Decision support system for inspection and maintenance:a case of oil pipelines

The existing method of pipeline health monitoring, which requires an entire pipeline to be inspected periodically, is unproductive. A risk-based decision support system (DSS) that reduces the amount of time spent on inspection has been presented. The risk-based DSS uses the analytic hierarchy process (AHP), a multiple attribute decision-making technique, to identify the factors that influence failure on specific segments and analyzes their effects by determining probability of occurrence of these risk factors. The severity of failure is determined through consequence analysis. From this, the effect of a failure caused by each risk factor can be established in terms of cost and the cumulative effect of failure is determined through probability analysis. The model optimizes the cost of pipeline operations by reducing subjectivity in selecting a specific inspection method, identifying and prioritizing the right pipeline segment for inspection and maintenance, deriving budget allocation, providing guidance to deploy the right mix labor for inspection and maintenance, planning emergency preparation, and deriving logical insurance plan. The proposed methodology also helps derive inspection and maintenance policy for the entire pipeline system, suggest design, operational philosophy, and construction methodology for new pipelines.

First in-vivo trials of a fibre Bragg grating based temperature profiling system

We describe the results of in-vivo trials of a portable fiber Bragg grating based temperature profile monitoring system. The probe incorporates five Bragg gratings along a single fiber and prevents the gratings from being strained. Illumination is provided by a superluminescent diode, and a miniature CCD based spectrometer is used for demultiplexing. The CCD signal is read into a portable computer through a small A/D interface; the computer then calculates the positions of the center wavelengths of the Bragg gratings, providing a resolution of 0.2°C. Tests were carried out on rabbits undergoing hyperthermia treatment of the kidney and liver via inductive heating of metallic implants and comparison was made with a commercial Fluoroptic thermometry system.

First in-vivo trials of a fibre Bragg grating based temperature profiling system

We describe the results of in-vivo trials of a portable fiber Bragg grating based temperature profile monitoring system. The probe incorporates five Bragg gratings along a single fiber and prevents the gratings from being strained. Illumination is provided by a superluminescent diode, and a miniature CCD based spectrometer is used for demultiplexing. The CCD signal is read into a portable computer through a small A/D interface; the computer then calculates the positions of the center wavelengths of the Bragg gratings, providing a resolution of 0.2 °C. Tests were carried out on rabbits undergoing hyperthermia treatment of the kidney and liver via inductive heating of metallic implants and comparison was made with a commercial Fluoroptic thermometry system.

Analytic hierarchy process analyses risk of operating cross-country petroleum pipelines in India

The existing method of pipeline health monitoring, which requires an entire pipeline to be inspected periodically, is both time-wasting and expensive. A risk-based model that reduces the amount of time spent on inspection has been presented. This model not only reduces the cost of maintaining petroleum pipelines, but also suggests an efficient design and operation philosophy, construction methodology, and logical insurance plans. The risk-based model uses the analytic hierarchy process (AHP), a multiple-attribute decision-making technique, to identify the factors that influence failure on specific segments and to analyze their effects by determining probability of risk factors. The severity of failure is determined through consequence analysis. From this, the effect of a failure caused by each risk factor can be established in terms of cost, and the cumulative effect of failure is determined through probability analysis. The technique does not totally eliminate subjectivity, but it is an improvement over the existing inspection method.

State detection of bond wires in IGBT modules using eddy current pulsed thermography

Insulated gate bipolar transistor (IGBT) modules are important safety critical components in electrical power systems. Bond wire lift-off, a plastic deformation between wire bond and adjacent layers of a device caused by repeated power/thermal cycles, is the most common failure mechanism in IGBT modules. For the early detection and characterization of such failures, it is important to constantly detect or monitor the health state of IGBT modules, and the state of bond wires in particular. This paper introduces eddy current pulsed thermography (ECPT), a nondestructive evaluation technique, for the state detection and characterization of bond wire lift-off in IGBT modules. After the introduction of the experimental ECPT system, numerical simulation work is reported. The presented simulations are based on the 3-D electromagnetic-thermal coupling finite-element method and analyze transient temperature distribution within the bond wires. This paper illustrates the thermal patterns of bond wires using inductive heating with different wire statuses (lifted-off or well bonded) under two excitation conditions: nonuniform and uniform magnetic field excitations. Experimental results show that uniform excitation of healthy bonding wires, using a Helmholtz coil, provides the same eddy currents on each, while different eddy currents are seen on faulty wires. Both experimental and numerical results show that ECPT can be used for the detection and characterization of bond wires in power semiconductors through the analysis of the transient heating patterns of the wires. The main impact of this paper is that it is the first time electromagnetic induction thermography, so-called ECPT, has been employed on power/electronic devices. Because of its capability of contactless inspection of multiple wires in a single pass, and as such it opens a wide field of investigation in power/electronic devices for failure detection, performance characterization, and health monitoring.

Mitigating inconsistencies by coupling data cleaning, filtering, and contextual data validation in wireless sensor networks

With the advent of peer to peer networks, and more importantly sensor networks, the desire to extract useful information from continuous and unbounded streams of data has become more prominent. For example, in tele-health applications, sensor based data streaming systems are used to continuously and accurately monitor Alzheimer's patients and their surrounding environment. Typically, the requirements of such applications necessitate the cleaning and filtering of continuous, corrupted and incomplete data streams gathered wirelessly in dynamically varying conditions. Yet, existing data stream cleaning and filtering schemes are incapable of capturing the dynamics of the environment while simultaneously suppressing the losses and corruption introduced by uncertain environmental, hardware, and network conditions. Consequently, existing data cleaning and filtering paradigms are being challenged. This dissertation develops novel schemes for cleaning data streams received from a wireless sensor network operating under non-linear and dynamically varying conditions. The study establishes a paradigm for validating spatio-temporal associations among data sources to enhance data cleaning. To simplify the complexity of the validation process, the developed solution maps the requirements of the application on a geometrical space and identifies the potential sensor nodes of interest. Additionally, this dissertation models a wireless sensor network data reduction system by ascertaining that segregating data adaptation and prediction processes will augment the data reduction rates. The schemes presented in this study are evaluated using simulation and information theory concepts. The results demonstrate that dynamic conditions of the environment are better managed when validation is used for data cleaning. They also show that when a fast convergent adaptation process is deployed, data reduction rates are significantly improved. Targeted applications of the developed methodology include machine health monitoring, tele-health, environment and habitat monitoring, intermodal transportation and homeland security.

Mitigating Inconsistencies by Coupling Data Cleaning, Filtering, and Contextual Data Validation in Wireless Sensor Networks

With the advent of peer to peer networks, and more importantly sensor networks, the desire to extract useful information from continuous and unbounded streams of data has become more prominent. For example, in tele-health applications, sensor based data streaming systems are used to continuously and accurately monitor Alzheimer's patients and their surrounding environment. Typically, the requirements of such applications necessitate the cleaning and filtering of continuous, corrupted and incomplete data streams gathered wirelessly in dynamically varying conditions. Yet, existing data stream cleaning and filtering schemes are incapable of capturing the dynamics of the environment while simultaneously suppressing the losses and corruption introduced by uncertain environmental, hardware, and network conditions. Consequently, existing data cleaning and filtering paradigms are being challenged. This dissertation develops novel schemes for cleaning data streams received from a wireless sensor network operating under non-linear and dynamically varying conditions. The study establishes a paradigm for validating spatio-temporal associations among data sources to enhance data cleaning. To simplify the complexity of the validation process, the developed solution maps the requirements of the application on a geometrical space and identifies the potential sensor nodes of interest. Additionally, this dissertation models a wireless sensor network data reduction system by ascertaining that segregating data adaptation and prediction processes will augment the data reduction rates. The schemes presented in this study are evaluated using simulation and information theory concepts. The results demonstrate that dynamic conditions of the environment are better managed when validation is used for data cleaning. They also show that when a fast convergent adaptation process is deployed, data reduction rates are significantly improved. Targeted applications of the developed methodology include machine health monitoring, tele-health, environment and habitat monitoring, intermodal transportation and homeland security.

Monitoring of down-hole parameters for early kick detection

The sudden hydrocarbon influx from the formation into the wellbore poses a serious risk to the safety of the well. This sudden influx is termed a kick, which, if not controlled, may lead to a blowout. Therefore, early detection of the kick is crucial to minimize the possibility of a blowout occurrence. There is a high probability of delay in kick detection, apart from other issues when using a kick detection system that is exclusively based on surface monitoring. Down-hole monitoring techniques have a potential to detect a kick at its early stage. Down-hole monitoring could be particularly beneficial when the influx occurs as a result of a lost circulation scenario. In a lost circulation scenario, when the down-hole pressure becomes lower than the formation pore pressure, the formation fluid may starts to enter the wellbore. The lost volume of the drilling fluid is compensated by the formation fluid flowing into the well bore, making it difficult to identify the kick based on pit (mud tank) volume observations at the surface. This experimental study investigates the occurrence of a kick based on relative changes in the mass flow rate, pressure, density, and the conductivity of the fluid in the down-hole. Moreover, the parameters that are most sensitive to formation fluid are identified and a methodology to detect a kick without false alarms is reported. Pressure transmitter, the Coriolis flow and density meter, and the conductivity sensor are employed to observe the deteriorating well conditions in the down-hole. These observations are used to assess the occurrence of a kick and associated blowout risk. Monitoring of multiple down-hole parameters has a potential to improve the accuracy of interpretation related to kick occurrence, reduces the number of false alarms, and provides a broad picture of down-hole conditions. The down-hole monitoring techniques have a potential to reduce the kick detection period. A down-hole assembly of the laboratory scale drilling rig model and kick injection setup were designed, measuring instruments were acquired, a frame was fabricated, and the experimental set-up was assembled and tested. This set-up has the necessary features to evaluate kick events while implementing down-hole monitoring techniques. Various kick events are simulated on the drilling rig model. During the first set of experiments compressed air (which represents the formation fluid) is injected with constant pressure margin. In the second set of experiments the compressed air is injected with another pressure margin. The experiments are repeated with another pump (flow) rate as well. This thesis consists of three main parts. The first part gives the general introduction, motivation, outline of the thesis, and a brief description of influx: its causes, various leading and lagging indicators, and description of the several kick detection systems that are in practice in the industry. The second part describes the design and construction of the laboratory scale down-hole assembly of the drilling rig and kick injection setup, which is used to implement the proposed methodology for early kick detection. The third part discusses the experimental work, describes the methodology for early kick detection, and presents experimental results that show how different influx events affect the mass flow rate, pressure, conductivity, and density of the fluid in the down-hole, and the discussion of the results. The last chapter contains summary of the study and future research.

Updating of an instrumented building model considering amplitude dependence of dynamic resonant properties extracted from seismic response records

The authors would like to express their gratitude to their supporters. Drs Jim Cousins, S.R. Uma and Ken Gledhill facilitated this research by providing access to GeoNet seismic data and structural building information. Piotr Omenzetter’s work within the Lloyd’s Register Foundation Centre for Safety and Reliability Engineering at the University of Aberdeen is supported by Lloyd’s Register Foundation. The Foundation helps to protect life and property by supporting engineering-related education, public engagement and the application of research.

Updating of an instrumented building model considering amplitude dependence of dynamic resonant properties extracted from seismic response records

The authors would like to express their gratitude to their supporters. Drs Jim Cousins, S.R. Uma and Ken Gledhill facilitated this research by providing access to GeoNet seismic data and structural building information. Piotr Omenzetter’s work within the Lloyd’s Register Foundation Centre for Safety and Reliability Engineering at the University of Aberdeen is supported by Lloyd’s Register Foundation. The Foundation helps to protect life and property by supporting engineering-related education, public engagement and the application of research.

Identification of unusual events in multi-channel bridge monitoring data using wavelet transform and outlier analysis

Peer reviewed

Professional development programs in health promotion : tools and processes to favor new practices

Developing innovative interventions that are in sync with a health promotion paradigm often represents a challenge for professionals working in local public health organizations. Thus, it is critical to have both professional development programs that favor new practices and tools to examine these practices. In this case study, we analyze the health promotion approach used in a pilot intervention addressing children’s vulnerability that was developed and carried out by participants enrolled in a public health professional development program. More specifically, we use a modified version of Guichard and Ridde’s (Une grille d’analyse des actions pour lutter contre les inégalités sociales de santé. In Potvin, L., Moquet, M.-J. and Jones, C. M. (eds), Réduire les Inégalités Sociales en Santé. INPES, Saint-Denis Cedex, pp. 297– 312, 2010) analytical grid to assess deductively the program participants’ use of health promotion practices in the analysis and planning, implementation, evaluation, sustainability and empowerment phases of the pilot intervention. We also seek evidence of practices involving (empowerment, participation, equity, holism, an ecological approach, intersectorality and sustainability) in the intervention. The results are mixed: our findings reveal evidence of the application of several dimensions of health promotion (equity, holism, an ecological approach, intersectorality and sustainability), but also a lack of integration of two key dimensions; that is, empowerment and participation, during various phases of the pilot intervention. These results show that the professional development program is associated with the adoption of a pilot intervention integrating multiple but not all dimensions of health promotion. We make recommendations to facilitate a more complete integration. This research also shows that the Guichard and Ridde grid proves to be a thorough instrument to document the practices of participants.