Enhanced demodulation band selection based on Operational Modal Analysis (OMA) for bearing diagnostics
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A flywheel magnetic bearing (MB) pulse width modulated power amplifier (PWM) configuration is selected to minimize noise generated by the PWMs in the flywheel position sensor system. Two types of noise are addressed: beat frequency noise caused by variations in PWM switching frequencies, and demodulation noise caused by demodulation of high order harmonics of the switching voltage into the MB control band. Beat frequency noise is eliminated by synchronizing the PWM switch frequencies, and demodulation noise is minimized by selection of a switching frequency which does not have harmonics at the carrier frequency of the sensor. The recommended MB PWM system has five synchronized PWMs switching at a non-integer harmonic of the sensor carrier.
A generalized modulation scheme, which includes minimum shift keying (MSK) and staggered quadriphase shift keying (SQPSK) as special cases, is analyzed. The general modulator is realized as a one-input, two-output sequence transducer whose outputs select the carrier signal for each band. This form of the modulator has the practical advantage of not requiring any RF filtering since there is no actual mixing of the carriers with the modulating signals. It is shown that the optimum demodulator (whether hard-decision or soft-decision) always can make its decisions from the received waveform over two bands when the interference is additive white Gaussian noise, thus generalizing a well-known result for hard decision demodulation of MSK and SQPSK signals. The power spectra of MSK and SQPSK signals are derived to isolate the role played by coherency between the modulating signals and the carriers.
Ground station networks connected to the cloud allow space missions to have global communications coverage without operating their own infrastructure. In this work, we describe the communications architecture for the TechEdSat-13 mission, which performed the first in-space characterization of a neuromorphic processor. The mission utilizes a commercial provider for S-band downlinks. A suite of cloud services and open-source software such as GNU Radio are leveraged to demodulate signals received by an AWS ground station during passes with TechEdSat-13 and store recovered data. Once a pass is scheduled, the entire process takes place without human intervention. On-orbit results the past year of operations are presented, demonstrating the advantages of this approach over traditional operator-owned ground stations. Use of software-defined radio makes possible custom signal processing. The homogeneity of apertures and their interfaces to the cloud simplifies scaling across many sites. This abundance of candidate links lays the groundwork for intelligent scheduling agents to optimize pass selection across several factors, automatically recover from failed contacts, and gather metrics to learn from past performance.