Search Results (7)

Background: Pertrochanteric fractures of the proximal femur present a common challenge for traumatologists, with intramedullary nailing emerging as the preferred treatment. Complication rates are around 20%, including screw jamming, refractures, implant breakage, or medial migration, with cut-out being the most common. A tip–apex distance (TAD) of >25 mm and incorrect cephalic screw position are predictive factors for cut-out. This study assesses outcomes using the Elos intramedullary nail, based on the experience of the Department of Orthopedics and Traumatology at Ospedale Maggiore in Bologna. Methods: We conducted a retrospective cohort study of 344 patients treated with the Elos intramedullary nail for pertrochanteric femoral fractures from 1 January 2017 to 31 December 2022. The Elos^®-Intrauma nail was implanted using the standard technique. Initial X-rays classified fractures according to the AO-OTA classification, and postoperative X-rays confirmed the cephalic screw’s placement per Cleveland’s regions. Patients were divided into two groups: optimal cephalic screw position (positions 5-8-9) and other positions. We evaluated TAD, calcar-referred TAD (CalTAD), and postoperative reduction quality using Chang’s criteria. The incidence of cut-out and other complications were assessed in connection with these measurements. Results: Among the 344 patients, 227 (65.9%) had the screw in positions 5-8-9, while 117 (34.1%) had it in other positions. The median TAD was 19.47 ± 6.26 mm (range 3.96–46.6), with TAD ≤ 25 mm in 265 patients (77%). The median CalTAD was 22.37 ± 5.65 mm (range 8.75–45.3), with CalTAD ≤ 25 mm in 231 patients (67.1%). According to Chang’s criteria, 8 cases (2.3%) had poor reduction, 139 cases (40.4%) had acceptable reduction, and 197 cases (57.3%) had excellent reduction. Cut-out occurred in four cases (1.19%). Multivariate analysis revealed only poor reduction and TAD > 25 mm as independent predictors of cut-out (p < 0.05), while cephalic screw position, CalTAD, and fracture type did not impact cut-out incidence. Conclusions: This study indicates that optimal TAD and quality of reduction are crucial for minimizing cut-out risks. The Elos intramedullary nail shows favorable outcomes with a low cut-out incidence when these parameters are met. Emphasis should be placed on achieving a TAD ≤ 25 mm and excellent reduction quality to reduce complications. Full article

The purpose of this work is a comparative analysis of the workpiece shape, and parameters of the stress-strain state during deformation on two radial-shear rolling mills with different roll configurations to determine the most suitable scheme for obtaining a screw reinforcement profile. During the FEM simulation of the radial-shear rolling process in the DEFORM program, a comparison of the workpiece shape change after rolling, equivalent strain, damage index, and Lode–Nadai index was carried out. Steel 10 (analogue of AISI 1010) was chosen as material workpiece. The analysis of the obtained data revealed that the most rational choice for the implementation of the reinforcement profile production process is the radial-shear rolling mill RSR 10-30. Subsequent modeling of the combined process of radial-shear rolling and twisting in a screw matrix showed that when using rolls of RSR 10-30 mill, the screw profile of the workpiece is formed successfully, whereas using rolls of the SVP-08 mill, the formation of a screw profile is impossible due to jamming due to an irregular cross-section shape. A laboratory experiment confirmed the possibility of forming a screw reinforcement profile at RSR 10-30 mill, and an assessment of the geometric parameters of the final workpiece showed full compliance with the dimensions of the profiles obtained during modeling and experiment. Full article

Efficient processing of end-of-life lithium-ion batteries in electric vehicles is an important and pressing challenge in a circular economy. Regardless of whether the processing strategy is recycling, repurposing, or remanufacturing, the first processing step will usually involve disassembly. As battery disassembly is a dangerous task, efforts have been made to robotise it. In this paper, a robotic disassembly platform using four industrial robots is proposed to automate the non-destructive disassembly of a plug-in hybrid electric vehicle battery pack into modules. This work was conducted as a case study to demonstrate the concept of the autonomous disassembly of an electric vehicle battery pack. A two-step object localisation method based on visual information is used to overcome positional uncertainties from different sources and is validated by experiments. Also, the unscrewing system is highlighted, and its functions, such as handling untightened fasteners, loosening jammed screws, and changing the nutrunner adapters with square drives, are detailed. Furthermore, the time required for each operation is compared with that taken by human operators. Finally, the limitations of the platform are reported, and future research directions are suggested. Full article

The work deals with the development of deterministic model-based condition-monitoring algorithms for an electromechanical flight control actuator with fault-tolerant architecture, in which two permanent magnets synchronous motors are coupled with differential ball screws in speed-summing paradigm, so that the system can operate even after a motor fault, an inverter fault or a mechanical jamming. To demonstrate the potential applicability of the system for safety-critical aerospace applications, the failure transients related to major fault modes have to be characterised and analysed. By focusing the attention to jamming faults, a detailed nonlinear model of the actuator is developed from physical first principles and experimentally validated in both time and frequency domains for normal condition and with different types of jamming. The validated model is then used to design the condition-monitoring algorithms and to characterize the system failure transient, by simulating mechanical blocks in different locations of the transmission. The operability after the fault, obtained via fault-tolerant control strategy and position regulator reconfiguration, is also verified, by highlighting and discussing possible enhancements and criticalities. Full article

The aerospace industry develops prognosis and health management algorithms to ensure better safety on board, particularly for in-flight controls where jamming is dreaded. For that, vibration signals are monitored to predict future defect occurrences. However, time series are not labeled according to severity level, and the user can only assess the system health from the data mining procedure. To that extent, a clustering algorithm using a deep neural network core is developed. Time series are encoded into pictures to be fed into an artificially trained neural network: U-NET. From the segmented output, one-dimensional information on cluster frontiers is extracted and filtered without any parameter selection. Then, a kernel density estimation finally transforms the signal into an empirical density. Ultimately, a Gaussian mixture model extracts the latter independent components. The method empowered us to reveal different degrees of severity faults in the studied data, with their respective likelihoods, without prior knowledge. It was then compared to state-of-the-art machine learning algorithms. However, internal clustering results evaluation for time series is an open question. As the state-of-the-art indexes were not producing relevant results, a new indicator was built to fulfill this task. We applied the whole method to an actuator consisting of an induction machine linked to a ball screw. This study lays the groundwork for future training of diagnosis and prognosis structures in the health management framework. Full article

Mechanical fault diagnosis of high-voltage circuit breakers (HVCBs) based on vibration signal analysis is one of the most significant issues in improving the reliability and reducing the outage cost for power systems. The limitation of training samples and types of machine faults in HVCBs causes the existing mechanical fault diagnostic methods to recognize new types of machine faults easily without training samples as either a normal condition or a wrong fault type. A new mechanical fault diagnosis method for HVCBs based on variational mode decomposition (VMD) and multi-layer classifier (MLC) is proposed to improve the accuracy of fault diagnosis. First, HVCB vibration signals during operation are measured using an acceleration sensor. Second, a VMD algorithm is used to decompose the vibration signals into several intrinsic mode functions (IMFs). The IMF matrix is divided into submatrices to compute the local singular values (LSV). The maximum singular values of each submatrix are selected as the feature vectors for fault diagnosis. Finally, a MLC composed of two one-class support vector machines (OCSVMs) and a support vector machine (SVM) is constructed to identify the fault type. Two layers of independent OCSVM are adopted to distinguish normal or fault conditions with known or unknown fault types, respectively. On this basis, SVM recognizes the specific fault type. Real diagnostic experiments are conducted with a real SF₆ HVCB with normal and fault states. Three different faults (i.e., jam fault of the iron core, looseness of the base screw, and poor lubrication of the connecting lever) are simulated in a field experiment on a real HVCB to test the feasibility of the proposed method. Results show that the classification accuracy of the new method is superior to other traditional methods. Full article

Removal of locking plates in many ways poses novel challenges compared to conventional plates. None of the techniques described for the removal of locking plates are adequate for all situations. We report our experience of 27 patients from whom a total of 33 locking plates were removed. We also describe a novel technique for the removal of locking plates which in our experience could be used in most of these patients because it is appropriate for all situations and, from a technical point of view, is easy to use. Our new technique consists of removing the problematic locking screw by cutting the plate on both sides of the screw hole and using the screw head-plate hole unit for removal. We analyzed all these patients for the location of the plate, number of locking screws, time of implant removal since the initial surgery, reason for removal of the plate, nature of the difficulties encountered during surgery, and any perioperative complications. A total of 43 (17.34%) screws were difficult to remove. Twenty screws were found to be stripped, 15 were jammed and 8 were broken. Fourteen of the 20 stripped screws and all 15 jammed screws were removed using our technique. We found this technique of locking plate removal to be very versatile and useful in most of the cases in which removal was difficult. At the same time, it also causes less damage to the bone compared to other techniques. Full article