Guoda Chen, Huafeng Yang, Huiqiang Cao, Shiming Ji, Xi Zeng and Qian Wang
For the climbing rod object with large diameter variation and the need of obstacle crossing, this paper aims to propose a new embracing-type climbing robot named as EVOC-I robot.
Abstract
Purpose
For the climbing rod object with large diameter variation and the need of obstacle crossing, this paper aims to propose a new embracing-type climbing robot named as EVOC-I robot.
Design/methodology/approach
The design philosophy and structural scheme are introduced. The kinematic analysis of embracing and telescoping mechanisms is carried out to provide the theoretical foundation for the effective climbing of the robot. Based on the prototype robot, three preliminary experiments are carried out to verify the effectiveness of the designed robot.
Findings
The theoretical and experimental analyses have verified the reasonability and effectiveness of the proposed robot design.
Research limitations/implications
As the preliminary study, the prototype still need a lot of improvement. The experimental verification is also limited. Future work will focus on improving the design and increasing the theoretical analysis, especially increasing experimental study and designing the next generation of the rod climbing robot.
Practical implications
The designed climbing robot can be used for climbing the rod with variation diameter and flange obstacle, especially the lightening rod in the transformer substation.
Originality/value
The paper designs a new climbing robot that integrates the ability of large variation diameter adaptation and obstacle crossing.
Details
Keywords
Xuan Yang, Hao Luo, Xinyao Nie and Xiangtianrui Kong
Tacit knowledge in frontline operations is primarily reflected in the holders’ intuition about dynamic systems. Despite the implicit nature of tacit knowledge, the understanding…
Abstract
Purpose
Tacit knowledge in frontline operations is primarily reflected in the holders’ intuition about dynamic systems. Despite the implicit nature of tacit knowledge, the understanding of complex systems it encapsulates can be displayed through formalization methods. This study seeks to develop a methodology for formalizing tacit knowledge in a dynamic delivery system.
Design/methodology/approach
This study employs a structured survey to gather experiential knowledge from dispatchers engaged in last-mile delivery operations. This knowledge is then formalized using a value function approximation approach, which transforms tacit insights into structured inputs for dynamic decision-making. We apply this methodology to optimize delivery operations in an online-to-offline pharmacy context.
Findings
The raw system feature data are not strongly correlated with the system’s development trends, making them ineffective for guiding dynamic decision-making. However, the system features obtained through preprocessing the raw data increase the predictiveness of dynamic decisions and improve the overall effectiveness of decision-making in delivery operations.
Research limitations/implications
This research provides a foundational framework for studying sequential dynamic decision problems, highlighting the potential for improved decision quality and system optimization through the formalization and integration of tacit knowledge.
Practical implications
This approach proposed in this study offers a method to preserve and formalize critical operational expertise. By embedding tacit knowledge into decision-making systems, organizations can enhance real-time responsiveness and reduce operational costs.
Originality/value
This study presents a novel approach to integrating tacit knowledge into dynamic decision-making frameworks, demonstrated in a real-world last-mile delivery context. Unlike previous research that focuses primarily on explicit data-driven methods, our approach leverages the implicit, experience-based insights of operational staff, leading to more informed and effective decision-making strategies.
Details
Keywords
Guoda Wang, Ping Li, Yumei Wen and Zhichun Luo
Existing control circuits for piezoelectric energy harvesting (PEH) suffers from long startup time or high power consumption. This paper aims to design an ultra-low power control…
Abstract
Purpose
Existing control circuits for piezoelectric energy harvesting (PEH) suffers from long startup time or high power consumption. This paper aims to design an ultra-low power control circuit that can harvest weak ambient vibrational energy on the order of several microwatts to power heavy loads such as wireless sensors.
Design/methodology/approach
A self-powered control circuit is proposed, functioning for very brief periods at the maximum power point, resulting in a low duty cycle. The circuit can start to function at low input power thresholds and can promptly achieve optimal operating conditions when cold-starting. The circuit is designed to be able to operate without stable DC power supply and powered by the piezoelectric transducers.
Findings
When using the series-synchronized switch harvesting on inductor circuit with a large 1 mF energy storage capacitor, the proposed circuit can perform 322% better than the standard energy harvesting circuit in terms of energy harvested. This control circuit can also achieve an ultra-low consumption of 0.3 µW, as well as capable of cold-starting with input power as low as 5.78 µW.
Originality/value
The intermittent control strategy proposed in this paper can drastically reduce power consumption of the control circuit. Without dedicated cold-start modules and DC auxiliary supply, the circuit can achieve optimal efficiency within one input cycle, if the input signal is larger than voltage threshold. The proposed control strategy is especially favorable for harvesting energy from natural vibrations and can be a promising solution for other PEH circuits as well.