Airborne Wireless Sensor Networks for Airplane Monitoring System

In traditional airplane monitoring system (AMS), data sensed from strain, vibration, ultrasound of structures or temperature, and humidity in cabin environment are transmitted to central data repository via wires. However, drawbacks still exist in wired AMS such as expensive installation and maintenance, and complicated wired connections. In recent years, accumulating interest has been drawn to performing AMS via airborne wireless sensor network (AWSN) system with the advantages of flexibility, low cost, and easy deployment. In this review, we present an overview of AMS and AWSN and demonstrate the requirements of AWSN for AMS particularly. Furthermore, existing wireless hardware prototypes and network communication schemes of AWSN are investigated according to these requirements. This paper will improve the understanding of how the AWSN design under AMS acquires sensor data accurately and carries out network communication efficiently, providing insights into prognostics and health management (PHM) for AMS in future

EKF/UKF-based channel estimation for robust and reliable communications in V2V and IIoT

Cyber-physical systems (CPSs) are characterized by integrating computation, communication, and physical system. In typical CPS application scenarios, vehicle-to-vehicle (V2V) and Industry Internet of Things (IIoT), due to doubly selective fading and non-stationary channel characteristics, the robust and reliable end-to-end communication is extremely important. Channel estimation is a major signal processing technology to ensure robust and reliable communication. However, the existing channel estimation methods for V2V and IIoT cannot effectively reduce intercarrier interference (ICI) and lower the computation complexity, thus leading to poor robustness. Aiming at this challenge, according to the channel characteristics of V2V and IIoT, we design two channel estimation methods based on the Bayesian filter to promote the robustness and reliability of end-to-end communication. For the channels with doubly selective fading and non-stationary characteristics of V2V and IIoT scenarios, in the one hand, basis extended model (BEM) is used to further reduce the complexity of the channel estimation algorithm under the premise that ICI can be eliminated in the channel estimation. On the other hand, aiming at the non-stationary channel, a channel estimation and interpolation method based on extended Kalman filter (EKF) and unscented Kalman filter (UKF) Bayesian filters to jointly estimate the channel impulse response (CIR) and time-varying time domain autocorrelation coefficient is adopted. Through the MATLAB simulation, the robustness and reliability of end-to-end communication for V2V and IIoT are promoted by the proposed algorithms

Proportional-Integral Synchronisation for Non-identical Wireless Packet-Coupled Oscillators with Delays

Precise timing among wireless sensor nodes is a key enabling technology for time-sensitive industrial Wireless Sensor Networks (WSNs). However, the accuracy of timing is degraded by manufacturing tolerance, ageing of crystal oscillators, and communication delays. This paper develops a framework of Packet-Coupled Oscillator (PkCOs) to characterise the dynamics of communication and time synchronisation of clocks in WSNs. A non-identical clock is derived to describe the embedded clock's behaviour accurately. The Proportional-Integral (PI) packet coupling scheme is proposed for synchronising networked embedded clocks, meanwhile, scheduling wireless Sync packets to different slots for transmission. It also possesses the feature of automatically eliminating the effects of unknown processing delay, which further improves synchronisation performance. The rigorous theoretical analysis of PI-based PkCOs is presented via studying a closed-loop time synchronisation system. The performance of PI-based PkCOs is evaluated on a hardware testbed of IEEE 802.15.4 WSN. The experimental results show that the precision of the proportional-integral PkCOs protocol is as high as 60us (i.e., 2 ticks) for 32.768kHz crystal oscillator-based clocks

Non-invasive load monitoring of induction motor drives using magnetic flux sensors

Existing load monitoring methods for induction machines are generally effective, but suffer from sensitivity problems at low speeds and non-linearity problems at high supply frequencies. This study proposes a new noninvasive load monitoring method based on giant magnetoresistance flux sensors to trace stray flux leaking from induction motors. Finite element analysis is applied to analyse stray flux features of test machines. Contrary to the conventional methods of measuring stator and/or rotator rotor voltage and current, the proposed method measures the dynamic magnetic field at specific locations and provides time-spectrum features (e.g. spectrograms), response time load and stator/rotor characteristics. Three induction motors with different starting loading profiles are tested at two separate test benches and their results are analysed in the time-frequency domain. Their steady features and dynamic load response time through spectrograms under variable loads are extracted to correlate with load variations based on spectrogram information. In addition, the transient stray flux spectrogram and time information are more effective for load monitoring than steady state information from numerical and experimental studies. The proposed method is proven to be a low-cost and non-invasive method for induction machine load monitoring

Modelling and Synchronisation of Delayed Packet-Coupled Oscillators in Industrial Wireless Sensor Networks

In this paper, a Packet-Coupled Oscillators (PkCOs) synchronisation protocol is proposed for time-sensitive Wireless Sensor Networks (WSNs) based on Pulse-Coupled Oscillators (PCO) in mathematical biology. The effects of delays on synchronisation performance are studied through mathematical modelling and analysis of packet exchange and processing delays. The delay compensation strategy (i.e., feedforward control) is utilised to cancel delays effectively. A simple scheduling function is provided with PkCOs to allocate the packet transmission event to a specified time slot, by configuring reference input of the system to a non-zero value, in order to minimise the possibility of packet collision in synchronised wireless networks. The rigorous theoretical proofs are provided to validate the convergence and stability of the proposed synchronisation scheme. Finally, the simulations and experiments examine the effectiveness of PkCOs with delay compensation and scheduling strategies. The experimental results also show that the proposed PkCOs algorithm can achieve synchronisation with the precision of $26.3\mu s$ ($1$ tick)

Independent Review of the 2021 CDP submission based on SCATTER by Newcastle City Council

The path to Net-Zero is always a complex one. Newcastle City Council has long been a leader on green city and climate policy, recently has developed the Net Zero Newcastle: 2030 Action Plan and currently is a CDT tier-A city (based on its 2020 submission). In 2020 Newcastle City Council (NCC) made a Carbon Disclosure Project (CDP) submission for the first time. NCC deems this as a successful submission, which scored highly (A score) as a city. NCC therefore set the bar high and need to maintain that standard going forwards, especially with COP looming. To this end, one of the areas where NCC can improve its 2021 submission is to have an independent evaluation of our emissions inventory for the city, which by and large is based on national data which is extrapolated to local level and is largely based on the attached analysis through a tool called SCATTER which has been developed by Anthesis and made available to UK Local Authorities through a time-limited grant support from BEIS central government. This exercise was undertaken jointly by Northumbria and Newcastle universities, in a pro-bono activity in their guise as civic universities supporting the implementation of the UN{\textquoteright}s Sustainable Development Goals, including as members of the COP26 Universities Network1 which both Northumbria and Newcastle University are part of. The independent evaluation took its cue from initial suggestions from NCC to verify – as far as possible within the time frame and the resources at hand - its 2021 SCATTER-based CDP submission (data, questionnaire, and local proxy data suggestions for the future) and to provide some general advice on how NCC (alongside its partners across the city and region) could potentially improve its disclosure and data strategy (including and especially with a more bottom-up one) in the future. A series of (online) meetings took place between NCC colleagues and the independent evaluations over June and July 2021, including an audit-style one where NCC colleagues demonstrated how they access and use the SCATTER tool, and obtain the data from there. Live questions were asked by the independent evaluators in the meeting, in addition to a list of questions that was shared with the NCC team only some hours before this audit-style meeting. NCC colleagues made a series of documents and data files available during the course of the exercise, including some reference examples after the audit-style meeting. The cross-universities independent evaluation team considers that Newcastle city Council is engaging well with the process and procedure of the SCATTER-based CDP disclosure activity, is committed to understand better inventory and the data pre-populated by the Anthesis Group for its submission, is clearly on the way to consider potential improvements for the future which may also rest (partly) on a more bottom-up (locally generated and verified data). The evaluators have made some comments on the SCATTER tool and methodological approach in this report, and furthermore discuss in general terms some of the current limitations. The report also provides some general pointers as to how a more bottom-up data strategy could be built in the future for both CDP-compliant disclosure, but also to consider the links between data recording and interventions/policy impacts on the journey towards Net Zero (or carbon neutrality) via meeting the city{\textquoteright}s 2030 carbon emission reductions target

Neural Membrane Mutual Coupling Characterisation Using Entropy-Based Iterative Learning Identification

This paper investigates the interaction phenomena of the coupled axons while the mutual coupling factor is presented as a pairwise description. Based on the Hodgkin-Huxley model and the coupling factor matrix, the membrane potentials of the coupled myelinated/unmyelinated axons are quantified which implies that the neural coupling can be characterised by the presented coupling factor. Meanwhile the equivalent electric circuit is supplied to illustrate the physical meaning of this extended model. In order to estimate the coupling factor, a data-based iterative learning identification algorithm is presented where the Rényi entropy of the estimation error has been minimised. The convergence of the presented algorithm is analysed and the learning rate is designed. To verified the presented model and the algorithm, the numerical simulation results indicate the correctness and the effectiveness. Furthermore, the statistical description of the neural coupling, the approximation using ordinary differential equation, the measurement and the conduction of the nerve signals are discussed respectively as advanced topics. The novelties can be summarised as follows: 1) the Hodgkin-Huxley model has been extended considering the mutual interaction between the neural axon membranes, 2) the iterative learning approach has been developed for factor identification using entropy criterion, and 3) the theoretical framework has been established for this class of system identification problems with convergence analysis