Portable and Non-Intrusive Fill-State Detection for Liquid-Freight Containers Based on Vibration Signals
Remote, automated querying of fill-states of liquid-freight containers can significantly boost the operational efficiency of rail- and storage-yards. Most existing methods for fill-state detection are intrusive, or require sophisticated instrumentation and specific testing conditions, making them un...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-10-01
|
| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/22/20/7901 |
| _version_ | 1797470039575625728 |
|---|---|
| author | Yanjue Song Ernest Van Hoecke Nilesh Madhu |
| author_facet | Yanjue Song Ernest Van Hoecke Nilesh Madhu |
| author_sort | Yanjue Song |
| collection | DOAJ |
| description | Remote, automated querying of fill-states of liquid-freight containers can significantly boost the operational efficiency of rail- and storage-yards. Most existing methods for fill-state detection are intrusive, or require sophisticated instrumentation and specific testing conditions, making them unsuitable here, due to the noisy and changeable surroundings and restricted access to the interior. We present a non-intrusive system that exploits the influence of the fill-state on the container’s response to an external excitation. Using a solenoid and accelerometer mounted on the exterior wall of the container, to generate pulsed excitation and to measure the container response, the fill-state can be detected. The decision can be either a <i>binary</i> (empty/non-empty) label or a (quantised) prediction of the liquid level. We also investigate the choice of the signal features for the detection/classification, and the placement of the sensor and actuator. Experiments conducted in real settings validate the algorithms and the prototypes. Results show that the placement of the sensor and actuator along the base of the container is the best in terms of detection accuracy. In terms of signal features, linear predictive cepstral coefficients possess sufficient discriminative information. The prediction accuracy is 100% for binary classification and exceeds 80% for quantised level prediction. |
| first_indexed | 2024-03-09T19:31:08Z |
| format | Article |
| id | doaj.art-d735d0f13cae4e1f99e84dc313a6779b |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T19:31:08Z |
| publishDate | 2022-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-d735d0f13cae4e1f99e84dc313a6779b2023-11-24T02:28:15ZengMDPI AGSensors1424-82202022-10-012220790110.3390/s22207901Portable and Non-Intrusive Fill-State Detection for Liquid-Freight Containers Based on Vibration SignalsYanjue Song0Ernest Van Hoecke1Nilesh Madhu2IDLab, Ghent University—imec, 9000 Gent, BelgiumIDLab, Ghent University—imec, 9000 Gent, BelgiumIDLab, Ghent University—imec, 9000 Gent, BelgiumRemote, automated querying of fill-states of liquid-freight containers can significantly boost the operational efficiency of rail- and storage-yards. Most existing methods for fill-state detection are intrusive, or require sophisticated instrumentation and specific testing conditions, making them unsuitable here, due to the noisy and changeable surroundings and restricted access to the interior. We present a non-intrusive system that exploits the influence of the fill-state on the container’s response to an external excitation. Using a solenoid and accelerometer mounted on the exterior wall of the container, to generate pulsed excitation and to measure the container response, the fill-state can be detected. The decision can be either a <i>binary</i> (empty/non-empty) label or a (quantised) prediction of the liquid level. We also investigate the choice of the signal features for the detection/classification, and the placement of the sensor and actuator. Experiments conducted in real settings validate the algorithms and the prototypes. Results show that the placement of the sensor and actuator along the base of the container is the best in terms of detection accuracy. In terms of signal features, linear predictive cepstral coefficients possess sufficient discriminative information. The prediction accuracy is 100% for binary classification and exceeds 80% for quantised level prediction.https://www.mdpi.com/1424-8220/22/20/7901fill-state detectionnon-intrusive measuringimpulse responselevel prediction |
| spellingShingle | Yanjue Song Ernest Van Hoecke Nilesh Madhu Portable and Non-Intrusive Fill-State Detection for Liquid-Freight Containers Based on Vibration Signals Sensors fill-state detection non-intrusive measuring impulse response level prediction |
| title | Portable and Non-Intrusive Fill-State Detection for Liquid-Freight Containers Based on Vibration Signals |
| title_full | Portable and Non-Intrusive Fill-State Detection for Liquid-Freight Containers Based on Vibration Signals |
| title_fullStr | Portable and Non-Intrusive Fill-State Detection for Liquid-Freight Containers Based on Vibration Signals |
| title_full_unstemmed | Portable and Non-Intrusive Fill-State Detection for Liquid-Freight Containers Based on Vibration Signals |
| title_short | Portable and Non-Intrusive Fill-State Detection for Liquid-Freight Containers Based on Vibration Signals |
| title_sort | portable and non intrusive fill state detection for liquid freight containers based on vibration signals |
| topic | fill-state detection non-intrusive measuring impulse response level prediction |
| url | https://www.mdpi.com/1424-8220/22/20/7901 |
| work_keys_str_mv | AT yanjuesong portableandnonintrusivefillstatedetectionforliquidfreightcontainersbasedonvibrationsignals AT ernestvanhoecke portableandnonintrusivefillstatedetectionforliquidfreightcontainersbasedonvibrationsignals AT nileshmadhu portableandnonintrusivefillstatedetectionforliquidfreightcontainersbasedonvibrationsignals |