A method for predicting a combustion error type of a combustion flame. A raw signal of an error parameter of the combustion flame within a predefined time span is measured, the error parameter is adapted for determining the combustion error type. A predefined frequency range from the raw signal is extracted using a by-pass filter, where the raw signal is decomposed. The number of peaks of the predefined frequency range within the time span is counted. An actual reference value is determined by dividing the number of counted peaks by the time span. The actual reference value is compared with a nominal reference value, wherein the nominal reference value is determined by dividing a predefined number of peaks of the predefined frequency range by the time span, so that the combustion error type is predictable if the actual reference value differs to the nominal reference value.

A system and method for calibrating flame current in a furnace is disclosed. The method includes initiating combustion within a combustion chamber by allowing flow of the fuel mixture to the combustion chamber; receiving, from a sensor, signals indicative of a flow rate of the air to the combustion chamber; receiving, from a flame rod sensor, signals indicative of a flame current of the combustion chamber; varying a flow rate of the air to the combustion chamber; receiving, from the flame rod sensor, responsive to varying flow rate of the air to the combustion chamber, signals indicative of a change in the flame current of the combustion chamber; and determining, based on varying flow rate of the air to the combustion chamber, and the change in flame current of the combustion chamber, a correlation between the flow rate of the air, and the flame current of the combustion chamber.

A sensitivity parameter storing portion stores, as known sensitivity parameters owned by a flame sensor, reference received light quantity, reference pulse width, probability of regular discharge, and probabilities of non-regular discharge in advance. The discharge probability is calculated based on the number of drive pulses applied to the flame sensor and the number of discharges determined to have occurred in the flame sensor having received the drive pulses. The calculated discharge probability and the known sensitivity parameters are used to calculate the received light quantity per unit time received by the flame sensor.

A method of operating a heat releasing reactor producing product gas. The method includes steps of (a) monitoring a current load of the reactor, (b) finding such a numerical value for a current computational maximum momentary load for which at least one product gas factor computed using currently monitored process data with a numerical model of the reactor fulfills an acceptance condition, and selecting the numerical value as the current computational maximum momentary load, (c) indicating the current computational maximum momentary load to the operator and/or, if the current load is (c1) less than the current computational maximum momentary load, (c1i) indicating the operator that the load may be increased, and/or (c1ii) automatically increasing the load, and/or (c2) greater than the current computational maximum momentary load, (c2i) indicating the operator that the load exceeds the current computational maximum boiler momentary load, and/or (c2ii) automatically reducing the boiler load.

An anomaly detection device detects an abnormal condition of a coal-fired boiler and includes a correlation calculating unit to acquire an index representing a correlation between a first parameter and a second parameter, the first parameter that is any one of a power generation amount and a first physical quantity, and the second parameter that is any one of a pressure of an exhaust gas and a second physical quantity and an anomaly determination unit configured to detect the abnormal condition in a case in which the index deviates from a predetermined range.

The invention relates to a computing device and method for estimating (100) a combustion efficiency value during flaring, over a time period, said method comprising the following steps: Acquiring (140) a video stream of the flare flame (61) over the time period; Segmenting (150) the video stream in several video segments, each video segments being associated with a video segment duration; Analyzing (160) the video segments, using a correlation model, so as to classify each video segments in at least one flame state category; andComputing (170) the combustion efficiency value, said computing (170) step using the video segment durations and a plurality of unburned reduction index values, each of said unburned reduction index values being specific to one of the flame state categories, specific to the industrial plant and calculated using computational fluid dynamics.

A system and method for optimizing combustion in boiler. The optimization of the combustion in the boiler involves obtaining various data relating to the flow of fuel and air to burners of the boiler and the flame in the burner zone of the boiler that is generated from the introduction of the fuel and air into the burner zone. The data is used to determine air flows to the burners. The data and air flows are used to balance air and fuel at individual burners by manipulating air to match the fuel flow. The balancing of air and fuel at individual burners by manipulating air to match the fuel flow uses a guided search optimization algorithm that mixes stoichiometry determinations with a custom search algorithm that accounts for measurement inaccuracies and unexpected interactions between burners.