Awad A H, Alsabaan Maazen, Ibrahem Mohamed I, Saraya M S, Elksasy M S M, Ali-Eldin Amr M T, Abdelsalam Mohamed M
Computers Engineering and Control Systems Department, Faculty of Engineering, Mansoura University, Mansoura, 35516, Egypt.
Department of Computer Engineering, College of Computer and Information Sciences, King Saud University, Riyadh, 11543, Saudi Arabia.
Heliyon. 2024 Nov 8;10(22):e40239. doi: 10.1016/j.heliyon.2024.e40239. eCollection 2024 Nov 30.
A cost-effective IoT-based real-time data acquisition and analysis hardware system was developed to enhance the performance of the mobile harbor cranes using a combination of a cost-effective quality control monitoring sensor dashboard (proximity sensors, angle position sensor, weight sensor, vibration sensor, and wind sensor), embedded microcontroller (Arduino), and embedded computer (Raspberry Pi). Hardware was operated using a specially developed novel Quality Control and Data Acquisition Multiprocessing software (QC-DAS). The QC-DAS can automatically collect and save real-time data of the sensors in a large-capacity SD card, monitor the state of health of the hardware, and transmit the real-time data of the sensors and the working state of the crane to an IoT server. The novelty of the QC-DAS design is that each function is encapsulated in a predefined module that is "immersed" in a message transmission medium. Modules interact by sending and receiving various signals through this medium. Modularity makes system design simpler, faster, and flexible. Thanks to modularity, users may incorporate their data processing modules when new sensors are added to match the system's needs. Thanks to modularity the DC-DAS can operate quality control hardware for any mobile cranes. There are several constraints in the quality control data acquisition system used by the Damietta Port Authority in Damietta, Egypt, SESCO TRANS company which cause the loading and unloading process to be slowed down. As a result, the SESCO TRANS company upgraded its quality control data acquisition system using the QC-DAS. The hardware was deployed for six months, during which the collected data was used to verify the crane's performance. The vibration produced by the slewing of the crane was monitored and compared with the bearing fault frequency limits, during the operation the wind speed was monitored and compared with the critical wind speed to stop the crane operation automatically, and the payloads data of the six months was collected and was used to calculate the working efficiency of the load and unload process of the crane. The results demonstrated that while maintenance costs were decreased, the crane load/unload procedure was improved. The SESCO TRANS company crane operators approved the developed approach and appreciated the achieved results.
开发了一种基于物联网的具有成本效益的实时数据采集与分析硬件系统，以提升移动式港口起重机的性能，该系统结合了具有成本效益的质量控制监测传感器仪表板（接近传感器、角度位置传感器、重量传感器、振动传感器和风传感器）、嵌入式微控制器（Arduino）以及嵌入式计算机（Raspberry Pi）。硬件通过专门开发的新型质量控制与数据采集多处理软件（QC-DAS）运行。QC-DAS能够自动收集传感器的实时数据并保存到大容量SD卡中，监测硬件的健康状态，并将传感器的实时数据以及起重机的工作状态传输到物联网服务器。QC-DAS设计的新颖之处在于，每个功能都封装在一个预定义模块中，该模块“融入”消息传输介质。模块通过该介质发送和接收各种信号进行交互。模块化使系统设计更简单、更快速且更灵活。得益于模块化，当添加新传感器以匹配系统需求时，用户可以纳入自己的数据处理模块。得益于模块化，DC-DAS可操作任何移动式起重机的质量控制硬件。埃及达米埃塔的达米埃塔港务局的SESO TRANS公司所使用的质量控制数据采集系统存在若干限制因素，导致装卸过程放缓。因此，SESO TRANS公司使用QC-DAS升级了其质量控制数据采集系统。该硬件部署了六个月，在此期间收集的数据用于验证起重机的性能。在起重机回转过程中产生的振动进行了监测，并与轴承故障频率限值进行比较，在运行过程中监测风速并与临界风速进行比较以自动停止起重机运行，收集了六个月的有效载荷数据并用于计算起重机装卸过程的工作效率。结果表明，在降低维护成本的同时，起重机的装卸程序得到了改善。SESO TRANS公司的起重机操作员认可了所开发的方法，并对取得的成果表示赞赏。
