【摘 要】
:
Traditional fire safety management in the electric power industry has significant drawbacks,including a lack of data,difficulty of maintenance,lack of supervision,and lack of interaction.This type of management lags behind current advanced safety manageme
【机 构】
:
Shanghai Electric High Voltage Industry Co.,Ltd.,Shanghai 200052,China
论文部分内容阅读
Traditional fire safety management in the electric power industry has significant drawbacks,including a lack of data,difficulty of maintenance,lack of supervision,and lack of interaction.This type of management lags behind current advanced safety management concepts such as “gate advancement” and “full process man-agement”,and it fails to meet the needs of future energy internet construction and development.In response to these problems,an internet of things system for smart firefighting in the electric power industry was constructed in this study.This system defines a centralized information window,trains a power intelligent firefighting brain,establishes a firefighting cloud management and control system,constructs a power firefighting interaction mech-anism,and performs multi-party coordination of firefighting mechanisms to realize concept of “a whole network on one screen and everything in one network” for managing fires.
其他文献
As an emerging visual task,vehicle re-identification refers to the identification of the same vehicle across multiple cameras.Herein,we propose a novel vehicle re-identification method that uses an improved ResNet-50 architecture and utilizes the topology
In this study,a multi-object tracking (MOT) scheme based on a light detection and ranging sensor was proposed to overcome imprecise velocity observations in object occlusion scenarios.By applying real-time velocity estimation,a modified unscented Kalman f
Analyzing a vehicle\'s abnormal behavior in surveillance videos is a challenging field,mainly due to the wide variety of anomaly cases and the complexity of surveillance videos.In this study,a novel intelligent vehicle behavior analysis framework based
Multi-object tracking is a vital problem as many applications require better tracking approaches.Although learning-based detectors are becoming extremely powerful,there are few tracking methods designed to work with them in real time.We explored an effici
Contemporary autonomous-driving technology relies on good environmental-perception systems and high-precision maps.For unknown environments or scenarios where perception fails,a human-in-the-loop remote-driving system can effectively complement common sol
In real-world scenarios,the uncertainty of measurements cannot be handled efficiently by traditional model predictive control (MPC).A stochastic MPC (SMPC) method for handling the uncertainty of states in autonomous driving lane-keeping scenarios is prese
The magic formula (MF) tire model is a semi-empirical tire model that can precisely simulate tire behavior.The heuristic optimization algorithm is typically used for parameter identification of the MF tire model.To avoid the defect of the traditional heur
This study proposes two speed controllers based on a robust adaptive non-singular terminal sliding mode control approach for the cooperative adaptive cruise control problem in a connected and automated vehicular platoon.The delay-based spacing policy is a
A high-precision map (HPM) is the key infrastructure to realizing the function of automated driving(AD) and ensuring its safety.However,the current laws and regulations on HPMs in China can lead to serious legal compliance problems.Thus,proper measures sh
To solve the problems of difficult control law design,poor portability,and poor stability of traditional multi-agent formation obstacle avoidance algorithms,a multi-agent formation obstacle avoidance method based on deep reinforcement learning (DRL) is pr