Hongsheng Su, Lixia Dong^*, Xiaoying Yu, Kai Liu

Energy Engineering, Vol.121, No.4, pp. 973-986, 2024, DOI:10.32604/ee.2023.043497

Abstract Time based maintenance (TBM) and condition based maintenance (CBM) are widely applied in many large wind farms to optimize the maintenance issues of wind turbine gearboxes, however, these maintenance strategies do not take into account environmental benefits during full life cycle such as carbon emissions issues. Hence, this article proposes a carbon emissions computing model for preventive maintenance activities of wind turbine gearboxes to solve the issue. Based on the change of the gearbox state during operation and the influence of external random factors on the gearbox state, a stochastic differential equation model (SDE) and corresponding carbon emission model are… More > Graphic Abstract

Wei Chen, Ming Li^*, Tingting Pei, Cunyu Sun, Huan Lei

Energy Engineering, Vol.121, No.1, pp. 125-144, 2024, DOI:10.32604/ee.2023.042812

Abstract At present, the operation and maintenance of photovoltaic power generation systems mainly comprise regular maintenance, breakdown maintenance, and condition-based maintenance, which is very likely to lead to over- or under-repair of equipment. Therefore, a preventive maintenance and replacement strategy for PV power generation systems based on reliability as a constraint is proposed. First, a hybrid failure function with a decreasing service age factor and an increasing failure rate factor is introduced to describe the deterioration of PV power generation equipment, and the equipment is replaced when its reliability drops to the replacement threshold in the last cycle. Then, based on… More >

Hang Cheng¹, Jiawen Fei¹, Jianfeng Wen^1,*, Shan-Tung Tu^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.27, No.2, pp. 1-1, 2023, DOI:10.32604/icces.2023.09663

Abstract Alkaline water electrolysis system for hydrogen production has the characteristics of complex structure, fault coupling and state nonlinearity, coupled with the restriction by many factors such as data acquisition methods and analysis methods. The operation status cannot be fully characterized through current monitoring information. In order to solve the problems in health status assessment in the operation of alkaline water electrolysis system, a digital twin-driven predictive maintenance method is put forward to achieve the real-time monitoring of operation status and prediction of remaining useful life. In the study, a multi-disciplinary simulation model of the alkaline electrolysis system and a physical… More >

Mingguang Yu^1,2, Xia Zhang^1,2,*

Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 1787-1806, 2023, DOI:10.32604/iasc.2023.038798

Abstract As cloud system architectures evolve continuously, the interactions among distributed components in various roles become increasingly complex. This complexity makes it difficult to detect anomalies in cloud systems. The system status can no longer be determined through individual key performance indicators (KPIs) but through joint judgments based on synergistic relationships among distributed components. Furthermore, anomalies in modern cloud systems are usually not sudden crashes but rather gradual, chronic, localized failures or quality degradations in a weakly available state. Therefore, accurately modeling cloud systems and mining the hidden system state is crucial. To address this challenge, we propose an anomaly detection… More >

Majida Kazmi^1,*, Maria Tabasum Shoaib^1,2, Arshad Aziz³, Hashim Raza Khan^1,2, Saad Ahmed Qazi^1,2

Computer Systems Science and Engineering, Vol.47, No.1, pp. 255-272, 2023, DOI:10.32604/csse.2023.038464

Abstract Predictive maintenance is a vital aspect of the industrial sector, and the use of Industrial Internet of Things (IIoT) sensor nodes is becoming increasingly popular for detecting motor faults and monitoring motor conditions. An integrated approach for acquiring, processing, and wirelessly transmitting a large amount of data in predictive maintenance applications remains a significant challenge. This study presents an IIoT-based sensor node for industrial motors. The sensor node is designed to acquire vibration data on the radial and axial axes of the motor and utilizes a hybrid approach for efficient data processing via edge and cloud platforms. The initial step… More >

Daniel Yabrudy Mercado^a,*, Juan Fajardo Cuadro^a, Bienvenido Sarria López^b, Camilo Cardona Agudelo^b

Frontiers in Heat and Mass Transfer, Vol.15, pp. 1-12, 2020, DOI:10.5098/hmt.15.25

Abstract This paper presents the efficiency-centered maintenance method to plan the maintenance intervention of the heat exchangers of a preheat train, taking into account the economic-energy improvement and maintenance cost. An appropriate cleaning schedule is needed to preserve the key performance parameters (KPPs) throughout the operation, if possible, nearest to the design values. The results of this work show that it is possible to schedule maintenance activities based on KPPs such as effectiveness and determine the time of execution and the type of maintenance that is most cost-efficient, without affecting and complementing the criteria for maintenance schedules based on reliability/risk. More >

Mingguang Yu^1,2, Xia Zhang^1,2,*

Computer Systems Science and Engineering, Vol.46, No.3, pp. 2975-2994, 2023, DOI:10.32604/csse.2023.037505

Abstract

In order to obtain information or discover knowledge from system logs, the first step is to perform log parsing, whereby unstructured raw logs can be transformed into a sequence of structured events. Although comprehensive studies on log parsing have been conducted in recent years, most assume that one event object corresponds to a single-line message. However, in a growing number of scenarios, one event object spans multiple lines in the log, for which parsing methods toward single-line events are not applicable. In order to address this problem, this paper proposes an automated log parsing method for multiline events (LPME). LPME… More >

Atif Ikram^1,2,*, Masita Abdul Jalil¹, Amir Bin Ngah¹, Adel Sulaiman³, Muhammad Akram³, Ahmad Salman Khan⁴

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5035-5048, 2023, DOI:10.32604/cmc.2023.034692

Abstract The successful execution and management of Offshore Software Maintenance Outsourcing (OSMO) can be very beneficial for OSMO vendors and the OSMO client. Although a lot of research on software outsourcing is going on, most of the existing literature on offshore outsourcing deals with the outsourcing of software development only. Several frameworks have been developed focusing on guiding software system managers concerning offshore software outsourcing. However, none of these studies delivered comprehensive guidelines for managing the whole process of OSMO. There is a considerable lack of research working on managing OSMO from a vendor’s perspective. Therefore, to find the best practices… More >

Atif Ikram^1,2,*, Masita Abdul Jalil¹, Amir Bin Ngah¹, Saqib Raza⁶, Ahmad Salman Khan³, Yasir Mahmood^3,4, Nazri Kama⁴, Azri Azmi⁴, Assad Alzayed⁵

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1871-1886, 2023, DOI:10.32604/cmc.2023.030818

Abstract Software maintenance is the process of fixing, modifying, and improving software deliverables after they are delivered to the client. Clients can benefit from offshore software maintenance outsourcing (OSMO) in different ways, including time savings, cost savings, and improving the software quality and value. One of the hardest challenges for the OSMO vendor is to choose a suitable project among several clients’ projects. The goal of the current study is to recommend a machine learning-based decision support system that OSMO vendors can utilize to forecast or assess the project of OSMO clients. The projects belong to OSMO vendors, having offices in… More >

Dongyan Shi^1,*, Hui Ma¹, Chunlong Ma^1,2

CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.3, pp. 1899-1923, 2023, DOI:10.32604/cmes.2022.022444

Abstract In multi-component systems, the components are dependent, rather than degenerating independently, leading to changes in maintenance schedules. In this situation, this study proposes a grouping dynamic maintenance strategy. Considering the structure of multi-component systems, the maintenance strategy is determined according to the importance of the components. The strategy can minimize the expected depreciation cost of the system and divide the system into optimal groups that meet economic requirements. First, multi-component models are grouped. Then, a failure probability model of multi-component systems is established. The maintenance parameters in each maintenance cycle are updated according to the failure probability of the components.… More > Graphic Abstract