Configuration lifecycle management maturity model
- Configuration lifecycle management (CLM) describes a configuration model that covers all product life cycles.
Configuration lifecycle management (CLM) encompasses all configuration models across a product’s life cycle. CLM covers manufacturers’ needs for complex configurable products, which tend to require more seamless integration of all ...
Intelligent fault diagnosis method of planetary gearboxes based on convolution neural network and discrete wavelet transform
- The paper focus on feature extraction and classification using deep learning method from time-frequency domain.
Considering the planetary gearbox vibration signals show highly non-stationary and non-linear behavior because of wind turbines (WTs) often working under time-varying running conditions, we propose an effective and reliable method ...
An image processing system for char combustion reactivity characterisation
- We proposed a system for automatic char detection and classification in images.
Coal is the most used fuel source to generate electricity by pulverised coal combustion. During this process, volatile compounds are liberated giving rise to the formation of a variety of char particles. Char particles morphology can ...
Optimizing the network energy of cloud assisted internet of things by using the adaptive neural learning approach in wireless sensor networks
- A reinforcement-based learning technique, Adaptive Q-Learning (AQL) for improving network performance in CIoT is proposed.
Cloud-assisted internet of things (CIoT) is backboned by the wireless sensor network (WSN) architecture. A sensor network is an autonomous self-resource constraint collection of internet of things (IoT) sensor nodes. The nodes ...
Interoperability assessment: A systematic literature review
- Presents a systematic literature review of Interoperability Assessment Approaches.
The development of Interoperability is a necessity for organisations to achieve business goals and capture new market opportunities. Indeed, interoperability allows enterprises to exchange information and use it to seize their shared ...
Deep convolutional neural network-based in-process tool condition monitoring in abrasive belt grinding
- This paper proposes a novel sound-based abrasive belt wear monitoring method using the DCNN.
Abrasive belt grinding has attracted attention in recent years in both industry and academia due to the rapid development of abrasive belts. In-process tool condition monitoring in abrasive belt grinding is difficult due to the large ...
Bearing performance degradation assessment using long short-term memory recurrent network
- Degradation simulation model is constructed for feature verification and selection.
Bearing is commonly used in rotating machinery, and it is significant to monitor bearing running states to ensure machine safety. Performance degradation assessment is an important work in bearing condition-based maintenance (CBM) and ...
Combining translation-invariant wavelet frames and convolutional neural network for intelligent tool wear state identification
- Nearly translation-invariant wavelet frames are constructed with centralized multiresolution analyzing ability.
On-machine monitoring of tool wear in machining processes has found its importance to reduce equipment downtime and reduce tooling costs. As the tool wears out gradually, the contact state of the cutting edge and the workpiece changes, ...
Generative adversarial networks for data augmentation in machine fault diagnosis
- Generative adversarial network is able to generate realistic samples.
- Model ...
Generative adversarial networks (GANs) have been proved to be able to produce artificial data that are alike the real data, and have been successfully applied to various image generation tasks as a useful tool for data augmentation. In ...
Automated bearing fault diagnosis scheme using 2D representation of wavelet packet transform and deep convolutional neural network
- This paper proposes an adaptive deep convolutional neural network (ADCNN).
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Bearings are one of the most crucial components in many industrial machines. Effective bearing fault diagnosis is essential for normal and safe machine operation. Existing fault diagnosis methods are mostly limited to manual feature ...
