A novel Adaptive Filtering approach to Drive File Identification for Service Environment Replication
| dc.contributor.author | Balasubramanya, Bharath | en |
| dc.contributor.committeechair | Southward, Steve C. | en |
| dc.contributor.committeemember | Kurdila, Andrew J. | en |
| dc.contributor.committeemember | Woolsey, Craig A. | en |
| dc.contributor.committeemember | Leonessa, Alexander | en |
| dc.contributor.department | Mechanical Engineering | en |
| dc.date.accessioned | 2024-11-28T09:00:13Z | en |
| dc.date.available | 2024-11-28T09:00:13Z | en |
| dc.date.issued | 2024-11-27 | en |
| dc.description.abstract | Service Environment Replication refers to the process of using test machines to apply controlled dynamic loads to test articles in order to replicate operating conditions that the article was designed for. Such test machines hence require the development of dynamic time series commands that drive the actuators in order to replicate the responses of the actual dynamic system measured separately in its service environment. A novel adaptive filtering approach, called the Pulse Train Filtered-x Least Mean Square algorithm for waveform generation and drive file identification is proposed in this thesis based on methods developed for Active Noise and Vibration Control. Simulation studies are considered using various test benches with varying degrees of nonlinearity to validate the performance of the proposed algorithm to rapidly converge to a dynamic solution in a small number of iterations. The PT-Fx-LMS algorithm is also shown to enable targeted iteration over isolated time slices within the data set, which challenge conventional iterative DFID techniques. Further modifications to the algorithm are proposed that uses a completely offline workflow using the estimated dynamics of the plant and an empirical termination criteria to improve performance and ensure stability of the adaptive process. The architecture developed is applicable for a wide array of dynamic systems with single or multiple actuators and sensors. Experimental validation of the proposed algorithm is conducted using an acoustic setup to replicate target sound fields for a wide array of configurations. | en |
| dc.description.abstractgeneral | Testing an article in the environment where it is designed to be operated can be a time consuming and expensive process without laboratory-based, repeatable testing environments. The goal of these test rigs is hence to replicate the service environment in order to design, develop and validate the article-under-test. Different methods have been developed over the years by manufacturers to replicate such environments within the confines of a laboratory where the most important task is to generate the required control signals to drive the actuators on the test rig to induce the required responses from the dynamic system under test. The objective of the thesis is to develop a novel time-domain based algorithm that can be used to iteratively derive the control signals required to replicate the responses of the dynamic system on a simulated test bench in as few iterations as possible, thereby saving computation time, experiment time and cost. The proposed algorithm is compared against conventional methods for deriving these control signals and further improvements to the proposed method are suggested in order to improve performance, stability, safety and ease of workflow on the test rig. | en |
| dc.description.degree | Doctor of Philosophy | en |
| dc.format.medium | ETD | en |
| dc.identifier.other | vt_gsexam:41788 | en |
| dc.identifier.uri | https://hdl.handle.net/10919/123665 | en |
| dc.language.iso | en | en |
| dc.publisher | Virginia Tech | en |
| dc.rights | In Copyright | en |
| dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | en |
| dc.subject | Service Environment Replication | en |
| dc.subject | Drive File Identification | en |
| dc.subject | Adaptive Filtering | en |
| dc.title | A novel Adaptive Filtering approach to Drive File Identification for Service Environment Replication | en |
| dc.type | Dissertation | en |
| thesis.degree.discipline | Mechanical Engineering | en |
| thesis.degree.grantor | Virginia Polytechnic Institute and State University | en |
| thesis.degree.level | doctoral | en |
| thesis.degree.name | Doctor of Philosophy | en |
Files
Original bundle
1 - 3 of 3
- Name:
- Balasubramanya_B_D_2024_support_1.pdf
- Size:
- 1.26 MB
- Format:
- Adobe Portable Document Format
- Description:
- Supporting documents
- Name:
- Balasubramanya_B_D_2024_support_3.pdf
- Size:
- 917.63 KB
- Format:
- Adobe Portable Document Format
- Description:
- Supporting documents