Non-Invasive Inspections: A Review on Methods and Tools

Non-Invasive Inspection (NII) has become a fundamental tool in modern industrial maintenance strategies. Remote and online inspection features keep operators fully aware of the health of industrial assets whilst saving money, lives, production and the environment. This paper conducted crucial research to identify suitable sensing techniques for machine health diagnosis in an NII manner, mainly to detect machine shaft misalignment and gearbox tooth damage for different types of machines, even those installed in a hostile environment, using literature on several sensing tools and techniques. The researched tools are critically reviewed based on the published literature. However, in the absence of a formal definition of NII in the existing literature, we have categorised NII tools and methods into two distinct categories. Later, we describe the use of these tools as contact-based, such as vibration, alternative current (AC), voltage and flux analysis, and non-contact-based, such as laser, imaging, acoustic, thermographic and radar, under each category in detail. The unaddressed issues and challenges are discussed at the end of the paper. The conclusions suggest that one cannot single out an NII technique or method to perform health diagnostics for every machine efficiently. There are limitations with all of the reviewed tools and methods, but good results possible if the machine operational requirements and maintenance needs are considered. It has been noted that the sensors based on radar principles are particularly effective when monitoring assets, but further comprehensive research is required to explore the full potential of these sensors in the context of the NII of machine health. Hence it was identified that the radar sensing technique has excellent features, although it has not been comprehensively employed in machine health diagnosis.

Dynamic Characteristic Analysis of Spur Gear System Considering Tooth Contact State Caused by Shaft Misalignment

Shaft misalignment will change the gear contact state, and then leads to the variation of the internal stiffness excitation of the gear pair, and finally the dynamic characteristics of the gear system will be affected. However, the influence of the gear contact state change on stiffness is usually neglected in the traditional stiffness calculation model for misaligned gears, and the underlying influence mechanism of the gear contact state changes aroused by the shaft misalignment on the dynamic characteristics of gear system is still unclear. To address these shortcomings, traditional loaded tooth contact analysis (LTCA) model is improved with the influences of fillet foundation deformation taken into consideration. Combined with the improved LTCA model, a new mesh stiffness calculation model for misaligned gear considering the tooth contact state is proposed, and then the effects of the contact state changes aroused by the shaft misalignment on the mesh stiffness excitation are studied. Moreover, a dynamic model of misaligned gear system with 8 degree of freedom (DOF) is established, and the dynamic characteristics of the system are simulated and finally verified by experiment. The results show that the proposed model can be used to evaluate the dynamic characteristics of the misaligned gear system with the change of gear tooth contact state taken into consideration. This study provides a theoretical method for the evaluation and identification of the shaft misalignment error.

The Implementation of Laser Shaft Alignment System on Rotating Machines in the Bulla Field, Platform 6

Shaft misalignment is a common fault in rotating machines in the industry. Inadequate coupling alignment of rotating shafts often results in serious vibration problems and premature machine component failure. This article introduces the concept of using a laser shaft alignment system to improve equipment reliability, maintenance efficiency, and reduce rotating component wear. This paper explores the concept of implementation of laser shaft alignment system on rotating machines in the Bulla field, Platform 6. For this purpose, an appropriate tool has been selected for further implementation. As compared to a traditional mechanical method, the proposed electronic approach has more accurate results and optimize the performance gained via the previous techniques. Additionally, the application of the proposed system is user friendly and faster compared to the previous method. The measurement procedure is issued as per system manufacturer recommendation, and manufacturer video training will be submitted to appropriate maintenance staff. The novelty of the approach is to increase the reliability of rotating machines on Platform 6 in the Bulla field and develop Company maintenance processes by implementing a new laser measurement system.

EXPERIMENTAL STUDY OF THE PERFORMANCE OF "DRY" SEALS IN THE PRESENCE OF ROTOR VIBRATION

The article presents the results of an experimental study of "dry" seals in the presence of rotary vibration. The descrip-tion of the dynamic stand measurement system is given. An assessment of the influence of vibration loads on leakage through the seal and an analysis of the influence of radial displacement and shaft misalignment on the operation of a "dry" seal are carried out. The analysis of the cause of the vibration defect is presented. The permissible values of the vibration amplitudes of the rotor of the gas pumping unit have been determined.

Pengaruh Looseness Terhadap Vibrasi Peralatan Yang Mengalami Unbalance Dan Misalignment

Looseness occurs in almost all machines and can changes the vibration of the machine. In this paper, experiments were conducted by using two sets of rotor model to observe the effects of looseness on vibration values and patterns on the spectrum of unbalance and misalignment conditions. Rotor model 1 was used to simulate unbalance condition by adding mass to the disk, while rotor model 2 was used to simulate misalignment by changing the position of the bearing housings. Looseness condition was achieved by loosening the bearing housing bolts. The result of vibration observations in unbalance machine showed that looseness changed the overall value and peak values of vibration spectrum. While in machine which has shaft misalignment condition, looseness changed the vibration patterns on the spectrum.

Wind Turbine Generator Controller Signals Supervised Machine Learning for Shaft Misalignment Fault Detection: A Doubly Fed Induction Generator Practical Case Study

With a continued strong increase in wind generator applications, the condition monitoring of wind turbine systems has become ever more important in ensuring the availability and reduced cost of produced power. One of the key turbine conditions requiring constant monitoring is the generator shaft alignment, which if compromised and untreated can lead to catastrophic system failures. This study explores the possibility of employing supervised machine learning methods on the readily available generator controller loop signals to achieve detection of shaft misalignment condition. This could provide a highly noninvasive and low-cost solution for misalignment monitoring in comparison with the current misalignment monitoring field practice that relies on invasive and costly drivetrain vibration analysis. The study utilises signal datasets measured on a dedicated doubly fed induction generator test rig to demonstrate that high consistency and accuracy recognition of shaft angular misalignment can be achieved through the application of supervised machine learning on controller loop signals. The average recognition accuracy rate of up to 98.8% is shown to be attainable through analysis of a key feature subset of the stator flux-oriented controller signals in a range of operating speeds and loads.

A reduced-order method with PGD for the analysis of misaligned journal bearing

In recent years, machine component design has been a major concern for researchers. Emphasis has been placed especially on the analysis of bearing systems in order to avoid detrimental contact. The shaft misalignment is one of the most problems that affects directly the operating conditions of these components. In this context, the present study proposes a reduced-order method "Proper Generalized Decomposition" (PGD) using the separation technique through the alternating direction strategy to solve the modified Reynolds equation, taking into account the presence of misalignment in the shafting system. The solution shows the representation of two types of misalignment geometry, especially axial and twisting. A comparison of the results between the proposed approach and the classical method, through several benchmark examples, made it possible to highlight that the new scheme is more efficient, converges quickly and provides accurate solutions, with a very low CPU time expenditure.