FAILBACK FAULT ANALYSIS ON BSG 9 TYPE ELECTRIC WESEL AT PURWOKERTO STATION

Authors

  • Dezan Claudio Universitas Peradaban
  • Randi Adzin Murdiantoro Universitas Peradaban

DOI:

https://doi.org/10.58436/jeepa.v2i2.1289

Keywords:

Point Machine (wesel), Wesel Maintance, BSG 9, railway system

Abstract

Wesel (point machine) for the external equipment in the railway system that is used to move the line from a straight back position or vice versa. In the use of electric Wesel lines, there is a driving motor called a point machine. In addition, wesel also require periodic maintenance, self-laser treatment using a period of 2 weeks. Used is descriptive quantitative by presenting data on the evaluation of electric point of view in the field without any engineering or other treatment to obtain data. There is data on the percentage of the physical condition of note 53 with a yield percentage of 87.0% and a failure percentage of 8.7%. And the cumulative percentage of success is 95.7% and the cumulative percentage of failure is 8.7%. In table 5.5 there is data on the percentage of the physical condition of point 23 with a yield percentage of 87.0% and a failure percentage of 8.7%. And the cumulative percentage of success is 95.7% and the cumulative percentage of failure is 8.7%.

References

S. Mutmainnah, “PEMILIHAN MODA TRANSPORTASI KERETA API MENUJU PELABUHAN BAKAUHENI,” JICE (Journal Infrastructural Civ. Eng., vol. 1, no. 01, 2020, doi: 10.33365/jice.v1i01.854.

Y. F. Suryana, “Pemodelan sistem dinamik sistem manajemen keselamatan transportasi kereta api dalam menurunkan angka kecelakaan dan rasio kecelakaan kereta api PT. Kereta …,” SKRIPSI-2020, 2020.

T. N. Wijaya, “Transportasi Darat,” kompasiana, 2021. .

kementrian perhubungan, “Undang-undang No. 23 Tahun 2007 tentang Perkeretaapian,” 2007.

A. Dishub, “Seputar pengertian transportasi darat,” dsihub@bulelengkab, 2017. .

Rudy, H. Pamuraharjo, E. S. Arti, N. Praptiningsih, and R. Sadiatmi, “Sosialisasi Penggunaan Moda Transportasi Darat dan Udara Dimasa Pandemi COVID 19,” J. Pengabdi. Kpd. Masy. Langit Biru, vol. 2, 2021, doi: 10.54147/jpkm.v2i01.433.

F. B. Nugraha, “Sistem Pelayanan Dinas Perhubungan Dalam Meningkatkan Jaringan Transportasi Darat Di Kota Samarinda,” Ilmu Pemerintah., vol. 1, no. 4, 2013.

S. Suryadi, “Kinerja Dan Peramalan Pertumbuhan Angkutan Kereta Api Menggunakan Model Sarima,” War. Penelit. Perhub., vol. 26, no. 7, 2019, doi: 10.25104/warlit.v26i7.922.

S. W. Mudjanarko, D. Sulastri, and A. Wahyuni, Metode Importance Performance Analysis (IPA) untuk Mengukur Kinerja Prasarana Kereta Api Melalui Kepuasan Pelanggan. 2020.

B. Drajat, J. R. . Hosang, T. C. . Korah, D. Djajadi, and U. P, “KAJIAN RENCANA PEMBANGUNAN DOUBLE TRACK PADA EMPLASEMEN STASIUN CILAME (LINTAS CIKAMPEK – PADALARANG),” J. Penelit. Sekol. Tinggi Transp. Darat, vol. 8, no. 1, 2017, doi: 10.55511/jpsttd.v8i1.44.

dea Andriyawan, “Mengenal Wesel dan Fungsi Pentingnya Bagi Perjalanan Kereta Api,” bisnis.com, 2020. .

J. Sa, Y. Choi, Y. Chung, H. Y. Kim, D. Park, and S. Yoon, “Replacement condition detection of railway point machines using an electric current sensor,” Sensors (Switzerland), vol. 17, no. 2, 2017, doi: 10.3390/s17020263.

J. Lee, H. Choi, D. Park, Y. Chung, H. Y. Kim, and S. Yoon, “Fault detection and diagnosis of railway point machines by sound analysis,” Sensors (Switzerland), vol. 16, no. 4, 2016, doi: 10.3390/s16040549.

P. Thaha, T. Ophiyandri, B. Hidayat, and Meilizar, “SISTEM PENDUKUNG KEPUTUSAN CERDAS PADA MODEL RANTAI PASOK INDUSTRI KONSTRUKSI BERKELANJUTAN: STUDI LITERATURE,” J. REKAYASA, vol. 9, no. 2, 2020, doi: 10.37037/jrftsp.v9i2.42.

Direktorat Pengelolaan Prasarana Signalling, Perawatan Fasopka Terencana 2: Pemeriksaan dan Perawatan STE. Bandung: PT Kereta Api Indonesia (Persero) Kantor Pusat Bandung., 2017.

S. Abbasnejad and A. Mirabadi, “Predicting the failure of railway point machines by using Autoregressive Integrated Moving Average and Autoregressive-Kalman methods,” Proc. Inst. Mech. Eng. Part F J. Rail Rapid Transit, vol. 232, no. 6, 2018, doi: 10.1177/0954409717748790.

V. Babishin and S. Taghipour, “An algorithm for estimating the effect of maintenance on aggregated covariates with application to railway switch point machines,” Eksploat. i Niezawodn., vol. 21, no. 4, 2019, doi: 10.17531/ein.2019.4.11.

S. Zhang, H. Dong, U. Maschek, and H. Song, “A digital-twin-assisted fault diagnosis of railway point machine,” 2021, doi: 10.1109/DTPI52967.2021.9540118.

N. Iwasawa, S. Ryuo, K. Kawasaki, and A. Hada, “Development of system for supporting lock position adjustment work for electric point machine,” Q. Rep. RTRI (railw. Tech. Res. Institute), vol. 56, no. 3, 2015, doi: 10.2219/rtriqr.56.200.

SIEMENS, Bsg.antr.9 Point Machine with internal locking. Braunschweig, Germany: SIEMENS, 2005.

K. H. Narges, M. Ahmad, and G. M. Fereydoun, “A hybrid fault diagnosis scheme for railway point machines by motor current signal analysis,” Proc. Inst. Mech. Eng. Part F J. Rail Rapid Transit, vol. 236, no. 9, 2022, doi: 10.1177/09544097211061918.

E. Resendiz, J. M. Hart, and N. Ahuja, “Automated visual inspection of railroad tracks,” IEEE Trans. Intell. Transp. Syst., vol. 14, no. 2, 2013, doi: 10.1109/TITS.2012.2236555.

Z. Li, Z. Yin, T. Tang, and C. Gao, “Fault diagnosis of railway point machines using the locally connected autoencoder,” Appl. Sci., vol. 9, no. 23, 2019, doi: 10.3390/app9235139.

C. Bian, S. Yang, T. Huang, Q. Xu, J. Liu, and E. Zio, “Degradation state mining and identification for railway point machines,” Reliab. Eng. Syst. Saf., vol. 188, 2019, doi: 10.1016/j.ress.2019.03.044.

S. U. N. Yongkui, C. A. O. Yuan, X. I. E. Guo, and W. E. N. Tao, “Condition monitoring for railway point machines based on sound analysis and support vector machine,” Chinese J. Electron., vol. 29, no. 4, 2020, doi: 10.1049/cje.2020.06.007.

Published

2022-11-30

How to Cite

[1]
D. Claudio and R. Adzin Murdiantoro, “FAILBACK FAULT ANALYSIS ON BSG 9 TYPE ELECTRIC WESEL AT PURWOKERTO STATION”, jeepa, vol. 2, no. 2, pp. 101–107, Nov. 2022.