Yushan Ye¹, Tao Gao¹, Liankun Wang², Junjie Ma², Yingchun Cai², Heng Liu^2,*, Xiaoge Liu²

Structural Durability & Health Monitoring, Vol.19, No.1, pp. 145-166, 2025, DOI:10.32604/sdhm.2024.053756 - 15 November 2024

Abstract To investigate the evolution of load-bearing characteristics of pre-stressed beams throughout their service life and to provide a basis for accurately assessing the actual working state of damaged pre-stressed concrete T-beams, destructive tests were conducted on full-scale pre-stressed concrete beams. Based on the measurement and analysis of beam deflection, strain, and crack development under various loading levels during the research tests, combined with the verification coefficient indicators specified in the codes, the verification coefficients of bridges at different stages of damage can be examined. The results indicate that the T-beams experience complete, incomplete linear, and… More >

Chao Zhang¹, Shang-Xi Lai¹, Hua-Ping Wang^1,2,*

Structural Durability & Health Monitoring, Vol.19, No.1, pp. 25-54, 2025, DOI:10.32604/sdhm.2024.053662 - 15 November 2024

Abstract Modal parameters can accurately characterize the structural dynamic properties and assess the physical state of the structure. Therefore, it is particularly significant to identify the structural modal parameters according to the monitoring data information in the structural health monitoring (SHM) system, so as to provide a scientific basis for structural damage identification and dynamic model modification. In view of this, this paper reviews methods for identifying structural modal parameters under environmental excitation and briefly describes how to identify structural damages based on the derived modal parameters. The paper primarily introduces data-driven modal parameter recognition methods… More >

Sabrina Meddah^1,2,*, Sid Ahmed Tadjer³, Abdelhakim Idir⁴, Kong Fah Tee^5,6,*, Mohamed Zinelabidine Doghmane¹, Madjid Kidouche¹

Structural Durability & Health Monitoring, Vol.19, No.1, pp. 77-103, 2025, DOI:10.32604/sdhm.2024.053541 - 15 November 2024

Abstract Maintaining the integrity and longevity of structures is essential in many industries, such as aerospace, nuclear, and petroleum. To achieve the cost-effectiveness of large-scale systems in petroleum drilling, a strong emphasis on structural durability and monitoring is required. This study focuses on the mechanical vibrations that occur in rotary drilling systems, which have a substantial impact on the structural integrity of drilling equipment. The study specifically investigates axial, torsional, and lateral vibrations, which might lead to negative consequences such as bit-bounce, chaotic whirling, and high-frequency stick-slip. These events not only hinder the efficiency of drilling… More >

Huayi Zhang¹, Maobin Song², Lei Shen^1,*, Nizar Faisal Alkayem¹, Maosen Cao³

Structural Durability & Health Monitoring, Vol.19, No.1, pp. 55-75, 2025, DOI:10.32604/sdhm.2024.052869 - 15 November 2024

Abstract The concrete panel of earth-rock dams in cold regions tends to crack due to the combination effect of non-uniform foundation settlement, ice expansion loads, and freeze-thaw damage. In this work, simulations are designed to investigate the effects of freeze-thaw damage degrees on the fracture behavior caused by the partial detachment and ice expansion loads on concrete panels. Results show that the range of detached panels and freeze-thaw damage degree are the dominant factors that affect the overall load-bearing capacity of the panel and the failure cracking modes, whereas the panel slope is a secondary factor. More >

Chaozhi Cai^*, Tiexin Xu, Jianhua Ren, Yingfang Xue

Structural Durability & Health Monitoring, Vol.19, No.1, pp. 125-144, 2025, DOI:10.32604/sdhm.2024.052813 - 15 November 2024

Abstract A bearing fault diagnosis method based on the Markov transition field (MTF) and SEnet (SE)-IShufflenetV2 model is proposed in this paper due to the problems of complex working conditions, low fault diagnosis accuracy, and poor generalization of rolling bearing. Firstly, MTF is used to encode one-dimensional time series vibration signals and convert them into time-dependent and unique two-dimensional feature images. Then, the generated two-dimensional dataset is fed into the SE-IShufflenetV2 model for training to achieve fault feature extraction and classification. This paper selects the bearing fault datasets from Case Western Reserve University and Paderborn University… More >

Xin Mao^*, Hongsheng Su, Jingxiu Li

Energy Engineering, Vol.121, No.12, pp. 3929-3951, 2024, DOI:10.32604/ee.2024.057106 - 22 November 2024

Abstract The virtual synchronous generator (VSG) technology has been proposed to address the problem of system frequency and active power oscillation caused by grid-connected new energy power sources. However, the traditional voltage-current double-closed-loop control used in VSG has the disadvantages of poor disturbance immunity and insufficient dynamic response. In light of the issues above, a virtual synchronous generator voltage outer-loop control strategy based on improved linear autonomous disturbance rejection control (ILADRC) is put forth for consideration. Firstly, an improved first-order linear self-immunity control structure is established for the characteristics of the voltage outer loop; then, the… More >

Li Wang^1,*, Xiaoyong Wang²

Energy Engineering, Vol.121, No.12, pp. 3953-3979, 2024, DOI:10.32604/ee.2024.056705 - 22 November 2024

Abstract Plug-in Hybrid Electric Vehicles (PHEVs) represent an innovative breed of transportation, harnessing diverse power sources for enhanced performance. Energy management strategies (EMSs) that coordinate and control different energy sources is a critical component of PHEV control technology, directly impacting overall vehicle performance. This study proposes an improved deep reinforcement learning (DRL)-based EMS that optimizes real-time energy allocation and coordinates the operation of multiple power sources. Conventional DRL algorithms struggle to effectively explore all possible state-action combinations within high-dimensional state and action spaces. They often fail to strike an optimal balance between exploration and exploitation, and… More >

Zhi Li¹, Yufei Zhao², Yueming Ji², Hanwen Gu², Zaibin Jiao^2,*

Energy Engineering, Vol.121, No.12, pp. 3899-3927, 2024, DOI:10.32604/ee.2024.055899 - 22 November 2024

Abstract By integrating advanced digital technologies such as cloud computing and the Internet of Things in sensor measurement, information communication, and other fields, the digital DC distribution network can efficiently and reliably access Distributed Generator (DG) and Energy Storage Systems (ESS), exhibiting significant advantages in terms of controllability and meeting requirements of Plug-and-Play (PnP) operations. However, during device plug-in and -out processes, improper system parameters may lead to small-signal stability issues. Therefore, before executing PnP operations, conducting stability analysis and adjusting parameters swiftly is crucial. This study introduces a four-stage strategy for parameter optimization to enhance… More >

Daixuan Zhou¹, Yujin Liu¹, Xu Wang², Fuxing Wang¹, Yan Jia^2,*

Energy Engineering, Vol.121, No.12, pp. 3573-3616, 2024, DOI:10.32604/ee.2024.055853 - 22 November 2024

Abstract With the increasing proportion of renewable energy in China’s energy structure, among which photovoltaic power generation is also developing rapidly. As the photovoltaic (PV) power output is highly unstable and subject to a variety of factors, it brings great challenges to the stable operation and dispatch of the power grid. Therefore, accurate short-term PV power prediction is of great significance to ensure the safe grid connection of PV energy. Currently, the short-term prediction of PV power has received extensive attention and research, but the accuracy and precision of the prediction have to be further improved. More > Graphic Abstract

Zhaoqiang Wang¹, Fuyin Ni^2,*

Energy Engineering, Vol.121, No.12, pp. 3779-3799, 2024, DOI:10.32604/ee.2024.055535 - 22 November 2024

Abstract Under the partial shading conditions (PSC) of Photovoltaic (PV) modules in a PV hybrid system, the power output curve exhibits multiple peaks. This often causes traditional maximum power point tracking (MPPT) methods to fall into local optima and fail to find the global optimum. To address this issue, a composite MPPT algorithm is proposed. It combines the improved kepler optimization algorithm (IKOA) with the optimized variable-step perturb and observe (OIP&O). The update probabilities, planetary velocity and position step coefficients of IKOA are nonlinearly and adaptively optimized. This adaptation meets the varying needs of the initial… More > Graphic Abstract