Davidyan Gabriel, Klein Renata, Bortman Jacob
PHM Laboratory, Department of Mechanical Engineering, Ben-Gurion University of the Negev, P.O. Box 653, 8410501, Beer-Sheva, Israel.
Sci Rep. 2024 Aug 19;14(1):19157. doi: 10.1038/s41598-024-70317-6.
The reliability and safety of locomotives is crucial for efficient train operation. Repeated turbocharger failures in Israel Railways locomotive fleet have raised serious safety concerns. An investigation into the failures revealed that the uncontrolled acceleration and overspeed transients of the turbocharger shaft occurred before the failure. Early detection of potential turbocharger failures by predicting overspeed conditions is critical to the safety and reliability of locomotives. In this study, an enhanced novel algorithm for estimating the Instantaneous Angular Speed (IAS) of the turbocharger and diesel engines is presented to overcome the challenges of transient operating conditions of diesel engines. Using adaptive dephasing, the algorithm effectively isolates critical asynchronous vibration components that are crucial for the early detection of turbocharger failures. This algorithm is suitable for non-stationary speeds and is applicable to any range of rotational speed and rate of change. The algorithm requires the input of the basic parameters of the system, while all other parameters that control the process are determined automatically. The algorithm was developed specifically for the special operating conditions of diesel engines and improves predictive maintenance and operational reliability. The method is robust as it correlates between several characteristic frequencies of the rotating parts of the system. The algorithm was verified and validated with simulated and experimental data.
机车的可靠性和安全性对于高效的列车运行至关重要。以色列铁路机车车队中涡轮增压器的反复故障引发了严重的安全担忧。对这些故障的调查表明，涡轮增压器轴的失控加速和超速瞬变在故障发生之前就已出现。通过预测超速情况来早期检测涡轮增压器的潜在故障对于机车的安全和可靠性至关重要。在本研究中，提出了一种用于估计涡轮增压器和柴油发动机瞬时角速度（IAS）的增强型新算法，以克服柴油发动机瞬态运行条件带来的挑战。该算法利用自适应去相位，有效地分离出对于早期检测涡轮增压器故障至关重要的关键异步振动分量。此算法适用于非恒定速度，并且适用于任何转速范围和变化率。该算法需要输入系统的基本参数，而所有其他控制过程的参数则自动确定。该算法是专门针对柴油发动机的特殊运行条件开发的，可改善预测性维护和运行可靠性。该方法具有鲁棒性，因为它关联了系统旋转部件的几个特征频率。该算法已通过模拟和实验数据进行了验证。
