A facility for control of a combustion apparatus comprising: a memory storing a limit value and a correction factor; a communication connection to a sensor and an actuator; and a processor. The processor: receives an input signal from the sensor; uses the signal to form a measured value specifying a fuel air ratio, an air ratio, and/or an oxygen content; and loads the limit value and compares the measured value with the limit value. If the measured value is less than or greater than the limit value, the processor either loads the correction factor and determines a correction value as a function of the limit value, the correction factor, and the measured value, or loads the stored correction value from the memory, and then creates an output signal as a function of the correction value and sends the output signal to the actuator.

A method and apparatus for controlling a process in a system comprising pre-processing of a raw material, processing the pre-processed raw material and acquisition of the result of the processing of the pre-processed raw material, comprising the steps of: capturing input and output variables of the pre-processing; capturing output variables of the processing of the pre-processed raw material; creating a first, second and third process model for at least two different time scales, which describes the effects of adapting the pre-processing of raw material, the effects of adapting the processing of the pre-processed raw material, the effects of adapting the pre-processing of raw material and adapting the processing of pre-processed raw material on the output variables of the processing of pre-processed raw material; wherein the process in the system is controlled using the prediction of the process model which currently provides the best predictions for the process in the system.

The present disclosure relates to a flame transfer function measurement system for predicting and reducing combustion instability in which is possible to obtain at once the flame transfer function in the full frequency range by conducting the test while automatically converting the range of the frequency to be measured. Accordingly, there is no need to conduct the test repeatedly while changing the frequency, and therefore, there is an effect of obtaining the flame transfer function in the full frequency range in a very short period of time.

A heat controlled oven system includes a plurality of oven levels, including an oven belt and gas burners; a gas flow network, including a gas supply line, a variable flow control valve, and on/off flow control valves; and a heat control unit, including a processor, a non-transitory memory, and input/output component, a heat modeler, a heat manager, a feedback controller, and a valve controller, such that the heat control unit is configured to calculate an estimated heat demand to adjust to a temperature set point, based on a heat model of the at least one oven level, and further calculates an optimized heat demand using a control loop feedback algorithm. Also disclosed is a method of heat calculation for an oven, including defining a heat model, calculating and optimizing the estimated heat demand, calculating and setting a variable valve position for the gas burners.

Systems and methods for firing an insulator is described. A kiln includes at least three zones on a wall of the kiln, a processing unit, and at least three PID controllers. The at least three zones have at least three burners arranged vertically. The processing unit determines firing ratio information for the at least three zones. Each of the PID controllers corresponds to a zone of the at least three zones. The at least three PID controllers control supply of gas and air to the at least three burners of the at least three zones based on the firing ratio information.

A flame analytics system that may incorporate a burner, one or more sensors at the burner, a historical database connected to the one or more sensors, a model training module connected to the historical database, and a runtime algorithm module connected to the one or more sensors and the model training module. The runtime algorithm may compare realtime data from the one or more sensors and historical data from the model training module in accordance with a machine learning algorithm. The system may further incorporate a fault detection module connected to the runtime algorithm module, a fault diagnostics module connected to the fault detection module, and an enunciator connected to the fault detection module. The one or more sensors may also include having video or acoustic sensitivity of combustion in the burner.

A flame analytics system that may incorporate a burner, one or more sensors at the burner, a historical database connected to the one or more sensors, a model training module connected to the historical database, and a runtime algorithm module connected to the one or more sensors and the model training module. The runtime algorithm may compare realtime data from the one or more sensors and historical data from the model training module in accordance with a machine learning algorithm. The system may further incorporate a fault detection module connected to the runtime algorithm module, a fault diagnostics module connected to the fault detection module, and an enunciator connected to the fault detection module. The one or more sensors may also include having video or acoustic sensitivity of combustion in the burner.

A flame analytics system that may incorporate a burner, one or more sensors at the burner, a historical database connected to the one or more sensors, a model training module connected to the historical database, and a runtime algorithm module connected to the one or more sensors and the model training module. The runtime algorithm may compare realtime data from the one or more sensors and historical data from the model training module in accordance with a machine learning algorithm. The system may further incorporate a fault detection module connected to the runtime algorithm module, a fault diagnostics module connected to the fault detection module, and an enunciator connected to the fault detection module. The one or more sensors may also include having video or acoustic sensitivity of combustion in the burner.

A heat controlled oven system includes a plurality of oven levels, including an oven belt and gas burners; a gas flow network, including a gas supply line, a variable flow control valve, and on/off flow control valves; and a heat control unit, including a processor, a non-transitory memory, and input/output component, a heat modeler, a heat manager, a feedback controller, and a valve controller, such that the heat control unit is configured to calculate an estimated heat demand to adjust to a temperature set point, based on a heat model of the at least one oven level, and further calculates an optimized heat demand using a control loop feedback algorithm. Also disclosed is a method of heat calculation for an oven, including defining a heat model, calculating and optimizing the estimated heat demand, calculating and setting a variable valve position for the gas burners.

A heat controlled oven system includes a plurality of oven levels, including an oven belt and gas burners; a gas flow network, including a gas supply line, a variable flow control valve, and on/off flow control valves; and a heat control unit, including a processor, a non-transitory memory, and input/output component, a heat modeler, a heat manager, a feedback controller, and a valve controller, such that the heat control unit is configured to calculate an estimated heat demand to adjust to a temperature set point, based on a heat model of the at least one oven level, and further calculates an optimized heat demand using a control loop feedback algorithm. Also disclosed is a method of heat calculation for an oven, including defining a heat model, calculating and optimizing the estimated heat demand, calculating and setting a variable valve position for the gas burners.