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Multi-size-window spectral augmentation: Neural network bearing fault classifier

- Amar, Muhammad, Gondal, Iqbal, Wilson, Campbell

  • Authors: Amar, Muhammad , Gondal, Iqbal , Wilson, Campbell
  • Date: 2013
  • Type: Text , Conference paper
  • Relation: 2013 8th IEEE Conference on Industrial Electronics and Applications (ICIEA) p. 261-266
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  • Description: Features extraction has always been crucial in rotary machines for Condition based machine health monitoring. Time-domain-segmentation being among the preliminary steps for further classification process plays a momentous role. Vibration signals from bearing are quasistationary in nature therefore calculation of constituent frequencies amplitudes in the vibration signal is dependent upon time-segmentation-window size. The proposed research confers the effects of time-segmentation window size on spectral features amplitudes calculation and its impacts on classification accuracy of the Artificial Neural Network (ANN). Using multi-size time-segmentation-window, for comprehensive spectral features calculation, ANN pattern classifier has been trained for enhanced classification. ANN learning assigns importance based relative weights to the links using supervised learning. Experimental results have shown that multi-size-window spectral features for ANN fault classifier perform efficiently for quasi-stationary bearing vibrations.

Representing ordered order-k Voronoi diagrams

- Wang, Yutang, Lee, Kyungmi, Lee, Ickjai

  • Authors: Wang, Yutang , Lee, Kyungmi , Lee, Ickjai
  • Date: 2011
  • Type: Text , Conference paper
  • Relation: 7th International Conference on Information Processing and Management, ICIPM 2011
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  • Description: The ordered order-k Voronoi diagram is a popular generalization of the ordinary Voronoi diagram modeling ordered k nearest sites. Despite of the usefulness of the ordered order-k Voronoi diagram, its structural complexity and wealth of information captured result in poor readability. Most research has focused on computational complexity, and visualization/representation of the ordered order-k Voronoi diagram has received little attention. This paper attempts to represent the ordered order-k Voronoi diagram through its relationship with other higher order Voronoi diagrams. The proposed method highlights topo-logical relationships between/among higher order Voronoi diagram families, and enhances the readability of the ordered order-k diagram.

Fuzzy logic inspired bearing fault-model membership estimation

- Amar, Muhammad, Gondal, Iqbal, Wilson, Campbell

  • Authors: Amar, Muhammad , Gondal, Iqbal , Wilson, Campbell
  • Date: 2013
  • Type: Text , Conference paper
  • Relation: 2013 IEEE Eighth International Conference on Intelligent Sensors, Sensor Networks and Information Processing p. 420-425
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  • Description: In rotary machines bearings are a primary cause of failure. In order to estimate the time before failure to provide information for timely bearing replacement strategies, condition-based machine health monitoring techniques are employed. This paper discusses a model for estimating the severity of bearing faults that can be used for residual bearing life estimation by processing the vibration signal. The proposed technique used in this model examines the spectral content of vibration signals across frequency bins and then fits Gaussian distributions to each frequency bin. With the use of these Gaussian models and training set examples with different fault severity levels, characteristic membership functions are constructed. This enables estimation of the severity levels of the bearing faults through a fuzzy-logic inspired process, whereby the severity level corresponds to the maximum of the set of corresponding membership functions. Thus based on discrete fault severity levels, trained Gaussian fittings of spectral bins and characteristic fault membership functions are capable to estimate the fault severity on a continuous scale.

Issues and challenges of balancing cost, performance and risk in heavy-haul rail asset management

- Chattopadhyay, Gopinath

  • Authors: Chattopadhyay, Gopinath
  • Date: 2016
  • Type: Text , Conference paper
  • Relation: 2016 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM) p. 521-525
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  • Description: ISO55000 is the International Organisation for Standardization (ISO) standard for asset management published in 2014. It stipulates that effective control and governance of assets by organizations is essential to realize value through managing risk and opportunity, in order to achieve the desired balance of cost, risk and performance. It is a challenge to industries on how to address this. This paper is on the issues and challenges of balancing cost, performance and risk in heavy haul rail asset management. Illustrative example from heavy haul network is used for this and on how to address some of the important challenges faced by heavy haul sector for managing life of rail assets.

StressCloud : A tool for analysing performance and energy consumption of cloud applications

- Chen, Feifei, Grundy, John, Schneider, Jean-Guy, Yang, Yun, He, Qiang

  • Authors: Chen, Feifei , Grundy, John , Schneider, Jean-Guy , Yang, Yun , He, Qiang
  • Date: 2015
  • Type: Text , Conference paper
  • Relation: 2015 IEEE/ACM 37th IEEE International Conference on Software Engineering (ICSE)
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  • Description: Finding the best deployment configuration that maximises energy efficiency while guaranteeing system performance of cloud applications is an extremely challenging task. It requires the evaluation of system performance and energy consumption under a wide variety of realistic workloads and deployment configurations. This paper demonstrates StressCloud, an automatic performance and energy consumption analysis tool for cloud applications in real-world cloud environments. StressCloud supports 1) the modelling of realistic cloud application workloads, 2) the automatic generation and running of load tests, and 3) the profiling of system performance and energy consumption.

Integration of LIDAR data and orthoimage for automatic 3D building roof plane extraction

- Awrangjeb, Mohammad, Fraser, Clive, Lu, Guojun

  • Authors: Awrangjeb, Mohammad , Fraser, Clive , Lu, Guojun
  • Date: 2013
  • Type: Text , Conference paper
  • Relation: 2013 IEEE International Conference on Multimedia and Expo (ICME)
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  • Description: Automatic 3D extraction of building roofs from remotely sensed data is important for many applications including city modeling. This paper proposes a new method for automatic 3D roof extraction through an effective integration of LIDAR (Light Detection And Ranging) data and multispectral orthoimagery. Using the ground height from a DEM (Digital Elevation Model), the raw LIDAR points are separated into two groups. The first group contains the ground points that are exploited to constitute a `ground mask'. The second group contains the non-ground points which are segmented using an innovative image line guided segmentation technique to extract the roof planes. The image lines extracted from the grey-scale version of the orthoimage are classified into several classes such as `ground', `tree', `roof edge' and `roof ridge' using the ground mask and colour and texture information from the orthoimagery. During roof plane extraction the lines from the later two classes are used to fit roof planes to the neighbouring non-ground LIDAR points. Finally, a new rule-based procedure is applied to remove planes constructed on trees. Experimental results show that the proposed method successfully removes vegetation and offers high extraction rates.

Movement safety control method of a haptic device for Minimally Invasive Surgery

- Saafi, Houssem, Laribi, Med Amine, Zeghloul, Saïd, Ibrahim, Yousef

  • Authors: Saafi, Houssem , Laribi, Med Amine , Zeghloul, Saïd , Ibrahim, Yousef
  • Date: 2014
  • Type: Text , Conference paper
  • Relation: 2014 IEEE 23rd International Symposium on Industrial Electronics (ISIE) p. 1233-1238
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  • Description: Abstract: The overall objective of this work is to develop a system composed of master, slave and a control system for special medical applications. A PROMIS (Pprime RObot for Minimally Invasive Surgery) system is designed to be cost-effective with a less complication of use and an application-specific for collaborative operations between the surgeon and the robot. This paper focuses on the introduction of a motion safety control methodology for a haptic device. The haptic device is used as a master with a parallel spherical architecture (SPM). The introduced control methodology is based on the workspace of the medical application. Three areas of the workspace are defined with a consideration of the degree of security. An algorithm that constantly keeps the mobile platform in a safe region, when the surgeon moves it, is presented and explained. The developed algorithm runs in real-time using a programmable logic controller (PLC). The control strategy of the haptic device was successfully tested and validated experimentally.

Building roof plane extraction from LIDAR data

- Awrangjeb, Mohammad, Lu, Guojun

  • Authors: Awrangjeb, Mohammad , Lu, Guojun
  • Date: 2013
  • Type: Text , Conference paper
  • Relation: 2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA)
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  • Description: This paper presents a new segmentation technique to use LIDAR point cloud data for automatic extraction of building roof planes. The raw LIDAR points are first classified into two major groups: ground and non-ground points. The ground points are used to generate a 'building mask' in which the black areas represent the ground where there are no laser returns below a certain height. The non-ground points are segmented to extract the planar roof segments. First, the building mask is divided into small grid cells. The cells containing the black pixels are clustered such that each cluster represents an individual building or tree. Second, the non-ground points within a cluster are segmented based on their coplanarity and neighbourhood relations. Third, the planar segments are refined using a rule-based procedure that assigns the common points among the planar segments to the appropriate segments. Finally, another rule-based procedure is applied to remove tree planes which are generally small in size and randomly oriented. Experimental results on three Australian sites have shown that the proposed method offers high building detection and roof plane extraction rates.

Utilisation of data mining in mining industry: Improvement of the shearer loader productivity in underground mines

- Balaba, Benhur, Ibrahim, Yousef, Gunawan, Indra

  • Authors: Balaba, Benhur , Ibrahim, Yousef , Gunawan, Indra
  • Date: 2012
  • Type: Text , Conference proceedings
  • Relation: Industrial Informatics (INDIN), 2012 10th IEEE International Conference, Beijing, China, 25-27 July 2012 p. 1041- 1046
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  • Description: This paper presents an investigative study in which data were gathered and used in underground mining to improve the planned maintenance program and reliability of the shearer loader in the underground mining. A cost effective maintenance and operation strategy and practices is mandatory to meet the production demand and the required level of service of this critical asset of the plant. The study conducted and presented in this paper includes a detailed review of failure history data and the use of analytical technique available to understand failure characteristics and its effect on the throughput and the overall performance of the longwall operation. This is to achieve further productivity increases to meet business goals. Analytical tools such as Failure Mode and Effect and Criticality Analysis (FMECA) and Weibull analysis were used in this investigation. The study has highlighted the criticality of some failures and the actions needed in this industrial case to improve the reliability and planned maintenance for a better mining productivity.

Estimation of strain of distorted FBG sensor spectra using a fixed FBGfilter circuit and an artificial neural network

- Kahandawa, Gayan, Epaarachchi, Jayantha, Lau, Alan, Canning, John

  • Authors: Kahandawa, Gayan , Epaarachchi, Jayantha , Lau, Alan , Canning, John
  • Date: 2013
  • Type: Text , Conference paper
  • Relation: 2013 IEEE 8th International Conference on Intelligent Sensors, Sensor Networks and Information Processing: Sensing the Future, ISSNIP 2013 p. 89-94
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  • Description: Fibre Bragg Grating (FBG) sensors are extremely sensitive to changes of strain, and are therefore an extremely useful candidate for Structural Health Monitoring (SHM) systems of composite structures. Sensitivity of FBGs to strain gradients originating from damage was observed as an indicator of initiation and propagation of damage in composite structures. To date there have been numerous research works done on distorted FBG spectra due to damage accumulation under controlled environments. Unfortunately, a number of related unresolved problems remain in FBG-based SHM systems development, making the present SHM systems unsuitable for real life applications. This paper reveals a novel configuration of FBG sensors to acquire strain reading and an integrated statistical approach to analyse data in real time. The proposed configuration has proven its capability to overcome practical constraints and the engineering challenges associated with FBG-based SHM systems. A fixed filter decoding system and an integrated artificial neural network algorithm for extracting strain from embedded FBG sensor were proposed and experimentally proved. Furthermore, the laboratory level experimental data was used to verify the accuracy of the system and it was found that the error levels were less than 0.3% in strain predictions.

Spectrum-Based Runtime Anomaly Localisation in Service-Based Systems

- He, Qiang, Xie, Xiaoyuan, Chen, Feifei, Vasa, Rajesh, Yang, Yun, Jin, Hai

  • Authors: He, Qiang , Xie, Xiaoyuan , Chen, Feifei , Vasa, Rajesh , Yang, Yun , Jin, Hai
  • Date: 2015
  • Type: Text , Conference paper
  • Relation: 2015 IEEE International Conference on Services Computing (SCC)
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  • Description: Runtime anomalies occurring to service-based systems (SBSs) must be located and fixed in a timely manner in order to guarantee successful delivery of outcomes in response to user requests. Monitoring all component services constantly is impractical due to excessive resource consumption. Inspecting all component services upon anomalies is time-consuming and thus also impractical. In this work, we propose a novel approach that employs spectrum-based fault localisation techniques to locate runtime anomalies in SBSs. Large-scale experiments are conducted and experimental results are presented to demonstrate the effectiveness and efficiency of the proposed approach.

An improved method to infer gene regulatory network using s-system

- Chowdhury, Ahsan, Chetty, Madhu

  • Authors: Chowdhury, Ahsan , Chetty, Madhu
  • Date: 2011
  • Type: Text , Conference paper
  • Relation: IEEE Congress on Evolutionary Computation (IEEE CEC) p. 1012-1019
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  • Description: Abstract—Gene Regulatory Network (GRN) plays an important role in the understanding of complex biological systems. In most cases, high throughput microarray gene expression data is used for finding these regulatory relationships among genes. In this paper, we present a novel approach, based on decoupled SSystem model, for reverse engineering GRNs. In the proposed method, the genetic algorithm used for scoring the networks contains several useful features for accurate network inference, namely a Prediction Initialization (PI) algorithm to initialize the individuals, a Flip Operation (FO) for better mating of values and a restricted execution of Hill Climbing Local Search over few individuals. It also includes a novel refinement technique which utilizes the fit solutions of the genetic algorithm for optimizing sensitivity and specificity of the inferred network. Comparative studies and robustness analysis using standard benchmark data set show the superiority of the proposed method.

Friction-based slippage and tangential force detection in robotic grasping

- Dzitac, Pavel, Mazid, Abdul Md, Ibrahim, Yousef, Choudhury, Tanveer, Appuhamillage, Gayan

Optimum clusters for reliable and energy efficient wireless sensor networks

- Sadat, Anwar, Karmakar, Gour

  • Authors: Sadat, Anwar , Karmakar, Gour
  • Date: 2011
  • Type: Text , Conference paper
  • Relation: 2011 10th IEEE International Symposium on Network Computing and Applications (NCA) p. 342-347
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  • Description: One of the challenging aspects for wireless sensor network (WSN) clustering is to estimate the optimal cluster number. Most WSN clustering techniques have used an a priori value to determine the cluster number. A few techniques, available at the literature, attempted to find the optimal cluster number by energy minimization. However, due to the assumption of lossless communication, these initiatives do not always converge to the minimum energy as wireless channels are error-prone. As wireless communication is always vulnerable to the signal interference, environmental noise, and so on, it suffers from data loss. To capture the characteristics of the communication phenomenon in a real context and have better reliability, we need to embed the link quality into the cluster number determination process. To address this issue, in this paper together with the energy, we incorporate link quality metric into the theoretical underpinning to achieve an optimal cluster number analytically and finally justified the result by simulation.

Efficient coding strategy for HEVC performance improvement by exploiting motion features

- Podder, Pallab, Paul, Manoranjan, Murshed, Manzur

  • Authors: Podder, Pallab , Paul, Manoranjan , Murshed, Manzur
  • Date: 2015
  • Type: Text , Conference paper
  • Relation: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing, Brisbane, QLD, 19th-24th April, 2015 p. 1414-1418
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  • Description: The striking feature of High Efficiency Video Coding (HEVC) Standard is emphasized by 50% bit-rate reduction compared to its predecessor H.264/AVC while keeping the same perceptual image quality. The time complexity - a congenital issue of HEVC has also increased to intensify the compression ratio. However, it is really a demanding task for the researchers to reduce the encoding time while preserving expected quality of the video sequences. Our contribution is to trim down the computational time by efficient selection of appropriate block-partitioning modes in HEVC using motion features based on phase-correlation. In this paper, we use phase-correlation between current and reference blocks to extract three motion features and combine them to determine binary motion pattern of the current block. The motion pattern is then matched against a codebook of predefined pattern templates to determine a subset of the inter-modes. Only the selected modes are exhaustively motion estimated and compensated for a coding unit. The experimental outcomes demonstrate that the average computational time can be down scaled by 30% of the HEVC while providing improved rate-distortion performance.

A machine vision based automatic optical inspection system for measuring drilling quality of printed circuit boards

- Wang, Wei, Chen, Shang-Liang, Chen, Liang-Bi, Chang, Wan-Jung

  • Authors: Wang, Wei , Chen, Shang-Liang , Chen, Liang-Bi , Chang, Wan-Jung
  • Date: 2017
  • Type: Text , Journal article
  • Relation: IEEE Access Vol. 5, no. (2017), p. 10817-10833
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  • Description: In this paper, we develop and put into practice an automatic optical inspection (AOI) system based on machine vision to check the holes on a printed circuit board (PCB). We incorporate the hardware and software. For the hardware part, we combine a PC, the three-axis positioning system, a lighting device, and charge-coupled device cameras. For the software part, we utilize image registration, image segmentation, drill numbering, drill contrast, and defect displays to achieve this system. Results indicated that an accuracy of 5 mu m could be achieved in errors of the PCB holes allowing comparisons to be made. This is significant in inspecting the missing, the multi-hole, and the incorrect location of the holes. However, previous work only focuses on one or other feature of the holes. Our research is able to assess multiple features: missing holes, incorrectly located holes, and excessive holes. Equally, our results could be displayed as a bar chart and target plot. This has not been achieved before. These displays help users to analyze the causes of errors and immediately correct the problems. In addition, this AOI system is valuable for checking a large number of holes and finding out the defective ones on a PCB. Meanwhile, we apply a 0.1-mm image resolution, which is better than others used in industry. We set a detecting standard based on 2-mm diameter of circles to diagnose the quality of the holes within 10 s.

Robust force control with a novel gain tuning methodology based on the stable margin theory

- Ogawa, Kenji, Ohnishi, Kouhei, Ibrahim, Yousef

  • Authors: Ogawa, Kenji , Ohnishi, Kouhei , Ibrahim, Yousef
  • Date: 2017
  • Type: Text , Conference paper
  • Relation: 2017 IEEE 26th International Symposium on Industrial Electronics (ISIE) p. 1123-1128
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  • Description: This paper proposes a force control system using the State Observer Based Disturbance Observer (SO-DOB) and the State Observer Based Reaction Force Observer (SO-RFOB) based on the novel observer gain tuning methodology. The observer gain tuning methodology is based on the stable margin theory. By using the proposed gain tuning methodology, the system stability and the robustness of the SO-DOB and the SO-RFOB is guaranteed. The validity of the proposed method was tested by both simulation and the experiment works. From the results, the control performance was improved compared with the DOB and the RFOB based on the Low Pass Filter (LPF) based estimation.

Mechatronics training through project-based learning and industry liaison

- Ibrahim, Yousef

  • Authors: Ibrahim, Yousef
  • Date: 2008
  • Type: Text , Conference paper
  • Relation: ISIE08 30 June 2008 to 2 July 2008 p. 1383-1387
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  • Description: This paper presents a technique that was used in the development of Mechatronics courses in Thailand and Australia. The technique was based on project-based learning and industry engagement. Mechatronics course development was supported by AusAID grant to the Royal Thai Government (RTG) to establish six different mechatronics programs in six Universities. Mechanisms were established to ensure industrypsilas input throughout the stages of mechatronics course development at each University. This paper discusses those mechanisms.

Improved symmetric-SIFT for Multi-modal image registration

- Hossain, Md. Tanvir, Lv, Guohua, Teng, Shyh, Lu, Guojun, Lackmann, Martin

  • Authors: Hossain, Md. Tanvir , Lv, Guohua , Teng, Shyh , Lu, Guojun , Lackmann, Martin
  • Date: 2011
  • Type: Text , Conference paper
  • Relation: 2011 International Conference on Digital Image Computing: Techniques and Applications p. 197-202
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  • Description: Multi-modal image registration has received significant research attention over the past decade. SymmetricSIFT is a recently proposed local description technique that can be used for registering multi-modal images. It is based on a well-known general image registration technique named Scale Invariant Feature Transform (SIFT). Symmetric-SIFT, however, achieves this invariance to multi-modality at the cost of losing important information. In this paper, we show how this loss may adversely affect the accuracy of registration results. We then propose an improvement to Symmetric-SIFT to overcome the problem. Our experimental results show that the proposed technique can improve the number of true matches by up to 10 times and overall matching accuracy by up to 30%.

Foreground motion and spatial saliency-based efficient HEVC Video Coding

- Podder, Pallab, Paul, Manoranjan, Murshed, Manzur

  • Authors: Podder, Pallab , Paul, Manoranjan , Murshed, Manzur
  • Date: 2015
  • Type: Text , Conference paper
  • Relation: 2015 International Conference on Image and Vision Computing New Zealand (IVCNZ)
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  • Description: High Efficiency Video Coding (HEVC) could not provide real time facilities to the limited processing and battery powered electronic devices as its encoding time complexity increases multiple times compared to its predecessor. Numerous researchers contribute to address this limitation by reducing a number of motion estimation (ME) modes where they analyze homogeneity, residual and statistical correlation among different modes. Although their approaches save some encoding time, however, could not reach the similar rate-distortion (RD) performance with HEVC encoder as they merely depend on existing Lagrangian cost function (LCF) within HEVC framework. To overcome this limitation, in this paper, we capture visual attentive Foreground motion and salient region (FMSR) which are sensitive to human visual system for quality assessment. The FMSR features captured by visual attentive and dynamic background modeling are adaptively synthesized to determine a subset of candidate modes. This preprocessing phase is independent from LCF. Since the proposed technique can avoid exhaustive exploration of all modes with simple criteria, it can reduce 27% encoding time on average. With efficient selection of FMSR-based appropriate block partitioning modes, it can also improve up to 1.0dB peak signal-to-noise ratio (PSNR).