that a neural network model is adopted, and based on first video information, first image information and oil smoke concentration information of a target cooking area, the first video information and the first image information are obtained; determining cookware size information, cookware type information, cooking temperature information, concentration standard exceeding information and cooking fume movement information; the lampblack movement information comprises lampblack speed information and lampblack direction information; according to the pot type information, the cooking temperature information, the concentration standard exceeding information and the oil smoke speed information, the suction demand level of the target cooking area is determined; according to the suction demand level and the cookware size information, the target height of a smoke gathering cavity corresponding to the target cooking area is determined, and the smoke gathering cavity is controlled to descend to the target height from the initial position. According to the technical scheme, the oil smoke suction efficiency of the range hood in a complex cooking scene can be improved, and the use experience of a user is improved.

The embodiment of the invention provides a single-bus communication method and device, a chip and a medium, and the method comprises the steps: enabling a host to enter an initialization mode after the host confirms that an internal power supply and a clock of a slave are stable; the host sends a wake-up code to the slave within a set time to wake up the slave, and releases the bus to enter a normal communication mode; the host sends a communication signal to the slave through the improved communication frame; after the host receives a response signal of the slave, the host releases the bus, the bus is pulled to a high level from an external pull-up resistor, and the transmission is ended; wherein the format of the improved communication frame comprises ten codes, one code corresponds to one bit, and the ten codes sequentially comprise one start bit, six address bits, one read-write control bit, one data bit and one response bit. A wake-up code is set before communication between the host and the slave, so that the slave is prevented from being mistakenly waken up. According to the communication mode, the coding mode is simplified, the chip area is reduced, and the transmission speed of the chip is also improved.

The invention discloses a pipeline defect positioning method, device and equipment, a medium and a product. An SPPF-LSKA optimization instance segmentation model is combined with an ORB-SLAN3 framework, and dynamic feature points are eliminated by using information of an RGB-D depth map and an instance segmentation mask; secondly, a sliding window confidence evaluation mechanism is introduced, the credibility of feature points can be dynamically evaluated, wrong feature points generated due to instantaneous false detection are removed in time, and high-precision dynamic point removal is achieved; and finally, in a back-end optimization stage, a double-layer map strategy is adopted, a static mapping layer participates in BA optimization to reduce a positioning error, and a dynamic observation layer independently records an optical flow speed and a segmentation result of a dynamic region for dynamic interference analysis and does not participate in global optimization, so that interference of dynamic factors on positioning precision is avoided.

The invention discloses an image transmission method, device and equipment of a remote operation system and a medium, the method is applied to a local operation end, the remote operation system comprises the local operation end and a remote operation end, and the method comprises the following steps: acquiring an initial ultrasonic image corresponding to a target object at the local operation end, performing feature extraction on the initial ultrasonic image to obtain a target ultrasonic image; determining an ultrasonic sub-image corresponding to the target ultrasonic image based on the knowledge graph, and determining an image value of the ultrasonic sub-image according to the ultrasonic image evaluation dimension; and transmitting the ultrasonic sub-image to a remote operation end according to the image value. Based on the technical scheme, the image is divided into the sub-images of different areas, the image values of the sub-images are determined, and the transmission methods corresponding to the sub-images are determined according to the image values, so that the preferential transmission of the high-value image is ensured, the overall bandwidth occupation and the system load are reduced, and the transmission efficiency is improved. And a key technical support is provided for the accuracy and safety of a remote operation.

The embodiment of the invention provides a client verification method and device and electronic equipment, and relates to the technical field of clients, and the method comprises the steps: obtaining a hardware fingerprint of a user terminal in real time under the condition that a verification probe is utilized to monitor a verification trigger event in the operation process of a client; under the condition that the verification trigger event is the first verification trigger event, obtaining a client identifier of the client; sending the hardware fingerprint of the user terminal and the client identifier of the client to a server, so that the server queries a historical binding fingerprint corresponding to the client based on the client identifier of the client, and verifies the hardware fingerprint of the user terminal based on the historical binding fingerprint of the client to obtain a first verification result; and receiving a first verification result fed back by the server. Therefore, the credibility requirements of various scenes on the client can be effectively met.

The invention provides an opencast coal mine data fusion method and device, electronic equipment and a storage medium, relates to the technical field of data processing, and realizes automatic access and integration of geological information, measurement data, mining parameters and safety monitoring data by constructing a unified data interaction platform and configuring a standardized interface protocol. Meanwhile, a three-dimensional real-scene model is generated based on automatic processing of field data collected by an unmanned aerial vehicle and a laser radar, loading and rendering are carried out in the platform, incremental updating is carried out on the three-dimensional real-scene model of a mining area by adopting a dynamic updating mechanism in combination with mine production real-time data, and volume change calculation is carried out based on the updated model; in addition, a cross-professional data association model is established by using an intelligent collaborative decision engine, and linkage analysis is performed according to the three-dimensional live-action model updated in real time and the safety monitoring data to generate risk behavior early warning information and output a mining plan dynamic optimization scheme, so that the problem of low data circulation efficiency in the prior art can be solved.

The invention discloses a method for constructing a three-dimensional digital core model of irregular concave-convex particles, and the method comprises the following steps: S1, generating regular small balls with the same radius distribution based on the radius distribution and shape characteristics of actual rock particles; s2, constructing a single particle with an irregular concave-convex shape based on a single regular small ball; s3, by setting modeling parameters of different regular small balls, on the basis of a construction method of a single particle with an irregular concave-convex shape, constructing a plurality of irregular concave-convex particles by the regular small balls with different sizes; and S4, simulating deposition and compaction diagenesis processes of a plurality of irregular concave-convex particles in a three-dimensional space to obtain digital core models with different pore structures. The modeling principle and process have the advantages of being easy to understand, controllable in concave-convex shape, diverse in result and the like, and a model foundation is laid for oil and gas reservoir rock physical analysis and modeling work.

The utility model relates to a garbage compression station which comprises a lifting mechanism arranged in a pit. The garbage can is arranged on the lifting mechanism, a feeding port is formed in the garbage can, and the lifting mechanism is used for driving the garbage can to ascend and descend up and down; the feeding opening is formed in the upper portion of the feeding opening, and the discharging opening is used for being in butt joint with the feeding opening; the feeding device comprises a feeding opening, a swing mechanism arranged on the side close to the feeding opening, and a feeding mechanism arranged on the swing mechanism and connected with the swing mechanism, and the swing mechanism is used for swinging the feeding mechanism so as to swing the feeding mechanism to be close to or away from the feeding opening. The feeding mechanism is used for turning over the garbage can so that garbage in the garbage can can be poured into the discharging opening. According to the garbage compression station, a new garbage feeding mode is added, and two feeding modes are achieved.

The invention discloses a compiling method for compiling a C language source code into an RISC-V assembly code. The method comprises the following steps: acquiring a C language source code; performing lexical analysis on the C language source code to generate a mark flow; performing syntactic analysis on the mark flow, and constructing an abstract syntax tree; performing semantic analysis on the abstract syntax tree to generate a target abstract syntax tree; constructing a runtime environment of the RISC-V assembly code; generating an intermediate code and a control flow diagram corresponding to the intermediate code according to a rule in the runtime environment and the target abstract syntax tree; generating a target code by using the intermediate code and the control flow diagram corresponding to the intermediate code; according to the technical scheme, the intermediate representation more adaptive to RISC-V custom instruction mapping can be generated, so that the execution efficiency of assembly codes is improved; and meanwhile, by designing a lightweight runtime environment, the performance overhead is further reduced.

The invention provides a scanning electron microscope objective lens system and a detection method, and relates to the technical field of scanning electron microscopes. The magnetic lens device is used for focusing an incident electron beam; the deflection device, the anastigmator, the Wien analyzer group and the detection device are all located in an accommodating space in the magnetic lens device; the deflection device, the anastigmator and the Wien analyzer group are arranged along the optical axis of the incident electron beam and are arranged around the optical axis; the deflection device and the anastigmator are respectively used for adjusting the movement direction and shape of the incident electron beam so as to scan a to-be-tested sample through the incident electron beam, so that the to-be-tested sample generates signal electrons; the Wien analyzer group is used for adjusting the movement direction of the signal electrons to enable the signal electrons to enter the detection device; the detection device is located on the side, close to the magnetic lens device, of the deflection device, the anastigmator and the Wien analyzer set and used for generating a detection signal according to the signal electrons and achieving surface imaging of the to-be-detected sample. The imaging precision and the detection efficiency of the objective lens system are improved.

The embodiment of the invention provides a multi-modal data retrieval method and device, equipment, a medium and a product, and the method comprises the steps: obtaining a natural language problem of a user, carrying out the intention understanding of the natural language problem, and obtaining the query intention of the natural language problem; performing retrieval path selection on the query intention, and determining at least one target modal type matched with the natural language question; the natural language question is distributed to vector databases corresponding to the target modal type to be retrieved, and candidate multi-modal retrieval results of the natural language question are obtained; and verifying the candidate multi-modal retrieval result according to a pre-constructed multi-modal business knowledge graph to obtain a target multi-modal retrieval result of the natural language problem. By utilizing the method, a collaborative mechanism of semantic comprehension, routing decision and knowledge enhancement is introduced, so that the cross-modal semantic comprehension capability and the information retrieval performance are remarkably improved.

The invention discloses a sedimentary facies model construction method and device, equipment and a storage medium. The method comprises the following steps: acquiring regional geological parameters of a target construction region; and determining structure interpretation data according to the regional geological parameters, and constructing a three-dimensional structure model according to the structure interpretation data. And analyzing distribution information of each lithofacies in the three-dimensional structure model according to regional logging data, and constructing a lithofacies framework model. A target sedimentary facies model corresponding to the target construction area is constructed according to the three-dimensional sedimentary point cloud and the lithofacies framework model based on a multi-point geostatistics algorithm, and the three-dimensional sedimentary point cloud is obtained by performing actual sedimentary simulation on the target sedimentary construction model obtained through pre-training based on the area geological parameters of the target construction area. According to the technical scheme, the three-dimensional sedimentary point cloud of the research area can be accurately extracted, high geological objectivity and physical authenticity are achieved, and therefore the objectivity and geological reliability of the sedimentary facies model are remarkably improved.

The invention provides an electrical stimulation and lower limb exoskeleton device fusion control method and system, and the method comprises the steps: driving an exoskeleton to move through bottom admittance control based on the actual human-computer interaction torque and expected torque of a knee joint and reference trajectory data of the knee joint in a gait cycle, and triggering ankle joint electrical stimulation through a fixed stimulation parameter group; after the gait cycle is finished, torque errors are calculated, and periodic iteration updating is conducted on the knee joint reference trajectory data through an iterative learning control algorithm till convergence is conducted to obtain target knee joint reference trajectory data; and then determining a target moment of a gait phase based on the target knee joint reference trajectory data, and obtaining a corresponding target stimulation parameter group from the set stimulation parameter time mapping library to replace the fixed stimulation parameter group for subsequent stimulation. According to the method, through single-cycle and cross-cycle trajectory iteration, the adaptation defect of a traditional fixed trajectory is avoided, the stimulation parameters are synchronously optimized, and the dorsiflexion assisting effect is indirectly improved.

This invention provides a novel GABA structure with better efficacy, reduced side effects, and greater safety for clinical use. A This invention relates to receptor agonists, specifically a phenol derivative, its preparation method, and its use in the central nervous system. The phenol derivative provided by this invention offers more and better drug options for inducing or maintaining anesthesia in animals or humans, promoting sedation and hypnosis, and treating and / or preventing anxiety, nausea, vomiting, migraines, seizures, epilepsy, neurodegenerative diseases, and other central nervous system-related disorders.

The embodiment of the invention discloses a task execution method and system. The method comprises the following steps: in response to a to-be-executed artificial intelligence task, identifying task features of the artificial intelligence task, and obtaining a first resource portrait of a general computing domain and a second resource portrait of an intelligent computing domain in a hybrid cloud environment; determining a first matching degree between the task feature and the first resource portrait, and determining a second matching degree between the task feature and the second resource portrait; and according to a numerical relationship between the first matching degree and the second matching degree, determining a target computing domain from the general computing domain and the intelligent computing domain, and allocating the artificial intelligence task to the target computing domain, so that the target computing domain is utilized to execute the artificial intelligence task. According to the technical scheme provided by the embodiment of the invention, the optimal balance between the cost and the performance can be realized.

The invention relates to the field of equipment diagnosis, and discloses a submersible fault time sequence causal chain diagnosis method and system, and the method comprises the steps: obtaining multi-dimensional operation monitoring data in the operation process of a submersible; performing exception association analysis on the multi-dimensional operation monitoring data to obtain a cross-dimensional collaborative exception coefficient of an association unit group under each monitoring dimension; performing threshold comparison on all the cross-dimension collaborative anomaly coefficients, and determining each anomaly association unit group; and determining a diagnosis dimension trigger signal of the submersible according to the number of the abnormal association unit groups and the evolution characteristics of the cross-dimension collaborative abnormal coefficients of all the abnormal association unit groups. And a diagnosis dimension trigger signal is dynamically generated through the change and evolution characteristics of the cross-dimension collaborative abnormal coefficient, so that fault diagnosis scheduling of the submersible is triggered, and the response mechanism ensures the flexibility and adaptability in the diagnosis process.

The invention provides a data analysis system and method for evaluating a data center cold water link state, and belongs to the technical field of data center infrastructure intelligent operation and maintenance. According to the system, multi-source operation data of a cold machine, a water pump, a tail end air conditioner and a cabinet monitoring system in a cold water link are collected, and a dynamic threshold pool is constructed after working condition layering preprocessing so as to identify equipment abnormity; the method comprises the following steps: establishing a directed graph model based on a chilled water system topological structure, constructing a Bayesian network by fusing process logic, and reversely calculating a root cause posterior probability of each device when a cabinet hotspot event occurs; and generating an influence weight ranking list by integrating the abnormal strength of the equipment, the root cause probability, the topological key coefficient and the redundancy weakening coefficient, and further performing quantitative scoring and state grading on the overall availability of the cold water link. According to the method, working condition self-adaptive anomaly detection, robust root cause positioning and executable operation and maintenance priority ranking of the cold water link are realized, and the operation and maintenance efficiency and reliability of the refrigeration system of the data center are improved.

The embodiment of the invention discloses a data query method and device, electronic equipment, a storage medium and a program. The method comprises the steps of obtaining a query statement input by a target user, and determining a query intention of the target user according to the query statement input by the target user; determining target hierarchical storage associated data from the hierarchical storage associated data of the target database according to the query intention of the target user; wherein the hierarchical storage associated data comprises at least one of message-level storage data, theme-level storage data and a dialogue flow graph; performing hierarchical retrieval on the target hierarchical storage associated data according to the query intention of the target user to obtain an associated query result of the query statement; and screening and adjusting the associated query result according to the query intention of the target user to generate a target query result of the target user. According to the technical scheme provided by the embodiment of the invention, hierarchical retrieval under different data granularity levels can be realized, so that the data query precision and efficiency are improved.

The present invention relates to a connector. The connector comprises: a board end connection portion which is to be mated with a wire end connection portion; the wire end connection portion which is provided with a plurality of mating cavities for mating a plurality of wire harness terminals and a retreat-stop member coupling structure; the plurality of wire harness terminals; and a retreat-stop member which is configured to allow the wire harness terminals to be fixed in the mating cavities of the wire end connection portion when the retreat-stop member coupling structure is in a first coupling state, and to allow the wire harness terminals and the wire end connection portion to be detachable when the retreat-stop member coupling structure is in a second coupling state.

The disclosure provides a large model-based quality inspection method, device, equipment, storage medium and program, relating to the technical field of data processing, specifically relating to artificial intelligence, deep learning and large language model technology, which can be applied in the field of AI medical technology, wherein the method comprises: obtaining to-be-inspected data of a target platform and a target quality inspection prompt template; wherein the target quality inspection prompt template comprises quality inspection task instructions and quality inspection question classification content; splicing the to-be-inspected data and the target quality inspection prompt template to obtain a target quality inspection prompt; inputting the target quality inspection prompt into a target large model to automatically inspect the to-be-inspected data according to the target quality inspection prompt through the target large model, and obtaining first quality inspection data. The embodiment of the disclosure can reduce the artificial quality inspection cost of platform quality inspection and improve the efficiency and accuracy of platform quality inspection.

The utility model discloses a display panel and display device, display panel includes substrate, color filter layer, transparent optical adhesive layer, pixel definition layer and cathode layer, pixel definition layer is located the one side of transparent optical adhesive layer away from substrate, wherein, transparent optical adhesive layer sets up first recess, pixel definition layer includes first definition branch, and cathode includes first cathode branch, along first direction, first recess, first definition branch and first cathode branch three project interlaced, and all with the non opening area projection interlaced of pixel definition layer, part first definition branch is located in first recess, forms first recess, part first cathode branch is located in first recess and forms reflecting electrode. Through setting up first recess in transparent optical adhesive layer, make corresponding first definition branch form first recess, and then make the first cathode branch of being located in first recess form reflecting electrode, utilize reflecting electrode and solve the light leakage problem between adjacent subpixels, improve display effect.

The application discloses an autonomous action prediction method based on a sequential space-time domain brain and muscle electric signal, first, a space-time graph network matrix is constructed, space-time data mapping is performed on the collected brain and muscle electric signal of a patient, and the signal is converted into a graph network matrix corresponding to a plurality of continuous time frames in a data window division manner; then, a graph network matrix of a future signal is predicted, the graph matrix data of the plurality of continuous time frames are sent into a graph convolutional neural network for analysis, and space-time data prediction is performed on the graph matrix corresponding to the future time frames; finally, target action recognition is performed, the predicted plurality of time frame graph matrices are subjected to pattern recognition through the graph convolutional neural network containing a plurality of full connection layers, the action corresponding to the signal is analyzed, and the corresponding action of a control auxiliary device is output in advance. The relatively high explainability of the algorithm can help popularize and apply the algorithm in the rehabilitation medical field, thereby helping more stroke patients.

The application relates to the field of metal support polishing, in particular to an automatic polishing tool and polishing method for a metal support, the tool comprising a base, a rotating shaft, a motor, clamping members and a conductive wire, the rotating shaft being arranged on the base and capable of rotating relative to the base around a rotating shaft axis parallel to the vertical direction, the rotating shaft axis coinciding with the central axis of the rotating shaft; the two clamping members are sequentially arranged on the rotating shaft along the vertical direction and are relatively fixed with the rotating shaft; the conductive wire is used for clamping between the two clamping members, and in the clamping state, the part of the conductive wire between the two clamping members is arranged in parallel to the rotating shaft and is spaced apart from the rotating shaft in the radial direction of the rotating shaft; the application can reduce the consumption of polishing liquid and reduce the damage to the metal support.