A Smart Modular Wireless System for Condition Monitoring Data Acquisition

Smart sensors, big data, the cloud and distributed data processing are some of the most interning changes in the way we collect, manage and treat data in recent years. These changes have not significantly influenced the common practices in condition monitoring for shipping. In part this is due to the reduced trust in data security, data ownership issues, lack of technological integration and obscurity of direct benefit. This paper presents a method of incorporating smart sensor techniques and distributed processing in data acquisition for condition monitoring to assist decision support for maintenance actions addressing these inhibitors

CAN Fieldbus Communication in the CSP-based CT Library

In closed-loop control systems several realworld entities are simultaneously communicated to through a multitude of spatially distributed sensors and actuators. This intrinsic parallelism and complexity motivates implementing control software in the form of concurrent processes deployed on distributed hardware architectures. A CSP based occam-like architecture seems to be the most convenient for such a purpose. Many, often conflicting, requirements make design and implementation of distributed real-time control systems an extremely difficult task. The scope of this paper is limited to achieving safe and real-time communication over a CAN fieldbus for an\ud existing CSP-based framework

Microelectromechanical Systems (MEMS) Resistive Heaters as Circuit Protection Devices

With increased opportunities for the exploitation (i.e., reverse engineering) of vulnerable electronic components and systems, circuit protection has become a critical issue. Circuit protection techniques are generally software-based and include cryptography (encryption/decryption), obfuscation of codes, and software guards. Examples of hardware-based circuit protection include protective coatings on integrated circuits, trusted foundries, and macro-sized components that self-destruct, thus destroying critical components. This paper is the first to investigate the use of microelectromechanical systems (MEMS) to provide hardware-based protection of critical electronic components to prevent reverse engineering or other exploitation attempts. Specifically, surface-micromachined polycrystalline silicon to be used as meandering resistive heaters were designed analytically and fabricated using a commercially available MEMS prototyping service (i.e., PolyMUMPs), and integrated with representative components potentially at risk for exploitation, in this case pseudomorphic high-electron mobility transistors (pHEMTs). The MEMS heaters were initiated to self-destruct, destroying a critical circuit component and thwart a reverse engineering attempt. Tests revealed reliable self-destruction of the MEMS heaters with approximately 25 V applied, resulting in either complete operational failure or severely altering the pHEMT device physics. The prevalent failure mechanism was metallurgical, in that the material on the surface of the device was changed, and the specific failure mode was the creation of a short-circuit. Another failure mode was degraded device operation due to permanently altered device physics related to either dopant diffusion or ohmic contact degradation. The results, in terms of the failure of a targeted electronic component, demonstrate the utility of using MEMS devices to protect critical components which are otherwise vulnerable to exploitation

Every Moment Counts: Synchrophasors for Distribution Networks with Variable Resources

Chapter 34 in the textbook, "Renewable Energy Integration: Practical Management of Variability, Uncertainty and Flexibility

Context-aware adaptation in DySCAS

DySCAS is a dynamically self-configuring middleware for automotive control systems. The addition of autonomic, context-aware dynamic configuration to automotive control systems brings a potential for a wide range of benefits in terms of robustness, flexibility, upgrading etc. However, the automotive systems represent a particularly challenging domain for the deployment of autonomics concepts, having a combination of real-time performance constraints, severe resource limitations, safety-critical aspects and cost pressures. For these reasons current systems are statically configured. This paper describes the dynamic run-time configuration aspects of DySCAS and focuses on the extent to which context-aware adaptation has been achieved in DySCAS, and the ways in which the various design and implementation challenges are met

Assessing the reliability of adaptive power system protection schemes

Adaptive power system protection can be used to improve the performance of existing protection schemes under certain network conditions. However, their deployment in the field is impeded by their perceived inferior reliability compared to existing protection arrangements. Moreover, their validation can be problematic due to the perceived high likelihood of the occurrence of failure modes or incorrect setting selection with variable network conditions. Reliability (including risk assessment) is one of the decisive measures that can be used in the process of verifying adaptive protection scheme performance. This paper proposes a generic methodology for assessing the reliability of adaptive protection. The method involves the identification of initiating events and scenarios that lead to protection failures and quantification of the probability of the occurrence of each failure. A numerical example of the methodology for an adaptive distance protection scheme is provided

Residential distributed generation : decision support software to evaluate opportunities in the residential market : a thesis submitted in partial fulfilment of the requirement for the degree of Masters of Engineering at Massey University, Palmerston North, New Zealand /

The residential market in New Zealand consumes a significant proportion of our electricity production and is one of the fastest growing sectors. As a vertically integrated generator retailer in the New Zealand electricity industry, Meridian Energy Ltd is concerned at retaining and growing their customer base. They recognise that utilisation of emerging distributed generation [DG] technologies can provide a competitive advantage in the market place. A decision tool was developed to help Meridian identify opportunities within the residential market for applications of DG. The model compares the cost to serve a household's energy needs using a business as usual case with a DG case on an annual basis for a single household or a neighbourhood. A modular approach was used for ease of development and to enable future enhancements. The main modules were: load profile development, DG technology, operation control, costing and a calculation engine. The load profile module estimated space heating/cooling, water heating and other electrical loads for each 30 minute period for 8 representative days of a year based on national end-use statistics and a set of 40 reference profiles. A Gamma distribution was used to simulate diversity between houses. The calculation engine computed the amount of demand that could be met by the DG technologies and hence the residual demand or surplus for export. The pricing module estimated the annual cost including aspects such as: capital cost, fuel cost, maintenance, value of export and cost of import. The technology modules allowed different DG technologies, as well as a range of parameters to be selected. It included renewable energy resource modelling. The performance module allowed different operation control of the heat engine technologies including: base load, electrical peaking, heat peaking, load following (heat-led) and load following(electricity-led). The model was implemented using Microsoft Visual Basic for Applications, in Excel. A series of user-forms were developed to enable the model to be run with a minimum of user input. Three case studies were undertaken. In the first, five technology types were modelled, with the heat pump and Stirling engine looking the most promising. The second case study involved these two technologies in a Christchurch urban area study. A hypothetical network analysis showed the benefit that these technologies could have in reducing peak loading on the network. The third case study examined the sensitivity of the results to the value of specific variables. Load size and capital cost had the strongest influence on NPV