Acoustic emission for diesel engine monitoring: A review and preliminary

Vibration analysis has been a prime tool in condition monitoring of rotating machines, however, its application to internal combustion engines remains a challenge because engine vibration signatures are highly non-stationary that are not suitable for popular spectrum-based analysis. Signal-to-noise ratio is a main concern in engine signature analysis due to severe background noise being generated by consecutive mechanical events, such as combustion, valve opening and closing, especially in multi-cylinder engines. Acoustic Emission (AE) has been found to give excellent signal-to-noise ratio allowing discrimination of fine detail of normal or abnormal events during a given cycle. AE has been used to detect faults, such as exhaust valve leakage, fuel injection behaviour, and aspects of the combustion process. This paper presents a review of AE application to diesel engine monitoring and preliminary investigation of AE signature measured on an 18-cylinder diesel engine. AE is compared with vibration acceleration for varying operating conditions: load and speed. Frequency characteristics of AE from those events are analysed in time-frequency domain via short time Fourier trasform. The result shows a great potential of AE analysis for detection of various defects in diesel engines.

A study on the use of acoustic emission technique as a structural health monitoring tool

As civil infrastructures such as bridges age, there is a concern for safety and a need for cost-effective and reliable monitoring tool. Different diagnostic techniques are available nowadays for structural health monitoring (SHM) of bridges. Acoustic emission is one such technique with potential of predicting failure. The phenomenon of rapid release of energy within a material by crack initiation or growth in form of stress waves is known as acoustic emission (AE). AEtechnique involves recording the stress waves bymeans of sensors and subsequent analysis of the recorded signals,which then convey information about the nature of the source. AE can be used as a local SHM technique to monitor specific regions with visible presence of cracks or crack prone areas such as welded regions and joints with bolted connection or as a global technique to monitor the whole structure. Strength of AE technique lies in its ability to detect active crack activity, thus helping in prioritising maintenance work by helping focus on active cracks rather than dormant cracks. In spite of being a promising tool, some challenges do still exist behind the successful application of AE technique. One is the generation of large amount of data during the testing; hence an effective data analysis and management is necessary, especially for long term monitoring uses. Complications also arise as a number of spurious sources can giveAEsignals, therefore, different source discrimination strategies are necessary to identify genuine signals from spurious ones. Another major challenge is the quantification of damage level by appropriate analysis of data. Intensity analysis using severity and historic indices as well as b-value analysis are some important methods and will be discussed and applied for analysis of laboratory experimental data in this paper.

Problem-solving courts, therapeutic jurisprudence and the constitution : if two is company, is three a crowd?

Court costs, resource-intensive trials, booming prison populations and the obduracy of recidivism rates all present as ugly excesses of the criminal law adversarial paradigm. To combat these excesses, problem-solving courts have evolved with an edict to address the underlying issues that have caused an individual to commit a crime. When a judge seeks to help a problem-solving court participant deal with issues like addiction, mental health or poverty, they are performing a very different role to that of a judicial officer in the traditional court hierarchy. They are no longer the removed, independent arbiter — a problem-solving court judge steps into the ‘arena’ with the participant and makes active use of their judicial authority to assist in rehabilitation and positive behavioural change. Problem-solving court judges employing the principles of therapeutic jurisprudence appreciate that their interaction with participants can have therapeutic and anti-therapeutic consequences. This article will consider how the deployment of therapeutic measures (albeit with good intention) can lead to the behavioural manifestation of partiality and bias on the part of problem-solving court judges. Chapter III of the Commonwealth Constitution will then be analysed to highlight why the operation and functioning of problem solving courts may be deemed unconstitutional. Part IV of this article will explain how a problem-solving court judge who is not acting impartially or independently will potentially contravene the requirements of the Constitution. It will finally be suggested that judges who possess a high level of emotional intelligence will be the most successful in administering an independent and impartial problem solving court.

Change Point Estimation in Monitoring Survival Time

Precise identification of the time when a change in a hospital outcome has occurred enables clinical experts to search for a potential special cause more effectively. In this paper, we develop change point estimation methods for survival time of a clinical procedure in the presence of patient mix in a Bayesian framework. We apply Bayesian hierarchical models to formulate the change point where there exists a step change in the mean survival time of patients who underwent cardiac surgery. The data are right censored since the monitoring is conducted over a limited follow-up period. We capture the effect of risk factors prior to the surgery using a Weibull accelerated failure time regression model. Markov Chain Monte Carlo is used to obtain posterior distributions of the change point parameters including location and magnitude of changes and also corresponding probabilistic intervals and inferences. The performance of the Bayesian estimator is investigated through simulations and the result shows that precise estimates can be obtained when they are used in conjunction with the risk-adjusted survival time CUSUM control charts for different magnitude scenarios. The proposed estimator shows a better performance where a longer follow-up period, censoring time, is applied. In comparison with the alternative built-in CUSUM estimator, more accurate and precise estimates are obtained by the Bayesian estimator. These superiorities are enhanced when probability quantification, flexibility and generalizability of the Bayesian change point detection model are also considered.

Functional and advanced functional and causal relationship diagrams for remote condition monitoring

Analysing the condition of an asset is a big challenge as there can be many aspects which can contribute to the overall functional reliability of the asset that have to be considered. In this paper we propose a two-step functional and causal relationship diagram (FCRD) to address this problem. In the first step, the FCRD is designed to facilitate the analysis of the condition of an asset by evaluating the interdependence (functional and causal) relationships between different components of the asset with the help of a relationship diagram. This is followed by the advanced FCRD (AFCRD) which refines the information from the FCRD into a comprehensive and manageable format. This new two-step methodology for asset condition monitoring is tested and validated for the case of a water treatment plant. © IMechE 2012.

Damage quantification techniques in acoustic emission monitoring

Acoustic emission (AE) analysis is one of the several diagnostic techniques available nowadays for structural health monitoring (SHM) of engineering structures. Some of its advantages over other techniques include high sensitivity to crack growth and capability of monitoring a structure in real time. The phenomenon of rapid release of energy within a material by crack initiation or growth in form of stress waves is known as acoustic emission (AE). In AE technique, these stress waves are recorded by means of suitable sensors placed on the surface of a structure. Recorded signals are subsequently analysed to gather information about the nature of the source. By enabling early detection of crack growth, AE technique helps in planning timely retrofitting or other maintenance jobs or even replacement of the structure if required. In spite of being a promising tool, some challenges do still exist behind the successful application of AE technique. Large amount of data is generated during AE testing, hence effective data analysis is necessary, especially for long term monitoring uses. Appropriate analysis of AE data for quantification of damage level is an area that has received considerable attention. Various approaches available for damage quantification for severity assessment are discussed in this paper, with special focus on civil infrastructure such as bridges. One method called improved b-value analysis is used to analyse data collected from laboratory testing.

Using fiber Bragg grating in geothermal monitoring

Earthquake precursor monitoring is the foundation of earthquake prediction and geothermal monitoring is one of the basic methods of earthquake precursor monitoring. High temperature well contains more information and therefore its monitoring is more important. However, electric sensors are hard to meet the monitoring requirements of high sensitivity and long lifetime. For a better observation of the earthquake precursor, a high sensitive fiber Bragg grating (FBG) temperature sensor is designed to monitoring a well at 87.5±1◦C. The performance of the FBG sensor demonstrates that it’s quite possible that applying FBG to high-sensitivity temperature-monitoring fields, such as geothermal monitoring. As far as we known, it is the first time that trying a high sensitive FBG temperature sensor in a practical application, let alone in the field of geothermal monitoring.

Extending persistent monitoring by combining ocean models and Markov decision processes

Ocean processes are complex and have high variability in both time and space. Thus, ocean scientists must collect data over long time periods to obtain a synoptic view of ocean processes and resolve their spatiotemporal variability. One way to perform these persistent observations is to utilise an autonomous vehicle that can remain on deployment for long time periods. However, such vehicles are generally underactuated and slow moving. A challenge for persistent monitoring with these vehicles is dealing with currents while executing a prescribed path or mission. Here we present a path planning method for persistent monitoring that exploits ocean currents to increase navigational accuracy and reduce energy consumption.

Hospital outpatient responses to potential driving impairment due to prescribed medications

Driving and using prescription medicines that have the potential to impair driving is an emerging research area. To date it is characterised by a limited (although growing) number of studies and methodological complexities that make generalisations about impairment due to medications difficult. Consistent evidence has been found for the impairing effects of hypnotics, sedative antidepressants and antihistamines, and narcotic analgesics, although it has been estimated that as many as nine medication classes have the potential to impair driving (Alvarez & del Rio, 2000; Walsh, de Gier, Christopherson, & Verstraete, 2004). There is also evidence for increased negative effects related to concomitant use of other medications and alcohol (Movig et al., 2004; Pringle, Ahern, Heller, Gold, & Brown, 2005). Statistics on the high levels of Australian prescription medication use suggest that consumer awareness of driving impairment due to medicines should be examined. One web-based study has found a low level of awareness, knowledge and risk perceptions among Australian drivers about the impairing effects of various medications on driving (Mallick, Johnston, Goren, & Kennedy, 2007). The lack of awareness and knowledge brings into question the effectiveness of the existing countermeasures. In Australia these consist of the use of ancillary warning labels administered under mandatory regulation and professional guidelines, advice to patients, and the use of Consumer Medicines Information (CMI) with medications that are known to cause impairment. The responsibility for the use of the warnings and related counsel to patients primarily lies with the pharmacist when dispensing relevant medication. A review by the Therapeutic Goods Administration (TGA) noted that in practice, advice to patients may not occur and that CMI is not always available (TGA, 2002). Researchers have also found that patients' recall of verbal counsel is very low (Houts, Bachrach, Witmer, Tringali, Bucher, & Localio, 1998). With healthcare observed as increasingly being provided in outpatient conditions (Davis et al., 2006; Vingilis & MacDonald, 2000), establishing the effectiveness of the warning labels as a countermeasure is especially important. There have been recent international developments in medication categorisation systems and associated medication warning labels. In 2005, France implemented a four-tier medication categorisation and warning system to improve patients' and health professionals' awareness and knowledge of related road safety issues (AFSSAPS, 2005). This warning system uses a pictogram and indicates the level of potential impairment in relation to driving performance through the use of colour and advice on the recommended behaviour to adopt towards driving. The comparable Australian system does not indicate the severity level of potential effects, and does not provide specific guidelines on the attitude or actions that the individual should adopt towards driving. It is reliant upon the patient to be vigilant in self-monitoring effects, to understand the potential ways in which they may be affected and how serious these effects may be, and to adopt the appropriate protective actions. This thesis investigates the responses of a sample of Australian hospital outpatients who receive appropriate labelling and counselling advice about potential driving impairment due to prescribed medicines. It aims to provide baseline data on the understanding and use of relevant medications by a Queensland public hospital outpatient sample recruited through the hospital pharmacy. It includes an exploration and comparison of the effect of the Australian and French medication warning systems on medication user knowledge, attitudes, beliefs and behaviour, and explores whether there are areas in which the Australian system may be improved by including any beneficial elements of the French system. A total of 358 outpatients were surveyed, and a follow-up telephone survey was conducted with a subgroup of consenting participants who were taking at least one medication that required an ancillary warning label about driving impairment. A complementary study of 75 French hospital outpatients was also conducted to further investigate the performance of the warnings. Not surprisingly, medication use among the Australian outpatient sample was high. The ancillary warning labels required to appear on medications that can impair driving were prevalent. A subgroup of participants was identified as being potentially at-risk of driving impaired, based on their reported recent use of medications requiring an ancillary warning label and level of driving activity. The sample reported previous behaviour and held future intentions that were consistent with warning label advice and health protective action. Participants did not express a particular need for being advised by a health professional regarding fitness to drive in relation to their medication. However, it was also apparent from the analysis that the participants would be significantly more likely to follow advice from a doctor than a pharmacist. High levels of knowledge in terms of general principles about effects of alcohol, illicit drugs and combinations of substances, and related health and crash risks were revealed. This may reflect a sample specific effect. Emphasis is placed in the professional guidelines for hospital pharmacists that make it essential that advisory labels are applied to medicines where applicable and that warning advice is given to all patients on medication which may affect driving (SHPA, 2006, p. 221). The research program applied selected theoretical constructs from Schwarzer's (1992) Health Action Process Approach, which has extended constructs from existing health theories such as the Theory of Planned Behavior (Ajzen, 1991) to better account for the intention-behaviour gap often observed when predicting behaviour. This was undertaken to explore the utility of the constructs in understanding and predicting compliance intentions and behaviour with the mandatory medication warning about driving impairment. This investigation revealed that the theoretical constructs related to intention and planning to avoid driving if an effect from the medication was noticed were useful. Not all the theoretical model constructs that had been demonstrated to be significant predictors in previous research on different health behaviours were significant in the present analyses. Positive outcome expectancies from avoiding driving were found to be important influences on forming the intention to avoid driving if an effect due to medication was noticed. In turn, intention was found to be a significant predictor of planning. Other selected theoretical constructs failed to predict compliance with the Australian warning label advice. It is possible that the limited predictive power of a number of constructs including risk perceptions is due to the small sample size obtained at follow up on which the evaluation is based. Alternately, it is possible that the theoretical constructs failed to sufficiently account for issues of particular relevance to the driving situation. The responses of the Australian hospital outpatient sample towards the Australian and French medication warning labels, which differed according to visual characteristics and warning message, were examined. In addition, a complementary study with a sample of French hospital outpatients was undertaken in order to allow general comparisons concerning the performance of the warnings. While a large amount of research exists concerning warning effectiveness, there is little research that has specifically investigated medication warnings relating to driving impairment. General established principles concerning factors that have been demonstrated to enhance warning noticeability and behavioural compliance have been extrapolated and investigated in the present study. The extent to which there is a need for education and improved health messages on this issue was a core issue of investigation in this thesis. Among the Australian sample, the size of the warning label and text, and red colour were the most visually important characteristics. The pictogram used in the French labels was also rated highly, and was salient for a large proportion of the sample. According to the study of French hospital outpatients, the pictogram was perceived to be the most important visual characteristic. Overall, the findings suggest that the Australian approach of using a combination of visual characteristics was important for the majority of the sample but that the use of a pictogram could enhance effects. A high rate of warning recall was found overall and a further important finding was that higher warning label recall was associated with increased number of medication classes taken. These results suggest that increased vigilance and care are associated with the number of medications taken and the associated repetition of the warning message. Significantly higher levels of risk perception were found for the French Level 3 (highest severity) label compared with the comparable mandatory Australian ancillary Label 1 warning. Participants' intentions related to the warning labels indicated that they would be more cautious while taking potentially impairing medication displaying the French Level 3 label compared with the Australian Label 1. These are potentially important findings for the Australian context regarding the current driving impairment warnings about displayed on medication. The findings raise other important implications for the Australian labelling context. An underlying factor may be the differences in the wording of the warning messages that appear on the Australian and French labels. The French label explicitly states "do not drive" while the Australian label states "if affected, do not drive", and the difference in responses may reflect that less severity is perceived where the situation involves the consumer's self-assessment of their impairment. The differences in the assignment of responsibility by the Australian (the consumer assesses and decides) and French (the doctor assesses and decides) approaches for the decision to drive while taking medication raises the core question of who is most able to assess driving impairment due to medication: the consumer, or the health professional? There are pros and cons related to knowledge, expertise and practicalities with either option. However, if the safety of the consumer is the primary aim, then the trend towards stronger risk perceptions and more consistent and cautious behavioural intentions in relation to the French label suggests that this approach may be more beneficial for consumer safety. The observations from the follow-up survey, although based on a small sample size and descriptive in nature, revealed that just over half of the sample recalled seeing a warning label about driving impairment on at least one of their medications. The majority of these respondents reported compliance with the warning advice. However, the results indicated variation in responses concerning alcohol intake and modifying the dose of medication or driving habits so that they could continue to drive, which suggests that the warning advice may not be having the desired impact. The findings of this research have implications for current countermeasures in this area. These have included enhancing the role that prescribing doctors have in providing warnings and advice to patients about the impact that their medication can have on driving, increasing consumer perceptions of the authority of pharmacists on this issue, and the reinforcement of the warning message. More broadly, it is suggested that there would be benefit in a wider dissemination of research-based information on increased crash risk and systematic monitoring and publicity about the representation of medications in crashes resulting in injuries and fatalities. Suggestions for future research concern the continued investigation of the effects of medications and interactions with existing medical conditions and other substances on driving skills, effects of variations in warning label design, individual behaviours and characteristics (particularly among those groups who are dependent upon prescription medication) and validation of consumer self-assessment of impairment.

Use of hierarchical cluster analysis to assess the representativeness of a baseline groundwater quality monitoring network: comparison of New Zealand’s national and regional groundwater monitoring programs

Baseline monitoring of groundwater quality aims to characterize the ambient condition of the resource and identify spatial or temporal trends. Sites comprising any baseline monitoring network must be selected to provide a representative perspective of groundwater quality across the aquifer(s) of interest. Hierarchical cluster analysis (HCA) has been used as a means of assessing the representativeness of a groundwater quality monitoring network, using example datasets from New Zealand. HCA allows New Zealand's national and regional monitoring networks to be compared in terms of the number of water-quality categories identified in each network, the hydrochemistry at the centroids of these water-quality categories, the proportions of monitoring sites assigned to each water-quality category, and the range of concentrations for each analyte within each water-quality category. Through the HCA approach, the National Groundwater Monitoring Programme (117 sites) is shown to provide a highly representative perspective of groundwater quality across New Zealand, relative to the amalgamated regional monitoring networks operated by 15 different regional authorities (680 sites have sufficient data for inclusion in HCA). This methodology can be applied to evaluate the representativeness of any subset of monitoring sites taken from a larger network.

Towards the development of a gas sensor system for monitoring pollutant gases in the low troposphere using small unmanned aerial vehicles

The world is facing problems due to the effects of increased atmospheric pollution, climate change and global warming. Innovative technologies to identify, quantify and assess fluxes exchange of the pollutant gases between the Earth’s surface and atmosphere are required. This paper proposes the development of a gas sensor system for a small UAV to monitor pollutant gases, collect data and geo-locate where the sample was taken. The prototype has two principal systems: a light portable gas sensor and an optional electric–solar powered UAV. The prototype will be suitable to: operate in the lower troposphere (100-500m); collect samples; stamp time and geo-locate each sample. One of the limitations of a small UAV is the limited power available therefore a small and low power consumption payload is designed and built for this research. The specific gases targeted in this research are NO2, mostly produce by traffic, and NH3 from farming, with concentrations above 0.05 ppm and 35 ppm respectively which are harmful to human health. The developed prototype will be a useful tool for scientists to analyse the behaviour and tendencies of pollutant gases producing more realistic models of them.