At present, rotating machinery is widely used in all walks of life and has become the key equipment in many production processes. It is of great significance to strengthen the condition monitoring of rotating machinery, timely diagnose and eliminate faults to ensure the safe and efficient operation of rotating machinery and improve the economic benefits of enterprises. When the state of a rotating machine deteriorates, the thermal energy that is much more than its normal operation will be generated due to the increase in the friction between the components or other factors. Therefore, using the infrared thermal camera to collect the infrared thermal images of rotating machinery and judge the health status of rotating machinery by observing the temperature distribution in the thermal images is often more rapid and effective than other technologies. Nevertheless, after decades of development, the research achievements of infrared thermography (IRT) and its application in various industrial fields are numerous and complex, and there is a lack of systematic sorting and summary of the achievements in this field. Accordingly, this paper summarizes the development and application of IRT as a non-contact and non-invasive tool for equipment condition monitoring and fault diagnosis, and introduces the basic theory of IRT, image processing technology and fault diagnosis methods of rotating machinery in detail. Finally, the review is summarized and some future potential topics are proposed, which will make the subject easier for beginners and non-experts to understand.

The safe operation of diesel engines performs a vital function in industrial production and life. Because diesel engines often work in harsh environmental conditions, they are prone to failure. Therefore, this paper proposes a fault analysis method based on a combination of optimized variational mode decomposition (VMD) and improved convolutional neural networks (CNN) to address the necessary need for preventive maintenance of diesel engines. The authentic vibration sign is first decomposed by using the (VMD) algorithm, then the greatest range of decomposition layers is decided by using scattering entropy and the useful components are preferentially chosen for reconstruction. The continuous wavelet transform (CWT) records preprocessing method is then delivered to radically change the noise-reduced vibration sign into a time-frequency map, which is fed into the CNN for model coaching and extraction of fault features. Finally, fault classification is realized by support vector machine (SVM) with excellent classification performance. Through preset fault experiments on diesel engines, it is established that the technique proposed in this paper can successfully identify fault states, and the classification accuracy is higher than alternative methods.

Complex two-dimensional warranty equipment is usually composed of many multi-component systems, which include several key components. During the warranty period, conducting maintenance according to the preventive maintenance plan of each component will increase the warranty costs. Opportunistic maintenance is an effective approach to combine the preventive maintenance of each individual component, which can reduce the warranty cost and improve the system availability. This study explored the optimal opportunistic maintenance scheme of multi-component systems. Firstly, the failure rate model and reliability evaluation model of the multi-component system considering failure dependence were established. Secondly, the preventive maintenance plan of each individual component was determined, with the goal of obtaining the lowest warranty cost per unit time in the component life cycle. Thirdly, the preventive maintenance work of each individual component was combined, and the two-dimensional warranty cost model of the multi-component system was established according to the reliability threshold when performing opportunistic maintenance. In the experimental verification and result analysis, the genetic algorithm was used to find the optimal opportunistic maintenance scheme for the power transmission device. The comparative analysis results show that the opportunistic maintenance scheme reduced the warranty cost by 5.5% and improved the availability by 10%, which fully verified the effectiveness of the opportunistic maintenance strategy.

For complex and durable products such as automobiles and construction machinery, the quality and reliability characteristics of these products become more and more complex. However, in many cases, the technical ability of users is not enough to perfect the daily maintenance of the product. Warranty policy plays an increasingly important role between manufacturers and users. Aiming at the problem that the availability of the two-dimensional (2D) warranty product is difficult to meet the actual needs of users during the warranty period, this paper makes use of the accelerated failure time (AFT) model to construct the failure rate function of the product based on imperfect preventive maintenance (PM), establishes the 2D warranty availability model and gives an effective solution. On this basis, this paper obtains the optimal PM interval with the numerical algorithm and particle swarm optimization (PSO) taking the maximal availability of the 2D warranty product as the optimization objective and compares the results and speed of the two algorithms. Finally, the validity and accuracy of the model are verified by a numerical example which provides a scientific basis for the manufacturer to formulate the 2D warranty strategy.

Human society is entering the era of Industry 4.0; engineering systems are becoming more complex, which increases the difficulties of maintenance support work. Failure dependence exists widely in multi-component systems. In this work, a model of two-dimensional (2D) warranty decision making was constructed by using a failure-dependence analysis for multi-component systems and by considering the extended warranty cost and the system availability. The decision was to cut the warranty cost as much as possible for manufacturers, while the constraint condition was the minimum acceptable availability for the customer. The model combined preventive maintenance as well as corrective maintenance strategies. Under the condition that the multi-component system is replaced upon the expiration of the extended warranty (EW), the optimal 2D EW duration and preventive maintenance interval could be obtained through the model. In a case analysis, the optimal EW scheme for the gearbox of an electric multiple unit (EMU) system was obtained by using a grid search algorithm, a PSO algorithm, and a PSO–BAS algorithm. Through comparison, the PSO–BAS algorithm obtained a better scheme with lower warranty costs and higher system availability. A comparative analysis and a sensitivity analysis showed that the model provides a theoretical basis for manufacturers to optimize their 2D extended gearbox warranties.

This paper tries to introduce a new intelligent method for the early fault diagnosis of diesel engines. Firstly, infrared thermography (IRT) is introduced into diesel engine condition monitoring, then infrared images of diesel engines in four health states, such as normal condition,...