Search Results (178)

Planetary gear systems offer compact design and high-power density, but they are strongly influenced by transmission error (TE), which originates from geometric deviations and elastic deflections. This study presents a dynamic model that integrates elastic compliance, mesh stiffness, damping, and error excitation to evaluate coupled gear responses. Numerical results show that planet–ring contacts undergo larger forces and deflections than sun–planet meshes. Time–frequency analysis with continuous wavelet transform (CWT) reveals nonstationary vibration patterns, while gear tooth flank inspection confirms torque bias and micro-pitting. The findings connect modeling predictions with observed wear, offering insights for planetary gear diagnostics and design. Full article

Permanent magnet synchronous motors (PMSMs) have been widely used in new-energy vehicles and industrial servo systems. However, demagnetization faults (DMFs) can lead to severe issues, including torque ripple and magnetic field distortion. This paper proposes an intelligent diagnostic approach for DMFs based on stator tooth flux (STF). A mathematical model of STF is formulated, and the magnetic flux change is measured using multiple sets of anti-series-connected detection coils (DCs). By combining finite element simulation with signal processing technology, we establish a comprehensive diagnostic system covering fault feature extraction, fault location identification, and severity assessment is established. The proposed method employs wavelet transform (WT) to extract time-frequency features of voltage signals and combines it with a convolutional neural network (CNN) to form the WT-CNN intelligent diagnosis model. Based on the extracted voltage signal features, the method achieves intelligent identification and visual localization of DMFs. Simulation results show that the proposed method achieves an accuracy above 80% for fault location identification (defined as sample-level multi-label classification accuracy across 12 PMs) and above 85% for demagnetization severity estimation (defined as classification accuracy across 9 severity degrees from 10% to 90%). These results provide an effective technical foundation for motor condition monitoring and fault early warning in simulation environments. Full article

Background/Objectives: Vision-language models (VLMs) such as GPT (Generative Pre-Trained Transformer) have shown potential for medical image interpretation; however, challenges remain in generating reliable radiological findings in clinical practice, as exemplified by dental pathologies. This study proposes a Self-correction Loop with Structured Output (SLSO) framework as an integrated processing methodology to enhance the accuracy and reliability of AI-generated findings for jaw cysts in dental panoramic radiographs. Methods: Dental panoramic radiographs with jaw cysts were used to implement a 10-step integrated processing framework incorporating image analysis, structured data generation, tooth number extraction, consistency checking, and iterative regeneration. The framework functioned as an external validation mechanism for GPT outputs. Performance was compared against the conventional Chain-of-Thought (CoT) method across seven evaluation items: transparency, internal structure, borders, root resorption, tooth displacement, relationships with other structures, and tooth number. Results: The SLSO framework improved output accuracy for multiple items compared to the CoT method, with the most notable improvements observed in tooth number identification, tooth displacement detection, and root resorption assessment. In successful cases, consistently structured outputs were achieved after up to five regenerations. The framework enforced explicit negative finding descriptions and suppressed hallucinations, although accurate identification of extensive lesions spanning multiple teeth remained limited. Conclusions: This investigation established the feasibility of the proposed integrated processing methodology and provided a foundation for future validation studies with larger, more diverse datasets. Full article

Plunge shaving is a widely used finishing process for high-precision gears due to its high productivity and cost-effectiveness. However, manufacturing the plunge-shaving cutter itself remains challenging, particularly for modified tooth profiles. Because the theoretical cutter flank exhibits a hyperboloid-like geometry in the lead direction, conventional disk-wheel grinding tends to introduce systematic twist-like topographic bias. To overcome this limitation, a comprehensive mathematical framework is developed for the generative grinding of plunge-shaving cutters using an involute-helicoid grinding worm. Based on envelope theory and homogeneous coordinate transformations, the theoretical cutter surface is first derived, followed by the establishment of a complete kinematic grinding model. A linear least-squares optimization algorithm is then formulated to determine the optimal center-distance compensation parameter for minimizing the normal deviation between the generated and theoretical surfaces. Numerical simulations demonstrate that the proposed method significantly suppresses twist-related topographic errors. In a benchmark moderate-helix case, the maximum residual deviation is controlled to approximately 2 µm. For a more demanding large-helix configuration, a two-level optimization strategy—combining machine-setting compensation and grinding-worm helix-angle adjustment—reduces the peak deviation from about 5.5 µm to 4.7 µm, corresponding to an improvement of approximately 15%. This confirms that worm-geometry tuning provides an additional, effective degree of freedom for high-helix cutter applications. Full article

Cracks in planetary gearbox casings generate additional vibration responses, which may be used for monitoring structural degradations. This paper provides a signal processing framework to effectively track casing crack-related features in planetary gearboxes using the carrier synchronous signal average (C-SSA). The proposed algorithm is based on processing the hunting-tooth synchronous signal average (H-SSA) to extract the C-SSA which contains the cyclic interaction between the gear loadings and the corresponding casing response. The root mean square (RMS) of the C-SSA signal can then serve as a health condition indicator (CI) to track crack propagation. Further enhancement can be achieved by applying the Hilbert transform (HT) on the C-SSA using the full bandwidth to derive squared envelope signal, which enhances the trending capability. To remove cyclic temperature influences observed in the trends, singular spectrum analysis technique (SSAT) has been used to ensure that the trend reflects the changes purely due to the damage progression. Experiments using three casing-mounted sensors show good capability to track crack progression. Tests under 100%, 125%, and 150% load levels show consistent performance across these operating conditions, with better results seen at higher loads. The results demonstrate that C-SSA and its squared envelope signal effectively enhance the sensitivity and reliability of vibration-based casing crack detection, providing a practical tool for long-term structural health monitoring of planetary gearboxes. Full article

This study compared the mechanical and thermal properties of new and retrieved multizone rhodium-coated superelastic nickel-titanium (NiTi) archwires across anterior and posterior segments. Using three-point bending tests, Scanning Electron Microscopy with Energy-Dispersive Spectroscopy analysis, and multiple linear regression, it was found that the posterior segments of new wires generated forces 0.50–0.80 N higher than those of anterior or retrieved specimens. While anterior segments exhibited higher austenite start and finish temperatures (by 6.15 °C and 5.21 °C, respectively) compared to posterior segments, these temperatures remained below average intraoral levels, and clinical retrieval did not significantly alter transformation temperatures. However, retrieved wires produced lower overall forces, likely due to surface cracking identified through microscopy. Ultimately, while posterior segments consistently generate higher forces than anterior segments, the observed reduction in force over time and the risk of surface degradation led to the conclusion that these archwires are not recommended for tooth movements exceeding 2 mm. Full article

During the assembly process of the bolter miner cutting drum, the varying installation postures of the cutting picks result in unique and non-repetitive irregular gaps between the tooth seat bottom surface and the cylindrical rotating surface. Such gaps are constrained by dual-surface geometry and lack batch statistical regularity, making traditional methods such as shim filling, selective assembly, or on-site welding inadequate for achieving high-precision fitting and reliable process implementation. To address this challenge, this paper proposes an automatic design method for compensation bodies based on computer-aided design, realizing a shift from experience dependence to algorithm-driven design. This method transforms the complex dual-surface gap filling problem into a serialized geometric modeling process: first, smooth extrapolation of the tooth seat bottom surface is achieved through a point sequence prediction model based on minimum mean square error; second, surface projection is simplified to boundary curve projection, enabling precise mapping onto the cylindrical surface and generating trimming surfaces; finally, a ruled surface is constructed to integrate the extended surface with the trimming surfaces, automatically generating a compensation body fully adapted to the gap morphology. Case verification demonstrates that this method can automatically and accurately generate compensation bodies that meet dual-surface fitting requirements, significantly improving geometric adaptability and weldability. This research not only resolves a critical technical bottleneck in the assembly of bolter miner cutting drums but also provides a universal and scalable computational framework for the intelligent compensation design of non-repetitive dual-surface gaps in complex equipment. Full article

Pediatric odontogenic tumors are rare but are frequently overlooked because they often mimic simple cysts on routine radiographic examinations. The radiographic appearance on panoramic imaging and cone-beam computed tomography (CBCT) frequently does not correlate with the true biological nature of these lesions. On CBCT, classic odontogenic tumors often demonstrate mixed radiolucent–radiopaque patterns with ill-defined borders, internal calcifications, septations, or other structural features. The diagnostic challenge arises when an odontogenic tumor mimics a unilateral, well-defined radiolucent area or a cystic lesion with clear borders and no associated tooth displacement, erosion, root resorption, or cortical bone dehiscence. Panoramic radiography has inherent diagnostic limitations but remains widely used for routine dental screening. CBCT provides enhanced three-dimensional assessment and improves diagnostic accuracy in the evaluation of jaw lesions. A marked increase in dental follicle diameter necessitates differentiation between cystic transformation, inflammatory processes, and other odontogenic pathologies. Cortical swelling and bone asymmetry warrant careful evaluation. In this context, an atypical cyst-like lesion detected on routine panoramic radiography prompted a needle aspiration biopsy, which revealed a dry tap and suggested a solid lesion. This prompted CBCT evaluation. Two juvenile cases are presented in which clinical findings, panoramic radiography, and CBCT provided discordant diagnostic impressions of cystic-appearing lesions with well-defined borders and bone expansion. These cases illustrate a diagnostic pathway in which imaging demonstrates a cyst-like appearance with benign radiological features, fine-needle aspiration biopsy reveals the absence of cystic fluid, and histopathology confirms that radiology alone cannot reliably distinguish true cysts from solid odontogenic tumors in pediatric patients. Full article

Background: Dental disorders, such as cavities, periodontal disease, and periapical infections, remain major global health issues, often resulting in pain, tooth loss, and systemic complications if not identified early. Traditional diagnostic methods rely heavily on visual inspection and manual interpretation of panoramic X-ray images by dental professionals, making them time-consuming, subjective, and less accessible in resource-limited settings. Objectives: Accurate and timely diagnosis is vital for effective treatment and prevention of disease progression, reducing healthcare costs and patient discomfort. Recent advances in deep learning (DL) have demonstrated remarkable potential to automate and improve the precision of dental diagnostics by objectively analyzing panoramic, periapical, and bitewing X-rays. Methods: In this research, a hybrid feature-fusion framework is proposed. It integrates handcrafted Histogram of Oriented Gradients (HOG) features with deep representations from DenseNet-201 and the Shifted Window (Swin) Transformer models. Sequential dependencies among the fused features were learned utilizing the Long Short-Term Memory (LSTM) classifier. The framework was evaluated on the Dental Radiography Analysis and Diagnosis (DRAD) dataset following preprocessing steps, including resizing, normalization, Contrast Limited Adaptive Histogram Equalization (CLAHE) enhancement, and image cropping. Results: The proposed LSTM-based hybrid model achieved 96.47% accuracy, 91.76% specificity, 94.92% precision, 91.76% recall, and 93.14% F1-score. Conclusions: The proposed framework offers flexibility, interpretability, and strong empirical performance, making it suitable for various image-based recognition applications and serving as a reproducible framework for future research on hybrid feature fusion and sequence-based classification. Full article

Recent breakthroughs in materials science have driven transformative advancements in restorative dentistry. Advanced dental materials, such as bioactive materials, nanocomposites, and fibre-reinforced composites, are attracting attention. Bioactive materials, such as calcium silicate-based cements and bioactive glass, represent a paradigm shift by interacting with biological tissues to stimulate regeneration. They promote hydroxyapatite formation, accelerating mineralisation in hard and soft tissues, and are pivotal tools in minimally invasive procedures due to their functions of structural support and biological interaction. Nanomaterials, especially nanocomposites with embedded nanoparticles, effectively address polymerisation shrinkage and wear in traditional composites. With just 1.5% shrinkage, a flexural strength over 150 MPa, and 44–60% higher wear resistance than conventional composites, they offer significant improvements. Nanocomposites also provide enamel-like translucency and a bond strength of 27–38 MPa to dentin, ensuring excellent aesthetics and durability—making them ideal for direct restorations. Fibre-reinforced composites with glass or polymer fibres balance aesthetics with strength and are increasingly used in restorations. Their high fracture resistance, which closely approaches that of a natural tooth, enables clinicians to preserve more healthy teeth during restoration, in line with the principles of modern conservative dentistry. Overall, bioactive materials enhance tissue repair, nanocomposites optimise form and function, and fibre-reinforced composites deliver strength without compromising aesthetics. As these materials transition from research to clinical practice, they promise longer-lasting treatments, fewer complications, and higher patient satisfaction. This narrative review aims to explore three types of advanced dental materials and their role in improving clinical outcomes. Full article

Background: Adult patients with a thin buccal cortical plate and fragile periodontal phenotype are at high risk of dehiscence, fenestration and recession during transverse orthodontic expansion. Conventional mechanics often create a cervical compression-dominant environment that exceeds the adaptive capacity of the periodontal ligament (PDL)–bone complex. Objectives: This study proposes an integrative mechanobiological model in which a skeletal-anchorage-assisted loading protocol (Bone Protection System, BPS) transforms expansion into a tension-dominant regime that favours buccal phenotype preservation. Methods: Patient-specific finite element models were used to compare conventional expansion with a BPS-modified force system. Regional PDL stress patterns and crown/apex displacement vectors were analysed to distinguish tipping-dominant from translation-dominated mechanics. A pilot CBCT proof-of-concept (n = 1 thin-phenotype adult) with voxel-based registration quantified changes in maxillary and mandibular alveolar ridge width and buccal cortical plate thickness before and after BPS-assisted expansion. The mechanical findings were integrated with current evidence on compression- versus tension-driven inflammatory and osteogenic pathways in the PDL and cortical bone. Results: FEM demonstrated that conventional expansion concentrates high cervical compressive stress along the buccal PDL and cortical surface, accompanied by bending-like crown–root divergence. In contrast, the BPS protocol redirected forces to create a buccal tensile-favourable region and a more parallel crown–apex displacement pattern, indicative of translation-dominated movement. In the proof-of-concept (n = 1) CBCT case, BPS-assisted expansion was associated with preservation or increase of buccal ridge dimensions without radiographic signs of cortical breakdown. Conclusions: A tension-dominant orthodontic loading environment generated by a skeletal-anchorage-assisted force system may support buccal cortical preservation and vestibular phenotype reinforcement in thin-phenotype patients. The proposed mechanobiological model links these imaging and FEM findings to known molecular pathways of inflammation, angiogenesis and osteogenesis. It suggests a functional biomaterial-based strategy for widening the biological envelope of safe tooth movement. Full article

Matrix metallopeptidases (MMPs) are enzymes that, in balance with their inhibitors, play a vital role in extracellular matrix remodelling, particularly during orthodontic tooth movement (OTM). Despite growing interest, significant research is still required to fully comprehend the mechanisms and signalling pathways involved in periodontal ligament remodelling and OTM, particularly those mediated by MMPs. This review explores recent in vitro and in vivo evidence on how specific MMPs—namely, MMP-1, -2, -3, -8, -9, -12, -13, and -14—respond to compressive and tensile forces, regulate collagen degradation, and influence periodontal ligament fibroblast and osteoblast behaviour, ultimately shaping tissue resorption and formation. We also summarize the roles of periodontal ligament cells, hypoxia, the neurovascular and immune systems, and well-known molecules—including receptor activator of nuclear factor kappa β, receptor activator of nuclear factor kappa β ligand, osteoprotegerin, macrophage colony-stimulating factor, tumour necrosis factor α, transforming growth factor, and interleukins—in orchestrating these responses. Finally, we address the clinical relevance of these pathways, highlighting the potential for therapeutic strategies targeting MMPs activity. Overall, this review underscores the pivotal contribution of MMPs to extracellular matrix turnover and tissue adaptation during OTM and suggests that modulating the MMPs/tissue inhibitors of matrix metallopeptidase (TIMPs) balance may enhance orthodontic outcomes. Full article

High-quality hole machining of Ti-6Al-4V is critical for precision aerospace components but remains challenging due to the alloy’s poor machinability. In this study, the influence of cutting parameters on milling force, burr formation and the hole quality of Ti-6Al-4V was investigated. The mechanical properties and microstructure of the milled holes were analyzed. The research results show that milling depth is the primary factor governing variations in milling force and burr formation. The minimum milling force of 3.61 N is achieved at a milling depth of 60 μm, a feed per tooth of 2 μm/z and a cutting speed of 31 m/min. Compared to pre-optimization parameters, the milling force is decreased by 91.74%. Correspondingly, entrance burr width and hole-axis deviation were substantially reduced, indicating marked improvement in hole quality and geometrical accuracy. Microstructural observations show no deleterious phase transformations or excessive work-hardening under the optimized regime. The results deliver quantitative guidelines for parameter selection and tool application in micro-hole milling of Ti-6Al-4V and provide a foundation for further process modelling and optimization for aerospace manufacturing. Full article

Bone remodelling is a physiological process influenced by mechanical stimuli such as those generated during orthodontic treatment. Biochemical markers allow the phases of remodelling to be identified, its progression to be assessed, alterations to be detected and scaffold-based tissue regeneration to be evaluated. This study reviews the main markers involved in bone formation and resorption, highlighting their clinical relevance. A literature search was conducted in biomedical databases, selecting studies that analysed crevicular gingival fluid samples in areas of tension and compression. The markers were classified according to their function and location, and their baseline values, temporal variations and methods of analysis were compiled. Among the markers of bone formation, Osteoprotegerin (OPG), Transforming Growth factor β1 (TGF-β1) and Interleukin 27 (IL-27) stand out; while resorption markers include Receptor Activator of Nuclear Factor appa β Ligand (RANKL), Tumour Necrosis Factor (TNF-α) and Interleukin 1β (IL-1β). The results show different expression patterns depending on the type of force applied and the timing of the follow-up, allowing molecular profiles associated with each phase of remodelling to be established. This characterisation improves our understanding of tooth movement and provides a basis for the development of more precise scaffolds and functional biomaterials in orthodontics. Full article

In manufacturing face-hobbing hypoid gears, the coupling between tooth flank errors and installation errors has a significant impact on dynamic meshing behavior, yet quantitative models for their synergistic effects remain scarce. This study elucidates the combined effects of three-dimensional (3D) installation errors and real tooth flank deviations on transmission error. First, a geometric model of the real tooth flank, incorporating midpoint pitch deviation, is established based on theoretical flank equations and coordinate transformations. Then, a finite element model integrating 3D installation errors is developed. Finally, the combined effects of installation errors and real tooth flanks on meshing performance are analyzed. Results reveal a dual role of installation errors: when compensating for midpoint pitch deviation, the peak-to-peak transmission error (PPTE) decreases by 3.78%, while the contact pattern length and area increase. Under certain conditions, despite a 26.28% increase in PPTE, the contact pattern length grows by 2.29%, accompanied by a notable reduction in maximum contact stress on the tooth flanks. Full article