Lisa M. Jackson

Effectiveness of a Novel Sensor Selection Algorithm in PEM Fuel Cell On-Line Diagnosis

The monitoring of engineering systems is becoming more common place because of the increasing demands on reliability and safety. Being able to diagnose a fault has been facilitated by technology developments. This has resulted in the application of methods yielding an earlier detection and thus prompted mitigation of corrective measures. The level of maturity of monitoring systems varies across domain areas, with more nascent systems in newly emerging technologies, such as fuel cells. With the increasing complexity of systems comes the inclusion of more sensors, and for expedient on-line diagnosis utilizing the information from the most appropriate sensors is key to enabling excellent diagnostic resolution. In this paper, a novel sensor selection algorithm is proposed and its performance in polymer electrolyte membrane (PEM) fuel cell on-line diagnosis is investigated. In the selection procedure, both sensor sensitivities to various failure modes and corresponding fuel cell degradation rates are considered. The optimal sensors determined from the proposed algorithm are compared with previous sensor selection techniques, where results show that the proposed algorithm can provide more efficient sensor selection results using less computational time, which makes this method better applied in practical PEM fuel cell systems for on-line diagnostic tasks.

Reachability and Mortality Problems for Restricted Hierarchical Piecewise Constant Derivatives

We show the NP-hardness of the reachability and mortality problems for a three dimensional variant of Piecewise Constant Derivative (PCD) system called a bounded 3-dimensional Restricted Hierarchical PCD (3-RHPCD). Both problems are shown to be in PSPACE, even for n-dimensional RHPCD. This is a restricted model with similarities to other models in the literature such as stopwatch automata, rectangular automata and PCDs. We also show that for an unbounded 3-RHPCD, both problems become undecidable via a simulation of a Minsky machine.

Scalar Ambiguity and Freeness in Matrix Semigroups over Bounded Languages

There has been much research into freeness properties of finitely generated matrix semigroups under various constraints, mainly related to the dimensions of the generator matrices and the semiring over which the matrices are defined. A recent paper has also investigated freeness properties of matrices within a bounded language of matrices, which are of the form \(M_1 M_2 \cdots M_k \subseteq \mathbb {F}^{n \times n}\) for some semiring \(\mathbb {F}\) [9]. Most freeness problems have been shown to be undecidable starting from dimension three, even for upper-triangular matrices over the natural numbers. There are many open problems still remaining in dimension two.

Police Officer Dynamic Positioning for Incident Response and Community Presence - Using Maximum Demand Coverage and Kernel Density Estimation to Plan Patrols

Police Forces are under a constant struggle to provide the best service possible with limited and decreasing resources. One area where service cannot be compromised is incident response. Resources which are assigned to incident response must provide attendance to the scene of an incident in a timely manner to protect the public . To ensure the possible demand is met maximum coverage location planning can be used so response officers are located in the most effective position for incident response. This is not the only concern of response officer positioning. Location planning must also consider targeting high crime areas, hotspots, as an officer presence in these areas can reduce crime levels and hence reduce future demand on the response officers. In this work hotspots are found using quadratic kernel density estimation with historical crime data. These are then used to produce optimal dynamic patrol routes for response officers to follow. Dynamic patrol routes result in reduced response times and reduced crime levels in hotspot areas resulting in a lower demand on response officers.

Developing a Sensor based Homecare System - The Role of Bluetooth Low-Energy in Activity Monitoring.

Home healthcare systems have become a focus of research due to the shifting care requirements of the elderly. Malnourishment, independence and activity are becoming vital metrics when monitoring in patient’s illness. Monitoring devices described in research however express issues in the consistent remote capture of these metrics. This work presents the role of Bluetooth Low-Energy Beacons (BLE) in community based healthcare by examining how passive activity monitoring can assist patients coping with independence and disease management within their homes as an Indoor Proximity System (IPS). BLE sensors will be placed on the patient, in their home and on objects of interest (OOI) such as water bottles, kettles and microwaves. Research described in this paper will focus on accuracy of BLE beacons as an IPS for lifestyle monitoring and its application to intelligent healthcare. This is achieved by creating a model of patient care requirements structured using activities of daily living (ADL) which is evaluated using patient activity pattern recognition in captured sensor data. Pattern analysis uses the changing distance values between BLE sensors to determine movement, motion and location which contribute to the activity, sensor based care model. Results support efficacy when using BLE beacons as an IPS with patient activity patterns becoming observable through monitoring with a consistent ability to distinguish interactions in activity patterns captured. Future experiments will focus on analysing captured sensor metrics to determine care outcomes.

Novel methodology for optimising the design, operation and maintenance of a multi-AGV system

Abstract Automated guided vehicles (AGVs) have long been identified as a potential driver to improve system efficiency and lower labour costs in material handling systems. Accordingly, the reliability and availability of AGV systems is crucial to assure the stability and efficiency of these systems. However, the reliability issues and maintenance strategies of AGVs have not previously been studied sufficiently. This is even more marked in the case of multi-AGV systems that consist of fleets of AGVs. To fill this knowledge gap, research is conducted considering a multi-AGV system, consisting of three AGVs, in order to develop a scientific methodology for optimising the layout design, operation and maintenance of a multi-AGV system. Once an AGV is failed, it will be towed to the maintenance site for repair by a recycle vehicle to prevent deadlock and conflict. The efficiency of the recycling process of failed AGVs in a multi-AGV system, with respect to the change of location of the maintenance site, is analysed by the approach of coloured Petri nets (CPNs). A CPN model simulating the corrective and periodic preventive maintenance processes of failed AGVs is also developed in order to investigate the impact of different AGV maintenance strategies on the operation efficiency of the multi-AGV system. The simulation results obtained clearly show that the location of maintenance sites and maintenance strategies do have significant influence on the performance of a multi-AGV system, where corrective maintenance is an effective measure to maintain the long-term reliability and stability of the system.

Variation in detainee risk assessment within police custody across England and Wales

ABSTRACT Every time a person is booked into police custody in England and Wales, they are assessed for risk of harm to themselves or others. National guidance is provided on what questions should be asked as part of this process; however, each year there are still instances of serious adverse incidents, self-harm and deaths in custody. The purpose of this study is to look at the extent to which the national guidance is being followed and the extent to which the risk assessment process varies between police forces. A Freedom of Information request was sent to all 43 police forces in England and Wales asking for information on their risk assessment process. This data was then analysed alongside findings from police custody inspection visits conducted by Her Majestys Inspectorate of Constabulary. This study provides evidence that the risk assessment process is not consistent across police forces in England and Wales. Not only does the process vary from the national guidance, the content and delivery differs considerably between police forces. The findings highlight a practical problem for police forces in ensuring that risk assessment processes are conducted to a consistent standard and reflect national guidance. The study is, to the authors’ knowledge, the first time that this data has been collated and compared.

Optimising police dispatch for incident response in real time

Abstract It is crucial that police forces operate in a cost efficient manner and, in the case of incident response, that the most efficient resources are allocated. The current procedure is that police response units are allocated manually by a dispatcher using a resource list and mapping software. The efficiency of this process can be improved by the use of integrated mathematical approaches embedded within an automatic framework, yielding the optimal selection framework developed in this paper. The framework combines mapping and routing algorithms, and a decision process to facilitate optimal officer selection for incident response. The decision process considers information such as quickest response time, predicted traffic conditions, driving qualifications, response unit availability and demand coverage. The selection framework has been tested and validated through simulation and has shown to increase the efficiency of response units through reduced response times, increased response unit availability, and greater demand coverage.

Modelling manufacturing processes using Markov chains

Optimizing manufacturing processes with inaccurate models of the process will lead to unre-liable results. This can be true when there is a strong human influence on the manufacturing process and many variable aspects. This study investigates modelling a manufacturing process influenced by human inter-action with very variable products being processed. To develop a more accurate process model for such pro-cesses radio frequency identification (RFID) tags can be used to track products through the process. The tags record information for each product and this data can be used to produce more accurate models of the manu-facturing process. The data produced has been used to create a Markov chain model. This model is used to predict future product paths for use in discrete event simulation. In this case an IT refurbishment company is used as a case study. RFID tags have been utilized to track the IT products moving through the refurbishment process and this information has been used to produce a Markov chain model.

Reliability modelling of PEM fuel cells with hybrid Petri nets

In this paper, a novel model for dynamic reliability analysis of a PEM fuel cell system is developed using Modelica language in order to account for multi-state dynamics and aging. The modelling approach constitutes the combination of physical and stochastic sub-models with shared variables. The physical model consist of deterministic calculations of the system state described by variables such as temperature, pressure, mass flow rates and voltage output. Additionally, estimated component degradation rates are also taken into account. The non-deterministic model, on the other hand, is implemented with stochastic Petri nets which represent different events that can occur at random times during fuel cell lifetime. A case study of effects of a cooling system on fuel cell performance was investigated. Monte Carlo simulations of the process resulted in a distribution of system parameters, thus providing an estimate of best and worst scenarios of a fuel cell lifetime.