摘要：【中文】本发明公开了一种阀厅用灭火机器人及阀厅消防系统，阀厅用灭火机器人，包括预设在阀厅内的：灭火机器人本体，包括：行走机构、灭火炮、通讯机构，以及控制机构；线缆收纳机构，包括：底座、受驱动地沿水平方向转动设置在底座上的转动台，以及设置在转动台上的电缆自动卷盘和/或灭火剂管自动卷盘；电缆自动卷盘和/或灭火剂管自动卷盘其二者分别与灭火机器人本体相连；灭火剂管自动卷盘受驱动的自动收纳水管，和/或电缆自动卷盘受驱动的自动收纳电缆线。通过上述与灭火机器人本体相配合的线缆收纳机构，可以有效地解决现有技术中的灭火机器人其灭火剂供应不足，其灭火能力不足，无法满足阀厅消防要求的问题。 【EN】The invention discloses a fire-extinguishing robot for a valve hall and a fire-extinguishing system for the valve hall, wherein the fire-extinguishing robot for the valve hall comprises a fire-extinguishing robot body, a fire-extinguishing robot body and a fire-extinguishing robot body, wherein the fire-extinguishing robot body is pre-arranged in the valve hall: fire-fighting robot body, includes: the fire extinguishing gun comprises a traveling mechanism, an extinguishing gun, a communication mechanism and a control mechanism; a cable take-up mechanism comprising: the automatic fire extinguishing device comprises a base, a rotating platform which is driven to rotate in the horizontal direction and is arranged on the base, and an automatic cable reel and/or an automatic fire extinguishing agent pipe reel which are arranged on the rotating platform; the automatic cable reel and/or the automatic fire extinguishing agent pipe reel are/is respectively connected with the fire extinguishing robot body; an automatic fire extinguishing agent pipe reel driven automatic storage water pipe, and/or an automatic cable reel driven automatic storage cable. Through the above-mentioned cable containing mechanism with fire-fighting robot body matched with, its fire extinguishing agent supply of fire-fighting robot among the prior art can be solved effectively is not enough, and its fire extinguishing ability is not enough, can't satisfy the problem of valve hall fire control requirement.

摘要：【中文】本发明提供了一种用于涡扇炮的智能自动瞄准灭火系统，包括：图像型火焰探测器，根据采集的图像信息识别火灾，当识别出火灾时生成火焰空间坐标和报警信息，传送至图像型瞄准器；图像型瞄准器安装固定在涡扇炮上，根据接收到的火焰空间坐标和报警信息，驱动涡扇炮运动，实时采集分析火灾现场的火源信息，使涡扇炮瞄准定位火源，根据瞄准定位到的火源信息生成驱动指令，发送至涡扇炮喷射控制装置；涡扇炮喷射控制装置，依据所述驱动指令驱动涡扇炮喷射水雾实施灭火。通过实施本发明，能够自动定位瞄准火灾中心区域，指挥涡扇炮喷射，依据涡扇炮水流参数及火焰运动特征，实时调节灭火系统，实现火灾准确识别、精准瞄准、有效喷射及抑制火灾。 【EN】The invention provides an intelligent automatic aiming fire extinguishing system for a turbofan cannon, which comprises: the image type flame detector identifies a fire according to the acquired image information, generates flame space coordinates and alarm information when identifying the fire, and transmits the flame space coordinates and the alarm information to the image type sighting device; the image type sighting device is fixedly arranged on the turbofan cannon, the turbofan cannon is driven to move according to the received flame space coordinate and alarm information, the fire source information of a fire scene is collected and analyzed in real time, the turbofan cannon is enabled to aim at and position a fire source, a driving instruction is generated according to the aimed and positioned fire source information, and the driving instruction is sent to the turbofan cannon injection control device; and the turbofan cannon injection control device drives the turbofan cannon to inject water mist to extinguish fire according to the driving command. By implementing the invention, the central area of the fire can be automatically positioned and aimed, the turbofan cannon can be commanded to jet, the fire extinguishing system can be adjusted in real time according to the water flow parameters and the flame motion characteristics of the turbofan cannon, and the accurate identification, accurate aiming, effective jetting and fire suppression of the fire are realized.

摘要：【中文】一种移动物联网中的高效、安全的多用户多任务卸载方法，涉及移动物联网移动边缘计算领域，为了实现在时间的约束下将能耗的加权总和最小化，使任务卸载能耗较低。建立通信模型；资源分配策略，量化本地计算和卸载计算的开销；压缩策略，采用JPEG算法对卸载计算时传输的用户数据进行压缩以减少能源消耗；安全策略；优化策略；构建一个考虑将资源分配、压缩和安全性的集成模型，将该模型表述为整数非线性问题，该问题的目标是在时间约束下使能量的加权总和最小化，获得任务卸载决策和任务压缩决策的最优解。减轻移动物联网的网络资源限制，在计算任务卸载的同时，兼顾考虑资源分配，传输数据压缩和安全性，实现在时间的约束下能耗的加权总和最小化。 【EN】An efficient and safe multi-user multi-task unloading method in a mobile Internet of things relates to the field of mobile edge calculation of the mobile Internet of things, and aims to minimize the weighted sum of energy consumption under the constraint of time and enable the energy consumption of task unloading to be low. Establishing a communication model; a resource allocation strategy for quantifying the overhead of local computation and offload computation; a compression strategy, wherein a JPEG algorithm is adopted to compress user data transmitted during unloading calculation so as to reduce energy consumption; a security policy; optimizing the strategy; and constructing an integrated model considering resource allocation, compression and safety, and expressing the model as an integer nonlinear problem, wherein the aim of the problem is to minimize the weighted sum of energy under the time constraint and obtain the optimal solution of task unloading decision and task compression decision. The network resource limitation of the mobile Internet of things is reduced, the resource allocation, the transmission data compression and the safety are considered while the calculation task is unloaded, and the weighted sum minimization of the energy consumption under the time constraint is realized.