Mechanical behaviour of reconstructed defected skull with custom PEEK implant and Titanium fixture plates under dynamic loading conditions using FEM.

Skull reconstruction using cranial implants is often required for repairing skull defects caused due to trauma, diseases, or malignancy to protect intracranial structures. For relieving Intracranial Pressure (ICP) surgeons restore cranial defects either using natural bones or fabricated custom cranial implants. With the increase in Traumatic Brain Injuries (TBI) and challenges faced by TBI patients to regain normalcy, it is imperative to analyse the mechanical behaviour of skull-implant assemblies under some Head Injury Criteria (HIC). Medical grade materials including Titanium Alloys (Ti-6Al-4V) and Polyether-ether-ketone (PEEK) are used by fabricating Patient-Specific Implants (PSI) manufactured using 3D imaging, modelling and printing techniques. 3D technologies are preferred over conventional manufacturing methods, as they enable fabrication of custom shapes, sizes and properties for these PSI. For an effective attachment of PSI with a defective skull, a stable joint and plate arrangement as fixture plates is necessary at their interface. These fixtures can have variable numbers, design shapes, materials and location arrangements. This paper presents the Finite Element Method/Analysis (FEM/FEA) study of PSI attached to a defected skull for reconstruction, with linear shaped fixture configuration, when subjected to an external dynamic loading at 5 m/s, strain rate of 10s-1 to 243s-1 and ICP of 15mm Hg from three sides of the skull faces. Three different materials as Neoprene (soft), Concrete (medium rigid) and E-Glass (highly rigid) have been used, in the form of a rectangular thin cuboidal wall structure, at an angle of 45° with the skull face. Four linear shaped fixture plates which were simplest to design, were used to attach the PSI-skull assembly, to ensure that weight of the PSI-fixation assembly on the patient remains minimal, overall assembly has symmetrical fixations and efforts required by a surgeon for fitment of these plates remain minimal. Placement of these fixture plates has been optimized to encompass the complete PSI-skull interface section, due to which the stresses within all the assembly components (PSI, fixture plate and skull) reduced by nearly 2.5 times than the initial design and remained within yielding limits, thereby, averting any failure under heavy external dynamic loading.

Development of low-cost non-contact structural health monitoring system for rotating machinery.

Condition monitoring systems are increasingly being employed in industrial applications to improve the availability of equipment to increase the overall equipment efficiency. Condition monitoring of gearboxes, a key element of rotating machines, ensures to continuously reduce and eliminate costs, unscheduled downtime and unexpected breakdowns. This study demonstrates a low-cost microcontroller-based non-contact data acquisition system for condition monitoring of rotating machinery. Experimental validation of the proposed system was carried out by performing examination tests on a gearbox test rig. A user-friendly graphical user interface was also developed which facilitates users to perform signal processing in both real-time and offline mode. The proposed system can perform most of the functions available in complex, stand-alone vibration analysers. The use of a general-purpose PC and standard programing language makes the system simple, economical and adaptable to a variety of problems. The tests show the developed system can perform properly as proposed.

Non-contact incipient fault diagnosis method of fixed-axis gearbox based on CEEMDAN.

Gearbox plays most essential role in the modern machinery for transmitting the required torque along with motion and contributes to wide range of applications. Any failure in gearbox components affects the productivity and efficiency of the system. Most machine breakdowns related to gears are a result of improper operating conditions and loading, hence lead to failure of the whole mechanism. Ensemble Empirical Mode Decomposition (EEMD) comprises advancement and valuable addition in Empirical Mode Decomposition (EMD) and has been widely used in fault detection of rotating machines. However, intrinsic mode functions (IMFs) produced by EEMD often carry the residual noise. Also, the produced IMFs are different in number due to addition of white Gaussian noise, which leads to final averaging problem. To alleviate these drawbacks, Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) was previously presented. This paper describes and presents the implementation of CEEMDAN for fault diagnosis of simulated local defects using sound signals in a fixed-axis gearbox. Statistical parameters are extracted from decomposed sound signals for different simulated faults. Results show the effectiveness of CEEMDAN over EEMD in order to obtain more accurate IMFs and fault severity.