Abstract: According to some embodiments, a message generated by a downstream device is received at upstream device. The message may, for example, be received via a peripheral interface and may not require a response. It may then be determined that an error is associated with the message, and an alert message may be sent from the upstream device to the downstream device via the peripheral interface.

Abstract: A method of monitoring and controlling the combustion dynamics of a gas turbine engine system is provided. The system includes at least one gas turbine that includes at least one combustor can. The method includes receiving a signal from a gas turbine engine sensor that is indicative of combustion dynamics in at least one of the combustor cans, processing the received signal to determine a probability of lean blowout for at least one combustor can, and controlling the gas turbine engine system to facilitate reducing a probability of a lean blowout (LBO) event using the determined probability of lean blowout.

Abstract: A method, system and software for reducing combustion chamber to chamber variation in a multiple-combustion chamber turbine system comprising sensing dynamic combustion pressure tones emitted from combustion chambers in a multiple combustion chamber turbine and determining a combustion chamber stratification index for the combustion chambers from the dynamic combustion pressure tones emitted for the combustion chambers to record and/or tune combustion chamber performance variations in the multiple-chamber combustion turbine system.

Abstract: A method for predicting lean blow-outs (LBOs) in a gas turbine engine includes extracting a plurality of tones in pressure signals representative of pressure within monitored combustor cans, tracking a frequency of a hot tone in each monitored can, and utilizing the extracted tones and the tracked frequency to determine a probability of an LBO.

Abstract: A system for ranking combustion chambers in a gas turbine in order of chamber combustion temperature including: at least one fuel nozzle supplying fuel to the combustion chambers at a predetermined fuel rate abnormally near a lean blow out (LBO) condition of the chambers; at least one dynamic pressure sensor in each chamber sensing combustion dynamic pressures in said combustion chambers and generating dynamic pressure signals representative of the dynamic pressure in each of said combustion chambers, wherein the dynamic pressure signals provide information regarding the dynamic pressure at a plurality of frequencies; a signal band pass filter segmenting the signals into a plurality of predefined frequency bands comprising a lean blow out (LBO) precursor frequency band, a cold tone frequency band and a hot tone frequency band; a processor determining a value for each chamber representative of amplitudes of the signals in each of LBO precursor frequency band, the cold tone frequency band and the hot tone frequ

Abstract: A gas turbine system is provided. The system includes a gas turbine engine including at least one combustor can, at least one of a combustor dynamics pressure sensor and flame sensor coupled to at least one of the combustor cans, the sensor configured to monitor combustion in each respective can and transmit a signal indicative of combustion in each respective can, and at least one control system configured to receive the signal from said at least one sensor. The control system is programmed to filter the combustion signal to determine the presence of a lean blowout (LBO) precursor, determine a probability of LBO from the filtered signal, and control the gas turbine system to facilitate reducing the probability of LBO.

Abstract: A method of monitoring and controlling the combustion dynamics of a gas turbine engine system is provided. The system includes at least one gas turbine that includes at least one combustor can. The method includes receiving a signal from a gas turbine engine sensor that is indicative of combustion dynamics in at least one of the combustor cans, processing the received signal to determine a probability of lean blowout for at least one combustor can, and controlling the gas turbine engine system to facilitate reducing a probability of a lean blowout (LBO) event using the determined probability of lean blowout.

Abstract: A system for ranking combustion chambers in a gas turbine in order of chamber combustion temperature including: at least one fuel nozzle supplying fuel to the combustion chambers at a predetermined fuel rate abnormally near a lean blow out (LBO) condition of the chambers; at least one dynamic pressure sensor in each chamber sensing combustion dynamic pressures in said combustion chambers and generating dynamic pressure signals representative of the dynamic pressure in each of said combustion chambers, wherein the dynamic pressure signals provide information regarding the dynamic pressure at a plurality of frequencies; a signal band pass filter segmenting the signals into a plurality of predefined frequency bands comprising a lean blow out (LBO) precursor frequency band, a cold tone frequency band and a hot tone frequency band; a processor determining a value for each chamber representative of amplitudes of the signals in each of LBO precursor frequency band, the cold tone frequency band and the hot tone frequ

Abstract: A method for identifying combustion characteristics of a plurality combustion chambers in a gas turbine, the method including: supplying fuel to the combustion chambers at a predetermined fuel rate; sensing combustion dynamic pressure in said plurality of combustion chambers and generating dynamic pressure signals representative of the dynamic pressure in each of said combustion chambers, wherein the dynamic pressure signals provide information regarding the dynamic pressure at a plurality of frequencies; segmenting the signals into a plurality of predefined frequency bands; determining a characteristic value for each of the segmented signals, and identifying an order of combustion chambers based on the characteristic value.

Abstract: According to some embodiments, a message generated by a downstream device is received at upstream device. The message may, for example, be received via a peripheral interface and may not require a response. It may then be determined that an error is associated with the message, and an alert message may be sent from the upstream device to the downstream device via the peripheral interface.

Abstract: A method, system and software for reducing combustion chamber to chamber variation in a multiple-combustion chamber turbine system comprising sensing dynamic combustion pressure tones emitted from combustion chambers in a multiple combustion chamber turbine and determining a combustion chamber stratification index for the combustion chambers from the dynamic combustion pressure tones emitted for the combustion chambers to record and/or tune combustion chamber performance variations in the multiple-chamber combustion turbine system.

Abstract: A method for identifying combustion characteristics of a plurality combustion chambers in a gas turbine, the method including: supplying fuel to the combustion chambers at a predetermined fuel rate; sensing combustion dynamic pressure in said plurality of combustion chambers and generating dynamic pressure signals representative of the dynamic pressure in each of said combustion chambers, wherein the dynamic pressure signals provide information regarding the dynamic pressure at a plurality of frequencies; segmenting the signals into a plurality of predefined frequency bands; determining a characteristic value for each of the segmented signals, and identifying an order of combustion chambers based on the characteristic value.

Abstract: A method of monitoring and controlling the combustion dynamics of a gas turbine engine system is provided. The system includes at least one gas turbine that includes at least one combustor can. The method includes receiving a signal from a gas turbine engine sensor that is indicative of combustion dynamics in at least one of the combustor cans, processing the received signal to determine a probability of lean blowout for at least one combustor can, and controlling the gas turbine engine system to facilitate reducing a probability of a lean blowout (LBO) event using the determined probability of lean blowout.

Abstract: A method for predicting lean blow-outs (LBOs) in a gas turbine engine includes extracting a plurality of tones in pressure signals representative of pressure within monitored combustor cans, tracking a frequency of a hot tone in each monitored can, and utilizing the extracted tones and the tracked frequency to determine a probability of an LBO.

Abstract: A computer implemented process is provided for assessing and characterizing the degree of success or failure of an operational event of a machine system such as a fluid compressor machine or turbine machine or the like on a continuous numerical scale. The computer implemented process develops and tracks machine unit signatures, machine site signatures and machine fleet signatures to evaluate various operational events and provide fault detection. At least some sensor data acquired from the machine system during an operational event is transformed to correct or at least reduce variabilities in the data caused by ambient conditions and fuel quality. The transformed data is then analyzed using statistical methods to determine how closely the operational event conforms to an expected normal behavior and the information is used to develop a single comprehensive quality assessment of the event.

Abstract: A computer implemented process is provided for assessing and characterizing the degree of success or failure of an operational event of a machine system such as a fluid compressor machine or turbine machine or the like on a continuous numerical scale. The computer implemented process develops and tracks machine unit signatures, machine site signatures and machine fleet signatures to evaluate various operational events and provide fault detection. At least some sensor data acquired from the machine system during an operational event is transformed to correct or at least reduce variabilities in the data caused by ambient conditions and fuel quality. The transformed data is then analyzed using statistical methods to determine how closely the operational event conforms to an expected normal behavior and the information is used to develop a single comprehensive quality assessment of the event.