Principle and Experiment of Electrostatic Circular Sensor on Turbojet Engine

2013 ◽  
Vol 401-403 ◽  
pp. 231-234
Author(s):  
Yu Fu ◽  
Hong Fu Zuo ◽  
Jing Cai ◽  
Jun Qiang Liu

The principle of gas path electrostatic circular sensor was discussed in this paper, in addition, a monitoring experiment with self-made circular sensor was carried out on turbojet engine, and electrostatic signals were collected successfully to verify the validity and feasibility of the sensor. According to the signals monitored over 131h, typical signals of 233-240 phases were analyzed. It was proved that the unusual particles were caused by carbon deposition from fuel spray nozzle. Therefore, under real-time monitoring of gas path changes with electrostatic circular sensor, early warning could be provided for initial fault condition as well as real-time reference for condition-based maintenance.

2012 ◽  
Vol 446-449 ◽  
pp. 3422-3427
Author(s):  
Wang Sheng Liu ◽  
Ming Zhao

Today there is an urgent need for effective monitoring whether for old buildings or new ones. While conventional early warning system for real-time monitoring is based on safety factor, this paper proposes a new reliability-based framework to monitor the safety of RC buildings probabilistically. The framework includes modeling resistance, predicting probability distribution of load effect, calculating reliability and setting reliability index threshold. The in-situ test data enables to update the resistance model through a Bayesian process. Meanwhile, the observed monitoring data predicts the probability distribution of load effect. FORM is used to calculate the reliability because the limit state function for real-time monitoring is linear and simple. This study shows that the reliability-based early warning system is of more scientific sense in quantifying the safety and may be applied to many engineering fields.


2015 ◽  
Vol 775 ◽  
pp. 264-267
Author(s):  
Xiao Dong Pan ◽  
Lei Zhao

Currently the settlement and deformation of factory building structure is monitored using total stations and other more conventional measuring instruments, it is difficult to reflect the health of the structure timely and accurately. In order to change the situation, we establish a set of system for real-time monitoring of deformation and safety warning. The system is formed of sensing layer, transport layer and application layer. Sensing layer is composed of static force level and biaxial inclinometer. The system can be used in dynamic real-time factory structure safety monitoring, also applied to other similar structural monitoring. This paper will study the system components and principle, early warning systems grading, calculation of real-time deformation of roof frame, laboratory test scheme and verification. Experiments showed that the system is suitable for the actual factory structure monitoring, while the choice of static force level and biaxial inclinometer of precision to meet the requirements.


2021 ◽  
Vol 13 (1) ◽  
pp. 1040-1052
Author(s):  
Dunlong Liu ◽  
Lei He ◽  
Qian Wu ◽  
Yan Gao ◽  
Bin Liu ◽  
...  

Abstract As geo-hazard monitoring data increases in category and size, conventional geo-hazard information management systems, without a unified integration framework and visualized data display, are unable to satisfy the urgent needs of geo-hazard information management. Representational State Transfer (REST), a resource-centered service architecture, abstracts data and services into resources for unified Uniform Resource Identifier access, enabling it to take full advantage of HTTP with great flexibility and scalability. Based on the REST service architecture, this paper constructs a 3D geo-hazard monitoring and early warning platform with sound service compatibility and scalability by integrating geographical information, real-time monitoring data, and early warning models into the 3D Digital Earth framework. The platform displays topography, stratum lithology, and relevant information, as well as real-time monitoring data in a 3D visual, and provides early warning services for geo-hazards through access to real-time early warning models. As a result, it is capable of providing comprehensive information management, monitoring, and early warning of multiple geo-hazards, aiding decision-making in disaster prevention and mitigation, and enhancing the information level of geo-hazard prevention and mitigation work.


2021 ◽  
Vol 3 (2) ◽  
Author(s):  
Hanifadinna Hanifadinna

Motor listrik merupakan salah satu instrumen yang memegang peranan penting dalam mengendalikan pergerakan mesin-mesin produksi di Pabrik Kelapa Sawit (PKS). Pada PKS Sungai Bengkal Jambi, proses penggantian atau rekondisi sebuah motor listrik dengan daya 60 HP akibat overheat (terbakar) memerlukan waktu lebih dari 1 (satu) bulan. Untuk menanggulangi hal tersebut, dirancang suatu sistem kontrol tertutup yang terdiri dari sensor, indikator, kontroler, dan aktuator. Sistem dibuat dengan menggunakan sensor IC LM35 untuk mendeteksi temperatur bagian dalam motor listrik. Informasi temperatur dari sensor tersebut diterima dan diolah oleh mikrokontroler yang diprogram untuk merespon perubahan temperatur dan memberikan feedback dengan melakukan trip pada motor listrik saat temperatur operasi melebihi set point yang telah ditentukan. Setelah loop selesai, sistem akan mengaktifkan kembali motor listrik saat temperatur operasi sudah kembali normal. Feedback yang diberikan juga digunakan sebagai sistem peringatan dini (early warning system dengan menambahkan lampu indikator dan sirine pada sistem. Selain itu, mikrokontroler diprogram untuk mengkonversi perubahan temperatur dari sensor untuk diolah menjadi keluaran data digital. Semua data tersimpan dalam data logger (perekam data) dan ditampilkan secara langsung pada sevent segment display. Untuk menguji akurasi sistem, telah dilakukan pengambilan data temperatur sebanyak 30 kali melalui data logger. dan didapatkan nilai standar deviasi sebesar 0,77% dengan rentang sebesar 0,71 °C. Perbedaan hasil pengukuran jika dibandingkan dengan Termolaser adalah sebesar 0,013%.


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