Sharif Digital Repository

In this research, a combination of the physical model based on Paris law and probability method is proposed for remaining useful life prediction of rolling element bearings. Level crossing is used as a feature that represents a linear relationship with defect size. Considering this linear relationship and using Paris law, a new model has been developed for bearings that follow degradation pattern with two stages. In this pattern, a bearing starts working in the healthy condition. Then it starts slow degradation stage and finally it goes to fast degradation stage until it reaches to the failure threshold. Considering a normal distribution for transition point from the slow degradation to the... 

Rolling element bearings (REBs) are usually considered among the most critical elements of rotating machines. Therefore, accurate prediction of remaining useful life (RUL) of REBs is a fundamental challenge to improve reliability of the machines. Vibration condition monitoring is the most popular method used for diagnosis of REBs and this is a motivating fact to use recorded vibration data in RUL prediction too. However, it is necessary to extract appropriate features from vibration signal that represent actual damage progress in the REB. In this paper, wavelet packet transform is used to extract signal features and artificial neural network is applied to estimate RUL of the REB. To obtain... 

Selecting appropriate features from the vibration condition monitoring data of ball-bearings is one of the main challenges in the application of data-driven methods for remaining useful life prediction purpose. In this article, a new feature based on the high-frequency vibration of ball-bearings is proposed. The feed forward neural network will be used for training and prediction. The experimental data of the bearing accelerated life in the PROGNOSTIA test (published in PHM 2012 IEEE conference) are used to verify the method. The results obtained by applying new features are compared with those of two popular features in the time domain (RMS and kurtosis) for prognostic purpose. Applying the... 

Polystyrene resin was functionalized by diethanolamine for the efficient removal of p-toluenesulfonic acid (p-TSA) from aqueous solution. Functionalized adsorbent (DEA-PS) was characterized by elemental analysis, Fourier transform infrared spectroscopy, point of zero charge measurement and field-emission scanning electron microscopy. According to the results, maximum removal of p-TSA was observed at the pH range of 2.5-5. The adsorption kinetics of p-TSA onto DEA-PS was represented by pseudo-first-order model and the equilibrium data followed Langmuir model well. The adsorption process was endothermic and spontaneous, along with the positive change of entropy. The regeneration of DEA-PS was... 

Unmanned aerial vehicles (UAVs) are developing rapidly owing to flexible deployment and access services as the air base stations. In this paper, by taking the realistic assumption of imperfect channel state information at transmitter (CSIT), we investigate the robust and secure design of downlink UAV network while considering the worst-case outage constraints due to communication link uncertainties. In our proposed heterogeneous network, comprised of both UAV-cells and macro-users, rate splitting technique is deployed by UAV base-station (UAV-BS) to enhance the system performance in terms of security, power saving, and robustness against imperfect CSIT. Through our proposed design, we... 

The earlier works in the context of low-rank-sparse-decomposition (LRSD)-driven stationary synthetic aperture radar (SAR) imaging have shown significant improvement in the reconstruction-decomposition process. Neither of the proposed frameworks, however, can achieve satisfactory performance when facing a platform residual phase error (PRPE) arising from the instability of airborne platforms. More importantly, in spite of the significance of real-time processing requirements in remote sensing applications, these prior works have only focused on enhancing the quality of the formed image, not reducing the computational burden. To address these two concerns, this article presents a fast and... 

In this paper, a cost-effective and high-accuracy precoding technique based on ϵ-Fuzzy pareto active learning (FPAL) is proposed for millimeter wave (mmWave) massive MIMO communications. The proposed method achieves a low iteration convergence with low complexity. Two practical structures, namely fully-connected and partially-connected structures are considered for hybrid precoding. Furthermore, the effect of high and low-resolution quantization in the digital-to-analog converter, phase shifter, and imperfect channel state information are discussed. The performance results of the proposed technique and alternating minimization methods beside fully digital techniques are compared and... 

Unmanned Aerial Vehicles (UAVs) have found compelling applications in intelligent logistics, search and rescue as well as in air-borne Base Station (BS). However, their communications are prone to both channel errors and eavesdropping. Hence, we investigate the max-min secrecy fairness of UAV-aided cellular networks, in which Cooperative Rate-Splitting (CRS) aided downlink transmissions are employed by each multi-antenna UAV Base Station (UAV-BS) to safeguard the downlink of a two-user Multi-Input Single-Output (MISO) system against an external multi-antenna Eavesdropper ( Eve ). Realistically, only Imperfect Channel State Information (ICSI) is assumed to be available at the transmitter.... 

Although Unmanned Aerial Vehicles (UAVs) are capable of significantly improving the information security by detecting the eavesdropper's location, their limited energy motivates our research to propose a secure and energy efficient scheme. Thanks to the common-message philosophy introduced by Rate-Splitting (RS), we no longer have to allocate a portion of the transmit power to radiate Artificial Noise (AN), and yet both the Energy Efficiency (EE) and secrecy can be improved. Hence we define and study the Secrecy Energy Efficiency (SEE) of a multi-carrier multi-UAV network, in which Cooperative Rate-Splitting (CRS) is employed by each multi-antenna UAV Base-Station (UAV-BS) for protecting... 

This paper investigates the physical layer security (PLS) design of an untrusted relaying network where the source node coexists with a multi-antenna eavesdropper (Eve). While the communication relies on untrustworthy relay nodes to increase reliability, we aim to protect the confidentiality of information against combined eavesdropping attacks performed by both untrusted relay nodes and Eve. Considering the hardware impairments (HIs), both total power budget constraint for the whole network and the individual power constraint at each node, this paper presents a novel approach to jointly optimize relay beamformer and transmit powers aiming at maximizing average secrecy rate (ASR). To... 

Unmanned aerial vehicles (UAVs) are capable of improving the performance of next generation wireless systems. However, their communication performance is prone to both channel estimation errors and potential eavesdropping. Hence, we investigate the effective network secrecy throughput (ENST) of the uplink UAV network, in which rate-splitting multiple access (RSMA) is employed by each legitimate user for secure transmission under the scenario of massive access. To maximize the ENST, the transmission rate versus power allocation relationship is formulated as a max-min optimization problem, relying on realistic imperfect channel state information (CSI) of both the legitimate users and passive... 

In the present investigation, different agricultural solid wastes namely: eggplant hull (EH), almond green hull (AGH), and walnut shell (WS), that are introduced as low cost adsorbents, were used for the removal of heavy metals (cobalt, strontium and mercury ions) from aqueous solutions. Activation process and/or chemical treatments using H 2O 2 and NH 3 were performed on these raw materials to increase their adsorption performances. The effectiveness of these adsorbents was studied in batch adsorption mode under a variety of experimental conditions such as: different chemical treatments, various amounts of adsorbents, initial metal-ion concentrations, pH of solutions, contact times, and... 

This paper presents a novel modification to a conventional rolling element bearing that allows it to monitor its own condition, and describes some preliminary tests on a prototype. The self monitoring feature is a thick-film vibration sensor deposited in a shallow groove around the outer race of the bearing. This has the virtue of being very close to the source of the impacts that are characteristic of a damaged bearing, as well as being robust and low cost. The form of the sensor is such that the loading surfaces of the outer race are only slightly modified and the bearing can be fitted into any conventional bearing housing with only minor modification to make electrical connection to the... 

In this paper a new approach to determine the size of defects in rolling element bearings is proposed. This approach is based on the statistical characteristics of the vibration signals generated by rolling element bearings. Although some traditional statistical parameters such as r.m.s. and kurtosis have some diagnostic capabilities, these parameters are not suitable for quantifying the defect size. The proposed new model was validated experimentally for both inner and outer race defects and it is concluded that the newly proposed model can determine the defect length of rolling bearings  

Remaining useful life prediction of rolling element bearings with offline condition monitoring data is the purpose of this paper. A data driven algorithm based on feedforward neural network is proposed for this aim. Since, usually the number of offline measurements are not much enough, the generalized Weibull failure rated function is used for producing the auxiliary points that are employed for training. Considering the physics of the bearing degradation, level of vibration in the highfrequency bandwidth of the spectrum is used as a feature and its performance in bearing prognostic problem is compared with that of using popular recommended features in the diagnostic standard. Bearing...