6 research outputs found
PROPOSED MIDDLEWARE SOLUTION FOR RESOURCE-CONSTRAINED DISTRIBUTED EMBEDDED NETWORKS
The explosion in processing power of embedded systems has enabled distributed embedded networks to perform more complicated tasks. Middleware are sets of encapsulations of common and network/operating system-specific functionality into generic, reusable frameworks to manage such distributed networks. This thesis will survey and categorize popular middleware implementations into three adapted layers: host-infrastructure, distribution, and common services. This thesis will then apply a quantitative approach to grading and proposing a single middleware solution from all layers for two target platforms: CubeSats and autonomous unmanned aerial vehicles (UAVs). CubeSats are 10x10x10cm nanosatellites that are popular university-level space missions, and impose power and volume constraints. Autonomous UAVs are similarly-popular hobbyist-level vehicles that exhibit similar power and volume constraints. The MAVLink middleware from the host-infrastructure layer is proposed as the middleware to manage the distributed embedded networks powering these platforms in future projects. Finally, this thesis presents a performance analysis on MAVLink managing the ARM Cortex-M 32-bit processors that power the target platforms
In-Ear-Voice: Towards Milli-Watt Audio Enhancement With Bone-Conduction Microphones for In-Ear Sensing Platforms
The recent ubiquitous adoption of remote conferencing has been accompanied by
omnipresent frustration with distorted or otherwise unclear voice
communication. Audio enhancement can compensate for low-quality input signals
from, for example, small true wireless earbuds, by applying noise suppression
techniques. Such processing relies on voice activity detection (VAD) with low
latency and the added capability of discriminating the wearer's voice from
others - a task of significant computational complexity. The tight energy
budget of devices as small as modern earphones, however, requires any system
attempting to tackle this problem to do so with minimal power and processing
overhead, while not relying on speaker-specific voice samples and training due
to usability concerns.
This paper presents the design and implementation of a custom research
platform for low-power wireless earbuds based on novel, commercial, MEMS
bone-conduction microphones. Such microphones can record the wearer's speech
with much greater isolation, enabling personalized voice activity detection and
further audio enhancement applications. Furthermore, the paper accurately
evaluates a proposed low-power personalized speech detection algorithm based on
bone conduction data and a recurrent neural network running on the implemented
research platform. This algorithm is compared to an approach based on
traditional microphone input. The performance of the bone conduction system,
achieving detection of speech within 12.8ms at an accuracy of 95\% is
evaluated. Different SoC choices are contrasted, with the final implementation
based on the cutting-edge Ambiq Apollo 4 Blue SoC achieving 2.64mW average
power consumption at 14uJ per inference, reaching 43h of battery life on a
miniature 32mAh li-ion cell and without duty cycling
Optimisation of vibration monitoring nodes in wireless sensor networks
This PhD research focuses on developing a wireless vibration condition monitoring
(CM) node which allows an optimal implementation of advanced signal processing
algorithms. Obviously, such a node should meet additional yet practical requirements
including high robustness and low investments in achieving predictive maintenance.
There are a number of wireless protocols which can be utilised to establish a wireless
sensor network (WSN). Protocols like WiFi HaLow, Bluetooth low energy (BLE),
ZigBee and Thread are more suitable for long-term non-critical CM battery powered
nodes as they provide inherent merits like low cost, self-organising network, and low
power consumption. WirelessHART and ISA100.11a provide more reliable and robust
performance but their solutions are usually more expensive, thus they are more suitable
for strict industrial control applications.
Distributed computation can utilise the limited bandwidth of wireless network and
battery life of sensor nodes more wisely. Hence it is becoming increasingly popular in
wireless CM with the fast development of electronics and wireless technologies in
recent years. Therefore, distributed computation is the primary focus of this research in
order to develop an advanced sensor node for realising wireless networks which allow
high-performance CM at minimal network traffic and economic cost.
On this basis, a ZigBee-based vibration monitoring node is designed for the evaluation
of embedding signal processing algorithms. A state-of-the-art Cortex-M4F processor is
employed as the core processor on the wireless sensor node, which has been optimised
for implementing complex signal processing algorithms at low power consumption.
Meanwhile, an envelope analysis is focused on as the main intelligent technique
embedded on the node due to the envelope analysis being the most effective and general
method to characterise impulsive and modulating signatures. Such signatures can
commonly be found on faulty signals generated by key machinery components, such as
bearings, gears, turbines, and valves.
Through a preliminary optimisation in implementing envelope analysis based on fast
Fourier transform (FFT), an envelope spectrum of 2048 points is successfully achieved
on a processor with a memory usage of 32 kB. Experimental results show that the simulated bearing faults can be clearly identified from the calculated envelope
spectrum. Meanwhile, the data throughput requirement is reduced by more than 95% in
comparison with the raw data transmission. To optimise the performance of the
vibration monitoring node, three main techniques have been developed and validated:
1) A new data processing scheme is developed by combining three subsequent
processing techniques: down-sampling, data frame overlapping and cascading. On
this basis, a frequency resolution of 0.61 Hz in the envelope spectrum is achieved on
the same processor.
2) The optimal band-pass filter for envelope analysis is selected by a scheme, in which
the complicated fast kurtogram is implemented on the host computer for selecting
optimal band-pass filter and real-time envelope analysis on the wireless sensor for
extracting bearing fault features. Moreover, a frequency band of 16 kHz is analysed,
which allows features to be extracted in a wide frequency band, covering a wide
category of industrial applications.
3) Two new analysis methods: short-time RMS and spectral correlation algorithms are
proposed for bearing fault diagnosis. They can significantly reduce the CPU usage,
being over two times less and consequently much lower power consumptio
The Virtual Bus: A Network Architecture Designed to Support Modular-Redundant Distributed Periodic Real-Time Control Systems
The Virtual Bus network architecture uses physical layer switching and a combination of space- and time-division multiplexing to link segments of a partial mesh network together on schedule to temporarily form contention-free multi-hop, multi-drop simplex signalling paths, or 'virtual buses'. Network resources are scheduled and routed by a dynamic distributed resource allocation mechanism with self-forming and self-healing characteristics. Multiple virtual buses can coexist simultaneously in a single network, as the resources allocated to each bus are orthogonal in either space or time. The Virtual Bus architecture achieves deterministic delivery times for time-sensitive traffic over multi-hop partial mesh networks by employing true line-speed switching; delays of around 15ns at each switching point are demonstrated experimentally, and further reductions in switching delays are shown to be achievable. Virtual buses are inherently multicast, with delivery skew across multiple destinations proportional to the difference in equivalent physical length to each destination. The Virtual Bus architecture is not a purely theoretical concept; a small research platform has been constructed for development, testing and demonstration purposes