Weizhuo Wang

Full-field non-contact vibration measurements provide a rich dataset for analysing structural dynamics. However, implementing the identification algorithm directly using high-spatial resolution data can be computationally expensive in modal identification. To address this challenge, performing identification in a shape-preserving but lower-dimensional feature space is more feasible. The full-field mode shapes can then be reconstructed from the identified feature mode shapes. This paper discusses two approaches, namely data-dependent and data-independent, for constructing the feature spaces. The applications of these approaches to modal identification on a curved plate are studied, and their performance is compared. In a case study involving a curved plate, it was found that a spatial data compression ratio as low as 1% could be achieved without compromising the integrity of the shape features essential for a full-field modal. Furthermore, the paper explores the optimal point-wise sensor placement using the feature space. It presents an alternative, data-driven method for optimal sensor placement that eliminates the need for a normal model, which is typically required in conventional approaches. Combining a small number of point-wise sensors with the constructed feature space can accurately reconstruct the full-field response. This approach demonstrates a two-step structural health monitoring (SHM) preparation process: offline full-field identification of the structure and the recommended point-wise sensor placement for online long-term monitoring.

The increasing size of these blades of wind turbines emphasises the need for reliable monitoring and maintenance. This brief review explores the detection and analysis of damage in wind turbine blades. The study highlights various techniques, including acoustic emission analysis, strain signal monitoring, and vibration analysis, as effective approaches for damage detection. Vibration analysis, in particular, shows promise for fault identification by analysing changes in dynamic characteristics. Damage indices based on modal properties, such as natural frequencies, mode shapes, and curvature, are discussed.

Background: Bladder cancer (BCa) is a malignant tumor that usually forms cancer cells in the inner lining of the bladder. Hundreds of thousands of people worldwide have BCa diagnosed each year. The purpose of this study was to construct a prognostic model by differential expression of genes between muscular and non-muscular invasive BCa, and to investigate the prognosis of BCa patients.Methods: The data of BCa patients was sourced from the GEO and TCGA database. Single-cell sequencing data was obtained from three patients in the GSE135337 database, and microarray data for verification was obtained from GSE32894. Univariate, Lasso and multivariate cox regression analyses were performed to construct the prognostic model. The prognostic features, immune features and drug sensitivity of the model were further evaluated. Single-cell data and microarray data were used to validate the differential expression of model genes between muscle-invasive and non-muscle-invasive BCa. The invasion and migration of BCa cells were evaluated using the transwell assay and wound-healing assay. The cell proliferation capacity was simultaneously evaluated using Colony formation experiments. The protein expression of the specific gene was detected by western blot analysis.Results: We identified 183 differentially expressed muscle-invasive-related differential genes (MIRDGs), among which four were selected to establish a prognostic model. Based on our signature, patients in different groups displayed varying levels of immune infiltration and immunotherapy profiles. Single-cell sequencing data and microarray data confirmed that four invasion-related genes were expressed at higher levels in muscle-invasive BCa. Given the critical role of S100A9 in the progression of BCa, we performed further analysis. The results showed that protein expression of S100A9 was high in muscle-invasive BCa, and S100A9 knockdown could inhibit the proliferation, migration and invasion of BCa.Conclusion: These findings demonstrated that the prognostic model for BCa patients was reasonably accurate and valid, and it may prove to be of considerable value for the treatment and prognosis of BCa patients in the future. S100A9 may become a better prognostic marker and potential therapeutic target to further guide clinical treatment decisions.

Due to the large size of offshore wind turbine blades (OWTBs) and the corrosive nature of salt water, OWTs need to be safer and more reliable that their onshore counterparts. To ensure blade reliability, an accurate and computationally efficient structural dynamic model is an essential ingredient. If damage occurs to the structure, the intrinsic properties will change, e.g., stiffness reduction. Therefore, the blade’s dynamic characteristics will differ from those of the intact ones. Hence, symptoms of the damage are reflected in the dynamic characteristics that can be extracted from the damaged blade. Thus, damage identification in OWTBs has become a significant research focus. In this study, modal model characteristics were used for developing an effective damage detection method for WTBs. The technique was used to identify the performance of the blade’s sections and discover the warning signs of damage. The method was based on a vibration-based technique. It was adopted by investigating the influence of reduced blade element rigidity and its effect on the other blade elements. A computational structural dynamics model using Rayleigh beam theory was employed to investigate the behaviour of each blade section. The National Renewable Energy Laboratory (NREL) 5MW blade benchmark was used to demonstrate the behaviour of different blade elements. Compared to previous studies in the literature, where only the simple structures were used, the present study offers a more comprehensive method to identify damage and determine the performance of complicated WTB sections. This technique can be implemented to identify the damage’s existence, and for diagnosis and decision support. The element most sensitive to damage was element number 14, which is NACA_64_618.

A wind turbine is subjected to a regime of varying loads. For example, each rotor revolution causes a complete gravity stress reversal in the low-speed shaft, and there are varying stresses from the out-of-plane loading cycle due to fluctuating wind load. Consequently, wind turbine blade design is governed by fatigue rather than ultimate load considerations. Previous studies have adopted many different beam theories, using different techniques and codes, to model the National Renewable Energy Laboratory (NREL) 5 MW offshore wind turbine blade. There are differences, from study to study, in the free vibration results and the dynamic response. Thecontribution of this study is to apply the code written by the authors to the different beam theories used with the aim of comparing the different beam theories presented in the literature and that developed by the authors. This paper reports the investigation of the effects of deformation parameters on the dynamic characteristics of the NREL 5 MW offshore wind turbine blades predicted by the different beam theories. The investigation of free vibrations is a fundamental step in the analysis of structural dynamics, and this study compares different computational structural methods and investigates their effect on the predicted dynamic response. The modalcharacteristics of every model examined have been combined with strip theory to determine the dynamic response of the blade.

Due to their large and increasing size and the corrosive nature of salt water and high wind speeds, offshore wind turbines are required to be more robust, more rugged and more reliable than their onshore counterparts. The dynamic characteristics of the blade and its response to applied forces may be influenced dramatically by rotor rotational speed, which may even threaten the stability of the wind turbine. An accurate and computationally efficient structural dynamics model is essential for offshore wind turbines. A comprehensive model that takes the centrifugal stiffening effect into consideration could make rapid and accurate decisions with live data sensed from the structure. Moreover, this can enhance both the performance and reliability of wind turbines. When a rotating blade deflects in its plane of rotation or perpendicular to it, the centrifugal force exerts an inertia force that increases the natural frequencies and changes the mode shapes, leading to changes in the dynamic response of the blade. However, in the previous literature, studies of centrifugal stiffening are rarely found. This study investigates the influence of centrifugal stiffening on the free vibrations and dynamic response of offshore wind turbine blades. The National Renewable Energy Laboratory (NREL) 5 MW blade benchmark was considered to study the effect of angular speed in the flap-wise and edge-wise directions. The results demonstrate that the angular speed directly affects the modal features, which directly impacts the dynamic response. The results also show that the angular velocity effect in the flap-wise direction is more significant than its effect in the edge-wise direction.

The harsh weather conditions offshore wind turbine blades are working under have necessitated the need for a more effective approach for detecting their failures. Dynamic characteristics e.g., vibration, carry useful information related to blades structural health. Critical analysis of the blade’s free vibration represents one of the fundamental steps for assessing structural dynamics. When a rotating blade deflects, either in the plane of rotation or perpendicular to it, the centrifugal force exerts inertia force along the blade span, which increases the blade’s natural frequencies compared with the stationary ones. However, the influence of different blade parameters on the flap-wise vibrations is not very well understood. In this paper, the effects of such parameters on dynamic characteristics of National Renewable Energy Laboratory (NREL) 5-MW wind turbine blades are investigated using different beam theories. The examined models have been used to determine the natural frequencies and mode shapes of the National Renewable Energy Laboratory (NREL) 5-MW wind turbine. Results demonstrate that increasing angular velocity significantly impacts the natural frequencies and mode shapes. The rotary inertia is found to influence the free vibration responses of the studied blades. Moreover, increasing hub radius, pre-cone and pitch angles are found to have less influence on the natural frequencies. Mode shape comparisons were also carried out using MSF (modal scale factor) and MAC (modal assurance criteria). Compared to the other investigated methods, Bernoulli’s based algorithms are found to produce less accurate results.