1147 results about "System maintenance" patented technology

The invention discloses a smart home energy management optimization method in an Internet of Things environment. According to the method, the Internet of Things technology is utilized, intelligent identification and classified management are carried out on equipment, multiple energy management strategies are preset, and a user can conveniently and autonomously adjust; energy data is monitored in real time through a sensor and an intelligent electric meter, an energy consumption rule is mined by using a big data analysis technology, and a demand trend is predicted; constructing an intelligent energy dispatching center, and formulating a dynamic energy distribution scheme by using an optimization algorithm; a mobile phone application and an intelligent control panel are developed, and a user is supported to check data, control equipment and carry out personalized customization; and meanwhile, equipment firmware upgrading and remote management are realized. According to the invention, energy consumption can be reduced, cost can be controlled, equipment collaboration and energy distribution efficiency can be improved, user experience can be enhanced, system maintenance and upgrading are facilitated, and intelligent household energy management is more efficient, intelligent and flexible so as to adapt to diversified household requirements.

Systems and methods for unsupervised multi-modal causal structure learning for root cause analysis. System logs of a cloud system can be transformed to time-series data using a log-tailored language model to obtain system log features of the cloud system. A metric causal graph and a log causal graph can be predicted from modality-specific representations and modality-invariant representations of extracted system metric features and system log features, respectively, using the deep neural network. The metric causal graph and log causal graph can be fused to obtain a fused causal graph. Root causes of system failure can be flagged for system maintenance based on ranked entities obtained from the fused causal graph to obtain flagged root causes. System maintenance can be performed autonomously based on the flagged root causes from identified system entities to optimize the cloud system with an updated configuration.

The invention discloses a high-precision current detection circuit calibration system, and belongs to the technical field of current detection circuit calibration. Comprising a shunt resistor, a Hall sensor array, a chopping amplifier, a low-noise operational amplifier, a temperature sensor, an ADC acquisition unit, an RC low-pass filter, a signal conditioning unit, a main control unit, an environmental parameter adaptive compensation module and a gain adaptive adjustment module. After an original signal is obtained from a multi-channel sensor, a dynamic error model is constructed in combination with temperature data, a long-term imbalance trend is extracted by using a moving average or median filtering algorithm, and real-time compensation is performed through a pre-calibrated temperature-drift function, so that the system maintenance period is remarkably prolonged.

The invention discloses an interactive simulation method for calculating aging parameters of a superconducting cable and a superconducting cable system.The system comprises the steps that a cable body electromagnetic transient model, a cooling system transient thermal model and a three-dimensional multi-field finite element model are built, and cable material characteristics, environment parameters and operation condition data are input; a model interaction interface is constructed through a simulation platform, data interaction and coupling among multiple models are realized, simulation parameters are dynamically adjusted, accurate matching of model step length and dynamic characteristics of the system is ensured, and aging parameters of the superconducting cable system under complex working conditions are calculated. According to the method, the operation state of the superconducting cable is evaluated by analyzing the mixed data, aging analysis of the superconducting cable system under multiple working conditions is carried out, and decision support is provided for system maintenance.

The invention relates to the technical field of data processing, can be applied to business scenes of financial science and technology, medical health, lease and the like, and discloses a distributed multi-terminal data cooperative processing method, which comprises the following steps: receiving a structured data unit containing business logic generated by an initiating terminal, and transmitting the structured data unit to a business verification server, receiving verification result data returned by the service verification server, and performing security encapsulation processing on the verification result data to generate security encapsulation data; calling a distributed communication service interface of the distributed operating system, and detecting a connectable device set in a network domain where the initiating terminal is located; and establishing a multi-path transmission link based on the transmission capability parameters of the terminal devices in the connectable device set, and distributing the security encapsulation data to the target terminal device group through the multi-path transmission link. According to the invention, efficient distribution and synchronization of data are realized through a multipath transmission link, the dependence on a background system is reduced, the timeliness and consistency of data synchronization are improved, and the maintenance cost of the system is reduced.

The invention provides an intelligent monitoring method and system based on task operation historical information, and relates to the technical field of intelligent monitoring, and the method comprises the steps: collecting target task operation data to construct a task operation portrait, carrying out the real-time monitoring, calculating a task health degree score, and when the health degree score is lower than a preset threshold value, executing the task operation. And an intelligent diagnosis mechanism is automatically triggered to identify the exception type and execute a corresponding processing strategy, and exception processing experience is stored in a historical information database to optimize the diagnosis accuracy. According to the invention, the intelligent level of task monitoring can be improved, rapid and accurate identification and processing of abnormities are realized, and the maintenance cost of the system is reduced.

The invention relates to the technical field of electric power system maintenance, and discloses an emergency commanding and dispatching system and method based on electric power business, and the system constructs an electric power business emergency commanding and dispatching platform comprising a real-time monitoring module, a data analysis module, a decision support module and a dispatching and commanding module. The real-time monitoring module is responsible for collecting electric power system data, and the data analysis module identifies abnormity and potential risks. And the decision support module is used for defining an emergency state space, an action space and a response strategy and combining an emergency strategy model constructed by a reinforcement learning algorithm to realize dynamic optimization and updating of a decision algorithm and a rule so as to ensure that an emergency processing scheme is rapidly and accurately formulated. And the scheduling command module is responsible for coordinating resource allocation and scheduling according to a decision result, and ensuring rapid recovery and stable power supply of the power system. According to the method, reinforcement learning is introduced, so that the intelligence and the adaptability of emergency response are improved, and the efficiency and the accuracy of electric power emergency command and dispatch are effectively improved.

The invention discloses an AI-based digital twinborn irrigation area automatic irrigation method and system, and relates to the technical field of artificial intelligence, and the method comprises the following steps: collecting data, and constructing a digital twinborn model; irrigation demand prediction is carried out according to the digital twinborn model; making an irrigation control decision according to the irrigation demand prediction result; performing automatic irrigation based on the irrigation control decision content; crop growth evaluation is carried out according to the irrigation execution result; performing irrigation strategy optimization according to a growth evaluation result; maintaining and updating the irrigation system according to the irrigation strategy; and performing water resource management based on the planning result. According to the method, the digital twin model can be updated in real time and adapt to environmental changes by introducing the data stream based on the Internet of Things and a reinforcement learning mechanism. The feedback mechanism based on AI and reinforcement learning enables the digital twinborn model to more accurately simulate an irrigation environment and provide an optimal irrigation strategy under different environmental conditions.

The invention discloses an intelligent flow sensor test analysis method and system, and relates to the technical field of sensor testing, and the method comprises the steps: applying a stepped flow excitation signal to a tested sensor through a standard flow generation device, and synchronously collecting the dynamic response data of the sensor; extracting a feature parameter set from the response data; performing similarity matching calculation to obtain a matching degree evaluation value of each error type; quantifying the induction relation strength among different error types; generating a composite weight coefficient in combination with the matching degree evaluation value and the evoked relationship strength; and making a multi-stage compensation strategy based on the composite weight coefficient. The method has the advantages that by combining error correlation network modeling driven by historical data, induction mechanisms and interaction relations of different error types can be analyzed, the pertinence of a compensation strategy is greatly improved, a multi-stage error suppression mechanism is formed, stable control over comprehensive errors is achieved under complex working conditions, and meanwhile the system maintenance requirement is lowered.

The invention discloses a fumigation treatment multi-parameter comprehensive monitoring system which comprises a multi-parameter sensor monitoring module, a multi-modal data processing and analyzing module, a system intelligent monitoring and adjusting module, a fumigation environment control module, a remote maintenance and management module and a system interaction and feedback module. The multi-parameter sensor monitoring module is used for collecting parameter data. The multi-modal data processing and analyzing module is used for fusing and analyzing data. The system intelligent monitoring and adjusting module is used for intelligently monitoring and adjusting fumigation strategies. The fumigation environment control module is used for adjusting environment parameters. The remote maintenance and management module is used for system maintenance and management. And the system interaction and feedback module is used for display interaction of data and a control state. According to the fumigation treatment multi-parameter comprehensive monitoring system, a multi-modal data fusion algorithm based on information channel decomposition is provided for multi-parameter data fusion and analysis; and a multi-parameter intelligent monitoring algorithm based on a multi-layer feedforward neural network is provided to intelligently monitor the fumigation environment.

The invention relates to the field of robot technology, machine vision, deep learning, computer graphics and digital twinning, in particular to a mechanical arm action recognition and control method based on the machine vision and the digital twinning technology. The motion state and environment information of the mechanical arm are captured in real time through the machine vision technology, high-precision recognition of the motion of the mechanical arm can be achieved in combination with an image processing algorithm, and a control strategy is adjusted in real time according to the recognition result; based on the digital twin model, the state change of the mechanical arm can be monitored in real time, and the mechanical arm and the virtual model are synchronously driven, so that the action of the mechanical arm is ensured to be consistent with the expected action; through intelligent identification and automatic adjustment, manual operation errors are reduced, the working efficiency and the production precision are improved, and the complexity of system maintenance is reduced; real-time optimization of the operation process of the mechanical arm can be achieved through combination of digital twinning and machine vision, potential faults are avoided through simulation and prediction, and stable operation of a production line is ensured.

The invention provides a new energy equipment system maintenance decision-making method and system based on a fault coupling model, and relates to the technical field of equipment predictive maintenance, and the method comprises the steps: collecting system structure information and system fault data of a complex new energy equipment system, and carrying out the maintenance decision-making of the complex new energy equipment system according to the system structure information and the system fault data; respectively constructing a function model view, a system level fault model view and each flow fault model view; constructing a fault coupling model corresponding to the complex new energy equipment system; probability estimation is carried out on the system fault data according to a kernel density estimation method, the fault probability of each fault node in the complex new energy equipment system is obtained, and key fault nodes in all the fault nodes and key node information corresponding to the key fault nodes are obtained; and mapping the key node information into a risk level corresponding to the key node information, and obtaining an optimal maintenance decision based on a decision tree analysis method and a plurality of maintenance decisions. According to the method, multi-dimensional analysis of a complex system can be realized, and fault modes of different components and subsystems can be identified more clearly, so that the fault detection and diagnosis efficiency is improved.

The invention discloses a superconducting cable aging state evaluation system and method based on mixed data, and the system comprises a data analysis module, an aging evaluation module, a physicochemical association module and a report generation module which are in communication connection. Wherein the data analysis module comprises a simulation sub-module, a data acquisition sub-module and a data processing sub-module connected with the data acquisition sub-module, and in the aging state evaluation process of the aging evaluation module, superconducting cable system model parameters are output and calibrated through a physicochemical association model; and then an aging state evaluation fitting function is output through the data processing sub-module, and an aging state evaluation report is automatically generated by the report generation module. According to the method, the operation state of the superconducting cable is evaluated by analyzing the mixed data, aging analysis of the superconducting cable system under multiple working conditions is carried out, and decision support is provided for system maintenance.

The invention discloses a multi-mode coordinated ship main and auxiliary power automatic switching system, which relates to the technical field of ship power systems and comprises a monitoring system, a diagnosis decision system, an execution system, a switching verification system, a maintenance management system and a data communication system. According to the invention, the airborne weather radar, the ship weather instrument and the weather fax receiver are used for monitoring the current weather condition of navigation and predicting the weather condition of a future navigation route, so that a prediction basis is provided for a power system operation mode selected by future ship navigation; meanwhile, the ship weather instrument monitors surrounding wind speed, wind direction, air temperature and humidity data in real time when the ship sails, the current data is stored in the data storage, a database is formed, and a follow-up maintenance management system can predict potential risks according to historical data conveniently.

A maintenance reservation system according to a first aspect includes: an equipment information acquisition unit configured to acquire equipment information including information about equipment; a maintenance contractor information acquisition unit configured to acquire maintenance contractor information including information about maintenance contractors who provide maintenance services on the basis of information transmitted from maintenance contractor terminals; a reservation information acquisition unit configured to acquire reservation information including desired conditions for the maintenance services on the basis of information transmitted from a user terminal; a processing unit configured to select maintenance contractor candidates on the basis of the equipment information and the maintenance contractor information, and narrow down the candidates on the basis of the desired conditions and the maintenance contractor information corresponding to the maintenance contractors included in the candidates; and a notification unit configured to notify the user terminal of the candidates narrowed down by the processing unit.

The present application provides a message-driven microservice dynamic orchestration method and related equipment. The method is applied to a microservice dynamic orchestration system, wherein the system includes multiple microservices, and the method includes: obtaining the impact factor of the microservice from the business message; generating the process orchestration data of the microservice according to the message subject preset by the microservice and the impact factor, and storing the process orchestration data in a cache center; allowing each of the microservices in all the microservices to read the process orchestration data from the cache center and determine the next microservice connected to it according to the process orchestration data. The method provided by the present application realizes the dynamic orchestration of microservices, and there is no need to change or restart the microservice when adjusting the microservice call link, thereby ensuring the work efficiency of the system, reducing the difficulty of system maintenance, and solving the problem that the microservice call link is difficult to adjust.

The application relates to the technical field of text label marking, and provides a text specification marking method and system based on a rule corpus, which comprises the following steps: analyzing a policy and regulation document, identifying and marking condition morphemes and conclusion morphemes in the policy and regulation document, constructing a logical relationship between the two by using a large language model, and forming a rule corpus composed of structured morpheme pairs; performing semantic embedding on the corpus to generate a semantic vector library; performing multi-label coding on a verification data set based on the rule corpus, and constructing a multi-label training data set; training a deep learning classification model by taking semantic vectors as features and multi-labels as targets, so that a text specification marking model is obtained; and automatically marking target text by using the model. The application significantly improves the accuracy, interpretability and business adaptability of text marking, improves the update quality of a system label data set, and reduces the system maintenance cost.

Techniques are described for configuring a data platform to schedule workloads using backlog indicators. For instance, processing circuitry of a data platform may obtain a generic backlog indicator for workloads to execute via the data platform. Each of the workloads may specify one or more storage system maintenance operations. Processing circuitry may obtain a custom backlog indicator for at least a subset of the workloads. A priority manager may calculate a single weighted backlog indicator value for each of the workloads by applying configurable weights to the generic backlog indicators and the custom backlog indicators. The data platform may schedule the workloads for execution on the data platform based on the single weighted backlog indicator value calculated for each workload. In some examples, the data platform processes the workloads according to the scheduling.

A maintenance system for maintaining a hardware system is described. The maintenance system includes an acquisition circuit and an analysis circuit. The acquisition circuit can be configured to acquire a plurality of operational parameters of the hardware system, the plurality of operational parameters being relevant to a health state of the hardware system. The acquisition circuit can be configured to forward the plurality of operational parameters to the analysis circuit. The analysis circuit can be configured to determine a device health score for the hardware system, a remaining useful life of the hardware system, and / or a user recommendation for operating the hardware system, each based on the plurality of operational parameters. Further, a method of analyzing and / or creating health information for a hardware system is described.

The utility model discloses a discharging structure and a mixing machine, and relates to the technical field of mixing machines, the discharging structure comprises a mixing cylinder arranged on a rack, a discharging port is arranged at the bottom of the mixing cylinder, and the discharging port is used for discharging materials; the rotating shaft is rotatably connected with the rack, one end of the rotating shaft is connected with the connecting rod assembly, and the connecting rod assembly is used for driving the rotating shaft to rotate; the material blocking plate set is connected with the peripheral side face of the rotating shaft, and the top face of the material blocking plate set abuts against the discharging opening. According to the discharging structure, the technical problems that an existing hydraulic driving discharging mode is prone to being affected by dust and damaged, a hydraulic system needs to be maintained regularly, and the maintenance cost is high are solved, the driving arm is manually pushed and pulled to drive the material blocking plate set to leave and block the discharging opening, namely the opening and closing state of the discharging opening is manually controlled through the lever principle, and the discharging efficiency is greatly improved. The whole discharging structure is simple and convenient, is not influenced by dust in the working environment, does not need regular maintenance, and effectively saves the maintenance cost.

The invention belongs to the technical field of gas detection, and relates to a ship exhaust gas multi-component synchronous online monitoring system and method based on a laser Raman spectrum. The system comprises a sampling module, a preprocessing module, an analysis module, a data processing module, a blowback module and a flow measurement module. The method comprises the following steps: starting and self-checking the system; sample collection, pretreatment and flow velocity measurement; laser excitation and signal acquisition; carrying out spectrum analysis and concentration inversion; data output and system maintenance; and performing periodic automatic calibration. According to the invention, a complete monitoring process chain from sampling, pretreatment, flow measurement, analysis to back flushing is creatively integrated. The high-efficiency pretreatment and back flushing design greatly reduces the influence of high-dust and high-humidity environment on the analysis system, and ensures the long-term stability and reliability of the system.

The invention discloses a building electromechanical system fault intelligent detection method and system, and relates to the technical field of building electromechanical system maintenance, and the method comprises the following steps: system data collection, health value evaluation, fault prediction, priority maintenance, and evaluation of the importance of electromechanical equipment needing maintenance through a priority scoring algorithm. And obtaining a maintenance priority score S, and notifying maintenance personnel to perform maintenance and data storage on the electromechanical equipment in sequence according to the maintenance priority score S. The method has the advantages that the equipment health value is quantized through an electromechanical system health evaluation algorithm, the equipment fault risk is predicted in combination with a fault probability prediction algorithm, and whether the equipment needs to be maintained or not is judged in advance; the system is prevented from being damaged by sudden faults, the downtime and the maintenance cost are reduced, the maintenance priority of the equipment is evaluated through a priority scoring algorithm, maintenance resources are reasonably distributed, the maintenance efficiency is improved, excessive maintenance is reduced, and stable operation of the electromechanical system is ensured.

A unitary hermetically sealed device is disclosed for providing self-contained electric propulsion drive power to a motor boat or sailboat, where the entire propulsion system is contained in a separable pressurized hermetic enclosure attached to the underside of the vessel and also acts as a keel of the vessel, and which simplifies production, provides improved safety from high voltages, and prevents drive system maintenance or repair when the vessel is located in the water. The rigid hermetically sealed device functions as a skid-plate to avoid damage to the softer typically fiberglass hull when running the vessel aground or when running up onto or off of the beach or onto or off a trailer.

The invention discloses an information acquisition system and method suitable for visually impaired people. The system comprises a hardware layer, a driving layer, an operating system layer, a middleware layer and an application layer which are sequentially in communication connection through interfaces. The application layer comprises a voice interaction module, a large model integration module and a braille conversion module; the hardware layer is used for collecting a voice input instruction and outputting a braille character sequence and a voice output result; the voice interaction module is used for converting a voice input instruction into a text input instruction and converting a text output result into a voice output result; the large model integration module is used for analyzing the text input instruction and generating a text output result; and the braille conversion module is used for converting the text output result into a braille character sequence, so that a hardware layer outputs the braille character sequence based on a timestamp alignment technology. Therefore, based on powerful semantic understanding and information retrieval of the large model integration module, accurate information acquisition is realized, and a five-layer decoupling architecture is adopted, so that the convenience of later system maintenance is improved.

The present disclosure provides a method and an Internet of Things (IoT) system for assessing a loss of a maintenance medium of a smart gas pipeline network. The method comprises: determining a degree of a maintenance impact based on maintenance data; determining a target supply for a maintenance pipeline branch in a target time period based on the degree of the maintenance impact and historical supply data; determining a target demand for the maintenance pipeline branch in the target time period based on historical usage data; determining a target loss in the target time period based on the target supply and the target demand; and determining a replenishment parameter based on the target loss.

The invention provides a DCS system maintenance system based on networking intelligent monitoring and a method thereof, and relates to the technical field of intelligent manufacturing and high-voltage circuit breaker health management. Firstly, an independent classification identifier and a unique increasing number are distributed for each type of high-voltage circuit breaker, and multi-dimensional operation data of temperature, pressure, vibration and current are collected at fixed time intervals and are stored in a high-voltage circuit breaker state data set according to the number and timestamp of the high-voltage circuit breaker. And then constructing a dynamic weight distribution formula, outputting a health state score and recording the health state score to a health state database. And extracting operation data in a fault state to construct an abnormal data set, combining the health state score with the abnormal data set, and performing deep training and prediction by using an LSTM model so as to obtain a future fault occurrence probability of the high-voltage circuit breaker. Once the predicted fault occurrence probability of the high-voltage circuit breaker is higher than a fault threshold value, the high-voltage circuit breaker is immediately calibrated as a potential fault high-voltage circuit breaker, a detailed and targeted maintenance plan is generated, and meanwhile, the operation parameters of the potential fault high-voltage circuit breaker are rapidly adjusted.

The invention relates to the technical field of hybrid submarine cable system maintenance, in particular to a reactive compensation method, system and device for a hybrid submarine cable system and a medium, and the method comprises the steps: obtaining the standard electrical parameters of an oil-filled submarine cable and an XLPE submarine cable; constructing an electromagnetic transient simulation model of the hybrid submarine cable system; calculating an ideal reactance compensation range; a plurality of groups of series reactance compensation schemes are set and applied in the electromagnetic transient simulation model, and three-phase transmission power distribution, total transmission power and voltage unbalance degree under each series reactance compensation scheme are simulated and calculated; comparing simulation results of each series reactance compensation scheme, and selecting the series reactance compensation scheme with the maximum total transmission power on the premise that the three-phase power unbalance degree is lower than a preset equilibrium constraint condition as an optimal compensation scheme; an optimal compensation scheme is applied in a hybrid submarine cable system. According to the invention, three-phase power balance and total transmission power maximization of the hybrid submarine cable system can be realized at the same time.

A fracking stack assembly coupled with a wellhead is disclosed. The fracking stack assembly can include a linear shear-flow controller configured to deliver the flow of pressurized lubricant to the fracking valve. The linear shear-flow controller can include a housing around an interior space, a supply port receiving a flow of pressurized lubricant, an outlet port; and a slide having a first end and a second end disposed within the interior space and movable along a linear axis. A first side of the slide can sealingly engage with a first sealing ring, and a second side of the slide can sealingly engage with a second sealing ring, such that the slide is slideable along the linear axis between blocked and open positions.

The invention provides a self-adaptive joint maintenance control method for a structural system under environmental heterogeneous damage. The method comprises the following specific steps: 1, modeling a damage accumulation trajectory of a structural component under an environmental heterogeneous mode; 2, predicting the service life of the part under the environment damage heterogeneous condition; 3, delayed maintenance control optimization of single structural components; 4, quantifying a single structural component-system joint maintenance mapping function; and 5, iterative grouping selection heuristic strategy solution algorithm planning is carried out. The method has the advantages that the dynamic capture of an environmental heterogeneity mode in a structural system damage rule is realized, so that a more accurate residual life prediction activity is carried out, and the sensitivity of a damage feature recognition process is ensured; self-adaptive dynamic updating of system maintenance schemes can be realized according to real-time state evaluation information and historical maintenance records of structural components, correlation in adjacent maintenance schemes can be quantified, the adaptability is high, and the intelligent level is high; the balance between the prolonging of the remaining service life of the structural component and the preparation buffering of the maintenance resources is realized, and the scientificity of the maintenance plan is ensured.

The invention relates to the technical field of computer system maintenance, and particularly discloses a computer system and a computer system maintenance method, and the method comprises the steps: obtaining the basic information of each to-be-installed patch corresponding to a target computer system, and carrying out the preliminary analysis to obtain the safety evaluation coefficient of each to-be-installed patch; collecting multi-dimensional data of the target computer system, and generating a virtual copy synchronized with the target computer system in real time in the isolation environment; installing each patch to be installed in the original target computer system in the isolation environment, running a core function module of the target computer system in the isolation environment, and further verifying a compatibility evaluation coefficient of each patch to be installed in the isolation environment; synchronously monitoring the dynamic operation behavior of each patch to be installed in real time in the isolation environment, and detecting a potential behavior threat assessment coefficient of each patch to be installed in the isolation environment; not only is the possibility of patch introduction reduced, but also a solid foundation is provided for long-term maintenance and safety management of the system.