Towards Explainable Augmented Intelligence (AI) for Crack Characterization

Crack characterisation is one of the central tasks of NDT&E (the Non-Destructive Testing and Evaluation) of industrial components and structures. These days data necessary for carrying out this task are often collected using ultrasonic phased arrays. Many ultrasonic phased array inspections are automated but interpretation of the data they produce is not. This paper offers an approach to designing an explainable AI (Augmented Intelligence) to meet this challenge. It describes a C code called AutoNDE, which comprises a signal-processing module based on a modified total focusing method that creates a sequence of two-dimensional images of an evaluated specimen; an image-processing module, which filters and enhances these images; and an explainable AI module—a decision tree, which selects images of possible cracks, groups those of them that appear to represent the same crack and produces for each group a possible inspection report for perusal by a human inspector. AutoNDE has been trained on 16 datasets collected in a laboratory by imaging steel specimens with large smooth planar notches, both embedded and surface-breaking. It has been tested on two other similar datasets. The paper presents results of this training and testing and describes in detail an approach to dealing with the main source of error in ultrasonic data—undulations in the specimens’ surfaces.

A BCI Based Alerting System for Attention Recovery of UAV Operators

As unmanned aerial vehicles have become popular, the number of accidents caused by an operator’s inattention have increased. To prevent such accidents, the operator should maintain an attention status. However, limited research has been conducted on the brain-computer interface (BCI)-based system with an alerting module for the operator’s attention recovery of unmanned aerial vehicles. Therefore, we introduce a detection and alerting system that prevents an unmanned aerial vehicle operator from falling into inattention status by using the operator’s electroencephalogram signal. The proposed system consists of the following three components: a signal processing module, which collects and preprocesses an electroencephalogram signal of an operator, an inattention detection module, which determines whether an inattention status occurred based on the preprocessed signal, and, lastly, an alert providing module that presents stimulus to an operator when inattention is detected. As a result of evaluating the performance with a real-world dataset, it was shown that the proposed system successfully contributed to the recovery of operator attention in the evaluating dataset, although statistical significance could not be established due to the small number of subjects.

Echo simulation of dual polarization Doppler weather radar based on the physical model

Using the scattering characteristics of particles to simulate the radar echo can supply the test signals close to the real precipitation echo for the weather radar and save the time and cost of the research and development and maintenance of the weather radar. In this paper, the precipitation echo of weather radar is simulated based on the theoretical basis that the falling raindrops have a shape well approximated by an oblate spheroid in the atmosphere. The Marshal-Palmer distribution is applied to describe the raindrop spectrum distribution of precipitation particles. It is assumed that the raindrop particles of different sizes have the random distribution in the radar resolution volume, and then the spatial distribution of precipitation particles in the resolution volume is modeled. The echo signals of horizontal and vertical polarization channels of dual-polarization weather radar are obtained by vector superposition of backscattering echoes of each particle. The experimental results show that this method can describe the microphysical characteristics of precipitation particles more completely and can be used to test the signal processing module of dual-polarization Doppler weather radar.

Echo Simulation of Dual Polarization Doppler Weather Radar Based on the Physical Model

Using the scattering characteristics of particles to simulate the radar echo can supply the test signals close to the real precipitation echo for the weather radar, and save the time and cost of the research and development and maintenance of the weather radar. In this paper, the precipitation echo of weather radar is simulated based on the theoretical basis that the falling raindrops have a shape well approximated by an oblate spheroid in the atmosphere. The Marshal-Palmer distribution is applied to describe the raindrop spectrum distribution of precipitation particles. It is assumed that the raindrop particles of different sizes have the random distribution in the radar resolution volume, and then the spatial distribution of precipitation particles in the resolution volume is modeled. The echo signals of horizontal and vertical polarization channels of dual polarization weather radar are obtained by vector superposition of backscattering echoes of each particle. The experimental results show that this method can describe the microphysical characteristics of precipitation particles more completely and can be used to test the signal processing module of dual polarization Doppler weather radar.

Echo Simulation of dual polarization Doppler Weather Radar based on physical Model

Using the scattering characteristics of particles to simulate the radar echo can supply the test signals close to the real precipitation echo for the weather radar, and save the time and cost of the research and development and maintenance of the weather radar. In this paper, the precipitation echo of weather radar is simulated based on the theoretical basis that the raindrops in the falling process satisfy the oblate spheroidal particles in the atmosphere. The Marshal-Palmer distribution is applied to describe the raindrop spectrum distribution of precipitation particles. It is assumed that the raindrop particles of different sizes have the random distribution in the radar resolution volume, and then the spatial distribution of precipitation particles in the resolution volume is modeled. The echo signals of horizontal and vertical polarization channels of dual polarization weather radar are obtained by vector superposition of backscattering echoes of each particle. The experimental results show that this method can describe the microphysical characteristics of precipitation particles more completely and can be used to test the signal processing module of dual polarization Doppler weather radar.

METHOD FOR MEASURING MOTION PARAMETERS OF MOVING OBJECTS

The paper considers a new method for measuring the angular deviations of moving objects. A specific measuring system is proposed to measure ship roll, pitch, heel and trim. The system consists of two measurement channels operating in parallel. The first channel is built on the position properties of a physical pendulum so as to build the base vertical. The second channel ensures the dynamic accuracy of the system. The principal of operation of the second channel involves correction of the signals from the first channel by using information obtained from linear MEMS accelerometers. To increase system measurement accuracy, a signal processing module is used through the Kalman filter algorithm.