Crack detection in rotating shafts using wavelet analysis, Shannon entropy and multi-class SVM

Incipient fault diagnosis is essential to detect potential abnormalities and failures in industrial processes which contributes to the implementation of fault-tolerant operations for minimizing performance degradation. In this paper, an innovative method named Self-adaptive Entropy Wavelet (SEW) is proposed to detect incipient transverse crack faults on rotating shafts. Continuous Wavelet Transform (CWT) is applied to obtain optimized wavelet function using impulse modelling and decompose a signal into multi-scale wavelet coefficients. Dominant features are then extracted from those vectors using Shannon entropy, which can be used to discriminate fault information in different conditions of shafts. Support Vector Machine (SVM) is carried out to classify fault categories which identifies the severity of crack faults. After that, the effectiveness of this proposed approach is investigated in testing phrase by checking the consistency between testing samples with obtained model, the result of which has proved that this proposed approach can be effectively adopted for fault diagnosis of the occurrence of incipient crack failures on shafts in rotating machinery

Audio steganography with AES for real-time covert Voice over Internet Protocol communications

As a popular real-time service on the Internet, Voice over Internet Protocol (VoIP) communication attracts more and more attention from the researchers in the information security field. In this study, we proposed a VoIP steganographic algorithm with variable embedding capacities, incorporating AES and key distribution, to realize a real-time covert VoIP communication. The covert communication system was implemented by embedding a secret message encrypted with symmetric cryptography AES-128 into audio signals encoded by PCM codec. At the beginning of each VoIP call, a symmetric session key (SK) was assigned to the receiver with a Session Initiation Protocol-based authentication method. The secret message was encrypted and then embedded into audio packets with different embedding algorithms before sending them, so as to meet the real-time requirements of VoIP communications. For each audio packet, the embedding capacity was calculated according to the specific embedding algorithm used. The encryption and embedding processes were almost synchronized. The time cost of encryption was so short that it could be ignored. As a result of AES-based steganography, observers could not detect the hidden message using simple statistical analysis. At the receiving end, the corresponding algorithm along with the SK was employed to retrieve the original secret message from the audio signals. Performance evaluation with state-of-the-art network equipment and security tests conducted using the Mann-Whitney-Wilcoxon method indicated that the proposed steganographic algorithm is secure, effective, and robust

Cloud-based data-intensive framework towards fault diagnosis in large-scale petrochemical plants

Industrial Wireless Sensor Networks (IWSNs) are expected to offer promising monitoring solutions to meet the demands of monitoring applications for fault diagnosis in large-scale petrochemical plants, however, involves heterogeneity and Big Data problems due to large amounts of sensor data with high volume and velocity. Cloud Computing is an outstanding approach which provides a flexible platform to support the addressing of such heterogeneous and data-intensive problems with massive computing, storage, and data-based services. In this paper, we propose a Cloud-based Data-intensive Framework (CDF) for on-line equipment fault diagnosis system that facilitates the integration and processing of mass sensor data generated from Industrial Sensing Ecosystem (ISE). ISE enables data collection of interest with topic-specific industrial monitoring systems. Moreover, this approach contributes the establishment of on-line fault diagnosis monitoring system with sensor streaming computing and storage paradigms based on Hadoop as a key to the complex problems. Finally, we present a practical illustration referred to this framework serving equipment fault diagnosis systems with the ISE

A review of research on acoustic detection of heat exchanger tube

Leakage in heat exchanger tubes can result in unreliable products and dangerous situations, which could cause great economic losses. Along with fast development of modern acoustic detection technology, using acoustic signals to detect leakage in heat exchange tube has been gradually accepted and considered with great potential by both industrial and research societies. In order to further advance the development of acoustic signal detection technology and investigate better methods for leakage detection in heat exchange tube, in this paper, firstly, we conduct a short overview of the theory of acoustic signal detection on heat exchanger tube, which had already been continuously developed for a few decades by researchers worldwide. Thereafter, we further expound the advantages and limitations of acoustic signal detection technology on heat exchanger tube in four aspects: 1) principles of acoustic signal detection, 2) characteristics of sound wave propagation in heat exchanger tube, 3) methods of leakage detection, and 4) leakage localization in heat exchanger tube

Efficient dynamic service maintenance for edge services

The emergence of many new computing applications, such as Internet of Vehicles (IoV) and smart homes, has been made possible by the large pool of cloud resources and services. However, the cloud computing paradigm is unable to meet the requirements of delay-sensitive business applications, such as low latency, mobility support, and location awareness. In this context, Mobile Edge Computing (MEC) is introduced to improve the quality of experience (QoE) by bringing cloud resources and services closer to the user by leveraging available resources in the edge networks. However, the performance of MEC is dynamic in nature due to its location awareness, mobility and proximity. As a result, an effective mechanism is needed for providing efficient dynamic service maintenance for edge services. In this paper, we propose applying the Skyline Graph Model and employing the Directed Acyclic Graph theory to store and update mobile edge services. Specifically, the Skyline Graph (SG) algorithm is designed to solve the insertion, deletion, updating and searching of mobile edge services to achieve efficient maintenance for edge services. Comprehensive experiments are conducted on both real-world web services and simulated datasets to evaluate the effectiveness and efficiency of our approaches. The results show that our algorithms can achieve significantly better performance and robustness than the baseline algorithm

IEEE Access special section editorial: collaboration for Internet of Things

The network of objects/things embedded with electronics, software, sensors, and network connectivity, Internet of Things (IoT), creates many exciting applications (e.g., smart grids, smart homes, and smart cities) by enabling objects/things to collect and exchange data so that they can be sensed and controlled. To fulfill IoT, one essential step is to connect various objects/things (e.g., mobile phones, cars, and buildings) so that they can "talk" to each other (i.e., collect and exchange data). However, substantial case studies show that simply connecting them without further collaboration among the objects/things when "talking" to each other leads to unnecessary energy consumption, uncertain security, unstable performance, etc., for IoT. Therefore, collaboration for IoT is very important. Specifically, there are a lot of critical issues to consider in terms of how to achieve robust collaboration among the objects/things for IoT. For instance, how to conduct collaboration among the objects/things so that more energy-efficient communication can be achieved for IoT? How to conduct collaboration among the objects/things so that computing with higher performance can be achieved for IoT? How to improve the security of IoT with collaboration among the objects/things? How to enhance the Quality of Service of IoT with collaboration among the objects/things? How to minimize the overhead costs when objects/things are collaborating in IoT

A review of artificial intelligence technologies in mineral identification : classification and visualization

Artificial intelligence is a branch of computer science that attempts to understand the essence of intelligence and produce a new intelligent machine capable of responding in a manner similar to human intelligence. Research in this area includes robotics, language recognition, image identification, natural language processing, and expert systems. In recent years, the availability of large datasets, the development of effective algorithms, and access to powerful computers have led to unprecedented success in artificial intelligence. This powerful tool has been used in numerous scientific and engineering fields including mineral identification. This paper summarizes the methods and techniques of artificial intelligence applied to intelligent mineral identification based on research, classifying the methods and techniques as artificial neural networks, machine learning, and deep learning. On this basis, visualization analysis is conducted for mineral identification of artificial intelligence from field development paths, research hot spots, and keywords detection, respectively. In the end, based on trend analysis and keyword analysis, we propose possible future research directions for intelligent mineral identification.The National Natural Science Foundation of China.https://www.mdpi.com/journal/jsanElectrical, Electronic and Computer Engineerin

A Passive Testing Approach for Protocols in Wireless Sensor Networks

Smart systems are today increasingly developed with the number of wireless sensor devices drastically increasing. They are implemented within several contexts throughout our environment. Thus, sensed data transported in ubiquitous systems are important, and the way to carry them must be efficient and reliable. For that purpose, several routing protocols have been proposed for wireless sensor networks (WSN). However, one stage that is often neglected before their deployment is the conformance testing process, a crucial and challenging step. Compared to active testing techniques commonly used in wired networks, passive approaches are more suitable to the WSN environment. While some works propose to specify the protocol with state models or to analyze them with simulators and emulators, we here propose a logic-based approach for formally specifying some functional requirements of a novel WSN routing protocol. We provide an algorithm to evaluate these properties on collected protocol execution traces. Further, we demonstrate the efficiency and suitability of our approach by its application into common WSN functional properties, as well as specific ones designed from our own routing protocol. We provide relevant testing verdicts through a real indoor testbed and the implementation of our protocol. Furthermore, the flexibility, genericity and practicability of our approach have been proven by the experimental results