Quadratic-Kalman-filter-based sensor fault detection approach for unmanned aerial vehicles
Sensors are crucial for the control of unmanned aerial vehicles (UAVs). However, sensor
faults will inevitably appear over time. Therefore, it is important to develop a sensor fault …
faults will inevitably appear over time. Therefore, it is important to develop a sensor fault …
Predictive digital twin for wind energy systems: a literature review
E Kandemir, A Hasan, T Kvamsdal… - Energy …, 2024 - Springer
In recent years, there has been growing interest in digital twin technology in both industry
and academia. This versatile technology has found applications across various industries …
and academia. This versatile technology has found applications across various industries …
Challenges, limitations, and measurement strategies to ensure data quality in deep-sea sensors
AM Skålvik, C Saetre, KE Frøysa, RN Bjørk… - Frontiers in Marine …, 2023 - frontiersin.org
In this paper we give an overview of factors and limitations impairing deep-sea sensor data,
and we show how automatic tests can give sensors self-validation and self-diagnostic …
and we show how automatic tests can give sensors self-validation and self-diagnostic …
Machine Learning and Fog Computing Enabled Sensor Drift Management in Precision Agriculture
Despite tremendous improvements in sensing mechanisms at the hardware level, sensor
drift is still an issue for reliable Internet of Things (IoT) applications. Existing literature is …
drift is still an issue for reliable Internet of Things (IoT) applications. Existing literature is …
Sensor fault diagnostics using physics-informed transfer learning framework
The field of smart health monitoring, intelligent fault detection and diagnosis is expanding
dramatically in order to maintain successful operation in many engineering applications …
dramatically in order to maintain successful operation in many engineering applications …
[HTML][HTML] Wavelet-Based Computational Intelligence for Real-Time Anomaly Detection and Fault Isolation in Embedded Systems
In today's technologically advanced landscape, sensors feed critical data for accurate
decision-making and actions. Ensuring the integrity and reliability of sensor data is …
decision-making and actions. Ensuring the integrity and reliability of sensor data is …
Data-driven state prediction and sensor fault diagnosis for multi-agent systems with application to a twin rotational inverted pendulum
When a multi-agent system is subjected to faults, it is necessary to detect and classify the
faults in time. This paper is motivated to propose a data-driven state prediction and sensor …
faults in time. This paper is motivated to propose a data-driven state prediction and sensor …
Fault cause assignment with physics informed transfer learning
To maintain successful operation, the field of health monitoring, fault detection and
diagnosis plays a key role. Within the scenarios of system faults, locating a fault in a complex …
diagnosis plays a key role. Within the scenarios of system faults, locating a fault in a complex …
Time series fragmental variation trend anomaly detection method based on a temporal sequential modeling approach
Time series fragmentation anomalies are a common phenomenon that occurs when
industrial systems undergo state transitions, such as the degradation of energy systems and …
industrial systems undergo state transitions, such as the degradation of energy systems and …
A Baseline Drift-Elimination Algorithm for Strain Measurement-System Signals Based on the Transformer Model
Y Wang, L Zhang, X Qi, X Yang, Q Tan - Applied Sciences, 2024 - mdpi.com
Strain measurements are vital in engineering trials, testing, and scientific research. In the
process of signal acquisition, baseline drift has a significant impact on the accuracy and …
process of signal acquisition, baseline drift has a significant impact on the accuracy and …