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IEEE International Conference on Prognostics and Health Management (ICPHM)

作者： Chen, Shaowei Wu, Meng Zhao, Shuai Wen, Pengfei Huang, Dengshan Wang, Yan Northwestern Polytech Univ Sch Elect & Informat Xian Peoples R China Aalborg Univ Dept Energy Technol DK-9220 Aalborg Denmark

ISBN: (纸本)9781538683576

Identifying the degradation state of aircraft engine accurately and carrying out suitable maintenance is significant for the safe and reliable operation of the aircraft system. In this paper, an anomaly detection system is proposed for multi-dimensional time series for aircraft engine. To represent the degradation degree of the device, the degradation index is proposed utilizing the dynamic time warping algorithm (DTW) which possesses good similarity measure quality and can capture the changing characteristics of the indicator well. On the basis of the degradation index, three decision-making strategies including the Cumulative Sum algorithm (CUSUM), the Youden Index, and the Impact Factor are applied to determine the threshold values. For the threshold, two detection time points are obtained to discriminate different degradation stages in the device, in which the former refers to the initiation of degradation and the latter time point indicates that the device suffers from the anomaly. The experimental results demonstrate that all three decision strategies are able to detect system performance effectively before the device fails, which facilitates the incipient fault warning of aircraft engine in order to keep the equipment safe and reliable.

关键词： anomaly detection dynamic time warping algorithm degradation index decision strategy aircraft engine

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Off-line Signature Verification based on Modified dynamic time warping algorithm

Off-line Signature Verification based on Modified Dynamic Ti...

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31st Chinese Control Conference

作者： Tian Wei Lv Jing-yuan Univ Jinan Sch Elect Engn Jinan 250022 Peoples R China Shandong Prov Publ Secur Dept Jinan 250001 Peoples R China

ISBN: (纸本)9789881563811

This work presents an innovative approach for off-line signature verification based on modified dynamic time warping (DTW) algorithm. Conventional DTW does not account for the relative importance regarding the phase difference between a reference point and a testing point, By using the projection profiles of signatures, the scheme employed Projection stability Point and Projection stability factor which acted as weighted DTW, in order to prevent minimum distance distortion caused by outliers.. The databases of English signatures are applied to the experiments and the average error rates of 11.4% are obtained to verify the effectiveness of the proposed system.

关键词： signature verification dynamic time warping algorithm projection feature

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Motion standard level system based on Internet of things

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INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS 2019年第4期15卷

作者： Yu, Miao Shenyang Sport Univ Sch Management & Journalism 36 Jinqiansong East Rd Shenyang 110102 Liaoning Peoples R China

Recognition of motion level is a popular research area in the field of image processing in recent years. Based on the sensor equipment of action data acquisition, this article analyses the sensitivity of the micro-electro-mechanical system sensor. Then, according to the data-centric characteristics of the Internet of things, a distributed memory file storage and file writing system is constructed in the Internet of things environment, and the reliability and effectiveness of SensorFS are verified. Finally, dynamic time warping algorithm is used to evaluate the standard degree of human movement with dynamic time warping difference as experimental parameter, and a demonstration experiment of shadowboxing is designed to verify it. The result error is less than 0.05% by changing the standard of shadowboxing artificially, which proves the accuracy of the system. It provides a theoretical basis for the establishment of the standard system based on the Internet of things.

关键词： micro-electro-mechanical system sensor Internet of things standard degree system dynamic time warping algorithm

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Quantitative Parameters Developing for Estimation of Rehabilitation Exercising on The Basis of IMU Sensor Device 7

Quantitative Parameters Developing for Estimation of Rehabil...

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7th Mediterranean Conference on Embedded Computing (MECO)

作者： Ashapkina, Maria S. Alpatov, Alexey, V Sablina, Victoria A. Chekushin, Alexander A. Ryazan State Radio Engn Univ Ryazan Russia Ryazan State Med Univ Ryazan Russia

ISBN: (纸本)9781538656839

An important part of any rehabilitation procedure is the patient's ability to control exercising accuracy in the real time. The doctor or training specialist provides feedback in the traditional mode of such exercises. In this work we suggest using smartphone MEMS sensors (which function for fixation of motion pattern) as the feedback. The main goal is comparing the acquired motion pattern with its model sample. DWT algorithm was chosen as the estimating method of similarity measure of the two patterns. Determination of parameters, which define exercising quality, was based on quantitative characteristics computation of each iteration of motion: accuracy, synchronicity, amplitude, number of repetitions.

关键词： rehabilitation recovery exercises MEMS sensors accelerometer gyroscope dynamic time warping algorithm

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Kinect-Based Virtual Game for the Elderly that Detects Incorrect Body Postures in Real time

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SENSORS 2016年第5期16卷 704-704页

作者： Saenz-de-Urturi, Zelai Soto, Begonya Garcia-Zapirain Univ Deusto DeustoTech LIFE Unit DeustoTech Inst Technol Bilbao 48007 Spain

Poor posture can result in loss of physical function, which is necessary to preserving independence in later life. Its decline is often the determining factor for loss of independence in the elderly. To avoid this, a system to correct poor posture in the elderly, designed for Kinect-based indoor applications, is proposed in this paper. Due to the importance of maintaining a healthy life style in senior citizens, the system has been integrated into a game which focuses on their physical stimulation. The game encourages users to perform physical activities while the posture correction system helps them to adopt proper posture. The system captures limb node data received from the Kinect sensor in order to detect posture variations in real time. The DTW algorithm compares the original posture with the current one to detect any deviation from the original correct position. The system was tested and achieved a successful detection percentage of 95.20%. Experimental tests performed in a nursing home with different users show the effectiveness of the proposed solution.

关键词： Kinect postural control virtual game elderly dynamic time warping algorithm

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Intelligent autonomous system for residential water end use classification: Autoflow

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APPLIED SOFT COMPUTING 2015年 31卷 118-131页

作者： Khoi Anh Nguyen Stewart, Rodney A. Zhang, Hong Jones, Christopher Griffith Univ Griffith Sch Engn Nathan Qld 4111 Australia City West Water Sunshine Vic 3020 Australia

Over half of the world's population will live in urban areas in the next decade, which will impose significant pressure on water security. The advanced management of water resources and their consumption is pivotal to maintaining a sustainable water future. To contribute to this goal, the aim of this study was to develop an autonomous and intelligent system for residential water end-use classification that could interface with customers and water business managers via a user-friendly web-based application. Water flow data collected directly from smart water metres connected to dwellings includes both single( e.g., a shower event occurring alone) and combined (i.e., an event that comprises several overlapping single events) water end use events. The authors recently developed an intelligent application called Autoflow which served as a prototype tool to solve the complex problem of autonomously categorising residential water consumption data into a registry of single and combined events. However, this first prototype application achieved overall recognition accuracy of 85%, which is not sufficient for a commercial application. To improve this accuracy level, a larger dataset consisting of over 82,000 events from over 500 homes in Melbourne and South-east Queensland, Australia, were employed to derive a new single event recognition method employing a hybrid combination of Hidden Markov Model (HMM), Artificial Neural Networks (ANN) and the dynamic time warping (DTW) algorithm. The classified single event registry was then used as the foundations of a sophisticated hybrid ANN-HMM combined event disaggregation module, which was able to strip apart concurrently occurring end use events. The new hybrid model's recognition accuracy ranged from 85.9% to 96.1% for single events and 81.8-91.5% for combined event disaggregation, which was a 4.9% and 8.0% improvement, respectively, when compared to the first prototype model. The developed Autoflow tool has far-reaching implicati

关键词： Water end use event Residential water flow trace disaggregation Water micro-component Hidden Markov Model dynamic time warping algorithm Artificial Neural Networka

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Intelligent model to categorise mechanised water end uses 21

Intelligent model to categorise mechanised water end uses

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21st International Congress on Modelling and Simulation (MODSIM) held jointly with the 23rd National Conference of the Australian-Society-for-Operations-Research / DSTO led Defence Operations Research Symposium (DORS

作者： Nguyen, K. A. Stewart, R. A. Zhang, H. Chowdhury, S. H. Griffith Univ Griffith Sch Engn Griffith NSW Australia

ISBN: (纸本)9780987214355

The current population boom has pushed demand on residential land in most world metropolitan cities to its extreme limit, and also imposed significant pressure on water security. To ease this problem, construction of residential apartment building has been the top priority of the governments. With the rapid advancement in technology, especially in water metering area, the next generation of these buildings is expected to not only offer their residents a comfortable living area but also make the water supply and management become much more effectively controllable. To contribute to this goal, the aim of this study was to develop an autonomous and intelligent system for residential water end-use classification that could interface with customers and water business managers via a user-friendly smartphone and webbased applications. The authors recently developed an intelligent application called Autoflow (c) which served as a prototype tool to solve the complex problem of autonomously categorising residential water consumption data into a registry of single and combined events. This model was developed using data collected in several cities in Australia, and when applied on single residential property, the achieved accuracy ranged from 86% - 96%. The only limitation of Autoflow (c) is that when being deployed overseas, a new water end use dataset must be collected to retrain the model to adapt to the new regions. The ultimate goal of this study is to develop the next Autoflow (c) generation, called AutoflowAB, which can be applied in all future apartment buildings to help disaggregate water consumption autonomously into the six main categories including: shower, toilet, tap, clothes washer, dishwasher and evaporative air cooler without relying on any previously collected data for training. The key employed techniques are dynamic time warping (DTW) and Decision Tree. The model has been tested on 150 residential properties in Australia where the accuracy ranges from 87 -

关键词： Water end use event residential water flow trace disaggregation water micro-component Hidden Markov Model dynamic time warping algorithm

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An autonomous and intelligent expert system for residential water end-use classification

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EXPERT SYSTEMS WITH APPLICATIONS 2014年第2期41卷 342-356页

作者： Khoi Anh Nguyen Stewart, Rodney A. Zhang, Hong Griffith Univ Griffith Sch Engn Nathan Qld 4222 Australia Griffith Univ Ctr Infrastruct Engn & Management Gold Coast Campus Qld 4222 Australia

Intelligent metering technology combined with advanced numerical techniques enable a paradigm shift in the current level of water consumption information provision that is available to the customer and the water business. The aim of this study was to develop an autonomous and intelligent system for residential water end-use classification that could interface with customers and water business managers via a user-friendly web-based application. Water flow data collected directly from smart water meters includes both single (e.g., a shower event occurring alone) and combined (i.e., an event that comprises several overlapping single events) water end use events. The authors recently developed intelligent algorithms to solve the complex problem of autonomously categorising residential water consumption data into a registry of single and combined events using a hybrid combination of techniques including Hidden Markov Model (HMM), dynamic time warping (DTW) algorithm, time-of-day probability functions, threshold values and various physical features. However, the issue still remained, which is the focus of this current paper, on how to integrate self-learning functionality into the visioned expert system, in order that it can learn from newly collected datasets from different cities, regions and countries, to that collected for the training data. Such versatility and adaptive capacity is essential to make the expert system widely applicable. Through applying alternate forms of HMM and DTW in association with a frequency analysis technique, a suitable self-learning methodology was formulated and tested on three independent households located in Melbourne, Australia with a prediction accuracy of between 80% and 90% for the major end-use categories. The three principle flow data processing modules (i.e., single and combined event recognition and self-learning function) were integrated into a prototype software application for performing autonomous water end-use analysis and i

关键词： Water end-use event Water micro-component Residential water flow trace disaggregation Hidden Markov Model dynamic time warping algorithm Gradient Vector Filtering Adaptive analysis Adaptive function Water demand management

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Road Network Inference from GPS Traces using DTW algorithm 17

Road Network Inference from GPS Traces using DTW Algorithm

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IEEE 17th International Conference on Intelligent Transportation Systems (ITSC)

作者： Xie, Xingzhe Philips, Wilfried Veelaert, Peter Aghajan, Hamid Univ Ghent TELIN IPI IMINDS Ghent Belgium Stanford Univ Dept Elect Engn Stanford CA 94305 USA

ISBN: (纸本)9781479960781

This paper proposes a method for inferring the road network from Global Position System (GPS) traces, which is composed of intersections and the roads between each pair of directly-connected intersections. Random Sampling (RANSAC) algorithm is used to cluster the turning points, where the users change their moving directions, into intersections. All of the GPS traces are segmented by the intersections, resulting in connectivity matrix of the intersections and small GPS tracks for each pair of directly-connected intersections. At last, the road between each two directly-connected intersections is extracted through aligning and averaging all of the tracks using dynamic time warping (DTW) algorithm. The main novelty of our methods is aligning the tracks point by point for each road using a "stretching and compression" strategy, which not only allows road estimation by averaging the aligned tracks, but also a deeper statistical analysis using their time alignment, such as analyzing the users' speed stability at a specific location. The experimental results show that our algorithm outperforms other methods by producing clean road network without spurious edges.

关键词： Global Positioning System inference mechanisms road vehicles signal sampling statistical analysis synchronisation time warp simulation DTW algorithm GPS traces GPS tracks Global Position System RANSAC algorithm connectivity matrix dynamic time warping algorithm random sampling algorithm road estimation road network inference time alignment user speed stability Euclidean distance Gold Heuristic algorithms Indexes Roads Turning

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Development of an intelligent model to categorise residential water end use events

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JOURNAL OF HYDRO-ENVIRONMENT RESEARCH 2013年第3期7卷 182-201页

作者： Nguyen, Khoi Zhang, Hong Stewart, Rodney Anthony Griffith Univ Griffith Sch Engn Gold Coast City Qld 4222 Australia Griffith Univ Ctr Infrastruct Engn & Management Gold Coast Campus Gold Coast City Qld 4222 Australia

The aim of this study was to disaggregate water flow data collected from high resolution smart water meters into different water end use categories. The data was obtained from a sample of 252 residential dwellings located within South East Queensland (SEQ), Australia. An integrated approach was used, combining high resolution water meters, remote data transfer loggers, household water appliance audits and a self-reported household water use diary. Disaggregating water flow traces into a registry of end use events (e.g. shower, clothes washer, etc.) is predominately a complex pattern matching problem, which requires a comparison between presented patterns and those contained with a large registry of categorised end use events. Water flow data collected directly from water meters includes both single (e.g. shower event occurring alone) and combined events (i.e. an event which comprises of several overlapped single events). To identify these former mentioned single events, a hybrid combination of the Hidden Markov Model (HMM) and the dynamic time warping algorithm (DTW) provided the most feasible and accurate approach available. Additional end use event physical context algorithms have been developed to aid accurate end use event categorisation. This paper firstly presents a thorough discussion on the single water end use event analysis process developed and its internal validation with a testing set. This is followed by the application of the developed approach on three independent households to examine its degree of accuracy in disaggregating two weeks of residential flow data into a repository of residential water end use events. Future stages of algorithm development and testing is discussed in the final section. (C) 2013 International Association for Hydro-environment Engineering and Research, Asia Pacific Division. Published by Elsevier B.V. All rights reserved.

关键词： Water end use event Water micro-component Residential water flow trace disaggregation Hidden Markov Model dynamic time warping algorithm Water demand management

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