Methods, devices, and systems for energy consumption modeling are described herein. One device includes a memory, and a processor configured to execute executable instructions stored in the memory to assign energy consumption data to an on state and an off state of a device, generate a model configured to predict a future state of the device and a duration of the future state based on a duration of a current state of the device, a duration of a previous state of the device, and operating conditions of the device, and predict a future energy consumption of the device using the assigned energy consumption data and the generated model.

A system and method for monitoring underground drilling in which vibration is monitored by creating a model of the drill string using finite element techniques or finite difference techniques and (i) predicting vibration by inputting real time values of operating parameters into the model, and then adjusting the model to agree with measured vibration data, (ii) predicting the weight on bit and drill string and mud motor speeds at which resonance will occur, as well as when stick-slip will occur, so that the operator can avoid operating regimes that will result in high vibration, (iii) determining vibration and torque levels along the length of the drill string based on the measured vibration and torque at one or more locations, (iv) determining the remaining life of critical components of the drill string based on the history of the vibration to which the components have been subjected, and (v) determining the optimum drilling parameters that will avoid excessive vibration of the drill string.

Diagnostic and response systems and methods for a fluid power system acquire data from pressure and temperature sensors disposed in the fluid power system, analyze the data in a failure algorithm to build a history of cumulative damage to hoses in the fluid power system, communicates an indication of potential imminent hose failure to a central location when a level of the cumulative damage indicates imminent failure of a hose, analyze the information at the central location to determine an appropriate response, and transmit information about the fluid power system, including location, and identification of the hose about to fail to a response unit. The response unit responds to the location and replaces the component prior to failure, or the communication might include information that the hose has failed, such that the response unit replaces the failed hose to return the fluid power system to normal operation.

A power strip may automatically disconnect a wired connection in response to received weather alert data based on a configuration file including one or more user preference settings. The power strip may include a receiver for a National Weather Service Specific Area Message Encoding system message including an alert type. The power strip may process the message and disconnect a wired connection based on the preference settings. A timer function may also define a time period that the power strip monitors its receiver for weather alert data and automatically disconnects and reconnects the wired connections.

A cam profile data creation apparatus sets cam profile data in which a phase of a drive shaft is associated with a displacement (set displacement) of a driven shaft, a rotation speed of the drive shaft, and an allowable error for the displacement of the driven shaft. A displacement (predictive displacement) of the driven shaft when the drive shaft rotates at the set rotation speed is found based on the set cam profile data, the set displacement and the predictive displacement are displayed to be comparable, and further a form of the display is changed depending on whether an error between the set displacement and the predictive displacement falls within the range of the allowable error.

A turbine blade maximum vibration response prediction method for predicting a maximum vibration response acting on a plurality of turbine moving blades provided along the circumferential direction of a turbine rotor includes the steps of: gaining, before turbine operation start, prior response data that is distribution data on vibration response of all the turbine moving blades for each turbine operating condition; gaining, by using the prior response data, operation response data that is distribution data on the vibration response of all the turbine moving blades during the operation of the turbine; and predicting, from the operation response data, the turbine moving blade of all the turbine moving blades on which the maximum vibration response is acting, and the magnitude of the maximum vibration response.

A multiple-input/multiple-output control routine in the form of a model predictive control (MPC) routine operates with wireless or other sensors that provide non-periodic, intermittent or otherwise delayed process variable measurement signals at an effective rate that is slower than the MPC controller scan or execution rate. The wireless MPC routine operates normally even when the measurement scan period for the controlled process variables is significantly larger than the operational scan period of the MPC controller routine, while providing control signals that enable control of the process in a robust and acceptable manner. During operation, the MPC routine uses an internal process model to simulate one or more measured process parameter values without performing model bias correction during the scan periods at which no new process parameter measurements are transmitted to the controller. When a new measurement for a particular process variable is available at the controller, the model prediction and simulated parameter values are updated with model bias correction based on the new measurement value, according to traditional MPC techniques.

Embodiments of the present invention include an occupancy sensing unit configured to monitor an environment illuminated by a lighting fixture. An inventive occupancy sensing unit may include an occupancy sensor to detect radiation indicative of at least one occupancy event in the environment illuminated by the lighting fixture according to sensing parameters. The occupancy sensor can be coupled to a memory that logs sensor data, which represent the occupancy events, provided by the occupancy sensor. A processor coupled to the memory performs an analysis of the sensor data logged in the memory and adjusts the sensing parameters of the occupancy sensor based on the analysis.

Methods, devices, and systems for energy consumption modeling are described herein. One device includes a memory, and a processor configured to execute executable instructions stored in the memory to assign energy consumption data to an on state and an off state of a device, generate a model configured to predict a future state of the device and a duration of the future state based on a duration of a current state of the device, a duration of a previous state of the device, and operating conditions of the device, and predict a future energy consumption of the device using the assigned energy consumption data and the generated model.

An optimized operation schedule of a control-target apparatus is ensured while maximally reducing a burden share to a facility operator. An energy predictor sets, for a control-target apparatus, a predicted value of energy consumption or energy supply within a predetermined future time period based on process data. A schedule optimizer optimizes an operation schedule of the control-target apparatus within the predetermined time period with a predetermined evaluation barometer based on the predicted value, the characteristic of the control-target apparatus, and the process data. An approval request determiner determines a necessity of an approval for a latest operation schedule based on a preset determining condition. A determination result transmitter transmits a determination result by the approval request determiner.