An autonomous assistive robot needs to recognize the body-limb posture of the person being assisted while he/she is lying in a bed to provide care services such as helping change the posture of the person or carrying him/her from the bed to a wheelchair. This paper presents a data-efficient classification of human postures when lying in a bed using a hybrid fuzzy logic and machine learning approach. The classifier was trained using a relatively small dataset containing 19,800 annotated depth images collected using Kinect from 32 test subjects lying in bed. An overall accuracy of 97.1% was achieved on the dataset. Furthermore, the image dataset including depth and red-green-blue (RGB) images, is available to the research community with the publication of this paper, with the hope that it can benefit other researchers.

At operated voltage, the movement behavior, partial discharge, and harmfulness of linear particle in different positions of GIS (high-voltage bus, shield ring, and insulator) are still not clear now. In order to study and solve this urgent engineering problem, the discharge signals, ultrasonic signal, and movement locus of linear particles were recorded and observed. The movement behavior, partial discharge characteristics, and harmfulness of metallic particle in different positions are analyzed and compared. The results suggest that: 1) at operated voltage, the movement behavior of linear particle has a great difference in different positions of GIS. The particle jumps with small height under the high-voltage bus, but the jumping frequency is very high and the time series of discharge signal has one-to-one correspondence with that of the ultrasonic signal. When the particle moves to the shielding ring, particle instantly jumps to the high-voltage electrode. At this time, the consistency between the discharge signal and the ultrasonic signal becomes worse. In addition, when the particle touches the insulator, it can attach to the insulator, never move, and become a fixed metallic particle. 2) When the metallic particle freely jumps under the high voltage bus and the shielding ring, the breakdown voltage of the GIS is still very high. However, when the particle attaches to the insulator, the creeping discharge of the particle will make it has serious harmfulness.

This article is concerned with a hyperboloid 3-D localization method of the transformer patrol robot based on the empirical mode decomposition (EMD) of ultrasonic signals and phase transform-beta (PHAT- β) generalized cross correlation (GCC). A linear sensor array is first employed to receive ultrasonic signals emitted by robot. The received signals are decomposed into several intrinsic mode functions (IMFs) of different scales by EMD. According to the correlation degree between IMFs and the received signals, the IMFs with large correlation coefficients are subsequently selected to reconstruct the signals. Furthermore, the PHAT- β GCC algorithm is used to estimate the time delay between the different sensors. Finally, multiple hyperboloids formed by sensors are intersected to accurately localize the robot. The simulation and experimental results demonstrate that the maximum relative errors in three typical positions are 5.6%, 4.8%, and 5.2%. The maximum localization error is less than 15 mm in a laboratory scale model with a size of length 800 mm, width 450 mm, and height 500 mm.

One of the most difficult problems of the three-coil wireless power transfer (WPT) systems is that the receiving coil is hardly fully aligned with the transmitting and relay coils, which affects the efficiency of the practical system seriously as the coupling exists among the transmitting, relay and receiving coils simultaneously. Therefore, this article presents a new mutual inductance identification and efficiency optimization method for the three-coil WPT system with a switchable relay coil. First, the mathematical model of the three-coil WPT system with and without the relay coil is constructed. Second, the mutual inductance identification method is proposed to analyze the mutual inductances among the three coils by the switchable relay coil, which does not need complicated mathematical calculation strategies and the operating frequency of the system can be held constant. Then the coil-to-coil efficiency of the system is compared with and without the relay coil when the load resistance or position varies. Finally, a coil-to-coil efficiency improvement method is proposed to ensure that the system can always operate under high-efficiency conditions according to the identified mutual inductances of the three-coil WPT system.

Because large oil-immersed transformers are enclosed by a metal shell, the on-site localization means it is difficult to achieve the accurate location of the patrol micro-robot inside a given transformer. To address this issue, a spatial ultrasonic localization method based on wavelet decomposition and PHAT-β-γ generalized cross correlation is proposed in this paper. The method is carried out with a five-element stereo ultrasonic array for the location of a transformer patrol robot. Firstly, the localization signal is decomposed into wavelet coefficients of different scales, which would realize the adaptive decomposition of the frequency of the localization signal from low frequencies to high frequencies. Then, the wavelet coefficients are denoised and reconstructed by using the semi-soft threshold function. Second, a modified phase transform-beta-gamma (PHAT-β-γ) method is used to calculate the exact time delay between different sensors by increasing the weights of the PHAT weighting function and introducing a correlation function. Finally, by using the proposed method, the accurate localization of the transformer patrol micro-robot is achieved with a five-element stereo ultrasonic array. The simulation and test results show that inside a transformer experimental oil tank (120 cm × 100 cm × 100 cm, L × W × H), the relative error of transformer patrol micro-robot spatial localization is within 4.1%, and the maximum localization error is less than 3 cm, which meets the requirement of engineering localization.

The application of metasurface in wireless power transfer (WPT) system has attracted great attention due to its excellent properties. However, most studies focus on singlefrequency transmission of energy (generally MHz-band frequency), while the operating frequency of most WPT systems is kHz band. In this letter, a cross-frequency (both kHz and MHz bands) metasurface cell for WPT system is designed and equivalent permeability extraction method is proposed for the first time. Firstly, a double-layer nested structure with two different helical coils is utilized to enable the metasurface cell to obtain two different resonant frequencies. Secondly, the equivalent circuit of this metasurface cell is established and detailed theoretical analysis of equivalent relative permeability is derived for cross-frequency metasurface unit cell. Finally, the precise prototype of unit cell is designed. The experimental results agree well with the theoretical ones. This work paves the way to dual-frequency band WPT system based on metasurface. Particularly, it provides a good preparation for the application of cross-frequency metasurface to realize simultaneous wireless power and data transfer in WPT system