54 results about "Plant state" patented technology

An information network which connects a centralized interactive unit for monitoring and controlling the operation of a plurality of plants and an individual interactive unit for monitoring and controlling a plant is connected to a control network which connects a control unit and the individual interactive unit by gateway means. The control unit multicasts a plant state quantity to the control network as a Tag if there is a significant change in the plant state quantity, and the centralized interactive unit and the individual interactive unit multicast a query about a plant state quantity to the control network and update a response from the control unit.

A process monitoring system includes: a plurality of field devices configured to measure state quantities in an industrial process implemented in a plant; a trend calculation unit configured to determine the variation trend of the state quantities based on time-sequence data output from each of the plurality of field devices and classify each of the variation trends of the state quantities into one of a pre-established plurality of statuses; a state change judgment unit configured to judge the existence or non-existence of a pre-indicator of a change in the plant state, in accordance with the existence or non-existence of a change in at least one of the statuses classified by the trend calculation unit; and a notification unit configured to notify of judgment results of the state change judgment unit.

The invention belongs to accessory equipment of water purifying plants. In order to solve the problem that a filter element can not be replaced immediately in a link of replacing the filter element for the water purifying plant, the invention provides a water purifying plant state reminding system which comprises a client end and a handy terminal, wherein the client end is a singlechip provided with a display module and is also provided with a control module, a storage module and a communication module, and the display module displays data stored by the storage module, contents displayed by the display module comprise time of replacing consumable items by the water purifying plant next time; the handy terminal comprises a first communication module and an input module, and the first communication module is communicated with the communication module on the client end and stores data to the storage module on the client end. The invention can be widely applied with the water purifying plant.

There is provided a plant analysis system capable of enhancing efficiency of works by sharing information within a plant. A storing means stores a logic defined via a reception means. A monitoring data creation means creates KPI (key performance indicator) in real time as data for monitoring the plant based on data to be acquired from the plant by use of the logic stored in the storing means. An analysis data creation means creates the KPI as analyzing data for analyzing a plant state in the past based on historical data stored in a historical data storage means by use of the logic stored in the storing means.

System and method to estimate variables in an integrated gasification combined cycle (IGCC) plant are provided. The system includes a sensor suite to measure respective plant input and output variables. An extended Kalman filter (EKF) receives sensed plant input variables and includes a dynamic model to generate a plurality of plant state estimates and a covariance matrix for the state estimates. A preemptive-constraining processor is configured to preemptively constrain the state estimates and covariance matrix to be free of constraint violations. A measurement-correction processor may be configured to correct constrained state estimates and a constrained covariance matrix based on processing of sensed plant output variables. The measurement-correction processor is coupled to update the dynamic model with corrected state estimates and a corrected covariance matrix. The updated dynamic model may be configured to estimate values for at least one plant variable not originally sensed by the sensor suite.

The invention discloses a giant hydraulic power plant state maintenance model construction method. The method comprises the steps of firstly collecting the hydraulic power plant equipment operation state information; performing diagnostic analysis; obtaining the equipment operation state evaluation; evaluating a system state maintenance strategy according to the state; and ending the maintenance process of the equipment until the equipment runs normally. According to the giant hydraulic power plant state maintenance model construction method provided by the invention, the operation reliabilityof the equipment can be improved, and the service life of the equipment can be prolonged by 1-3 years in the life cycle, the equipment maintenance cost is reduced, and the equipment purchase and installation funds can be saved within the service life period of the electromechanical equipment. The method comprises the following steps of taking prevention of equipment faults as a center, classifying all system equipment, analyzing the possible fault modes of different types of equipment, determining the fault mode of each type of equipment, formulating the corresponding preventive monitoring and maintenance tasks and periods thereof for each type of fault modes, and realizing prevention of the equipment faults by utilizing the state maintenance.

A neural-Model Predictive Control (MPC) controller is described to control a dynamical system (i.e., “plant”). The MPC controller receives, in a base controller, a measurement of a current state of a plant and generates a control signal based on the measurement of the current state of the plant. A forward module receives the measurement of the current state of the plant and the control signal to generate a forward module prediction. A forward module corrector receives the measurement of the current state of the plant and the control signal from the base controller to generate an additive correction to the forward module prediction to generate a predicted plant state. Control sequences of length L of pairs of control signals and corresponding predicted plant states are generated until N_s control sequences have been generated. A next plant control signal is generated based on the N_s control sequences.

When an abnormality is detected, a decision about whether or not the abnormality should be dealt with is made based onon the basis of experiences in operating a plant. However, it is preferable to make the decision on the basis ofbased on a risk (expected loss amount) that would occur when if the abnormality iswere to be left as is. In order to achieve this, the present invention is a plant diagnosis device equipped with multiple diagnosis means for diagnosing an abnormality state of the plant, and characterized by being equipped with a comprehensive diagnosis means that, upon determining degrees of accuracy in detecting the abnormal states with respect to each of the multiple diagnosis means on the basis of measurement signal data pertaining to plant states and facility management information data pertaining to past abnormal states, evaluates expected loss amounts on the basis of the degrees of accuracy and loss amounts associated with the abnormal states.

A production planning system (6) for a raw materials industry plant (ANL), which determines the production planning data (Pi) thereof and specifies said data to the automation system (1) of the plant (ANL). A state monitoring system (7) determines previous and future anticipated states (Z1) of components of the plant (ANL). A quality determination system (8) determines states (Z2) of output products (Ai) produced and still to be produced by the plant (ANL) and/or past and future states (Z3) of the plant (ANL) as a whole. A maintenance planning system (9) and/or the production planning system (6) receive, from the state monitoring system (7), the states (Z1) of the components of the plant (ANL), determined by the state monitoring system (7) and, from the quality determination system (8), the states (Z2 and Z3) of the output products (Ai) and/or of the plant (ANL) as a whole, determined by the quality determination system (8). They consider the data received from the state monitoring system (7) and from the quality determination system (8) in the determination of maintenance planning data (W) and/or the production planning data (Pi).

The invention provides an energy-flow-based ship power plant state monitoring system. The energy-flow-based ship power plant state monitoring system comprises a sensor set, a converter, an energy flow display device and a fault alarm device which are connected in sequence; the sensor set is used for collecting related parameter data of a corresponding power consumption device; the converter is used for processing data collected by the sensor and converting the collected data into a data form of energy; the energy flow display device is used for letting people know the operation state of the ship power plant through displaying energy flow directions and numerical values of energy consumption devices in real time; and the fault alarm device is used for alarming when a safety failure or abnormal energy flows happen. The invention also provides an energy-flow-based ship power plant state monitoring method. The energy-flow-based ship power plant state monitoring system and method introduce an energy flow principle, can determine and eliminate equipment faults through monitoring and controlling energy flows, add the energy consumption alarm device on the basis of the original fault alarm device, and guarantee the ship power plant to always operate safely and efficiently.

The invention relates to the technical field of plant condition monitoring, and discloses a plant condition monitoring method, device, system, and apparatus, and a storage medium. The method comprisesthe steps of: obtaining the status of the factory change item, and setting a score value of the status of the factory change item to obtain the status score value of the factory change item, whereinthe factory change item at least comprises a change in output, a change in inventory and a change in a production-sales balance; and the status of the factory change item at least comprises four states of normal, attention, abnormality and early warning; The plant state score is calculated according to the plant change item state score, and the plant state is judged according to the plant state score. The invention monitors the status of each factory change item in the production process in real time, and digitally processes the status of each factory change item to monitor whether the statusof the factory is normal or not, so as to achieve the purpose of real-time monitoring the production situation, timely discovering the production error, and making the plant operation more efficient.

The invention discloses a giant hydraulic power plant state maintenance model and a construction method. The method comprises the steps of collecting operation state information of various devices ofa hydraulic power plant; Carrying out analysis; Carrying out score evaluation on the equipment; Determining the equipment as a normal state, an attention state, an abnormal state and a dangerous state; And finally, making an equipment facility maintenance level and a power station annual equipment maintenance plan according to the level state of the equipment. On the basis of periodic overhaul stipulated by the country and industry, formulating an equipment state overhaul strategy by taking equipment operation reliability as a center and according to equipment operation trend annual analysis,risk and service life evaluation and other means, and determining an equipment overhaul interval, outage time and an overhaul mode of an overhaul project according to diagnosis and evaluation results.And the equipment hidden danger can be timely discovered and eliminated, equipment faults and even accidents are avoided, the service life of the equipment is prolonged, the workload of maintenance personnel and the maintenance management difficulty are reduced, and the maintenance management efficiency is also improved to a certain extent.

The invention belongs to the technical field of nuclear power plant operation, and relates to a data processing method for nuclear power plant accident processing guide rule confirmation. The data processing method sequentially comprises the following steps: (1) selecting key function related parameters and respectively extracting data; (2) determining a corresponding relation between the key function related parameters and the power plant state; (3) calculating different working conditions based on an optimal estimation system program, and reasonably judging whether recalculation is needed ornot according to a calculation result; (4) drawing a key function time sequence change table according to a calculation result; and (5) comparing the time sequence change tables under different working conditions, and evaluating the effectiveness of operation intervention. According to the data processing method for nuclear power plant accident processing guide rule confirmation, data observation, screening and processing analysis can be better carried out when symptom guiding accident processing guide rule confirmation work is carried out, and therefore part of confirmation results can be used for nuclear power plant accident processing links related to evaluation and operation intervention.

The invention provides a plant growth prediction method and device based on a machine learning model, equipment and a computer readable storage medium. The machine learning model comprises a first sub-model, a second sub-model and a third sub-model, and the plant growth prediction method comprises the steps of obtaining greenhouse control parameters, weather data and plant state data; utilizing the first sub-model to generate a first feature vector according to the greenhouse control parameters; generating a second feature vector according to the weather data by using the second sub-model; generating a third feature vector according to the plant state data by using the third sub-model; and generating a plant growth prediction result after the predetermined time period based on the first feature vector, the second feature vector and the third feature vector.

The invention provides the detection method and device of a plant state, and an intelligent flowerpot. The detection device of the plant state comprises detection equipment used for detecting reference information and identification equipment used for determining the current state of plant according to the reference information, wherein the reference information includes the appearance characteristic of the plant; and the current state includes a health state and a non-health state. A user can conveniently and timely determine the state of the plant and take measures when the plant is sick, and the user can be assisted to take care of the plant and keep the plant as healthy as possible.

An object of the invention is to provide an operation support system for plant accidents that estimates events reflecting plant states changing momentarily at plant accidents. The invention includes an event narrow-down device that narrows down occurring event candidates based on at least one of a sensor signal, a device state signal, and an alarm signal and a discriminant rule, an event analysis device that analyzes a plant behavior based on a plurality of event narrow-down results as output of the event narrow-down device, the sensor signal, the device state signal, and the alarm signal, and an event estimation device that estimates an occurring event by comparing an analysis result from an analysis of a process state as output of the event analysis device and the sensor signal, wherein the event estimation device outputs the analysis result of the process state and the sensor signal corresponding to the occurring event as an event estimation result.

Methods, sensing and control devices for plant state data transmission are disclosed. The method includes: measuring, by a sensing device (12), instantaneous state data of a controlled plant (11) (S21); analog-encoding the measured instantaneous state data when determining that a preset transmission condition is satisfied (S22); and transmitting the encoded instantaneous state data directly to a control device (13) that controls the controlled plant (11) over a wireless channel without sending a channel resource scheduling request to the control device (13) (S23). Thus, the data transmission overheads and the access latency can be significantly reduced.

The invention discloses a cultivation device for increasing the survival rate of nursery stocks and a method, relates to the technical field of cultivation devices, and aims to solve the problem that the survival rate of plants planted by a user who does not know a planting method is low due to the fact that the cultivation device on the market at present cannot provide different planting schemes for different plant types during planting. A cover plate is fixedly arranged in the middle of the upper end of the shell, four supporting seats are sequentially arranged at the lower end of the interior of the shell, a sensor box is arranged in the middle of each supporting seat, a flowerpot is arranged above each supporting seat, and a control unit is installed on the inner wall of one side of the shell. A soil loosening mechanism is movably installed above the cover plate, first electric telescopic rods are fixedly arranged between the adjacent flowerpots, shading mechanisms are fixedly arranged above the first electric telescopic rods, and a cultivation control system comprises a variety recognition system, a plant state analysis system, a planting depth system and a control sensing system.