Sökning: "Sensor Reconstruction"
Visar resultat 1 - 5 av 36 uppsatser innehållade orden Sensor Reconstruction.
1. Unsupervised Anomaly Detection in Multivariate Time Series Using Variational Autoencoders
Magister-uppsats, Lunds universitet/Matematik LTHSammanfattning : In this master’s thesis, a novel unsupervised anomaly detection tool was developed in collaboration with Sandvik Rock Processing to assist engineers and experts in analyzing large amounts of sensor data from cone crushers used in the stone crushing industry. The tool focuses on analyzing power, pressure, and CSS sensor data. LÄS MER
2. Compact Radar System
Kandidat-uppsats, Blekinge Tekniska Högskola/Institutionen för matematik och naturvetenskapSammanfattning : Context: Radar was developed in secret during world war II to detectobstacles or any incoming threat. The term radar was coined in 1940by United States Military as an acronym for "Radio Detection andRanging". Using radio waves a radar detects any incoming threat orobstacle [10]. The basic purpose of radar is for monitoring and security. LÄS MER
3. Virtual Sensing of Hauler Engine Sensors
Master-uppsats, Högskolan i Halmstad/Akademin för informationsteknologiSammanfattning : The automotive industry is becoming more dependent on sustainable and efficient systems within vehicles. With the diverse combination of conditions affecting vehicle performance, such as environmental conditions and drivers' behaviour, the interest in monitoring machine health increases. LÄS MER
4. Building dense reconstructions with SLAM and Spot
Uppsats för yrkesexamina på avancerad nivå, Lunds universitet/Institutionen för reglerteknikSammanfattning : Having access to dense reconstruction of ongoing building constructions provides insight into the building process and could serve as both a tool for error detection and documentation of the actual outcome. In this thesis, Spot, the quadruped robot designed by Boston Dynamics is evaluated as a platform for site inspection. LÄS MER
5. Jet Printing Quality ImprovementThrough Anomaly Detection UsingMachine Learning
Master-uppsats, KTH/Skolan för industriell teknik och management (ITM)Sammanfattning : This case study examined emitted sound and actuated piezoelectric current in a solderpaste jet printing machine to conclude whether quality degradation could be detected with an autoencoder machine learning model. An autoencoder was used to detect anomalies in non-realtime that were defined asa diameter drift with an averaging window from a target diameter. LÄS MER