Machine vision for the automatic classification of images acquired from Non-destructive tests

This project is based on Artificial Intelligence (A.I) and Digital Image processing (I.P) for automatic condition monitoring of sleepers in the railway track. Rail inspection is a very important task in railway maintenance for traffic safety issues and in preventing dangerous situations. Monitoring railway track infrastructure is an important aspect in which the periodical inspection of rail rolling plane is required.Up to the present days the inspection of the railroad is operated manually by trained personnel. A human operator walks along the railway track searching for sleeper anomalies. This monitoring way is not more acceptable for its slowness and subjectivity. Hence, it is desired to automate such intuitive human skills for the development of more robust and reliable testing methods. Images of wooden sleepers have been used as data for my project. The aim of this project is to present a vision based technique for inspecting railway sleepers (wooden planks under the railway track) by automatic interpretation of Non Destructive Test (NDT) data using A.I. techniques in determining the results of inspection.

Road Sign Recognition based onInvariant Features using SupportVector Machine

Since last two decades researches have been working on developing systems that can assistsdrivers in the best way possible and make driving safe. Computer vision has played a crucialpart in design of these systems. With the introduction of vision techniques variousautonomous and robust real-time traffic automation systems have been designed such asTraffic monitoring, Traffic related parameter estimation and intelligent vehicles. Among theseautomatic detection and recognition of road signs has became an interesting research topic.The system can assist drivers about signs they don’t recognize before passing them.Aim of this research project is to present an Intelligent Road Sign Recognition System basedon state-of-the-art technique, the Support Vector Machine. The project is an extension to thework done at ITS research Platform at Dalarna University [25]. Focus of this research work ison the recognition of road signs under analysis. When classifying an image its location, sizeand orientation in the image plane are its irrelevant features and one way to get rid of thisambiguity is to extract those features which are invariant under the above mentionedtransformation. These invariant features are then used in Support Vector Machine forclassification. Support Vector Machine is a supervised learning machine that solves problemin higher dimension with the help of Kernel functions and is best know for classificationproblems.

MACHINE VISION FOR AUTOMATICVISUAL INSPECTION OF WOODENRAILWAY SLEEPERS USING UNSUPERVISED NEURAL NETWORKS

The motivation for this thesis work is the need for improving reliability of equipment and quality of service to railway passengers as well as a requirement for cost-effective and efficient condition maintenance management for rail transportation. This thesis work develops a fusion of various machine vision analysis methods to achieve high performance in automation of wooden rail track inspection.The condition monitoring in rail transport is done manually by a human operator where people rely on inference systems and assumptions to develop conclusions. The use of conditional monitoring allows maintenance to be scheduled, or other actions to be taken to avoid the consequences of failure, before the failure occurs. Manual or automated condition monitoring of materials in fields of public transportation like railway, aerial navigation, traffic safety, etc, where safety is of prior importance needs non-destructive testing (NDT).In general, wooden railway sleeper inspection is done manually by a human operator, by moving along the rail sleeper and gathering information by visual and sound analysis for examining the presence of cracks. Human inspectors working on lines visually inspect wooden rails to judge the quality of rail sleeper. In this project work the machine vision system is developed based on the manual visual analysis system, which uses digital cameras and image processing software to perform similar manual inspections. As the manual inspection requires much effort and is expected to be error prone sometimes and also appears difficult to discriminate even for a human operator by the frequent changes in inspected material. The machine vision system developed classifies the condition of material by examining individual pixels of images, processing them and attempting to develop conclusions with the assistance of knowledge bases and features.A pattern recognition approach is developed based on the methodological knowledge from manual procedure. The pattern recognition approach for this thesis work was developed and achieved by a non destructive testing method to identify the flaws in manually done condition monitoring of sleepers.In this method, a test vehicle is designed to capture sleeper images similar to visual inspection by human operator and the raw data for pattern recognition approach is provided from the captured images of the wooden sleepers. The data from the NDT method were further processed and appropriate features were extracted.The collection of data by the NDT method is to achieve high accuracy in reliable classification results. A key idea is to use the non supervised classifier based on the features extracted from the method to discriminate the condition of wooden sleepers in to either good or bad. Self organising map is used as classifier for the wooden sleeper classification.In order to achieve greater integration, the data collected by the machine vision system was made to interface with one another by a strategy called fusion. Data fusion was looked in at two different levels namely sensor-level fusion, feature- level fusion. As the goal was to reduce the accuracy of the human error on the rail sleeper classification as good or bad the results obtained by the feature-level fusion compared to that of the results of actual classification were satisfactory.

Simultaneous prediction of symptom severity and cause in data from a test battery for Parkinson patients, using machine learning methods

The main purpose of this thesis project is to prediction of symptom severity and cause in data from test battery of the Parkinson’s disease patient, which is based on data mining. The collection of the data is from test battery on a hand in computer. We use the Chi-Square method and check which variables are important and which are not important. Then we apply different data mining techniques on our normalize data and check which technique or method gives good results.The implementation of this thesis is in WEKA. We normalize our data and then apply different methods on this data. The methods which we used are Naïve Bayes, CART and KNN. We draw the Bland Altman and Spearman’s Correlation for checking the final results and prediction of data. The Bland Altman tells how the percentage of our confident level in this data is correct and Spearman’s Correlation tells us our relationship is strong. On the basis of results and analysis we see all three methods give nearly same results. But if we see our CART (J48 Decision Tree) it gives good result of under predicted and over predicted values that’s lies between -2 to +2. The correlation between the Actual and Predicted values is 0,794in CART. Cause gives the better percentage classification result then disability because it can use two classes.

ANALYSIS & STUDY OF AI TECHNIQUES FORAUTOMATIC CONDITION MONITORING OFRAILWAY TRACK INFRASTRUCTURE : Artificial Intelligence Techniques

Since the last decade the problem of surface inspection has been receiving great attention from the scientific community, the quality control and the maintenance of products are key points in several industrial applications.The railway associations spent much money to check the railway infrastructure. The railway infrastructure is a particular field in which the periodical surface inspection can help the operator to prevent critical situations. The maintenance and monitoring of this infrastructure is an important aspect for railway association.That is why the surface inspection of railway also makes importance to the railroad authority to investigate track components, identify problems and finding out the way that how to solve these problems. In railway industry, usually the problems find in railway sleepers, overhead, fastener, rail head, switching and crossing and in ballast section as well. In this thesis work, I have reviewed some research papers based on AI techniques together with NDT techniques which are able to collect data from the test object without making any damage. The research works which I have reviewed and demonstrated that by adopting the AI based system, it is almost possible to solve all the problems and this system is very much reliable and efficient for diagnose problems of this transportation domain. I have reviewed solutions provided by different companies based on AI techniques, their products and reviewed some white papers provided by some of those companies. AI based techniques likemachine vision, stereo vision, laser based techniques and neural network are used in most cases to solve the problems which are performed by the railway engineers.The problems in railway handled by the AI based techniques performed by NDT approach which is a very broad, interdisciplinary field that plays a critical role in assuring that structural components and systems perform their function in a reliable and cost effective fashion. The NDT approach ensures the uniformity, quality and serviceability of materials without causing any damage of that materials is being tested. This testing methods use some way to test product like, Visual and Optical testing, Radiography, Magnetic particle testing, Ultrasonic testing, Penetrate testing, electro mechanic testing and acoustic emission testing etc. The inspection procedure has done periodically because of better maintenance. This inspection procedure done by the railway engineers manually with the aid of AI based techniques.The main idea of thesis work is to demonstrate how the problems can be reduced of thistransportation area based on the works done by different researchers and companies. And I have also provided some ideas and comments according to those works and trying to provide some proposal to use better inspection method where it is needed.The scope of this thesis work is automatic interpretation of data from NDT, with the goal of detecting flaws accurately and efficiently. AI techniques such as neural networks, machine vision, knowledge-based systems and fuzzy logic were applied to a wide spectrum of problems in this area. Another scope is to provide an insight into possible research methods concerning railway sleeper, fastener, ballast and overhead inspection by automatic interpretation of data.In this thesis work, I have discussed about problems which are arise in railway sleepers,fastener, and overhead and ballasted track. For this reason I have reviewed some research papers related with these areas and demonstrated how their systems works and the results of those systems. After all the demonstrations were taking place of the advantages of using AI techniques in contrast with those manual systems exist previously.This work aims to summarize the findings of a large number of research papers deploying artificial intelligence (AI) techniques for the automatic interpretation of data from nondestructive testing (NDT). Problems in rail transport domain are mainly discussed in this work. The overall work of this paper goes to the inspection of railway sleepers, fastener, ballast and overhead.

TCA Evaluation : Lab Measurements, Modelling and System Simulations

The study reported here is part of a large project for evaluation of the Thermo-Chemical Accumulator (TCA), a technology under development by the Swedish company ClimateWell AB. The studies concentrate on the use of the technology for comfort cooling. This report concentrates on measurements in the laboratory, modelling and system simulation. The TCA is a three-phase absorption heat pump that stores energy in the form of crystallised salt, in this case Lithium Chloride (LiCl) with water being the other substance. The process requires vacuum conditions as with standard absorption chillers using LiBr/water. Measurements were carried out in the laboratories at the Solar Energy Research Center SERC, at Högskolan Dalarna as well as at ClimateWell AB. The measurements at SERC were performed on a prototype version 7:1 and showed that this prototype had several problems resulting in poor and unreliable performance. The main results were that: there was significant corrosion leading to non-condensable gases that in turn caused very poor performance; unwanted crystallisation caused blockages as well as inconsistent behaviour; poor wetting of the heat exchangers resulted in relatively high temperature drops there. A measured thermal COP for cooling of 0.46 was found, which is significantly lower than the theoretical value. These findings resulted in a thorough redesign for the new prototype, called ClimateWell 10 (CW10), which was tested briefly by the authors at ClimateWell. The data collected here was not large, but enough to show that the machine worked consistently with no noticeable vacuum problems. It was also sufficient for identifying the main parameters in a simulation model developed for the TRNSYS simulation environment, but not enough to verify the model properly. This model was shown to be able to simulate the dynamic as well as static performance of the CW10, and was then used in a series of system simulations. A single system model was developed as the basis of the system simulations, consisting of a CW10 machine, 30 m2 flat plate solar collectors with backup boiler and an office with a design cooling load in Stockholm of 50 W/m2, resulting in a 7.5 kW design load for the 150 m2 floor area. Two base cases were defined based on this: one for Stockholm using a dry cooler with design cooling rate of 30 kW; one for Madrid with a cooling tower with design cooling rate of 34 kW. A number of parametric studies were performed based on these two base cases. These showed that the temperature lift is a limiting factor for cooling for higher ambient temperatures and for charging with fixed temperature source such as district heating. The simulated evacuated tube collector performs only marginally better than a good flat plate collector if considering the gross area, the margin being greater for larger solar fractions. For 30 m2 collector a solar faction of 49% and 67% were achieved for the Stockholm and Madrid base cases respectively. The average annual efficiency of the collector in Stockholm (12%) was much lower than that in Madrid (19%). The thermal COP was simulated to be approximately 0.70, but has not been possible to verify with measured data. The annual electrical COP was shown to be very dependent on the cooling load as a large proportion of electrical use is for components that are permanently on. For the cooling loads studied, the annual electrical COP ranged from 2.2 for a 2000 kWh cooling load to 18.0 for a 21000 kWh cooling load. There is however a potential to reduce the electricity consumption in the machine, which would improve these figures significantly. It was shown that a cooling tower is necessary for the Madrid climate, whereas a dry cooler is sufficient for Stockholm although a cooling tower does improve performance. The simulation study was very shallow and has shown a number of areas that are important to study in more depth. One such area is advanced control strategy, which is necessary to mitigate the weakness of the technology (low temperature lift for cooling) and to optimally use its strength (storage).

Solar thermal components adapted to common building standards (SCAS)

Pilot versions of a solar heating/natural gas burner system, of a solar heating/pellet burner system and of a façade/roof integrated polymeric collector have been installed in the summer of 2006 in a number of demonstration houses in Denmark, Sweden and Norway.These three new products have been evaluated by means of measurements of the thermal performance and energy savings of the pilot systems in practice and by means of a commercial evaluation.The conclusion of the evaluations is that the products are attractive for the industry partners METRO THERM A/S, Solentek and SOLARNOR. It is expected that the companies will bring the products into the market in 2007.Further, the results of the project have been presented atinternational and national congresses and seminars for the solar heating branch. The congresses and seminars attracted a lot of interested participants.Furthermore, the project results have been published in international congress papers as well as in national journals in the energy field.Consequently, the Nordic solar heating industry will benefit from the project.

A testing and demonstration facility for PV systems and components

A test and demonstration facility for PV and PV hybrid systems and system components has been designed and installed at Dalarna University in Sweden. The facility allows studies of complete PV systems or single components in a range of 0.1-10 kW. The facility includes two grid-connected PV systems, a PV Hybrid off-grid system, three emulators and the necessary measurement and control equipment. Tests can be done manually or automatically through programmed test procedures controlled that will be implemented in Labview. The facility shall be used by researchers, professionals of the industry and engineering students.

Fjärrvärmedrivna vitvaror : Erfarenheter från utveckling, installationer och kostnadsberäkningar

Värmedrivna vitvaror eller HWC-maskiner som de kallas av tillverkaren värms med varmt vatten från en cirkulerande krets via en värmeväxlare inbyggd i maskinen, till skillnad från konventionella maskiner som värms med el. Denna teknik skall inte förväxlas med maskiner som är anslutna till varmvattenledningen och fylls på med varmt vatten och som därmed begränsas till disk- och tvätt. Syftet med fjärrvärmedrivna vitvaror är alltså att använda fjärrvärme, som har lägre kvalitet och pris än elenergi för uppvärmning och torkning och på så sätt spara el och utöka fjärrvärmeunderlaget. En jämförelse av koldioxidutsläpp och primärenergianvändning mellan konventionella vitvaror och fjärrvärmedrivna vitvaror visar att både koldioxidutsläpp och primärenergianvändning blir lägre för fjärrvärmedrivna vitvaror om biobränsle anses koldioxidneutralt och den el som ersätts är producerad i kolkraftverk eller gaskombikraftverk.   Denna rapport beskriver utveckling och kommersialisering av värmedrivna vitvaror (disk- och tvättmaskiner samt torktumlare och torkskåp) och hur de kan anslutas mot fjärrvärmesystem i olika systemlösningar. Dessutom har de energimässiga och ekonomiska förutsättningarna för tekniken undersökts. Erfarenheterna från fältprovning är dock mycket begränsade, eftersom de byggen där fälttesterna skulle ske försenades. Under 2013 färdigställs ett flerbostadshus med värmedrivna vitvaror i 160 lägenheter i Västerås.   De utvecklade maskinernas värmeanvändning som andel av total energianvändning vid 60 graders framledningstemperatur har uppmätts till ca 50 % för diskmaskinen, 67 % för tvättmaskinen, 80 % för torktumlaren och 93 % för torkskåpet. I det studerade flerbostadshuset av passivhusstandard uppgår lasten från värmedrivna vitvaror komfortgolvvärme och handdukstorkar till upp mot 30 % av husets totala värmeanvändning. För småhus är motsvarande siffra upp mot 20 %. Att använda fjärrvärme istället för elvärme till dessa installationer som normalt är elvärmda kan allts minska elbehovet betydligt i lågenergibebyggelse vilket också minskar både koldioxidutsläppen och primärenergianvändningen.   Ekonomiska analyser har genomförts för två olika systemkoncept (separat vitvarukrets och Västeråsmodellen) för nybyggda småhusområden och flerfamiljshus där fjärrvärme inte bara används till vitvaror utan också till handdukstorkar och komfortgolvvärme. De ekonomiska analyserna visar att Västeråsmodellen är den mest ekonomiskt intressanta systemlösningen med värmedrivna vitvaror, handdukstork och komfortgolvvärme. I flerfamiljshus kan den vara konkurrenskraftig mot de elvärmda alternativen (konventionellt system med eldrivna vitvaror, komfortgolvvärme och handdukstorkar) om prisskillnaden mellan el och fjärrvärme är större än 0,7 kr/kWh. En parameterstudie visar att kapitalkostnaden blir ganska hög jämfört med energikostnaden, vilket betyder att lång livslängd och många cykler är viktigt för att förbättra de ekonomiska förutsättningarna för värmedrivna vitvaror. För passiva småhus blir kostnaden för Västeråsmodellen med värmedrivna vitvaror, handdukstork och komfortgolvvärme likvärdig med de elvärmda alternativen vid energiprisskillnader på 0,7 kr/kWh inklusive moms, medan det krävs prisskillnader på 0,9 kr/kWh inklusive moms för normalisolerade småhusområden.   Sammanfattningsvis kan sägas att i kommuner med ett konkurrenskraftigt fjärrvärmepris finns det viss lönsamhet för hela konceptet enligt Västeråsmodellen med värmedrivna vitvaror, komfortgolvvärme, och handdukstorkar. Om man däremot ser på konkurrensen för enskilda vitvaror är det främst torktumlaren som är konkurrenskraftig i bostäder. Målpriset på 1000 kr extra för värmedrift har inte kunnat uppnås inom projektet för diskmaskiner och tvättmaskiner. Det krävs lägre priser och låga anslutningskostnader för att räkna hem diskmaskinen och tvättmaskinen som enskilda komponenter.   Värmedrivna tvättmaskiner och torktumlare är konkurrenskraftiga i flerfamiljstvättstugor. Speciellt i de fall där beläggningen är god och flera maskiner delar på anslutningskostnaden till fjärrvärmecentralen kan värmedrift bli riktigt lönsam. Torkskåpens konkurrenskraft har inte kunnat utvärderas, då priset ännu inte fastställts. Att använda VVC-systemet för värmedistribution till värmedrivna vitvaror kan vara mycket intressant, men det kräver att legionellaproblematiken kan lösas. I nuläget finns ingen lösning som uppfyller formuleringarna i boverkets byggregler. Ett annat distributionssätt som kan vara intressant, men som inte undersökts i studien är att använda VVC för varmvattendistribution och en gemensam radiator- och vitvarukrets med konstant framledningstemperatur. Den aktör som förväntas ha störst ekonomiskt intresse av att tekniken implementeras är sannolikt fjärrvärmebolagen som får sälja mer värme och det ligger därmed främst på deras ansvar att marknadsföra tekniken i mötet med sina kunder.

Using locally available components and local knowledge to build sustainable stand-alone power systems

The aim of this paper is to point out benefits as well as disadvantages associated with the use of locally available, not necessarily standardized, components in stand-alone electrical power systems at rural locations. Advantages and challenges arising when the direct involvement in design, construction and maintenance of the power system is reserved to people based in the area of implementation are discussed. The presented research is centered around one particular PV-diesel hybrid system in Tanzania; a case study in which technical and social aspects related to the particular power system are studied.

Computerized identification of motor complications in Parkinson's disease

Objective: To investigate whether spirography-based objective measures are able to effectively characterize the severity of unwanted symptom states (Off and dyskinesia) and discriminate them from motor state of healthy elderly subjects. Background: Sixty-five patients with advanced Parkinson’s disease (PD) and 10 healthy elderly (HE) subjects performed repeated assessments of spirography, using a touch screen telemetry device in their home environments. On inclusion, the patients were either treated with levodopa-carbidopa intestinal gel or were candidates for switching to this treatment. On each test occasion, the subjects were asked trace a pre-drawn Archimedes spiral shown on the screen, using an ergonomic pen stylus. The test was repeated three times and was performed using dominant hand. A clinician used a web interface which animated the spiral drawings, allowing him to observe different kinematic features, like accelerations and spatial changes, during the drawing process and to rate different motor impairments. Initially, the motor impairments of drawing speed, irregularity and hesitation were rated on a 0 (normal) to 4 (extremely severe) scales followed by marking the momentary motor state of the patient into 2 categories that is Off and Dyskinesia. A sample of spirals drawn by HE subjects was randomly selected and used in subsequent analysis. Methods: The raw spiral data, consisting of stylus position and timestamp, were processed using time series analysis techniques like discrete wavelet transform, approximate entropy and dynamic time warping in order to extract 13 quantitative measures for representing meaningful motor impairment information. A principal component analysis (PCA) was used to reduce the dimensions of the quantitative measures into 4 principal components (PC). In order to classify the motor states into 3 categories that is Off, HE and dyskinesia, a logistic regression model was used as a classifier to map the 4 PCs to the corresponding clinically assigned motor state categories. A stratified 10-fold cross-validation (also known as rotation estimation) was applied to assess the generalization ability of the logistic regression classifier to future independent data sets. To investigate mean differences of the 4 PCs across the three categories, a one-way ANOVA test followed by Tukey multiple comparisons was used. Results: The agreements between computed and clinician ratings were very good with a weighted area under the receiver operating characteristic curve (AUC) coefficient of 0.91. The mean PC scores were different across the three motor state categories, only at different levels. The first 2 PCs were good at discriminating between the motor states whereas the PC3 was good at discriminating between HE subjects and PD patients. The mean scores of PC4 showed a trend across the three states but without significant differences. The Spearman’s rank correlations between the first 2 PCs and clinically assessed motor impairments were as follows: drawing speed (PC1, 0.34; PC2, 0.83), irregularity (PC1, 0.17; PC2, 0.17), and hesitation (PC1, 0.27; PC2, 0.77). Conclusions: These findings suggest that spirography-based objective measures are valid measures of spatial- and time-dependent deficits and can be used to distinguish drug-related motor dysfunctions between Off and dyskinesia in PD. These measures can be potentially useful during clinical evaluation of individualized drug-related complications such as over- and under-medications thus maximizing the amount of time the patients spend in the On state.

Emergency department triage scales and their components : a systematic review of the scientific evidence

Emergency department (ED) triage is used to identify patients' level of urgency and treat them based on their triage level. The global advancement of triage scales in the past two decades has generated considerable research on the validity and reliability of these scales. This systematic review aims to investigate the scientific evidence for published ED triage scales. The following questions are addressed: 1. Does assessment of individual vital signs or chief complaints affect mortality during the hospital stay or within 30 days after arrival at the ED? 2. What is the level of agreement between clinicians' triage decisions compared to each other or to a gold standard for each scale (reliability)? 3. How valid is each triage scale in predicting hospitalization and hospital mortality? A systematic search of the international literature published from 1966 through March 31, 2009 explored the British Nursing Index, Business Source Premier, CINAHL, Cochrane Library, EMBASE, and PubMed. Inclusion was limited to controlled studies of adult patients (≥15 years) visiting EDs for somatic reasons. Outcome variables were death in ED or hospital and need for hospitalization (validity). Methodological quality and clinical relevance of each study were rated as high, medium, or low. The results from the studies that met the inclusion criteria and quality standards were synthesized applying the internationally developed GRADE system. Each conclusion was then assessed as having strong, moderately strong, limited, or insufficient scientific evidence. If studies were not available, this was also noted. We found ED triage scales to be supported, at best, by limited and often insufficient evidence. The ability of the individual vital signs included in the different scales to predict outcome is seldom, if at all, studied in the ED setting. The scientific evidence to assess interrater agreement (reliability) was limited for one triage scale and insufficient or lacking for all other scales. Two of the scales yielded limited scientific evidence, and one scale yielded insufficient evidence, on which to assess the risk of early death or hospitalization in patients assigned to the two lowest triage levels on a 5-level scale (validity).