Sensors Solutions and Predictive Maintenance Tools to Decrease Kiln and Conveyor Belt Downtime

被引：2

作者：

Bartknecht, Felix ^{[1
]}

Siegfried, Moritz ^{[2
]}

Weber, Harald ^{[3
]}

机构：

[1] SICK AG, Erwin Sick Str 1, D-79183 Waldkirch, Germany

[2] SICK AG, Gisela Sick Str 1, D-79276 Reute, Germany

[3] SICK AG, Product Unit Ranging LiDAR, Gisela Sick Str 1, D-79276 Reute, Germany

来源：

2019 IEEE-IAS/PCA CEMENT INDUSTRY CONFERENCE (IAS/PCA) | 2019年

关键词：

conveyor belt; cyclone blockage; kiln back end; kiln inlet; LiDAR; predictive maintenance; preventive maintenance; process gas analyzer; sensors; volume flow measurement;

D O I：

10.1109/citcon.2019.8729094

中图分类号：

TU [建筑科学];

学科分类号：

0813 ;

摘要：

This paper will discuss the importance and benefits of sensors and their applications for predictive maintenance in today's modern cement plants. Increased attention is to be paid in particular to technologies used for process gas monitoring at the kiln inlet area as well as modern LiDAR sensors applied on conveyor belts. In combination with analyzing parameters of condition in different machineries of a cement plant, added value can be created leading e.g. to increased production rates and higher capital efficiency.

引用

页数：9

共 3 条

[1] Conveyor tools ease maintenance, prevent belt slippage
Min Eng (Littleton Colo), 7 (34):
[2] Integrated decision making for predictive maintenance of belt conveyor systems
Liu, Xiangwei
He, Daijie
Lodewijks, Gabriel
Pang, Yusong
Mei, Jie
RELIABILITY ENGINEERING & SYSTEM SAFETY, 2019, 188 : 347 - 351
[3] Machine learning-based digital twin of a conveyor belt for predictive maintenance
Pulcini, Valerio
Modoni, Gianfranco
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2024, 133 (11-12): : 6095 - 6110

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