In this paper, coating removal characteristics of water jet by micro jet flow affected by cleaning parameters is analyzed. Numerical simulation of fluid field calculates the velocity and pressure distribution of a water jet impinging on a rigid wall, which is used for design experiments of coating removal affected by jet pressure, traversal speed, and repeated impacting times. The removal width is used as a measure of water jet coating removal capability. Experiment results show that the coating removal width is constant, independent with traversal speed or repeated times when total exposure time of waterjet impingement is fixed. According to results of coating removal by a linear moving water jet, this study also analyzes characteristics of coating removal by rotating jet disc, especially residual coating affected by rotational and moving speed of the cleaning disc. The research is helpful to improve the coating removal efficiency of cleaning disc devices.

Due to the extremely high pressures in the deep sea, heavy ballast tanks and pressure compensating hydraulic tanks are typically required to support the operation of classic buoyancy controls. Buoyancy control systems driven by phase-change materials (PCM) have unique advantages over conventional hydraulically actuated buoyancy control systems, including high adaptability for deep-sea exploration and simple, lightweight, and compact structures. Inspired by this, a buoyancy control module (BCM) was designed with flexible material as the shell. Instead of a conventional mechanical system, the device uses an electric heating drive to control buoyancy by heating and cooling the PCM. Based on the principle of pressure compensation, this device can adjust the buoyancy of a small underwater vehicle in a deep-sea high-pressure environment. The BCM successfully adjusts the buoyancy to lift itself up and down in the South China Sea at a depth of 3223 m. The performance of the phase-change BCM to control buoyancy under high pressure is validated by systematic experiments and theoretical analysis. Our work proposes a flexible scheme for the design of a deep-sea phase-change-driven BCM and highlights its potential application in deep-sea micro-mechanical systems, especially soft robots.

Efficiently salvaging shipwrecks is of the utmost importance for safeguarding shipping safety and preserving the marine ecosystem. However, traditional methods find it difficult to salvage shipwrecks in deep water. This article presents a novel salvage technology that involves multiple hydraulic claws for directly catching and lifting a 2500-ton shipwreck at 600 m depth. To ensure lifting stability, a semi-active heave compensation (SAHC) system was employed for each lifter to mitigate the effects of sea waves. However, the response delays arising from the hydraulic, control, and filtering systems resist the heave compensation performance. Predicting the barge motion to mitigate measuring and filtering delays and achieve leading compensation is necessary for the salvage. Therefore, a multivariate long short-term memory (LSTM) based neural network was trained to forecast the barge’s heave and pitch motions, exhibiting satisfactory results for the next 5 s. According to the results of numerical simulations, the proposed LSTM-based motion predictive SAHC system demonstrates remarkable effectiveness in compensating for shipwreck motion.

The deep-sea autonomous underwater vehicle (AUV) is equipment of vital importance for ocean exploration, monitoring, and surveying. With a variable buoyancy system (VBS), AUV can achieve rising, diving, and hovering in the water column. This paper proposes a deep-sea AUV with an oil bladder type hydraulic VBS, which controls the oil flow rate with a proportional valve. However, the implementation of accurate depth control for AUV faces various challenges due to the varying water density with depth, the non-linear feature of the hydraulic system, and the disturbance from sea flows and currents. To tackle these problems, a third-order linear active disturbance rejection controller (LADRC) and its fuzzy adaptive version were designed and implemented in MATLAB/Simulink based on the state-space function of the proposed AUV system. Compared with the conventional PID controller, the simulation results indicate that the proposed LADRC controller shows strong robustness to disturbance, with other advantages including smaller steady-state error, overshoot, settling time, and response time. Moreover, the proposed fuzzy LADRC controller could further decrease the overshoot caused by the increasing target distance. The results prove that the designed depth controllers can meet the control requirements of the proposed deep-sea AUV.

Considering the further exploration of the ocean, the requirements for deep-sea operation equipment have increased. Many problems existing in the widely used deep-sea hydraulic system have become increasingly prominent. Compared with the traditional deep-sea hydraulic system, actuators using a paraffin phase change material (PCM) have incomparable advantages, including lightweight structure, low energy consumption, high adaptability to the deep sea, and good biocompatibility. Thus, a deep-sea drive microunit (DDM) based on paraffin PCM is proposed in this paper. The device adopts a flexible shell, adapting to the high-pressure environment of the deep-sea based on the principle of pressure compensation. The device realizes the output of displacement and force through the electrothermal drive, which can be used as actuator or power source of other underwater operation equipment. The microunit successfully completes the functional verification experiments in air, shallow water, and hydrostatic pressure of 110 MPa. In accordance with experimental results, a reasonable control curve is fitted, highlighting its potential application in deep-sea micro electro mechanical systems, especially in underwater soft robot.

This paper presents a developed dislocation superimposed method (DSM) for automatically extracting the component of impulsive signals from abnormal noise signals of an engine at a single speed range on the basis of the initial DSM. This method consists of three steps: using a correlation analysis to select an appropriate starting superposition point, superimposing abnormal sound signals to improve the signal‐to‐noise ratio, and intercepting superimposed signals to separate the fault component. Experimental results show that the developed DSM can effectively extract the fault characteristics of cylinder knocking and connecting rod bearing knocking. The developed approach can be applied to separate the fault characteristics of other types of rotating machines.