Intelligent prognostics of machinery health utilising suspended condition monitoring data

The ability to forecast machinery failure is vital to reducing maintenance costs, operation downtime and safety hazards. Recent advances in condition monitoring technologies have given rise to a number of prognostic models for forecasting machinery health based on condition data. Although these models have aided the advancement of the discipline, they have made only a limited contribution to developing an effective machinery health prognostic system. The literature review indicates that there is not yet a prognostic model that directly models and fully utilises suspended condition histories (which are very common in practice since organisations rarely allow their assets to run to failure); that effectively integrates population characteristics into prognostics for longer-range prediction in a probabilistic sense; which deduces the non-linear relationship between measured condition data and actual asset health; and which involves minimal assumptions and requirements. This work presents a novel approach to addressing the above-mentioned challenges. The proposed model consists of a feed-forward neural network, the training targets of which are asset survival probabilities estimated using a variation of the Kaplan-Meier estimator and a degradation-based failure probability density estimator. The adapted Kaplan-Meier estimator is able to model the actual survival status of individual failed units and estimate the survival probability of individual suspended units. The degradation-based failure probability density estimator, on the other hand, extracts population characteristics and computes conditional reliability from available condition histories instead of from reliability data. The estimated survival probability and the relevant condition histories are respectively presented as “training target” and “training input” to the neural network. The trained network is capable of estimating the future survival curve of a unit when a series of condition indices are inputted. Although the concept proposed may be applied to the prognosis of various machine components, rolling element bearings were chosen as the research object because rolling element bearing failure is one of the foremost causes of machinery breakdowns. Computer simulated and industry case study data were used to compare the prognostic performance of the proposed model and four control models, namely: two feed-forward neural networks with the same training function and structure as the proposed model, but neglected suspended histories; a time series prediction recurrent neural network; and a traditional Weibull distribution model. The results support the assertion that the proposed model performs better than the other four models and that it produces adaptive prediction outputs with useful representation of survival probabilities. This work presents a compelling concept for non-parametric data-driven prognosis, and for utilising available asset condition information more fully and accurately. It demonstrates that machinery health can indeed be forecasted. The proposed prognostic technique, together with ongoing advances in sensors and data-fusion techniques, and increasingly comprehensive databases of asset condition data, holds the promise for increased asset availability, maintenance cost effectiveness, operational safety and – ultimately – organisation competitiveness.

Conveying identity with mobile content

A series of mobile phone prototypes called The Swarm have been developed in response to the user needs identified in a three-year empirical study of young people’s use of mobile phones. The prototypes take cues from user led innovation and provide multiple avatars that allow individuals to define and manage their own virtual identity. This paper briefly maps the evolution of the prototypes and then describes how the pre-defined, color coded avatars in the latest version are being given greater context and personalization through the use of digital images. This not only gives ‘serendipity a nudge’ by allowing groups to come together more easily, it provides contextual information that can reduce gratuitous contact.

Development of an online condition monitoring system for slow speed machinery

One of the main challenges of slow speed machinery condition monitoring is that the energy generated from an incipient defect is too weak to be detected by traditional vibration measurements due to its low impact energy. Acoustic emission (AE) measurement is an alternative for this as it has the ability to detect crack initiations or rubbing between moving surfaces. However, AE measurement requires high sampling frequency and consequently huge amount of data are obtained to be processed. It also requires expensive hardware to capture those data, storage and involves signal processing techniques to retrieve valuable information on the state of the machine. AE signal has been utilised for early detection of defects in bearings and gears. This paper presents an online condition monitoring (CM) system for slow speed machinery, which attempts to overcome those challenges. The system incorporates relevant signal processing techniques for slow speed CM which include noise removal techniques to enhance the signal-to-noise and peak-holding down sampling to reduce the burden of massive data handling. The analysis software works under Labview environment, which enables online remote control of data acquisition, real-time analysis, offline analysis and diagnostic trending. The system has been fully implemented on a site machine and contributing significantly to improve the maintenance efficiency and provide a safer and reliable operation.

Development of a diagnostic tool for condition monitoring of rotating machinery

This paper presents an overview of the CRC for Infrastructure and Engineering Asset Management (CIEAM)’s rotating machine health monitoring project and the status of the research progress. The project focuses on the development of a comprehensive diagnostic tool for condition monitoring and systematic analysis of rotating machinery. Particularly attention focuses on the machine health monitoring of diesel engines, compressors and pumps by using acoustic emission and vibration-based monitoring techniques. The paper also provides a brief summary of the work done by the three main research collaborating partners in the project, namely, Queensland University of Technology (QUT), Curtin University of Technology (CUT) and the University of Western Australia (UWA). Preliminary test and analysis results from this work are also reported in the paper

Education on plant and machinery valuation for the real market : Malaysian practicality

The purpose of this paper is to determine and discuss on the plant and machinery valuation syllabus for higher learning education in Malaysia to ensure the practicality of the subject in the real market. There have been limited studies in plant and machinery area, either by scholars or practitioners. Most papers highlighted the methodologies but limited papers discussed on the plant and machinery valuation education. This paper will determine inputs for plant and machinery valuation guidance focussing on the syllabus set up and references for valuers interested in this area of expertise. A qualitative approach via content analysis is conducted to compare international and Malaysian plant and machinery valuation syllabus and suggest improvements for Malaysian syllabus. It is found that there are few higher education institutions in the world that provide plant and machinery valuation courses as part of their property studies syllabus. Further investigation revealed that on the job training is the preferable method for plant and machinery valuation education and based on the valuers experience. The significance of this paper is to increase the level of understanding of plant and machinery valuation criteria and provide suggestions to Malaysian stakeholders with the relevant elements in plant and machinery valuation education syllabus.

A practical signal processing approach for condition monitoring of low speed machinery using Peak-Hold-Down-Sample algorithm

A simple and effective down-sample algorithm, Peak-Hold-Down-Sample (PHDS) algorithm is developed in this paper to enable a rapid and efficient data transfer in remote condition monitoring applications. The algorithm is particularly useful for high frequency Condition Monitoring (CM) techniques, and for low speed machine applications since the combination of the high sampling frequency and low rotating speed will generally lead to large unwieldy data size. The effectiveness of the algorithm was evaluated and tested on four sets of data in the study. One set of the data was extracted from the condition monitoring signal of a practical industry application. Another set of data was acquired from a low speed machine test rig in the laboratory. The other two sets of data were computer simulated bearing defect signals having either a single or multiple bearing defects. The results disclose that the PHDS algorithm can substantially reduce the size of data while preserving the critical bearing defect information for all the data sets used in this work even when a large down-sample ratio was used (i.e., 500 times down-sampled). In contrast, the down-sample process using existing normal down-sample technique in signal processing eliminates the useful and critical information such as bearing defect frequencies in a signal when the same down-sample ratio was employed. Noise and artificial frequency components were also induced by the normal down-sample technique, thus limits its usefulness for machine condition monitoring applications.

Social cars : sensing, gathering, sharing and conveying social cues to road users

Intelligent Transport Systems (ITS) resembles the infrastructure for ubiquitous computing in the car. It encompasses a) all kinds of sensing technologies within vehicles as well as road infrastructure, b) wireless communication protocols for the sensed information to be exchanged between vehicles (V2V) and between vehicles and infrastructure (V2I), and c) appropriate intelligent algorithms and computational technologies that process these real-time streams of information. As such, ITS can be considered a game changer. It provides the fundamental basis of new, innovative concepts and applications, similar to the Internet itself. The information sensed or gathered within or around the vehicle has led to a variety of context-aware in-vehicular technologies within the car. A simple example is the Anti-lock Breaking System (ABS), which releases the breaks when sensors detect that the wheels are locked. We refer to this type of context awareness as vehicle/technology awareness. V2V and V2I communication, often summarized as V2X, enables the exchange and sharing of sensed information amongst cars. As a result, the vehicle/technology awareness horizon of each individual car is expanded beyond its observable surrounding, paving the way to technologically enhance such already advanced systems. In this chapter, we draw attention to those application areas of sensing and V2X technologies, where the human (driver), the human’s behavior and hence the psychological perspective plays a more pivotal role. The focal points of our project are illustrated in Figure 1: In all areas, the vehicle first (1) gathers or senses information about the driver. Rather than to limit the use of such information towards vehicle/technology awareness, we see great potential for applications in which this sensed information is then (2) fed back to the driver for an increased self-awareness. In addition, by using V2V technologies, it can also be (3) passed to surrounding drivers for an increased social awareness, or (4), pushed even further, into the cloud, where it is collected and visualized for an increased, collective urban awareness within the urban community at large, which includes all city dwellers.

Standardisation of plant and machinery valuation practices in Malaysia

Plant and machinery valuation is important to every company.s annual financial reporting. It is reported under the non-current assets section, and the valuers are generally employed to provide the up to date valuation of the non-current assets valuation such as property, plant and equipment that can make up to 80% of the total assets of a company. The valuation of plant and machinery is also important for other purposes such as securing loan facilities, sales, takeover, insurance and auction. The application of 2005 International Financial Reporting Standard (IFRS) has a subsequent impact on the financial sector, as a whole. The accountants have to choose between the Historical Cost approach and Market Value approach in determining the value of the client.s assets. In Malaysia, the implementation of IFRS has a domino effect on the financial system, especially for plant and machinery valuation for financial reporting. The comparison data for plant and machinery valuation is limited unlike land and building valuation. The question of Malaysian valuer.s ability to comply with the IFRS standard keeps rising every day, not just to the accountants, but also other related parties such as financial institutions, government agencies and the clients. This is happening because of different interpretations of premise of value for plant and machinery, as well as methods been used and differences in standards of reporting among the valuers conducting plant and machinery valuation. The root of the problem lies in the lack of practical guidelines governing plant and machinery valuation practices and different schools of thought among the valuers. Some follow the United Kingdom.s RICS guidelines, whilst some valuers are more comfortable with the United State.s USPAP rules, especially on the premise of value. This research is to investigate the international best practices of plant and machinery valuation and to establish the common valuation concept, awareness and application of valuation methodology and valuation process for plant and machinery valuation in Malaysia. This research uses a combination of the qualitative and quantitative research approach. In the qualitative approach, the content analyses were conducted from the international practices and current Malaysian implementation of plant and machinery valuation. A survey (quantitative approach) via questionnaire was implemented among the registered and probationary valuers in Malaysia to investigate their understanding and opinion relating to plant and machinery valuation based on the current practices. The significance of this research is the identification of international plant and machinery practices and the understanding of current practices of plant and machinery valuation in Malaysia. It is found that issues embedding plant and machinery valuation practices are limited numbers of resources available either from scholars or practitioner. This is supported by the general finding from the research survey that indicates that there are immediate needs for practical notes or guidelines to be developed and implemented to support the Malaysian valuers practising plant and machinery valuation. This move will lead to a better understanding of plant and machinery valuation, reducing discrepancies in valuation of plant and machinery and increased accuracy among practising valuers.

Dancing Diseases : an applied theatre response to the challenge of conveying emotionally contradictory messages in HIV education

Health educators face an unusual challenge in relation to HIV: the need to convey two emotionally contradictory messages. On the one hand, there is currently no cure for HIV, which eventually leads to death (emotionally negative message). On the other hand, people with HIV can live long, healthy and productive lives (emotionally positive message). In developing countries where HIV prevalence is high, it is imperative that both messages are conveyed effectively. This article reports on a specific form, Dancing Diseases, implemented as one component of the Life Drama pilot study on Karkar Island, Papua New Guinea. Life Drama is an applied theatre and performance approach to HIV education. The article discusses Dancing Diseases as an example of applied theatre and performance practice, reflects on the participant group’s engagement with the form, and offers some ways in which the form could be refined and used in other health education contexts.