Abstract: Systems and methods for simultaneously analyzing time-series and dominant frequency data from both a process domain and an electrical domain of a facility, such as an industrial plant, to detect instances of deviation from optimal, normal, or other predefined process conditions or electrical trips. Detecting when changes in frequencies occur in the time-series data creates a time-series of the changes in dominant frequencies. A data analysis server detects instances of deviation from the predefined process conditions or electrical trips by detecting one or more of correlations, patterns, clusters, and the like in the rates of change. The data analysis server employs one or more of statistical analyses, data mining, machine learning, deep neural networks, parallel coordinate analyses, etc. to identify the deviations and predict or detect onset of an undesired event such as a process perturbation or electrical trip.

Abstract: Provided herein are a control system and a control method for pest killing by microwave, and a computer device and a storage medium thereof. The control system for pest killing by microwave includes: an inactivation module; an electromagnetic shielding module; a conveyor belt; and a microwave pest killing device, which is a waveguide structure with two open ends and four closed sides. The pest killing method maintains the temperature of the tobacco packages within a specific range, ensuring the quality of the tobacco while effectively inactivating the pests, thereby enhancing the economic efficiency of tobacco factories. The pest killing method employs a reactance counter-current type electromagnetic shielding method, which ensures the smooth operation of the conveyor belt without affecting the health of the operators or the safety of the environment.

Abstract: A system for energy management in a water treatment comprises at least one processor coupled to at least one non-transitory computer-readable medium storing a high-level energy optimization machine learned model (HLEOMLM) and a low-level energy optimization machine learned model (LLEOMLM), and a clean-in-place (CIP) system. In general, the processor is configured to obtain input data from an input data source, and constraints data from a constraints data source. The processor executes the HLEOMLM and LLEOMLM to process the input and constraints data to provide as output a long-term maintenance schedule that optimizes energy consumption and a current-maintenance schedule that optimizes operating cost for the water treatment plant. The CIP system receives the output from the processor and executes at least one of a CIP maintenance process and MR maintenance process in response to the output.

Abstract: A system for energy management in a water treatment comprises at least one processor coupled to at least one non-transitory computer-readable medium storing a high-level energy optimization machine learned model (HLEOMLM) and a low-level energy optimization machine learned model (LLEOMLM), and a clean-in-place (CIP) system. In general, the processor is configured to obtain input data from an input data source, and constraints data from a constraints data source. The processor executes the HLEOMLM and LLEOMLM to process the input and constraints data to provide as output a long-term maintenance schedule that optimizes energy consumption and a current-maintenance schedule that optimizes operating cost for the water treatment plant. The CIP system receives the output from the processor and executes at least one of a CIP maintenance process and MR maintenance process in response to the output.

Abstract: Provided herein are a control system and a control method for pest killing by microwave, and a computer device and a storage medium thereof. The control system for pest killing by microwave includes: an inactivation module; an electromagnetic shielding module; a conveyor belt; and a microwave pest killing device, which is a waveguide structure with two open ends and four closed sides. The pest killing method maintains the temperature of the tobacco packages within a specific range, ensuring the quality of the tobacco while effectively inactivating the pests, thereby enhancing the economic efficiency of tobacco factories. The pest killing method employs a reactance counter-current type electromagnetic shielding method, which ensures the smooth operation of the conveyor belt without affecting the health of the operators or the safety of the environment.

Abstract: Systems and methods for simultaneously analyzing time-series and dominant frequency data from both a process domain and an electrical domain of a facility, such as an industrial plant, to detect instances of deviation from optimal, normal, or other predefined process conditions or electrical trips. Detecting when changes in frequencies occur in the time-series data creates a time-series of the changes in dominant frequencies. A data analysis server detects instances of deviation from the predefined process conditions or electrical trips by detecting one or more of correlations, patterns, clusters, and the like in the rates of change. The data analysis server employs one or more of statistical analyses, data mining, machine learning, deep neural networks, parallel coordinate analyses, etc. to identify the deviations and predict or detect onset of an undesired event such as a process perturbation or electrical trip.

Abstract: A method and system of analyzing health of a solar tracker, including confirming solar tracker is in a starting position, driving solar tracker through a range of angles, collecting data regarding performance of solar tracker, analyzing the collected data, and presenting one or more aspects of the collected data on a user interface indicating the health of the solar tracker.

Abstract: A method can include generating a first predictive model associated with a first well of a plurality of wells in a cluster, the first well configured to produce a first fluid output and a second well of the plurality of wells configured to produce a second fluid output, the first and the second fluid outputs flow to a cluster manifold via a system of pipelines in the cluster. The method includes receiving data characterizing one or more pressure measurements in the cluster and indicative of one or more pressure values associated with the first fluid output, and the second fluid output. The method can further include recalibrating the first predictive model based on the one or more of the pressure measurements and historical data associated with the first well. Related apparatus, systems, articles, and techniques are also described.

Abstract: In one embodiment, a water desalination and power generation system includes a power generation subsystem, a water desalination subsystem, and an ejector that links the power generation subsystem and the water desalination subsystem, the ejector being adapted to entrain working fluid steam that has exited the water desalination subsystem into working fluid steam that has exited the power generation subsystem to generate mixed steam that drives the water desalination subsystem.

Abstract: In one embodiment, a water desalination and power generation system includes a power generation subsystem, a water desalination subsystem, and an ejector that links the power generation subsystem and the water desalination subsystem, the ejector being adapted to entrain working fluid steam that has exited the water desalination subsystem into working fluid steam that has exited the power generation subsystem to generate mixed steam that drives the water desalination subsystem.