In this paper fully centralized, hierarchical decentralized, and fully decentralized multisensor structures of Kalman filter are introduced and compared with together and with one sensor structure of Kalman filter. Decentralized structures are obtained through parallelism in centralized Kalman filter and give high processing speed. Fully decentralized structure requires no central processor and each processor estimates system's states. Therefore, the system is very resilient to loss of one or more of its processors and its survivability and robustness are increased. Decentralized algorithms are modified so that t-he computation complexity is reduced with keeping the same accuracy. Simulation results 'for time-variant system illustrate clearly that despite of reducing the computation complexity, the accuracy of the estimation is remained the same. Also, multisensory structures have high accuracy of estimation in comparison to one sensor structure.

Magnetic Flux Leakage (MFL) is an indirect measurement technique. Therefore, calibration curves are generally used to estimate the depths of the defects from the measured MFL signals. This has been shown to give good results on varying degrees of the single defects. However due to the interaction between the leakage fluxes, nearby pittings can-not be discriminated and properly assessed using the conventional MFL technique. In order to ensure reliable measurement for this case, the MFL technique is combined with the optical inspection technique. The main contributions of this study are to develop a new calibration method based on the defect depth, defect area as well as the amplitude of the corresponding MFL signal and propose a novel combined approach for detection and identification of the nearby pittings. MFL and optical inspection techniques are applied to a test specimen containing the nearby pittings. The results obtained from the experimental tests demonstrate the efficacy of the proposed approach.

Pipelines are widely used in transporting large quantities of water and sewage over long distances. These valuable infrastructures attract public attention only when they fail. The quantitative and early detection of defects in sewer pipelines is very important in order to avoid severe consequences. In many countries, sewer pipeline inspection is usually carried out using CCTV (Closed-Circuit TV) cameras and off-line human surveys through raw image assessment for failure identification. CCTV-based techniques have some limitations that restrict their implementation. One of the disadvantages of CCTVbased techniques is the lack of visibility in the interior of the pipes. The other disadvantage of CCTVbased techniques is the poor quality of the obtained images because of difficult lighting conditions. In consequence, CCTV-based techniques can only detect gross defects reliably. In recent decades, thermography, microwave, laser, and sonar-based techniques have been proposed to complement the conventional CCTV-based technique and to improve inspection results. Also, new inspection devices employing multiple sensors and being capable of carrying out remote sewer inspection tasks have been proposed. This paper presents an overview of the conventional and novel inspection technologies for sewer pipelines. Furthermore, different types of robots for in pipe inspection tasks are discussed.

These days, the most important areas of research in many different applications, with different tools, are focused on how to get awareness. One of the serious applications is the awareness of the behavior and activities of patients. The importance is due to the need of ubiquitous medical care for individuals. That the doctor knows the patient's physical condition, sometimes is very important. Of course, there are other important applications for this information. There are a variety of methods and tools for measurement, gathering, and analysis of the physical behaviors and activities’ information. One of the most successful tools for this aim are ubiquitous intelligent electronic devices, specifically smartphones, and smart watches. There are many sensors in these devices, some of which can be used to understand the activities of daily living. As an output result, these sensors produce many raw data. Thus, it is needed to process these information and recognize the individual behavior of the output of this processing. In this paper, the basic components of the analysis phase for this process have been proposed. Simulations validate the benefits and superiority of this method.

Aims The use of intrauterine devices (IUDs) has been one of the most effective, the safest and cost-effective methods for preventing pregnancy, for a long time. However, some complications have been reported for IUDs. The complications may be reduced by using a specific technique for placement of IUD. The objective of this study was to introduce the rotating withdrawal technique for the first time, which was investigated to reduce the complications of IUD insertion. Materials & Methods This historical cohort study was conducted on 1199 females who referred to Sarem Medical Center for IUD insertion from 1984 to 1995. After primary examinations, IUD was inserted by rotating withdrawal technique. The subjects were followed up for 2 years. Findings Displacement was observed just in 20 cases (1. 67%). All of them were seen in the first month after placement. For these cases, IUD insertion was done again. After the second replacement, displacement was observed in 4 cases (0. 035%) after one month. Therefore, it was recommended to them to use another preventive method. There was no pregnancy or displacement in the other cases during 2 years. Conclusion The rotating withdrawal technique can minimize the pregnancy rate when IUD is used. In addition to the type and quality of IUD, insertion method of IUD can increase its effectiveness.

In this paper, a new method for extending and relaxing the noise-coupling (NC) technique is proposed to enhance the noise-shaping order without adding the number of integrators. The noise-shaping order of the introduced ∑∆ modulator whit applying a second-order noise-coupling technique is enhanced and its performance with optimizing the noise transfer function (NTF) zeros is improved. Also, by removing the analog adder at feedforward path and transferring it to a new feedback branch before the last integrator and adding second-order NC path can be decreased the input voltage swing to the quantizer. Thus, by improving the modulator resolution, power consumption can be reduced. Mathematical analyses and behavioural simulation results confirm the effectiveness of the new NC method. To examine its performance, a 2nd-order single loop ΣΔ modulator was designed. The new noise-coupling method is used to achieve the three-order noise shaping to increase the resolution with low complexity and low-power. The results show an outstanding improvement in signal-to-noise and distortion ratio (SNDR) compared to the conventional structure.

Blades play a vital role in the performance of wind turbine systems. However, they are prone to damage from complex and irregular loading, which can lead to catastrophic degradation and costly maintenance. Defects or damage to wind turbine blades (WTBs) not only reduce the lifetime and efficiency of wind turbine electricity generation but also increase monitoring errors, safety hazards, and maintenance costs. Therefore, damage detection for WTBs is of high importance for preventing failures, planning maintenance, and ensuring the operational stability of wind turbines. This review article provides a comprehensive overview of advanced damage detection techniques for WTBs, including many updated methods based on strain measurement, acoustic emission, ultrasound, thermography, and machine vision. With the development of machine vision approaches and image processing technology, machine vision-based detection has become a promising and primary technique for detecting surface damage and measuring the deformation of WTBs [28] due to its low cost, ease of operation, and no need for prior knowledge about damage locations. In this review article, common damages to WTBs are introduced comprehensively at first. In the second stage, the principles of detection, development methods, advantages, and disadvantages of the aforementioned techniques for blade inspection are examined. The trend in damage detection in wind turbines is moving towards methods that offer full capabilities, long-range, contactless, non-destructive, wireless, and online monitoring. Timely detection of blade damage and continuous assessment of the structural health of wind turbines are increasingly important. This review article proposes a new idea for the design and integration of energy harvesters and WTB damage detection methods, in which the devices are automatic and wireless. Finally, potential research directions, and WTB damage detection techniques through comparative analysis, are reviewed and concluded. This review is expected to provide guidelines for practical WTB inspections as well as research perspectives for damage detection techniques.