Introduction to Pd Detection

What is/are Pd Detection?

Pd Detection - The ultra-wideband frequency response of this antenna makes it a suitable and promising sensor for PD detection and PD recognition on high voltage equipment such as power transformers. ^[1] Both ultra-high frequency (UHF) technique and acoustic means have been popularly used in PD detection to enable the reliable, cost-effective life extension of existing plants. ^[2] To improve detection accuracy and practicality, we first identify two challenges that affect the accuracy of binary NPD detection: (i) pointer aliasing, and (ii) untrusted source identification. ^[3] A vialess passive metamaterial (MTM)-based Quadrature Phase Shift Keying (QPSK) modulated chipless Radio Frequency Identification (RFID) tag is integrated with a partial discharge (PD) sensor with the objective of PD detection and identification. ^[4] More analysis on the input sound type, the RP image size, and the deep learning structures will be included in our future work for further improving the performance of PD detection from voice. ^[5] The performance of a PD detection system depends heavily on the quality of these features. ^[6] Thirteen UPD events were identified in cases with prior normal SNP chromosomal microarray results, demonstrating the additional diagnostic value of UPD detection by trio ES. ^[7] PD detection traditionally relies on hand-crafted features and domain expertise to identify very specific pulses in the electrical current, and the performance declines in the presence of noise or of superposed pulses. ^[8] In this work, we present the design and experimental verification of a UHF antenna with relatively small aperture and radome for PD detection. ^[9] Recently, ultra-high-frequency (UHF) based PD detection system is gaining popularity, as it can also localize the PD source, through the measurement of time-difference-of-arrivals (TDOAs) at multiple antennas, which are place around the object under investigation. ^[10] The Spirobank Smart is a simple and adequate tool for early COPD detection in outpatient clinics. ^[11] The PD detection technique according to IEEE 400. ^[12] Conclusions: In China, the CSIT is recommended to improve the sensitivity of PD detection. ^[13] Methods Observational study in the context of an early COPD detection and smoking cessation project. ^[14] However, the disadvantage of this method is that excessive amounts of phenylboronic acid causes the formation of triphenylboroxin that may lead to instrument fouling and reduces the sensitivity of this 3-MCPD detection method. ^[15] Moreover, KP has been reported to play a biomarker role in PD detection. ^[16] In this paper, a PD detection method based on super high frequency (SHF, 3-30 GHz) technique and signal down-mixing principle is applied to detect the PD under square wave. ^[17] In addition, the differences of the studies on various sensor developments based on PD detection in the past 27 years are also discussed. ^[18] This study explores static and dynamic speech features relating to PD detection. ^[19] Recently, the deep learning models for PD detection have been used to diagnose the PD fault of facilities and cables. ^[20] This paper reviews and evaluates the current state-of-the-art methods for PD detection and localization techniques, and methodologies in power transformers. ^[21] The impact of this study is to provide a basis for further investigation of 3-MCPD detection in palm oil using electrochemical method due to its simplicity for the development of a portable, fast and reliable 3-MCPD sensor. ^[22] On the other hand, the AUC for aPD detection by miR-31 was 0. ^[23] 59% have been obtained across all datasets for PD detection and stage classification, respectively. ^[24] However, OPD detection is often limited to shorter wavelengths, whereas photodetection in the near-infrared (NIR) region is increasingly being required for wearable electronics and medical device applications. ^[25] The PD detection shows excellent linearity with stray light down to 8% and an effective path length at 73% of a 75 μm id capillary. ^[26] The proposed map is then used for PD detection and classification. ^[27] The objective was to develop and evaluate the performance of a novel multimodal, multitask, multiattention (M3) deep learning framework on RPD detection. ^[28] The effectiveness of HCC features is utilized to perform classification, and regression analysis for PD detection. ^[29] Recent PD studies have extracted the features from vocal disorders as a harbinger for PD detection, as patients face vocal changes and impairments at the early stages of PD. ^[30] However, conventional techniques for PD detection are often hand-crafted, in which special expertise is needed. ^[31] At the same time, a comparative study on the performance tests of different types of PD detection equipment has been carried out. ^[32] To this end, long read speech from COPD and control groups was recorded, and the following experiments were performed: (a) a statistical analysis over the study and control groups to analyse the effects of physical effort and medication on speech; and (b) an automatic classification experiment to analyse how different recording conditions can affect the performance of a COPD detection system. ^[33] The procedure of PD detection and transient modeling is performed in MATLAB for two pressure levels (atmospheric and half-atmospheric). ^[34] 5 quantum dots (QDs) were prepared and applied for AN and 3-MCPD detection depending on fluorescence quenching and wavelength shifts. ^[35] To derive the LNR-combined criteria, different Tg cut-off values for identifying the PET/CT-indicated group for PD detection were applied individually to subgroups initially classified based on LNR cut-off values. ^[36] In order to improve the time-delay estimation accuracy of a multielement PD UHF pulse signal sensor array and reduce the cost of the PD detection system, a fuzzy interpolation cross-correlation method for time-delay estimation of PD UHF pulse signals was proposed in this paper. ^[37] The results demonstrate that the method proposed in this paper is promising in the field of PD detection. ^[38] Thus, PD detection is a crucial issue in high voltage insulation area. ^[39]

fluorescent optical fiber

In this work, the fluorescent optical fiber sensor was manufactured and applied to the PD detection in gas insulated switch (GIS) and transformer, fluorescent optical fiber was used as a probe, which was connected with the transmission optical fiber by coupler, and the photomultiplier tube was used to convert the optical signal into electrical signal for displaying by oscilloscope. ^[1] Then, we made a fluorescent optical fiber sensor for PD detection in GIS and compared it with the pulse current method and ultrahigh-frequency (UHF) method. ^[2]

Uhf Pd Detection

This two-part paper aims to give a comprehensive review about the application of signal processing and machine learning technologies in UHF PD detection and diagnosis. ^[1] The performance check and comparison test research of UHF PD detection equipment provides an important basis for the arrival acceptance and regular check of UHF PD detectors, and also provides strong technical support for field testers. ^[2] In this work, an experimental study has been conducted in the laboratory and in substations to investigate the localisation ability of the UHF PD detection system. ^[3] It is shown that the designed antenna is a very good candidate for UHF PD detection inside of high-voltage equipment. ^[4] The bushing tap, iron core, and high-voltage (HV) winding can be used as internal UHF sensor for UHF PD detection. ^[5]

Early Pd Detection

These results suggest the viability of using a low-cost and easy-to-use activity sensor for detecting movement abnormalities due to PD and motivate further research on early PD detection and tracking of PD symptom severity. ^[1] Multivariate and univariate data analyses were applied to reveal metabolic changes among the groups in attempt to discover new putative markers for early PD detection and disease progression. ^[2] As a cast-resin transformer is one of the main components of a power system, early PD detection is extremely important to ensure power system operation reliability. ^[3] Therefore, healthcare providers should implement early PD detection and intervention to prevent the adverse outcomes. ^[4]

Automated Pd Detection

To overcome these limitations, automated PD detection using smoothed pseudo-Wigner Ville distribution (SPWVD) coupled with convolutional neural networks (CNN) called Parkinson’s disease CNN (PDCNNet) is proposed. ^[1] Therefore, this work presents a new graph-based aspirin model for automated PD detection using EEG signals. ^[2] Therefore, different machine learning methods have been developed for automated PD detection. ^[3]

Site Pd Detection

A powerful tool for conducting on-site PD detection and location in power cables is urgently needed. ^[1] For on-site PD detection, the ultra-high frequency (UHF) method was employed in the field and showed its effectiveness as a detection technique. ^[2]

pd detection method

However, the disadvantage of this method is that excessive amounts of phenylboronic acid causes the formation of triphenylboroxin that may lead to instrument fouling and reduces the sensitivity of this 3-MCPD detection method. ^[1] In this paper, a PD detection method based on super high frequency (SHF, 3-30 GHz) technique and signal down-mixing principle is applied to detect the PD under square wave. ^[2] It is found that under PD test condition, the apparent charge of the PDs is less than 1 pC for particles smaller than 5 mm, and the conventional PD detection method have limitations in detecting these small defects. ^[3] The existing ultrasonic PD detection method generally needs the power supply and the electronic measuring instrument. ^[4] The ultrasonic sensing is one of the PD detection methods proposed in the literature. ^[5] Until now, common PD detection methods are based on one channel measurements, e. ^[6] Most existing PD detection methods are based on the processing of PD waveforms. ^[7] PD detection method that is not subject to any electromagnetic interference has not been found yet. ^[8] However, the traditional PD detection method could be ineffective or insensitive because of the serious disturbance of displacement current under fast rising repetitive square voltage, which leads to great difficulty in PD-based insulation assessment. ^[9] This PD detection method solves the problem that the internal UHF sensor has security risks while the external sensor is susceptible to interference. ^[10]

pd detection system

The performance of a PD detection system depends heavily on the quality of these features. ^[1] The main contributions of this work are: (1)We propose a multimodal PD detection system based on both static and dynamic features obtained from evoked face gestures; (2) we propose a novel set of 17 dynamic features to characterize the facial expressiveness and demonstrate that facial dynamics features can be used to improve PD detection; and (3) we analyze different evoked facial expressions and its performance for PD detection. ^[2] Recently, ultra-high-frequency (UHF) based PD detection system is gaining popularity, as it can also localize the PD source, through the measurement of time-difference-of-arrivals (TDOAs) at multiple antennas, which are place around the object under investigation. ^[3] With the advantages of high sensitivity and non-intrusiveness, HFCT PD detection systems are implemented in order to monitor incipient faults of power cables. ^[4] To this end, long read speech from COPD and control groups was recorded, and the following experiments were performed: (a) a statistical analysis over the study and control groups to analyse the effects of physical effort and medication on speech; and (b) an automatic classification experiment to analyse how different recording conditions can affect the performance of a COPD detection system. ^[5] In order to improve the time-delay estimation accuracy of a multielement PD UHF pulse signal sensor array and reduce the cost of the PD detection system, a fuzzy interpolation cross-correlation method for time-delay estimation of PD UHF pulse signals was proposed in this paper. ^[6] In this work, an experimental study has been conducted in the laboratory and in substations to investigate the localisation ability of the UHF PD detection system. ^[7]

pd detection sensor

To settle this problem, a novel GIS PD detection sensor integrated with the optical fiber and UHF method is developed in this paper, which can fully utilize the advantages both of UHF and optical methods. ^[1] The PD detection sensor used is a detecting impedance (RC) sensor to detecting the surface PD that occurs and measure the characteristics of it. ^[2] Selection of improved technology and performance of PD detection sensor, effective measurement technique and smart user friendly of graphical user interface (GUI) system are contributed towards the development of efficient monitoring system. ^[3]

pd detection technique

This paper explores the advantages and disadvantages of radiometric techniques and presents an overview of a radiometric PD detection technique that uses a transistor reset integrator (TRI)-based wireless sensor network (WSN). ^[1] The PD detection technique according to IEEE 400. ^[2] A cost-effective, non-intrusive, and smart PD detection technique is needed for the diagnosis of different power equipment. ^[3]

pd detection equipment

At the same time, a comparative study on the performance tests of different types of PD detection equipment has been carried out. ^[1] The performance check and comparison test research of UHF PD detection equipment provides an important basis for the arrival acceptance and regular check of UHF PD detectors, and also provides strong technical support for field testers. ^[2]