There is a significant need to identify approaches for classifying chemical sensor array data with high success rates that would enhance sensor detection capabilities. The present study attempts to fill this need by investigating six machine learning methods to classify a dataset collected using a chemical sensor array: K-Nearest Neighbor (KNN), Support Vector Machine (SVM), Classification and Regression Trees (CART), Random Forest (RF), Naïve Bayes Classifier (NB), and Principal Component Regression (PCR). A total of 10 predictors that are associated with the response from 10 sensor channels are used to train and test the classifiers. A training dataset of 4 classes containing 136 samples is used to build the classifiers, and a dataset of 4 classes with 56 samples is used for testing. The results generated with the six different methods are compared and discussed. The RF, CART, and KNN are found to have success rates greater than 90%, and to outperform the other methods.

The use of Bluetooth technology for gathering traffic data is becoming increasingly popular due to the large volume of data that can be gathered at a relatively low cost. The limited number of devices in discoverable mode and potential long discovery time of the Bluetooth devices creates an opportunity for evaluating the sensor array setup that can maximize the sample of devices identified. This thesis investigates several factors that have a significant impact on the quality of the data obtained using Bluetooth, including the number of Bluetooth readers, orientation of the Bluetooth antennas, position of the readers relative to one another, and the location of the Bluetooth stations. The thesis begins with an overview of Bluetooth technology and literature review on the use of Bluetooth in previous traffic studies. Next, the methodology for the setup of the Bluetooth system and the four tests performed to evaluate the factors affecting the quality of the data are described. Through the results of these tests, it was observed that a "flat" antenna orientation allows for the greatest detection range and that the walls of buildings can prevent detection of Bluetooth devices inside the buildings. In addition, using multiple Bluetooth readers per sensor array resulted in statistically significant increases in number of detections of single reader sensors, and horizontally separated sensor arrays were observed to be more effective than vertically separated sensor arrays. Finally, the thesis concludes with a summary of findings and a discussion of further research needs.

In der vorliegenden Arbeit wird die Entwicklung eines auf mikromechanischen Sensorstrukturen basierenden Schwingungsmesssystems dargestellt. Die Besonderheit besteht im frequenzselektiven Wirkprinzip. Der Sensor siebt an seiner Resonanzstelle aus einem breitbandigen Anregungssignal ein schmales Band heraus und unterdrückt die anderen Frequenzbereiche. Auf diese Weise werden ohne Fourier-Transformation direkt spektrale Informationen gewonnen. Weiterhin sind die Resonanzfrequenz und damit der Messbereich mittels elektrostatischer Kräfte in einem weiten Bereich abstimmbar.

Vehicle navigation systems incorporate on-board sensors/signal receivers and provide necessary positioning and guidance information for land, marine, airborne and space vehicles. Among different navigation solutions, the Global Positioning System (GPS) and an Inertial Navigation System (INS) are two basic navigation systems. Due to their complementary characters in many aspects, a GPS/INS integrated navigation system has been a hot research topic in recent decades. Both advantages and disadvantages of each individual system and their combination are analysed in this thesis. The Micro Electrical Mechanical Sensors (MEMS) successfully solved the problems of price, size and weight with traditional INS, and hence are widely applied in GPS/INS integrated systems. The main problem of MEMS is the large sensor errors, which rapidly degrade the navigation performance in an exponential speed. By means of different methods, such as autoregressive model, Gauss-Markov process, Power Spectral Density and Allan Variance, we analyse the stochastic errors within the MEMS sensors. The test results show that different methods give similar estimates of stochastic error sources. An equivalent model of coloured noise components (random walk, bias instability and ramp noise) is given. Three levels of GPS/IMU integration structures, i.e. loose, tight and ultra-tight GPS/IMU navigation, are introduced with a brief analysis of each character. The loose integration principles are presented with detailed equations as well as the INS navigation principles. The Extended Kalman Filter (EKF) is introduced as the data fusion algorithm, which is the core of the whole navigation system. Based on the system model, we show the propagation of position standard errors with the tight integration structure under different scenarios. Even less than 4 observable GNSS satellites can contribute to the integrated system, especially for the orientation errors. A real test with loose integration is carried out, and the EKF performance is analysed in detail. Since the GPS receivers are normally working with a digital map, the map matching principle and its link-choosing problem are briefly introduced. This problem is proposed to be solved by the lane detection from real-time images. The procedures for the lane detection based on image processing are presented. The test on high ways, city streets and pathways are successfully carried out, and analyses with possible solutions are given for some special failure situations. To solve the large error drift of the IMU, we propose to support the IMU orientation with camera motion estimation from image pairs. First the estimation theory and computer vision principles are briefly introduced. Then both point and line matches algorithms are given. Finally the L1-norm estimator with balanced adjustment is proposed to deal with possible mismatches (outliers). Tests and comparisons with the RANSAC algorithm are also presented. For the latest trend of MEMS chip sensors, their industry and market are introduced. To evaluate the MEMS navigation performance, we augment the EKF with an equivalent coloured noise model, and the basic observability analysis is given. A realistic simulated navigation test is carried out with single and multiple MEMS sensors, and a sensor array of 5-10 sensors are recommended according to the test results and analysis. Finally some suggestions for future research are proposed. / <p>QC 20131016</p>

An electrochemical sensor array can provide information about the spatial and temporal distribution of chemicals in liquid turbulent plumes. Planar laser induced fluorescence (PLIF) and amperometric sensor arrays were used to record signals from modulated chemical plumes released into a recirculating aquatic flume. Coherence analysis was applied to extract the frequency components contained in the sensor response. Effects due to release distance, modulation frequency, and array orientation were investigated. This study has demonstrated that frequency encoded information can be extracted from a turbulent chemical plume using an array of amperometric sensors with optimized three-dimensional geometry and tuning.

Techn. University, Diss., 2007--Darmstadt.

Techn. University, Diss., 2006--Darmstadt.

Zugl.: Ilmenau, Techn. Univ., Diss., 2008

Techn. Hochsch., Diss., 2003--Aachen.

Universiẗat, Diss., 2004--Tübingen.