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渣缓冷场智能巡检系统的研制及应用

  • 作者:
  • 王润年|刘留|朱世彬|张阶青
  • 作者单位:
  • 河南中原黄金冶炼厂有限责任公司|安徽光智科技有限公司|安徽光智科技有限公司|安徽光智科技有限公司
  • 基金项目:

  • isnull
  • 详细信息:

  • 作者简介:
  • 王润年(1968—),男,高级工程师,从事工业自动化、智能化、信息化建设和企业数字化转型的一线工作;E-mail:575795001@qq.com
  • 通讯作者:
  • isnull
  • PDF下载

Development and application of intelligent inspection system for slag slow cooling fields

  • English Author:
  • Henan Zhongyuan Gold Smelter LLC.|Anhui Guangzhi Technology Co.,Ltd.|Anhui Guangzhi Technology Co.,Ltd.|Anhui Guangzhi Technology Co.,Ltd.
  • Unit:
  • 摘要
  • 在线预览
  • 参考文献

摘要:

为解决传统渣缓冷场巡检方式依赖人工、安全风险大、效率低、成本高、准确率低及环境恶劣等问题,研制并应用了渣缓冷场智能巡检系统。利用云台式红外热像仪获取渣包和冷却水喷淋设备的热成像图片和可见光图片,并通过红外热成像温度算法和AI智能识别,精准监测渣包温度变化和喷淋设备运行状态,自动识别异常情况并及时告警。系统应用后,以高稳定性和高精准度帮助工作人员及时处理了现场巡检的各项问题,保障了生产的安全和稳定,为金属冶炼行业提供了一种高效、智能的巡检解决方案,推进了行业的数字化转型和智能化升级。

关键词:

渣缓冷场;智能巡检;物联网;红外热成像;AI智能识别;数据分析;数字工厂

Abstract:

To address the issues associated with traditional inspection methods for slag slow cooling fields,which rely on manual operations and are characterized by high safety risks,low efficiency,high costs,low accuracy,and harsh environments,an intelligent inspection system for slag slow cooling fields has been developed and applied.This system uses a gimbal infrared thermal imager to capture thermal and visible light images of slag package and cooling water spray.By applying infrared thermal imaging temperature algorithms and AI-based intelligent recognition,the system accurately monitors temperature changes in slag package and the operational status of the spray,automatically identifying anomalies and issuing timely warnings.Since its implementation,the system has demonstrated high stability and precision,enabling staff to address various on-site inspection issues,thereby ensuring production safety and stability.This system offers an efficient and intelligent inspection solution for the metal smelting industry,promoting digital transformation and intelligent upgrades within the sector.

Keywords:

slag slow cooling field;intelligent inspection;Internet of Things;infrared thermal imaging;AI intelligent recognition;data analysis;digital factory