Research on path planning of autonomous manganese nodule mining vehicle based on lifting mining system.

Deep-sea manganese nodules are abundant in the ocean, with high exploitation potential and commercial value, and have become mineral resources that coastal countries compete to develop. The pipeline-lifting mining system is the most promising deep-sea mining system at present. A deep-sea mining vehicle is the core equipment of this system. Mining quality and efficiency rely on mining vehicles to a great extent. According to the topographic and geomorphic environmental characteristics of deep-sea manganese nodules at the bottom of the ocean, a new deep-sea mining system based on an autonomous manganese nodule mining vehicle is proposed in this paper. According to the operating environment and functional requirements of the seabed, a new mining method is proposed, and the global traverse path planning research of the autonomous manganese nodule mining vehicle based on this mining method is carried out. The arc round-trip acquisition path planning method is put forward, and the simulation verification shows that the method effectively solves the problems of low efficiency of mining vehicle traversing acquisition and obstacle avoidance.

Underwater Undulating Propulsion Biomimetic Robots: A Review.

The traditional propeller-based propulsion of underwater robots is inefficient and poorly adapted to practice. By contrast, underwater biomimetic robots show better stability and maneuverability in harsh marine environments. This is particularly true of undulating propulsion biomimetic robots. This paper classifies the existing underwater biomimetic robots and outlines their main contributions to the field. The propulsion mechanisms of underwater biomimetic undulating robots are summarized based on theoretical, numerical and experimental studies. Future perspectives on underwater biomimetic undulating robots are also presented, filling the gaps in the existing literature.

Bio-Mimic, Fast-Moving, and Flippable Soft Piezoelectric Robots.

Cheetahs achieve high-speed movement and unique athletic gaits through the contraction and expansion of their limbs during the gallop. However, few soft robots can mimic their gaits and achieve the same speed of movement. Inspired by the motion gait of cheetahs, here the resonance of double spiral structure for amplified motion performance and environmental adaptability in a soft-bodied hopping micro-robot is exploited. The 0.058 g, 10 mm long tethered soft robot is capable of achieving a maximum motion speed of 42.8 body lengths per second (BL/s) and a maximum average turning speed of 482° s-1 . In addition, this robot can maintain high speed movement even after flipping. The soft robot's ability to move over complex terrain, climb hills, and carry heavy loads as well as temperature sensors is demonstrated. This research opens a new structural design for soft robots: a double spiral configuration that efficiently translates the deformation of soft actuators into swift motion of the robot with high environmental adaptability.

Artificial Intelligence Enhanced Reliability Assessment Methodology With Small Samples.

Due to the high price of the product and the limitation of laboratory conditions, reliability tests often get a small number of failed samples. If the data are not handled properly, the reliability evaluation results will incur grave errors. In order to solve this problem, this work proposes an artificial intelligence (AI) enhanced reliability assessment methodology by combining Bayesian neural networks (BNNs) and differential evolution (DE) algorithms. First, a single hidden layer BNN model is constructed by fusing small samples and prior information to obtain the 95% confidence interval (CI) of the posterior distribution. Then, the DE algorithm is used to iteratively generate optimal virtual samples based on the 95% CI and small samples trends. A reliability assessment model is reconstructed based on double hidden layers BNN model by combining virtual samples and test samples in the last stage. In order to verify the effectiveness of the proposed method, an accelerated life test (ALT) of the subsurface electronic control unit (S-ECU) was carried out. The verification test results show that the proposed method can accurately evaluate the reliability life of a product. And compared with the two existing methods, the results show that this method can effectively improve the accuracy of the reliability assessment of a test product.

A defect localization method based on self-sensing and orthogonal matching pursuit.

In conventional structural health monitoring (SHM), a sensor array enables to localize a potential defect by using at least three lead zirconate titanate (PZT) patches. To reduce the vast number of patches needed for large-scaled structure, this paper presents an extremely sparse sensor array with only one single PZT patch, which could actuate and sense simultaneously. Firstly, a half-bridge circuit, referred as a self-sensing circuit is developed with a capacitor connected with the PZT patch, and the capacitance parameter and self-sensing performance are studied subsequently. Then, an orthogonal matching pursuit (OMP)-based sparse decomposition and dispersion removal algorithm is proposed to separate and reconstruct wave packets which are acutely overlapped. Subsequently, a matching strategy is proposed to determine the matching relationship between wave packets and wave paths. Finally, the ellipse-type imaging approach is employed to image the defect location. Two cases: one and two defects respectively are implemented to verify its efficacy. Experimental results illustrate that the proposed self-sensing unit and signal process method could erase the adverse effect of sensor-actuator interval and dispersion characteristic to the localization resolution and accuracy.

Modeling and Analysis of Acoustic Emission Generated by Fatigue Cracking.

The acoustic emission (AE) method is a popular and well-developed method for passive structural health monitoring of metallic and composite structures. The current study focuses on the analysis of one of its processes, sound source or signal propagation. This paper discusses the principle of plate wave signal sensing using piezoelectric transducers, and derives an analytical expression for the response of piezoelectric transducers under the action of stress waves, to obtain an overall mathematical model of the acoustic emission signal from generation to reception. The acoustic emission caused by fatigue crack extension is simulated by a finite element method, and the actual acoustic emission signal is simulated by a pencil lead break experiment. The results predicted by the mathematical model are compared with the experimental results and the simulation results, respectively, and show good agreement. In addition, the presence of obvious S0 mode Lamb waves is observed in the simulation results and experimental results, which further verifies the correctness of the analytical model prediction.

Ultrasound Defect Localization in Shell Structures with Lamb Waves Using Spare Sensor Array and Orthogonal Matching Pursuit Decomposition.

Lamb waves have multimodal and dispersion effects, which reduces their performance in damage localization with respect to resolution. To detect damage with fewest sensors and high resolution, a method, using only two piezoelectric transducers and based on orthogonal matching pursuit (OMP) decomposition, was proposed. First, an OMP-based decomposition and dispersion removal algorithm is introduced, which is capable of separating wave packets of different propagation paths and removing the dispersion part successively. Then, two simulation signals, with nonoverlapped and overlapped wave packets, are employed to verify the proposed method. Thereafter, with the proposed algorithm, the wave packets reflected from the defect and edge are all separated. Finally, a sparse sensor array with only two transducers succeeds in localizing the defect. The experimental results show that the OMP-based algorithm is beneficial for resolution improvement and transducer usage reduction.

Time-Frequency Distribution Map-Based Convolutional Neural Network (CNN) Model for Underwater Pipeline Leakage Detection Using Acoustic Signals.

Detection technology of underwater pipeline leakage plays an important role in the subsea production system. In this paper, a new method based on the acoustic leak signal collected by a hydrophone is proposed to detect pipeline leakage in the subsea production system. Through the pipeline leakage test, it is found that the radiation noise is a continuous spectrum of the medium and high-frequency noise. Both the increase in pipe pressure and the diameter of the leak hole will narrow the spectral structure and shift the spectrum center towards the low frequencies. Under the same condition, the pipe pressure has a greater impact on the noise; every 0.05 MPa increase in the pressure, the radiation sound pressure level increases by 6-7 dB. The time-frequency images were obtained by processing the acoustic signals using the Ensemble Empirical Mode Decomposition (EEMD) and Hilbert-Huang transform (HHT), and fed into a two-layer Convolutional Neural Network (CNN) for leakage detection. The results show that CNN can correctly identify the degree of pipeline leakage. Hence, the proposed method provides a new approach for the detection of pipeline leakage in underwater engineering applications.

The Analysis of Biomimetic Caudal Fin Propulsion Mechanism with CFD.

In nature, fish not only have extraordinary ability of underwater movement but also have high mobility and flexibility. The low energy consumption and high efficiency of fish propulsive method provide a new idea for the research of bionic underwater robot and bionic propulsive technology. In this paper, the swordfish was taken as the research object, and the mechanism of the caudal fin propulsion was preliminarily explored by analyzing the flow field structure generated by the swing of caudal fin. Subsequently, the influence of the phase difference of the heaving and pitching movement, the swing amplitude of caudal fin, and Strouhal number (St number) on the propulsion performance of fish was discussed. The results demonstrated that the fish can obtain a greater propulsion force by optimizing the motion parameters of the caudal fin in a certain range. Lastly, through the mathematical model analysis of the tail of the swordfish, the producing propulsive force principle of the caudal fin and the caudal peduncle was obtained. Hence, the proposed method provided a theoretical basis for the design of a high-efficiency bionic propulsion system.

Flow Field Perception of a Moving Carrier Based on an Artificial Lateral Line System.

At present, autonomous underwater vehicles (AUVs) cannot perceive local environments in complex marine environments, where fish can obtain hydrodynamic information about the surrounding environment through a lateral line. Inspired by this biological function, an artificial lateral line system (ALLS) was built on a moving bionic carrier using the pressure sensor in this paper. When the carrier operated with different speeds in the flow field, the pressure distribution characteristics surrounding the carrier were analyzed by numerical simulation, where the effect of the flow angle between the fluid velocity direction and the carrier navigation direction was considered. The flume experiment was carried out in accordance with the simulation conditions, and the analysis results of the experiment were consistent with those in the simulation. The relationship between pressure and fluid velocity was established by a fitting method. Subsequently, the pressure difference method was investigated to establish a relationship model between the pressure difference on both sides of the carrier and the flow angle. Finally, a back propagation neural network model was used to predict the fluid velocity, flow angle, and carrier speed successfully in the unknown fluid environment. The local fluid environment perception by moving carrier carrying ALLS was studied which may promote the engineering application of the artificial lateral line in the local perception, positioning, and navigation on AUVs.

A Hyper-Elastic Creep Approach and Characterization Analysis for Rubber Vibration Systems.

Rubber materials are extensively utilized for vibration mitigation. Creep is one of the most important physical properties in rubber engineering applications, which may induce failure issues. The purpose of this paper is to provide an engineering approach to evaluate creep performance of rubber systems. Using a combination of hyper-elastic strain energy potential and time-dependent creep damage function, new creep constitutive models were developed. Three different time-decay creep functions were provided and compared. The developed constitutive model was incorporated with finite element analysis by user subroutine and its engineering potential for predicting the creep response of rubber vibration devices was validated. Quasi-static and creep experiments were conducted to verify numerical solutions. The time-dependent, temperature-related, and loading-induced creep behaviors (e.g., stress distribution, creep rate, and creep degree) were explored. Additionally, the time-temperature superposition principle was shown. The present work may enlighten the understanding of the creep mechanism of rubbers and provide a theoretical basis for engineering applications.

High-Resolution Crack Localization Approach Based on Diffraction Wave.

The delay-and-sum imaging algorithm is a promising crack localization approach for crack detection and monitoring of key structural regions. Most studies successfully offer a hole-like damage position. However, cracks are more common than hole-like damages in a structure. To solve this issue, this paper presents a crack localization approach, based on diffraction wave theory, which is capable of imaging crack endpoints. The guided wave propagated to the crack endpoints and transformed into a diffraction wave. A line sensor array was used to record the diffraction waveform. Then, dispersion compensation was applied to shorten the dispersive wave packets and separate the overlapping wave packets. Subsequently, half-wave compensation was executed to improve the localization accuracy. Finally, the effectiveness of this high-resolution crack localization method was validated by an experimental example.

Dislocation Evaluation of Fe Twist Grain Boundary Based on Molecular Dynamics.

The grain boundary and dislocation motion characteristics on the atomic scale are significant for the study of material failure mechanisms. In the present work, by theoretical analysis and numerical simulation, the most stable phase of Fe crystal under given conditions is confirmed. Distribution of dislocation potential under different torsion angles is studied for BCC-Fe (001) twist grain boundary. The dislocation motion in Fe (001), Fe (110) and Fe (111) twist grain boundary under tension, compression and shear loading are also investigated.

Damage detection of offshore platforms using acoustic emission analysis.

This paper aims to detect the structure damage in KT type jacket offshore platforms using acoustic emission analysis. Experimental investigation has been implemented to analyze the transmission characteristics, attenuation law, and source localization of the acoustic emission signals. The range of energy attenuation coefficient α and the signal amplitude attenuation law were obtained from experimental data. Hence, the layout of acoustic emission sensors was optimized based on the energy attenuation to achieve online damage monitoring for KT-jacket platforms. In order to validate the performance of the optimized sensor layout, another experimental test was conducted on the designed KT-jacket offshore platform to locate the acoustic emission sources. The test results demonstrate that a positioning error of 8 mm or below can be obtained using the optimized sensor layout, and the number of sensors can be reduced by 80% compared with that of the theoretical layout. As a result, the optimized sensor layout enables efficient and effective damage detection for KT-jacket offshore platforms.

Research on Flow Field Perception Based on Artificial Lateral Line Sensor System.

In nature, the lateral line of fish is a peculiar and important organ for sensing the surrounding hydrodynamic environment, preying, escaping from predators and schooling. In this paper, by imitating the mechanism of fish lateral canal neuromasts, we developed an artificial lateral line system composed of micro-pressure sensors. Through hydrodynamic simulations, an optimized sensor structure was obtained and the pressure distribution models of the lateral surface were established in uniform flow and turbulent flow. Carrying out the corresponding underwater experiment, the validity of the numerical simulation method is verified by the comparison between the experimental data and the simulation results. In addition, a variety of effective research methods are proposed and validated for the flow velocity estimation and attitude perception in turbulent flow, respectively and the shape recognition of obstacles is realized by the neural network algorithm.

Structural Insights into the Redox-Sensing Mechanism of MarR-Type Regulator AbfR.

As a master redox-sensing MarR-family transcriptional regulator, AbfR participates in oxidative stress responses and virulence regulations in Staphylococcus epidermidis. Here, we present structural insights into the DNA-binding mechanism of AbfR in different oxidation states by determining the X-ray crystal structures of a reduced-AbfR/DNA complex, an overoxidized (Cys13-SO2H and Cys13-SO3H) AbfR/DNA, and 2-disulfide cross-linked AbfR dimer. Together with biochemical analyses, our results suggest that the redox regulation of AbfR-sensing displays two novel features: (i) the reversible disulfide modification, but not the irreversible overoxidation, significantly abolishes the DNA-binding ability of the AbfR repressor; (ii) either 1-disulfide cross-linked or 2-disulfide cross-linked AbfR dimer is biologically significant. The overoxidized species of AbfR, resembling the reduced AbfR in conformation and retaining the DNA-binding ability, does not exist in biologically significant concentrations, however. The 1-disulfide cross-linked modification endows AbfR with significantly weakened capability for DNA-binding. The 2-disulfide cross-linked AbfR adopts a very "open" conformation that is incompatible with DNA-binding. Overall, the concise oxidation chemistry of the redox-active cysteine allows AbfR to sense and respond to oxidative stress correctly and efficiently.

Small-molecule targeting of a diapophytoene desaturase inhibits S. aureus virulence.

The surge of antibiotic resistance in Staphylococcus aureus has created a dire need for innovative anti-infective agents that attack new targets, to overcome resistance. In S. aureus, carotenoid pigment is an important virulence factor because it shields the bacterium from host oxidant killing. Here we show that naftifine, a US Food and Drug Administration (FDA)-approved antifungal drug, blocks biosynthesis of carotenoid pigment at nanomolar concentrations. This effect is mediated by competitive inhibition of S. aureus diapophytoene desaturase (CrtN), an essential enzyme for carotenoid pigment synthesis. We found that naftifine attenuated the virulence of a variety of clinical S. aureus isolates, including methicillin-resistant S. aureus (MRSA) strains, in mouse infection models. Specifically, we determined that naftifine is a lead compound for potent CrtN inhibitors. In sum, these findings reveal that naftifine could serve as a chemical probe to manipulate CrtN activity, providing proof of concept that CrtN is a druggable target against S. aureus infections.

A Review of Artificial Lateral Line in Sensor Fabrication and Bionic Applications for Robot Fish.

Lateral line is a system of sense organs that can aid fishes to maneuver in a dark environment. Artificial lateral line (ALL) imitates the structure of lateral line in fishes and provides invaluable means for underwater-sensing technology and robot fish control. This paper reviews ALL, including sensor fabrication and applications to robot fish. The biophysics of lateral line are first introduced to enhance the understanding of lateral line structure and function. The design and fabrication of an ALL sensor on the basis of various sensing principles are then presented. ALL systems are collections of sensors that include carrier and control circuit. Their structure and hydrodynamic detection are reviewed. Finally, further research trends and existing problems of ALL are discussed.

Morphology and Molecular Phylogeny of Two Freshwater Peritrich Ciliates, Epistylis chlorelligerum Shen 1980 and Epistylis chrysemydis Bishop and Jahn 1941 (Ciliophora, Peritrichia).

Two populations of Epistylis chlorelligerum Shen 1980, a colonial limnetic peritrich ciliate, were collected from different locations in China: E. chlorelligerum 1 from West Lake, Hangzhou; E. chlorelligerum 2 from East Lake, Wuhan. The morphology, infraciliature and SSU rRNA gene sequence of the two populations were investigated based on living and protargol-stained specimens. Although both populations are consistent with previous descriptions of protargol-stained specimens of this species, some differences in the morphology in vivo were observed. The two populations had identical SSU rRNA gene sequences. A second species, Epistylis chrysemydis Bishop and Jahn 1941, was also collected from East Lake, Wuhan, and was investigated for its morphology, infraciliature and SSU rRNA gene sequence. Phylogenetic analyses based on SSU rRNA gene sequence data indicate that the two populations of E. chlorelligerum are nested within the Epistylididae clade near E. wenrichi and E. urceolata. Epistylis chrysemydis is sister to the group comprising E. chlorelligerum, E. wenrichi, and E. urceolata.

Insights into community-based discrimination of water quality status using an annual pool of phytoplankton in mid-subtropical canal systems.

With rapid response to environmental changes, phytoplankton communities have been used as a favorable bioindicator to evaluate environmental stress and anthropogenic impacts in aquatic ecosystems. The feasibility for their community-based bioassessment was studied in a mid-subtropical canal (Tiesha River), southern China, during a 1-year cycle (November 2009-December 2010). Samples were monthly collected at four sampling stations within a contamination gradient. Environmental variables, such as water temperature, dissolved oxygen (DO), chemical oxygen demand (COD), biological oxygen demand (BOD5), total phosphorus (TP), and total nitrogen (TN), were measured synchronously for comparison with biotic parameters. The phytoplankton community structures showed a significant difference among four stations. The spatial variation in abundance was significantly correlated with the changes in environmental variables, especially TN, TP, and COD. Four dominant species (Aulacoseira granulata, Leptocylindrus danicus, Oscillatoria tenuis, and Radiococcus nimbatus) were significantly correlated with nutrients, while the species richness index represented a significant correlation with BOD5. The phytoplankton-based Saprobien indices could not reveal the spatial variation in water quality status although may reflect water pollution levels (from ß- to α-mesosaprobic zone) in the canal system. It is suggested that phytoplankton communities might be used as a potentially robust bioindicator for discriminating environmental quality status in mid-tropical canal systems.