Due to the current structure of digital factory, it is necessary to build the smart factory to upgrade the manufacturing industry. Smart factory adopts the combination of physical technology and cyber technology and deeply integrates previously independent discrete systems making the involved technologies more complex and precise than they are now. In this paper, a hierarchical architecture of the smart factory was proposed first, and then the key technologies were analyzed from the aspects of the physical resource layer, the network layer, and the data application layer. In addition, we discussed the major issues and potential solutions to key emerging technologies, such as Internet of Things (IoT), big data, and cloud computing, which are embedded in the manufacturing process. Finally, a candy packing line was used to verify the key technologies of smart factory, which showed that the overall equipment effectiveness of the equipment is significantly improved.

Smart Factory of Industry 4.0: Key Technologies, Application Case, and Challenges

Methods for compensating for phase shifts of a communication signal. The methods involve determining a first reference signal (V ref-1 ) at a first location along a transmission path and a second reference signal (V ref-2 ) at a second location along the transmission path. V ref-2 is the same as V ref-1 . At the first location, a first phase offset is determined using V ref-1 and a first communication signal. At the second location, a second phase offset is determined using V ref-2 and a second communication signal. A phase of a third communication signal is adjusted at the second location using the first and second phase offsets to obtain a modified communication signal. The first, second, and third communication signals are the same communication signal obtained at different locations along the transmission path.

Closed loop phase control between distant points

A control method for optimizing an operation of a power plant having generating units during a selected operating period subdivided so to include regular intervals within which each of the generating units comprises one of an on-condition and an off-condition. The control method may include: determining a preferred case for each of the competing operating modes for the intervals; based upon the preferred cases, selecting proposed turndown operating sequences for the selected operating period; determining a shutdown operation for each of the generating units comprising the off-condition for one or more intervals during the selected operating period and, therefrom, calculating a shutdown economic outcome; determining a turndown operation for each of the generating units comprising the on-condition for one or more intervals during the selected operating period and, therefrom, calculating a turndown economic outcome; calculating a sequence economic outcome for each of the proposed turndown operating sequences; and comparing the sequence economic outcomes.

Methods and systems for enhancing control of power plant generating units

A method for correcting transmission phasing errors in an plurality of antenna elements is provided. The method includes receiving at least a first signal having a first frequency at the plurality of antenna elements at an angle of arrival (AOA). The method also includes identifying an actual fractional wavelength value (ƒtrue) for the first signal received with respect to a reference location for at least one of the plurality of antenna elements, obtaining a estimated phase propagation of the first signal at the one of the plurality of antenna elements relative to the reference location based at least on configuration data for plurality of antenna elements, and updating the configuration data associated with the AOA for the one of the plurality of antenna elements based on the estimated phase propagation and ƒtrue.

Systems and methods for compensating for transmission phasing errors in a communications system using a receive signal

Methods and systems for low emission power generation in hydrocarbon recovery processes are provided. One system includes integrated pressure maintenance and miscible flood systems with low emission power generation. An alternative system provides for low emission power generation, carbon sequestration, enhanced oil recovery (EOR), or carbon dioxide sales using a hot gas expander and external combustor. Another alternative system provides for low emission power generation using a gas power turbine to compress air in the inlet compressor and generate power using hot carbon dioxide laden gas in the expander. Other efficiencies may be gained by incorporating heat cross-exchange, a desalination plant, co-generation, and other features.

Low emission power generation and hydrocarbon recovery systems and methods

A method for determining an estimated operating parameter for a gas turbine including the steps of: determining an estimated operating parameter using an algorithm have an input from a sensor, wherein the algorithm includes a trim factor; determining a first trim factor based on a comparison of the first estimated operating parameter and the output of the sensor when a condition of the sensor is in a first mode, and during a subsequent determination of the estimated operating parameter, applying the first trim factor to subsequently determine the estimated operating condition if the condition of second sensor is in a second mode.

Method and system for incorporating an emission sensor into a gas turbine controller

Embodiments of systems and methods for tuning a turbine are provided In one embodiment, a method may include receiving at least one of a measured operating parameter or a modeled operating parameter of a turbine during operation; and tuning the turbine during operation The turbine may be tuned during operation by applying the measured operating parameter or modeled operating parameter or parameters to at least one operational boundary model, applying the measured operating parameter or modeled operating parameter or parameters to at least one scheduling algorithm, comparing the output of the operational boundary model or models to the at output of the scheduling algorithm or algorithms to determine at least one error term, and closing loop on the one error term or terms by adjusting at least one turbine control effector during operation of the turbine

Methods and Systems for Model-Based Control of Gas Turbines

A method for simulating a gas turbine including the steps of: sensing values of a plurality of first operating parameters of an actual gas turbine; applying the sensed values of the first operating parameters to a model of the gas turbine, wherein the model generates a plurality of predicted second operating parameters; determining difference values between the predicted second operating parameters and corresponding sensed second operating parameters of the actual gas turbine; modifying the difference values based on tuning factors generated by a Kalman filter gain matrix during operation of the gas turbine, and using the adjusted difference values to adjust the model of the gas turbine. The method may further comprise generating the tuning factors by applying to the model the sensed values of the plurality of first operating parameters and perturbated values of the adjusted different values to determine optimal tuning factors.

Method and system for gas turbine engine simulation using adaptive Kalman filter

Embodiments of the invention can provide systems and methods for initializing dynamic model states using a Kalman or similar type filter. In one embodiment, an adaptable model-based control system for controlling a gas turbine engine is provided. The system can include at least one sensor adapted to obtain dynamic-type information about a current state of the engine. Furthermore, the system can include an engine model adapted to receive information from the sensor, and further adapted to reflect the current state of the engine. In addition, the system can include a model filter adapted to initialize the model with at least a portion of the dynamic-type information, wherein at least one value based at least in part on the dynamic-type information is input to the engine model. Moreover, the model can be further adapted to determine an output from the engine model based at least in part on the at least one value. Further, the system can include a controller adapted to determine an engine control action based at least in part on the output from the engine model, and further adapted to output a control command to implement the engine control action.

Systems and Methods for Initializing Dynamic Model States Using a Kalman Filter

A method for determining a target exhaust temperature for a gas turbine including: determining a target exhaust temperature based on a compressor pressure condition; determining a temperature adjustment to the target exhaust temperature based on at least one parameter of a group of parameters consisting of specific humidity, compressor inlet pressure loss and turbine exhaust back pressure; and adjusting the target exhaust temperature by applying the temperature adjustment.

Timothy Andrew Healy

Papers

Method and system for incorporating an emission sensor into a gas turbine controller

Methods and Systems for Model-Based Control of Gas Turbines

Method and system for gas turbine engine simulation using adaptive Kalman filter

Systems and Methods for Initializing Dynamic Model States Using a Kalman Filter

Method for controlling fuel splits to gas turbine combustor