{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/105222"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/105222","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"On-the-go soil physical properties characterization using acoustic emission detection","abstract":"Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2021-05-01","abstract_html":"Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2021-05-01","abstract_has_math":false,"creators":["Kuhns, Brendan Matthew"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Technical Systems Management","degree_department":null,"school":null,"contributors":["Grift, Tony E."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2019,"date_issued":"2019-08-23T20:48:17Z","date_published":"2019-08-23T20:48:17Z","updated_at":"2026-07-22T22:24:44Z","subjects":["soil physical sensing","acoustic emission","soil texture","soil compaction","on-the-go sensor","frequency spectra"],"languages":["en"],"rights":["© 2019 Brendan Matthew Kuhns"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/105222","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Grift, Tony E."]},{"key":"dc:creator","label":"Author","values":["Kuhns, Brendan Matthew"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2019-08-23T20:48:17Z","2021-08-24T09:15:38Z","2019-04-22","2019-05"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Technical Systems Management"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["soil physical sensing","acoustic emission","soil texture","soil compaction","on-the-go sensor","frequency spectra"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["© 2019 Brendan Matthew Kuhns"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/105222"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2021-05-01","The student, Brendan Kuhns, accepted the attached license on 2019-04-18 at 09:31.","Soil physical properties are a foundational classification of measurements with direct relation to the productivity of agricultural soils. Currently, measurements of these properties are either crudely taken in field or low volumes are meticulously characterized in laboratory settings at high costs. This work outlines the development of a novel system for on-the-go characterization of soil physical properties. The system utilizes a piezoelectric acoustic emission sensor with a voltage output, embedded in a wedge which measures the interaction at the soil-wedge interface. Experiments took place in the field and in indoor and outdoor soil bins. Effects of the speed of the implement, compaction, and texture were analyzed using voltage vs. time series and frequency spectra. A linear relationship was found between the speed of the implement and the sensor output with a coefficient of determination R2 of 0.79. Measurements taken in a high compaction soil were compared to those taken in a soil with low compaction. A difference in the population median signal energy was found at an 𝛼 of 0.01. Four soil textures were sampled and their frequency spectra analyzed to determine a correlation between the soil texture and its corresponding frequency spectrum. Analytical techniques included the Welch’s power spectral density estimate, wavelet analysis, and moving average Fourier transforms. Principal component analysis using the z-score normalization of the Welch distribution allowed for separation of the frequency spectra given the texture. High levels of self-similarity between replications were seen in sands and moderate levels in loam. An analysis of variance using the Welch correction was performed and subsequent post-hoc evaluation using the Games-Howell method was completed. The results show that at an α of 0.05 all textures are separable with respect to each other texture. Future work should investigate effects of other soil properties on the acoustic signature and include development of machine learning approaches to classify soils based on these data.","The student, Brendan Kuhns, submitted this Thesis for approval on 2019-04-18 at 09:51.","This Thesis was approved for publication on 2019-04-22 at 10:40.","DSpace SAF Submission Ingestion Package generated from Vireo submission #13739 on 2019-08-22 at 16:23:09","Made available in DSpace on 2019-08-23T20:48:17Z (GMT). No. of bitstreams: 2 KUHNS-THESIS-2019.pdf: 6230944 bytes, checksum: e5534e06d0953e686d0336faf286ea8e (MD5) LICENSE.txt: 4210 bytes, checksum: 51da350e020f9828dfc5023e13a61332 (MD5) Previous issue date: 2019-04-22","Embargo set by: Seth Robbins for item 112344 Lift date: 2021-08-23T20:48:32Z Reason: Author requested closed access (OA after 2yrs) in Vireo ETD system","Limited Restriction Lifted for Item 112344 on 2021-08-24T09:15:38Z."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["On-the-go soil physical properties characterization using acoustic emission detection"]}]}],"canonical_facts":{"dc:contributor":["Grift, Tony E."],"dc:creator":["Kuhns, Brendan Matthew"],"dc:date":["2019-08-23T20:48:17Z","2021-08-24T09:15:38Z","2019-04-22","2019-05"],"dc:description":["Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2021-05-01","The student, Brendan Kuhns, accepted the attached license on 2019-04-18 at 09:31.","Soil physical properties are a foundational classification of measurements with direct relation to the productivity of agricultural soils. Currently, measurements of these properties are either crudely taken in field or low volumes are meticulously characterized in laboratory settings at high costs. This work outlines the development of a novel system for on-the-go characterization of soil physical properties. The system utilizes a piezoelectric acoustic emission sensor with a voltage output, embedded in a wedge which measures the interaction at the soil-wedge interface. Experiments took place in the field and in indoor and outdoor soil bins. Effects of the speed of the implement, compaction, and texture were analyzed using voltage vs. time series and frequency spectra. A linear relationship was found between the speed of the implement and the sensor output with a coefficient of determination R2 of 0.79. Measurements taken in a high compaction soil were compared to those taken in a soil with low compaction. A difference in the population median signal energy was found at an 𝛼 of 0.01. Four soil textures were sampled and their frequency spectra analyzed to determine a correlation between the soil texture and its corresponding frequency spectrum. Analytical techniques included the Welch’s power spectral density estimate, wavelet analysis, and moving average Fourier transforms. Principal component analysis using the z-score normalization of the Welch distribution allowed for separation of the frequency spectra given the texture. High levels of self-similarity between replications were seen in sands and moderate levels in loam. An analysis of variance using the Welch correction was performed and subsequent post-hoc evaluation using the Games-Howell method was completed. The results show that at an α of 0.05 all textures are separable with respect to each other texture. Future work should investigate effects of other soil properties on the acoustic signature and include development of machine learning approaches to classify soils based on these data.","The student, Brendan Kuhns, submitted this Thesis for approval on 2019-04-18 at 09:51.","This Thesis was approved for publication on 2019-04-22 at 10:40.","DSpace SAF Submission Ingestion Package generated from Vireo submission #13739 on 2019-08-22 at 16:23:09","Made available in DSpace on 2019-08-23T20:48:17Z (GMT). No. of bitstreams: 2 KUHNS-THESIS-2019.pdf: 6230944 bytes, checksum: e5534e06d0953e686d0336faf286ea8e (MD5) LICENSE.txt: 4210 bytes, checksum: 51da350e020f9828dfc5023e13a61332 (MD5) Previous issue date: 2019-04-22","Embargo set by: Seth Robbins for item 112344 Lift date: 2021-08-23T20:48:32Z Reason: Author requested closed access (OA after 2yrs) in Vireo ETD system","Limited Restriction Lifted for Item 112344 on 2021-08-24T09:15:38Z."],"dc:format":["application/pdf"],"dc:identifier":["http://hdl.handle.net/2142/105222"],"dc:language":["en"],"dc:rights":["© 2019 Brendan Matthew Kuhns"],"dc:subject":["soil physical sensing","acoustic emission","soil texture","soil compaction","on-the-go sensor","frequency spectra"],"dc:title":["On-the-go soil physical properties characterization using acoustic emission detection"],"dc:type":["text"],"thesis:degree_discipline":["Technical Systems Management"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["M.S."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:24:44Z"}