| 1. |
- Lundgren, Jan, 1977-
(author)
-
Behavioral Level Simulation Methods for Early Noise Coupling Quantification in Mixed-Signal Systems
- 2005
-
Licentiate thesis (other academic/artistic)abstract
- In this thesis, noise coupling simulation is introduced into the behavioral level. Methods and models for simulating on-chip noise coupling at a behavioral level in a design flow are presented and verified for accuracy and validity. Today, designs of electronic systems are becoming denser and more and more mixed-signal systems such as System-on-Chip (SoC) are being devised. This raises problems when the electronics components start to interfere with each other. Often, digital components disturb analog components, introducing noise into the system causing degradation of the performance or even introducing errors into the functionality of the system. Today, these effects can only be simulated at a very late stage in the design process, causing large design iterations and increased costs if the designers are required to return and make alterations, which may have occurred at a very early stage in the process. This is why the focus of this work is centered on extracting noise coupling simulation models that can be used at a very early design stage such as the behavioral level and then follow the design through the various design stages. To realize this, SystemC is selected as a platform and implementation example for the behavioral level models. SystemC supports design refinement, which means that when designs are being refined and are crossing the design levels, the noise coupling models can also be refined to suit the current design. This new way of thinking in primarily mixed-signal designs is called Behavioral level Noise Coupling (BeNoC) simulation and shows great promise in enabling a reduction in the costs of design iterations due to component cross-talk and simplifies the work for mixed-signal system designers.
|
|
| 2. |
- Lundgren, Jan, 1977-
(author)
-
Simulating Behavioral Level On-Chip Noise Coupling
- 2007
-
Doctoral thesis (other academic/artistic)abstract
- In this thesis, noise coupling simulation is introduced into the behavioral level. Methods andmodels for simulating on-chip noise coupling at the behavioral level in a design flow are presentedand verified for accuracy and validity. Today, designs of electronic systems are becoming denserand more and more mixed-signal systems such as System-on-Chip (SoC) are being devised. Thisraises problems when the electronics components start to interfere with each other. Often, digitalcomponents disturb analog components, introducing noise into the system causing degradation ofthe performance or even introducing errors into the functionality of the system.Today, these effects can only be simulated at a very late stage in the design process, causinglarge design iterations and increased costs if the designers are required to return and makealterations, which may have occurred at a very early stage in the process.This is why the focus of this work is centered on extracting noise coupling simulation modelsthat can be used at a very early design stage, such as at the behavioral level and then follow thedesign through the various design stages. To achieve this, SystemC is selected as a platform andimplementation example for the behavioral level models. SystemC supports design refinement,which means that when designs are being refined and are crossing the design levels, the noisecoupling models can also be refined to suit the current design.This new method of thinking in primarily mixed-signal designs is called Behavioral levelNoise Coupling (BeNoC) simulation and shows great promise in enabling a reduction in the costsof design iterations due to component cross-talk and simplifies the work for mixed-signal systemdesigners.
|
|
| 3. |
- Shaikh, Muhammad Saad
(author)
-
Hyperspectral imaging for in-situ applications : Methods to improve the classification of materials using hyperspectral imaging
- 2024
-
Doctoral thesis (other academic/artistic)abstract
- This thesis addresses several research questions related to in-situ hyperspectral imaging systems, proposes measurement methods for more accurate imaging, and examines the impact of the methods on material classification.First, the thesis investigates the possibility of successfully calibrating a hyperspectral imaging system using a low-cost PTFE reference. A hyperspectral imaging system and practical calibration procedure using an inexpensive calibration reference are introduced. This reference enables accurate measurement of a material’s reflectance spectra independent of lighting and the camera’s spectral distribution of intensity and sensitivity. The study presents experiments conducted on winter roads covered with water, snow, and ice. The results show the robustness of the calibration and the suitability of the system for classifying materials.The thesis further focuses on increasing the dynamic range (DR) of line scanning hyperspectral cameras. A method that relies on the use of multiple exposures is proposed to increase DR, benefiting applications such as plastic detection and polymer sorting. Experiments show that the proposed method can increase the DR for hyperspectral SWIR imaging from 43 dB to 73 dB. Material classification experiments reveal significant accuracy improvements with multiple exposures for large dynamic ranges.The thesis also examines the effect of variations in relative humidity. It shows that even minor changes in humidity can significantly affect measurements. Frequent calibration and pruning of active wavelength bands are proposed as solutions to reduce the classification error rate for polymers from 20% to less than 1%.The thesis also investigates the classification of colored materials by combining visible and infrared imaging. The classification algorithm shows high overall accuracy, close to 99.9% for one test case, which also shows the potential of this approach.Finally, the use of infrared hyperspectral imaging combined with Convolutional Neural Networks (CNN) for the classification of black polymers is evaluated. CNN outperforms all traditional classification algorithms, further demonstrating the potential of the proposed method. Further research on larger and more diversified material samples is recommended.
|
|
| 4. |
- Ahmad, Naeem
(author)
-
Modelling and optimization of sky surveillance visual sensor network
- 2012
-
Licentiate thesis (other academic/artistic)abstract
- A Visual Sensor Network (VSN) is a distributed system of a largenumber of camera sensor nodes. The main components of a camera sensornode are image sensor, embedded processor, wireless transceiver and energysupply. The major difference between a VSN and an ordinary sensor networkis that a VSN generates two dimensional data in the form of an image, whichcan be exploited in many useful applications. Some of the potentialapplication examples of VSNs include environment monitoring, surveillance,structural monitoring, traffic monitoring, and industrial automation.However, the VSNs also raise new challenges. They generate large amount ofdata which require higher processing powers, large bandwidth requirementsand more energy resources but the main constraint is that the VSN nodes arelimited in these resources.This research focuses on the development of a VSN model to track thelarge birds such as Golden Eagle in the sky. The model explores a number ofcamera sensors along with optics such as lens of suitable focal length whichensures a minimum required resolution of a bird, flying at the highestaltitude. The combination of a camera sensor and a lens formulate amonitoring node. The camera node model is used to optimize the placementof the nodes for full coverage of a given area above a required lower altitude.The model also presents the solution to minimize the cost (number of sensornodes) to fully cover a given area between the two required extremes, higherand lower altitudes, in terms of camera sensor, lens focal length, camera nodeplacement and actual number of nodes for sky surveillance.The area covered by a VSN can be increased by increasing the highermonitoring altitude and/or decreasing the lower monitoring altitude.However, it also increases the cost of the VSN. The desirable objective is toincrease the covered area but decrease the cost. This objective is achieved byusing optimization techniques to design a heterogeneous VSN. The core ideais to divide a given monitoring range of altitudes into a number of sub-rangesof altitudes. The sub-ranges of monitoring altitudes are covered by individualsub VSNs, the VSN1 covers the lower sub-range of altitudes, the VSN2 coversthe next higher sub-range of altitudes and so on, such that a minimum cost isused to monitor a given area.To verify the concepts, developed to design the VSN model, and theoptimization techniques to decrease the VSN cost, the measurements areperformed with actual cameras and optics. The laptop machines are used withthe camera nodes as data storage and analysis platforms. The area coverage ismeasured at the desired lower altitude limits of homogeneous as well asheterogeneous VSNs and verified for 100% coverage. Similarly, the minimumresolution is measured at the desired higher altitude limits of homogeneous aswell as heterogeneous VSNs to ensure that the models are able to track thebird at these highest altitudes.
|
|
| 5. |
|
|
| 6. |
|
|
| 7. |
|
|
| 8. |
- Cheng, Peng
(author)
-
Applications of embedded sensors in loader crane positioning and rotor RPM measurement
- 2011
-
Doctoral thesis (other academic/artistic)abstract
- In this thesis, two novel applications involving embedded sensors arestudied, one dealing with loader crane positioning and the other involving rotorRevolutions Per Minute (RPM) measurement. The thesis presents a generalintroduction to the embedded sensor, its architecture and its use in mechanicalindustry, and provides the reader with an overview of conventional sensortechnologies within the fields of angle sensors and angular speed sensors, coveringtheir working principles, features, advantages and disadvantages and typicalapplications. The particular problems associated with the use of conventionalsensors in both loader crane positioning and rotor RPM measurement aredescribed and these problems provided the motivation for the designs of theembedded sensor systems developed in this thesis.In the case of the loader crane positioning, the origins of the project and thespecial requirements of the application are described in detail. In addition, apreliminary study is conducted in relation to the idea of a contactless joint angularsensor using MEMS inertial sensors in which four different methods, namely, theCommon-Mode-Rejection with Gyro Integration (CMRGI), Common-Mode-Rejection (CMR), Common-Mode-Rejection with Gyro Differentiation (CMRGD)and Distributed Common-Mode-Rejection (DCMR), are conceived, modeled andtested on a custom-designed prototype experimental setup. The results gatheredfrom these four methods are compared and analyzed in order to identify thedifferences in their performances. The methods, which proved to be suitable, arethen further tested using the prototype sensor setup on a loader crane and theperformance results are analyzed in order to make a decision in relation to the twomost suitable methods for the application of the loader crane positioning. Theresults suggested that the two most suitable were the CMRGD and the DCMR. Thepractical design issues relating to this sensor system are highlighted andsuggestions are made in the study. Additionally, possible future work for thisproject is also covered.In the first case for the rotor RPM measurement, the thesis presents themodeling and simulation of the stator-free RPM sensor idea using the Monte Carlomethod, which demonstrated the special features and performance of this sensor.The design aspects of the prototype sensor are described in detail and theprototype is tested on an experimental setup. The conclusions for the stator-freeRPM sensor are then made from the analysis of the experimental results and futurework in relation to this sensor is also proposed.In the second case of the rotor RPM measurement, the thesis presentsanother idea involving the laser mouse RPM sensor and the main focus of thestudy is on the performance characterization of the laser mouse sensor and theverification of the RPM sensor idea. Experiments are conducted using the test setup and results are gathered and analyzed and conclusions are drawn.Possibilities in relation to future work for this laser mouse RPM sensor are alsoprovided.The summary and the conclusion form the final chapter of the thesis andseveral important aspects of the designs relating to both the loader cranepositioning project and the rotor RPM measurement project are discussed.
|
|
| 9. |
- Imran, Muhammad
(author)
-
Investigation of Architectures for Wireless Visual Sensor Nodes
- 2011
-
Licentiate thesis (other academic/artistic)abstract
- Wireless visual sensor network is an emerging field which has proveduseful in many applications, including industrial control and monitoring,surveillance, environmental monitoring, personal care and the virtual world.Traditional imaging systems used a wired link, centralized network, highprocessing capabilities, unlimited storage and power source. In manyapplications, the wired solution results in high installation and maintenancecosts. However, a wireless solution is the preferred choice as it offers lessmaintenance, infrastructure costs and greater scalability.The technological developments in image sensors, wirelesscommunication and processing platforms have paved the way for smartcamera networks usually referred to as Wireless Visual Sensor Networks(WVSNs). WVSNs consist of a number of Visual Sensor Nodes (VSNs)deployed over a large geographical area. The smart cameras can performcomplex vision tasks using limited resources such as batteries or alternativeenergy sources, embedded platforms, a wireless link and a small memory.Current research in WVSNs is focused on reducing the energyconsumption of the node so as to maximise the life of the VSN. To meet thischallenge, different software and hardware solutions are presented in theliterature for the implementation of VSNs.The focus in this thesis is on the exploration of energy efficientreconfigurable architectures for VSNs by partitioning vision tasks on software,hardware platforms and locality. For any application, some of the vision taskscan be performed on the sensor node after which data is sent over the wirelesslink to the server where the remaining vision tasks are performed. Similarly,at the VSN, vision tasks can be partitioned on software and the hardwareplatforms.In the thesis, all possible strategies are explored, by partitioning visiontasks on the sensor node and on the server. The energy consumption of thesensor node is evaluated for different strategies on software platform. It isobserved that performing some of the vision tasks on the sensor node andsending compressed images to the server where the remaining vision tasks areperformed, will have lower energy consumption.In order to achieve better performance and low power consumption,Field Programmable Gate Arrays (FPGAs) are introduced for theimplementation of the sensor node. The strategies with reasonable designtimes and costs are implemented on hardware-software platform. Based onthe implementation of the VSN on the FPGA together with micro-controller,the lifetime of the VSN is predicted using the measured energy values of theplatforms for different processing strategies. The implementation resultsprove our analysis that a VSN with such characteristics will result in a longerlife time.
|
|
| 10. |
|
|
