Cunsong Wang

Nanjing Tech University | NJUT · Institute of Intelligent Manufacturing

The ability to preemptively identify potential failures in industrial parts is crucial for minimizing downtime, reducing maintenance costs and ensuring system reliability and safety. However, challenges such as data nonlinearity, temporal dependencies, and imbalanced datasets complicate accurate fault prediction. In this study, we propose a novel c...

The remaining useful life (RUL) prediction of rolling bearings is crucial for optimizing maintenance schedules, reducing downtime, and extending machinery lifespan. However, existing multi-channel feature fusion methods do not fully capture the correlations between channels and time points in multi-dimensional sensor data. To address the above prob...

Transceivers are critical components of phased array radar systems, and accurate fault diagnosis is essential for ensuring their reliability. However, many transceiver faults exhibit similar characteristics, making them difficult to identify. To address this challenge, a two-stage fault diagnosis method employing both rough and fine classifiers is...

With the advance of industrial systems, the online equipment fault diagnosis has encountered many challenges such as data drift and data imbalance under varying operating conditions, thus making stable and accurate diagnosis increasingly critical. Considering the above issues, a multi-scale attention mechanism diagnosis method with adaptive model t...

Control valves play a vital role in process production. In practical applications, control valves are prone to blockage and leakage faults. At the small control valve openings, the vibration signals exhibit the drawbacks of significant interference and weak fault characteristics, which causes subpar fault diagnosis performance. To address the issue...

Accurate parameter prediction is necessary for nonlinear, long-delayed water treatment process to raise water quality. To improve the prediction model precision and computational efficiency, a cascade broad learning system based on the sparrow search algorithm and slow feature analysis is proposed in this paper. First, the slow feature analysis met...

The Zebra Optimization Algorithm (ZOA) is a newly proposed heuristic algorithm, which simulates the foraging behavior and defense strategy of zebras in nature. Like other optimization algorithms, ZOA also has some limitations. In this paper, an improved Zebra Optimization Algorithm (IZOA) was proposed. An adaptive oscillation weight is used to repl...

This paper investigates the distributed fault‐tolerant tracking control (FTTC) problem for multiple unmanned aerial vehicles (UAVs) in the presence of state constraints, input quantization and actuator failures. The unified barrier function (UBF) is first developed to convert the original constrained system model into an unconstrained one, which ac...

This paper investigates a class of nonholonomic chained systems with integral input-to-state stable (iISS) inverse dynamics subject to unknown virtual control directions and parameter uncertainty included in drift terms. First, the system is divided into two interconnected subsystems according to the system’s structure. Second, one controller is de...

There are a large number of bearings in aircraft engines that are subjected to extreme operating conditions, such as high temperature, high speed, and heavy load, and their fatigue, wear, and other failure problems seriously affect the reliability of the engine. The complex and variable bearing operating conditions can lead to differences in the di...

This paper focuses on the anomaly detection for ionospheric total electron content (TEC) before earthquakes. In this paper, a novel unsupervised approach is proposed. First, interval-based method is employed to granulate the TEC series. Justifiable granularity principle is utilized to construct interval information granules (IGs) for representing TE...

Effective fault diagnosis of critical components is essential to ensure the safe and reliable operation of the entire system. This paper deals with the fault diagnosis of transmitter/receiver module, which is a critical component in the phased array radar system, by proposing a novel deep belief network learning method. A sparse deep belief network...

Rotating machinery often works under complex and variable working conditions; the vibration signals that are widely used for the health monitoring of rotating machinery show extremely complicated dynamic frequency characteristics. It is unlikely that a few certain frequency components are used as the representative fault signatures for all working...

System-level remaining useful life (RUL) estimation is difficult due to multiple degrading components, external disturbances and variable operational conditions. A similarity-based approach is more suitable for system-level RUL estimation. However, for practical applications, how to capture effective degradation features from raw data, how to fuse...

Prognostics and health management (PHM) with failure prognosis and maintenance decision-making as the core is an advanced technology to improve the safety, reliability, and operational economy of engineering systems. However, studies of failure prognosis and maintenance decision-making have been conducted separately over the past years. Key challen...

Practical degradation prognostics for aero engines is difficult owing to the degradation features covered by the continuous switching among various operational conditions. A novel degradation prognostics strategy for aero engines under various operating conditions is proposed in this study. Specifically, to remove the influence of different operati...

Maintenance is fundamental to ensure the safety, reliability and availability of engineering systems, and predictive maintenance is the leading one in maintenance technology. This paper aims to develop a novel data-driven predictive maintenance strategy that can make appropriate maintenance decisions for repairable complex engineering systems. The...

Remaining useful life (RUL) prediction is an advanced technique for system maintenance scheduling. Most of existing RUL prediction methods are only interested in the precision of RUL estimation; the adverse impact of over-estimated RUL on maintenance scheduling is not of concern. In this work, an RUL estimation method with risk-averse adaptation is...

Degradation prognostics of aero-engine are a well-recognized challenging issue. Data-driven prognostic techniques have been receiving attention because they rely on neither expert knowledge nor mathematic model of the system. But they are highly dependent on the quantity and quality of degradation data. To solve the problems caused by unlabeled, un...

Remaining useful life (RUL) prediction is essential to ensure safety and reliability of engineering systems. To achieve better prediction performance, causalities among the physical quantities are considered by applying Bayesian Network (BN) to RUL prediction. For this purpose, several improvements on BN modeling are made in this paper, to handle t...

Diagnostic health monitoring without prior knowledge is still a hard problem in the prognostic and health management field. A multivariate diagnostic health monitoring strategy is proposed based on telemetry data for in-orbit spacecrafts with component degradation. Compared with the existing univariate or direct diagnostic health monitoring methods...

Aircraft engines are with highly complex structures and a large number of performance parameters monitored in their degradation processes. These bring huge challenges to the existing remaining useful life (RUL) prediction methods, and the prediction accuracy is still lower than the hoped in industry. In this paper, a novel method based on the simil...

On-line remaining-useful-life (RUL) prognosis is still a problem for satellite Lithium-ion (Li-ion) batteries. Meanwhile, capacity, widely used as a health indicator of a battery (HI), is inconvenient or even impossible to measure. Aiming at practical and precise prediction of the RUL of satellite Li-ion batteries, a dynamic long short-term memory...

For multi-aircraft formations attacking cooperatively on targets, a new optimal path search algorithm and time cooperative control method is proposed. Firstly, the Voronoi diagram is used to establish route model available for flight, according to the position of the threat points in the battlefield. Then, an optimal route search algorithm combined...

Traditional potential field algorithm is a common method of path planning for aircraft; however, it is not applicable to cases like goal non-reach with obstacle nearby (GNRON), local minimum, no evaluation mechanism, etc. A hierarchical potential field algorithm of path planning for aircraft is proposed to deal with the above problems. In this algo...

The Virtual Reality Platform's (VRP) secondary development always using other's programming software, the software with interface management and response ability is week about matrix transformation and scientific computing. In order to solve this problem, Three-Dimensional Virtual Reality Platform (TDVRP) was built, based on Multiple Software Platf...

In order to solve the obstacle avoidance problem when the Multi-Agent formation get through the area full of obstacles, improved the traditional Artificial Potential Field method, add the vectorial information to the agent’s model, presented the Three-Dimensional Vectorial Artificial Potential Field method (TDVAPF). Firstly, improved the model of a...