Time-averaged active controller for turbofan engine fan noise reduction

Abstract

An active control system has been developed and used experimentally on an operational turbofan engine to reduce inlet tonal noise at the fan blade passage frequency. Both single channel and multichannel systems were tested. The control approach used is the feedforward derivative measurement time-averaged adaptive algorithm. This algorithm is capable of adapting to a nonstationary system, requiring no prior knowledge of the system. A reference sensor mounted in the casing of the fan provides the fan blade passing frequency reference signal to the controller. Microphones with a large sensing area are placed in the acoustic far field of the engine. The control algorithms minimize a cost function, the sum of the error signal mean-square-values, by activating loudspeakers that are mounted around the inlet of the engine. The control signals are obtained by filtering the reference signal with finite impulse response digital filters. The control algorithm finds the optimum filter weights by using statistical estimates of the cost function to be minimized. A single channel control system was tested on an axisymmetric dominant mode case and produced reductions of up to 17 dB at the error microphone. The controller maintained reductions in the fan tone even as the engine speed was increased. In a traverse of the radiated sound field of the engine the fan blade passage tone was reduced over a sector of 30 deg around the error sensor with a considerable spillover increase in the fan tone outside of this sector. Two six-channel control systems were developed and tested on both axisymmetric and spinning mode dominant cases. Reductions of up to 19.7 dB were achieved over large sectors around the error microphones with significantly reduced spillover. Nomenclature C = cost function D = diameter of engine at the fan stage d = disturbance signal = error signal = transfer function = input signal to control sources = adaptive finite impulse response filter coefficients = reference signal = control source output signal = coherence = convergence parameter

Development of an Experimental Rig for Investigation of Higher Order Modes in Ducts

“…In several previous duct noise control experiments 19,20,21 , an adaptive feedforward control algorithm was used to minimize acoustic energy in a duct due to an undesirable noise source. In the current application, the same type of control algorithm is used to drive measured wall pressures to a distribution corresponding to a specified hard-wall cut on duct mode at the test frequency.…”