A review on prognostic techniques for non-stationary and non-linear rotating systems

The field of prognostics has attracted significant interest from the research community in recent times. Prognostics enables the prediction of failures in machines resulting in benefits to plant operators such as shorter downtimes, higher operation reliability, reduced operations and maintenance cost, and more effective maintenance and logistics planning. Prognostic systems have been successfully deployed for the monitoring of relatively simple rotating machines. However, machines and associated systems today are increasingly complex. As such, there is an urgent need to develop prognostic techniques for such complex systems operating in the real world. This review paper focuses on prognostic techniques that can be applied to rotating machinery operating under non-linear and non-stationary conditions. The general concept of these techniques, the pros and cons of applying these methods, as well as their applications in the research field are discussed. Finally, the opportunities and challenges in implementing prognostic systems and developing effective techniques for monitoring machines operating under non-stationary and non-linear conditions are also discussed.

Improved ANN technique combined with Jaya algorithm for crack identification in plates using XIGA and experimental analysis

In this paper, the interplay and relationship between digital twin and Industrial Internet are discussed at first. The sensing/transmission network capability, which is one of the main characteristics of Industrial Internet, can be a carrier for providing digital twin with a means of data acquisition and transmission. Conversely, with the capability of high-fidelity virtual modeling and simulation computing/analysis, digital twin evolving from lifecycle management for a single product to application in production/manufacturing in the shop-floor/enterprise, can further greatly enhance the simulation computing and analysis of Industrial Internet. This paper proposes a digital twin enhanced Industrial Internet (DT-II) reference framework towards smart manufacturing. To further illustrate the reference framework, the implementation and operation mechanism of DT-II is discussed from three perspectives, including product lifecycle level, intra-enterprise level and inter-enterprise level. Finally, steam turbine is taken as an example to illustrate the application scenes from above three perspectives under the circumstance of DT-II. The differences between with and without DT-II for design and development of steam turbine are also presented.

DT-II:Digital twin enhanced Industrial Internet reference framework towards smart manufacturing

A general methodology for performance prediction of pumps-as-turbines using Artificial Neural Networks

The use of artificial neural network (ANN) for modeling the useful life of the failure assessment in blades of steam turbines

The corrosion behavior originated by sulfate-reducing bacteria (SRB) was studied in two regions of welded API X-70 steel pipeline. The studies were focused on base material (BM) and heat affected zone (HAZ), from the internal region of the pipe. SRB were extracted from oil and grown in a Postgate medium. Corrosion was evaluated at 60 °C for times between 5 and 64 days. Potentiodynamic polarization curves, obtained by electrochemical techniques, indicated surface activation at short times. Structural and morphological characterizations were carried out by scanning electron microscopy (SEM) and optical microscopy (OM). H2S concentration and pH were also measured. Results showed an important increase in the corrosion damage up to 20 days, influenced by the SRB activity, which lead to a maximum of H2S (pH minimum). It was found a localized corrosion attack in the HAZ in a higher quantity compared to BM; and the formation of a thin film on the steel surface, originated by corrosion products and bacterial activity.

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J. E. Flores

Papers

The use of artificial neural network (ANN) for modeling the useful life of the failure assessment in blades of steam turbines

Study of sulphate-reducing bacteria corrosion in the weld joint for API X-70 steel