Search results

Vision, audition, olfactory, tactile and taste are five important senses that human uses to interact with the real world. As facing more and more complex environments, a sensing system is essential for intelligent robots with various types of sensors. To mimic human-like abilities, sensors similar to human perception capabilities are indispensable. However, most research only concentrated on analyzing literature on single-modal sensors and their robotics application.

This study presents a systematic review of five bioinspired senses, especially considering a brief introduction of multimodal sensing applications and predicting current trends and future directions of this field, which may have continuous enlightenments.

This review shows that bioinspired sensors can enable robots to better understand the environment, and multiple sensor combinations can support the robot’s ability to behave intelligently.

The review starts with a brief survey of the biological sensing mechanisms of the five senses, which are followed by their bioinspired electronic counterparts. Their applications in the robots are then reviewed as another emphasis, covering the main application scopes of localization and navigation, objection identification, dexterous manipulation, compliant interaction and so on. Finally, the trends, difficulties and challenges of this research were discussed to help guide future research on intelligent robot sensors.

For the purpose of reducing the incidence of hazardous materials transport accident, eliminating the potential threats and ensuring their safety, aiming at the shortcomings in the process of current hazardous materials transportation management, this paper aims to construct the framework of hazardous materials transportation safety management system under the vehicle-infrastructure connected environment.

The system takes the intelligent connected vehicle as the main supporter, integrating GIS, GPS, eye location, GSM, networks and database technology.

By analyzing the transportation characteristics of hazardous materials, this system consists of five subsystems, which are vehicle and driver management subsystem, dangerous sources and hazardous materials management subsystem, route analysis and optimization subsystem, early warning and emergency rescue management subsystem, and basic information query subsystem.

Hazardous materials transportation safety management system includes omnibearing real-time monitoring, timely updating of system database, real-time generation and optimization of emergency rescue route. The system can reduce the transportation cost and improve the ability of accident prevention and emergency rescue of hazardous materials.

This paper aims to carry out tribological experiments to explore the applications of femtosecond laser surface texturing technology on rock bit sliding bearing to enhance the lifetime and working performance of rock bit sliding bearing under high temperature and heavy load conditions.

Surface textures on beryllium bronze specimen were fabricated by femtosecond laser ablation (800 nm wavelength, 40 fs pulse duration, 1 kHz pulse repetition frequency), and then the tribological behaviors of pin-on-disc configuration of rock bit bearing were performed with 20CrNiMo/beryllium bronze tribo-pairs under non-Newtonian lubrication of rock bit grease.

The results showed that the surface texture on beryllium bronze specimens with specific geometrical features can be achieved by optimizing femtosecond laser processing via adjusting laser peak power and exposure time; more than 52 per cent of friction reduction was obtained from surface texture with a depth-to-diameter ratio of 0.165 and area ratio of 5 per cent at a shear rate of 1301 s−1 under the heavy load of 20 MPa and high temperature of 120°C, and the lubrication regime of rock bit bearing unit tribo-pairs was improved from boundary to mixed lubrication, which indicated that femtosecond laser ablation technique showed great potential in promoting service life and working performance of rock bit bearing.

Femtosecond laser-irradiated surface texture has the potential possibility for application in rock bit sliding bearing to improve the lubrication performance. Because proper micro dimples showed good lubrication and wear resistance performance for unit tribo-pairs of rock bit sliding bearing under high temperature, heavy load and non-Newtonian lubrication conditions, which is very important to improve the efficiency of breaking rock and accelerate the development of deep-water oil and gas resources.

The research approach is based on the concept that a failure event is rarely random and is often generated by a chain of previous events connected by a sort of domino effect. Thus, the purpose of this study is the optimal selection of the components to predictively maintain on the basis of their failure probability, under budget and time constraints.

Assets maintenance is a major challenge for any process industry. Thanks to the development of Big Data Analytics techniques and tools, data produced by such systems can be analyzed in order to predict their behavior. Considering the asset as a social system composed of several interacting components, in this work, a framework is developed to identify the relationships between component failures and to avoid them through the predictive replacement of critical ones: such relationships are identified through the Association Rule Mining (ARM), while their interaction is studied through the Social Network Analysis (SNA).

A case example of a process industry is presented to explain and test the proposed model and to discuss its applicability. The proposed framework provides an approach to expand upon previous work in the areas of prediction of fault events and monitoring strategy of critical components.

The novel combined adoption of ARM and SNA is proposed to identify the hidden interaction among events and to define the nature of such interactions and communities of nodes in order to analyze local and global paths and define the most influential entities.