Electrostatic Monitoring Research Articles

The research of multi-information fusion in electrostatic monitoring for rolling bearing

The monitoring of rolling bearing with electrostatic method is a novel technology at present. Few experiments have been investigated with information fusion technique to improve the efficient of monitoring. This paper introduced a new method called moving window local outlier factor (MWLOF) to process electrostatic monitoring signals of rolling bearing under variable operating conditions. In the load and accelerated life tests, the extracted features can reduce the impact and accurately reflect the wear condition of the bearings compared with traditional features. It can detect weak faults earlier and has a better sensitivity and performance degradation trend than conventional techniques, which has a bright future in industrial application.

Analysis of Spatial Sensitivity Based on Electrostatic Monitoring Technique in Oil-Lubricated System

In this paper, for the detection of wear particles in lubricating oil roads, by an-alyzing the particle belt motor, a mathematical model of the oil circuit electro-static sensor considering the dielectric constant is proposed. At the same time, the concept of spatial sensitivity and visual field is introduced. The influencing factors of the position of the charged abrasive particles, the axial length of the sensor and the radial radius were studied respectively. The influence of each variable on the sensitivity was obtained, and the accuracy of the mathematical model was also verified. The simulation results show that reducing the radial radius of the sensor can effectively increase the spatial sensitivity of the electrostatic sensor; the larger the axial length L of the electrode, the higher the sensitivity, and the more uniform the cross-sectional sensitive field distribution; in the axial and radial directions, the larger the shaft diameter ratio, the more sensitive the sensor is and the more sensitive it is.

A wireless and wearable measurement system for human body electrostatic monitoring application

In particular, electrostatic discharge (ESD) and electric overstress (EOS), for the production assembly, were concluded as the common problems for all electronic manufacturers in worldwide. Uncontrollable and invisible electrostatic discharge events were the major problems, because production quality was performed by well-controlled electrostatic discharge and electric overstress. Currently, it was passively managed the electrostatic grounding path by a connection on the assembly line, the correct wearing of electrostatic ground wrist/ankle straps, and the installation of static ionizers on top of the riskiest workstations to dissipate the electrostatic energy, with the regular check of electrostatic discharge being eliminated or dissipated by static ionizers. The above methods could merely detect fixed locations, but could not real time detect the electrostatic conditions of an operator and record the related events for the database analysis. In order to improve the above issue, the study proposed a wearable and wireless human body electrostatic monitoring system to real-time detect the ESD event of an operator and record the ESD events for the database analysis. By using the real-time alert mechanism, the proposed system could effectively prevent these ESD damages: (1) could inform the operator to immediately discharge the cumulative electric charge; (2) could be transmit to the back-end host system via Bluetooth to make up the careless mistake in the operation, and this alert could be regarded as the second prevention; (3) could be recorded in database for successive data analyses. Finally, the proposed system was also validated and applied in the production assembly and the experimental results indicated that it could exactly provide an effective way to reduce the influence of ESD/EOS.

Symbolic Time-Series Analysis of Gas Turbine Gas Path Electrostatic Monitoring Data

The aero-engine gas-path electrostatic monitoring system is capable of providing early warning of impending gas-path component faults. In the presented work, a method is proposed to acquire signal sample under a specific operating condition for on-line fault detection. The symbolic time-series analysis (STSA) method is adopted for the analysis of signal sample. Advantages of the proposed method include its efficiency in numerical computations and being less sensitive to measurement noise, which is suitable for in situ engine health monitoring application. A case study is carried out on a data set acquired during a turbojet engine reliability test program. It is found that the proposed symbolic analysis techniques can be used to characterize the statistical patterns presented in the gas path electrostatic monitoring data (GPEMD) for different health conditions. The proposed anomaly measure, i.e., the relative entropy derived from the statistical patterns, is confirmed to be able to indicate the gas path components faults. Finally, the further research task and direction are discussed.

Experimental investigation on electrostatic monitoring technology for civil turbofan engine

This study analyzes the necessity, development, and principles of aero-engine electrostatic monitoring technology. An electrostatic sensor with specific size is assembled in the exhaust nozzle of an RB-211 turbofan engine located near the low-pressure turbine outlet, a stress checking procedure for safety is conducted. Two test program cycles are included in the whole experimental process. Electrostatic signal processing flow is presented, and feature parameters used for analysis are root-mean-square (RMS), activity level (AL), negative event rate (NER), positive event rate (PER), kurtosis, impulse factor, and absolute mean value. Thrust is used to parameterize the working conditions of the turbofan engine. Moreover, data fitting is conducted to determine the relations between feature and performance parameters. Accordingly, lubrication oil leakage fault and fuel-rich combustion condition are detected in two test run cycles, which result in the appearance of abnormal signals. The AL, RMS, and absolute mean values exhibit similar trends with the change in thrust. A positive linear correlation is also observed between the AL and the thrust in the varying thrust test period. The method of blade-casing rubbing fault recognition is discussed. Experiment results show that the electrostatic sensor is very sensitive to large-sized charged particles in the exhaust emissions.

Design and Test of Sensor for Aircraft Engine Gas Path Debris Electrostatic Monitoring

The research and design of sensor for aircraft engine gas path debris electrostatic monitoring are given in this paper. The mechanism of charged debris and principle of electrostatic induction of sensor are researched firstly, and when the charged material near or keep away from the electrostatic sensor, the induced charge of opposite polarity will be induced on the sensor’s probe. And then, the structure of electrostatic monitoring sensor is designed based on the principle of electrostatic induction. Electrostatic sensor is constituted by sensitive element, dielectric, internal circuit and grounding shell. Due to the particularity of working environment of electrostatic sensor, various factors such as performance requirements and using occasions should be considered in designed process. Finally, the effectiveness of electrostatic monitoring sensor is verified using experimental system. From the experimental results we can know when the charged particles through the electrostatic sensor, the sensing signal amplitude and the activity level are change obviously. These works provide theoretical method for the early fault warning of aircraft engine gas path components, and the monitoring and management of aircraft engine working condition.

航空发动机滑油系统全流量在线磨粒静电监测方法现状分析

综述了目前国内外全流量在线磨粒静电监测技术现状，介绍了全流量在线磨粒静电监测方法。针对目前滑油系统全流量磨粒在线静电监测模拟实验荷电机理之一摩擦荷电原理，指出了摩擦荷电的关键性问题。针对国内目前滑油系统全流量静电监测技术模拟实验方法存在的优缺点，指出了如何自动控制颗粒流速是实验模拟的关键问题，最后，进一步明确了滑油系统全流量在线磨粒静电监测方法现状。 The paper summarizes the current situation of the oil-line debris electrostatic monitoring tech-nology and introduces the method about the oil-line debris electrostatic monitoring. Aiming at the friction charging mechanism of the oil-line debris electrostatic monitoring, it pointed out the key problem of friction charging. In view of the advantages and disadvantages of the present experimental method for oil-line debris electrostatic monitoring, it is pointed out that the key problem of the experimental simulation is how to automatically control the particle velocity. At last, the actuality of the oil-line debris electrostatic monitoring has been further clarified.

Theoretical analysis and finite element method simulations on dynamic sensitivity of hemisphere-shaped electrostatic sensors

Electrostatic sensors are key components of electrostatic monitoring systems. Their sensitivity characteristics have a direct influence on monitoring accuracy. In previous studies, spatial sensitivity, which is called static sensitivity here, was used to describe the sensitivity characteristics. However, it only reflects a basic relationship between static charged particles and induced charges on an electrostatic sensor’s probe. Besides, as a three-dimensional defined parameter, it is difficult to build a unified model if actual boundary conditions are considered. Thus, it is not quite proper for applications that detect moving particles. To solve this problem, dynamic sensitivity is proposed in this article. As for a hemisphere-shaped electrostatic sensor, first, a more accurate model of static sensitivity is built. Based on it, dynamic sensitivity is defined and modeled analytically. Then, a calibration method is proposed to improve the model’s accuracy under actual boundary conditions. In the end, finite element method simulations are done for validations. The results demonstrate that dynamic sensitivity reflects a relationship between moving charged particles and the actual output signals of a sensor, thus it is direct and practical for moving particles. And the theoretical results are highly consistent with the simulated ones. Moreover, the dynamic sensitivity indicates localized sensing characteristics of hemisphere-shaped electrostatic sensors.

Electrostatic monitoring of wind turbine gearbox on oil-lubricated system

The electrostatic sensing technique has been verified to be a viable method for tribo-contact monitoring under laboratory conditions in previous investigations. This paper reports on the evolution of electrostatic monitoring on a real oil-lubricated wind turbine gearbox, using a modified oil-line sensor. In a nominal test and a ramp-up test, features were extracted and the presence of debris can be detected. The permutation entropy was further introduced in an accelerated life test. It can accurately reflect the wear condition of the gearboxes and detect early faults earlier than conventional techniques, which also has a better sensitivity and performance degradation trend than time-domain features.

Electrostatic monitoring of coal velocity and mass flowrate at a power plant

ABSTRACTIt is necessary to monitor and balance the pulverized coal velocity and flowrate among the conveying pipelines leading to injection burners and to optimize the air-coal ratio for safety, economical operation, and reduction of pollution of coal-fired boilers in power plants. A novel electrostatic sensing system is reported for monitoring the velocity and relative mass flowrate of pulverized coal. The design, implementation, and on-plant trials of the system are reported. The velocity of pulverized coal was determined by autocorrelating the output derived from a linear electrostatic sensor array. The relative concentration and mass flowrate were obtained by the root mean square values of the output of two ring-shaped electrodes with the consideration of the pulverized coal velocity. The instrumentation was evaluated on a full-scale 600 MW power generation unit. The results demonstrate that the technique provides reliable measurement of pulverized coal velocity, relative flowrate, and split distribution among the injection pipes from the same pulverizing mill. The prototype achieved split balance and optimized air/coal ratio in combination with the pulverized coal balancing control valve and proportional-integral-derivative controller in fuel injection pipes in a power plant.

Formation Mechanism Analysis and Detection of Charged Particles in an Aero-engine Gas Path

The components of an aero-engine gas path cannot be monitored in a timely way due to a lack of real-time monitoring technologies. As an attempt to address this problem, we have conducted research on a condition monitoring technology based on the charging characteristics of particles in an aero-engine gas path, and emphatically analyze the formation of particles in an aero-engine gas path, the charging mechanism of carbon particles and the factors that influence the charge quantity and polarity. The verification experiments are performed on the simulated experiment platform and a turbo-shaft engine test bench. The results show the carbon particles' carry charge, and an obvious change in the total electrostatic charge level in the aero-engine gas path due to the increased carbon particles produced by burning or abnormal metal particles; the charge number is related to the size of particles, and the bigger carbon particles carry a negative charge and metal particles carry a positive charge; the change in engine power can lead to an obvious change in the level of electrostatic charge in the gas path, and the change in electrostatic charge results from the extra carbon particles formed in the rich-oil burning process. The research provides a reference for establishing the baseline of electrostatic charge while the engine runs on different power. The study also demonstrates the validity of the electrostatic monitoring technology and establishes a base for developing the application of electrostatic monitoring technology in aero-engines.

Feature extraction for rolling bearing fault diagnosis by electrostatic monitoring sensors

There are mainly two problems with the current feature extraction methods used in the electrostatic monitoring of rolling bearings, which affect their abilities to identify early faults: (1) since noises are mixed in the electrostatic signals, it is difficult to extract weak early fault features; (2) traditional time and frequency domain features have limited ability to provide a quantitative indicator of degradation state. With regard to these two problems, a new feature extraction method for rolling bearing fault diagnosis by electrostatic monitoring sensors is proposed in this paper. First, the spectrum interpolation is adopted to suppress the power-frequency interference in the electrostatic signal. Then the resultant signal is used to construct Hankel matrix, the number of useful components is automatically selected based on the difference spectrum of singular values, after that the signal is reconstructed to remove background noises and random pulses. Finally, the permutation entropy of the denoised signal is calculated and smoothed using the exponential weighted moving average method, which is used to be a quantitative indicator of bearing performance state. The simulation and experimental results show that the proposed method can effectively remove noises and significantly bring forward the time when early faults are detected.

Research on Aero-Engine Gas Path Detection System Based on Electrostatic Induction

A large number of charged particles exist in the aero-engine gas path, the electrostatic monitoring technology mainly monitors the electrostatic charge in the exhaust gas of aero-engine by arranging an electrostatic sensor, and predicts the performance and working state of gas path components by using signal process algorithms and intelligent decision model. Considering the characteristics of the aero-engine gas path and the requirements of the gas path parameter detection, an electrostatic induction-based electrostatic sensor is built to detect the anomalously charged particles in the gas path on line, providing an important basis for aero-engine Prognostics and Health Management (PHM). Simulation experiments are implemented to investigate the time response and frequency characteristic of the output signals of the sensor and analyze the influence factors.

The Electrostatic Sensor Applied to the Online Monitoring Experiments of Combustor Carbon Deposition Fault in Aero-Engine

According to the principle of gas path electrostatic monitoring in aero-engine, it has established aero-engine gas path electrostatic monitoring system that can tolerate the high-temperature and high-speed airflow. There was developing the research about the mechanism of combustor carbon deposition and online electrostatic monitoring, the fault of combustor carbon deposition in aero engine. It was chose eight stages data from the large scale data of online electrostatic monitoring experiments and being based the time of checking the combustor in aero engine, comparably analyzing rms and Kurtosis being extracted from the data as features. In order to regain the accurate charge signal and discard certain trend item, it uses least mean square to finish the transforming process that is from electrostatic voltage to electrostatic charge. The changes of exhaust gas path electrostatic level illustrate by the features, including active level, positive event rate, and negative event rate extracted from the electrostatic charge signal. It responds for the fault of combustor carbon deposition in aero-engine as well as a slight ablation fault in testing process by the features of electrostatic voltage and charge, respectively, which is being to verify the monitoring results by the report of the engine dismantled. The research of online electrostatic monitoring the fault of combustor carbon deposition in this paper would be the foundation to achieve the application of the technology in aircraft.

Electrostatic Monitoring of Oil Lubricated Rolling Bearing Performance Degradation and Experiment

Electrostatic Monitoring of Oil Lubricated Rolling Bearing Performance Degradation and Experiment

Experimental study on engine gas-path component fault monitoring using exhaust gas electrostatic signal

This paper presents the recent development in engine gas-path components health monitoring using electrostatic sensors in combination with signal-processing techniques. Two ground-based engine electrostatic monitoring experiments are reported and the exhaust gas electrostatic monitoring signal-based fault-detection method is proposed. It is found that the water washing, oil leakage and combustor linear cracking result in an increase in the activity level of the electrostatic monitoring signal, which can be detected by the electrostatic monitoring system. For on-line health monitoring of the gas-path components, a baseline model-based fault-detection method is proposed and the multivariate state estimation technique is used to establish the baseline model for the electrostatic monitoring signal. The method is applied to a data set from a turbo-shaft engine electrostatic monitoring experiment. The results of the case study show that the system with the developed method is capable of detecting the gas-path component fault in an on-line fashion.

Characteristics analysis and experiment verification of electrostatic sensor for aero-engine exhaust gas monitoring

An electrostatic sensor is a critical component of the electrostatic monitoring system for an aero-engine gas path. In this paper, the basic principles of the electrostatic sensor are described and the materials selection process for sensor electrodes and an isolation medium is introduced. The finite element method was adopted to calculate the sensitivity distribution, and the influence of relevant structural parameters on the sensitivity distribution characteristic is analyzed. The data fitting method was employed to acquire the unified spatial sensitivity distribution functions for a given structure sensor, which provides a useful reference for the sensor’s installation location. Based on the unified function, the sensitivity distribution function along the particle moving direction and the frequency characteristic of the electrostatic sensor were acquired. Then the corresponding influence factors of the frequency properties were analyzed. An experiment platform was established to verify the model and the theoretical analysis results. Then, simulated experiments were applied to verify the feasibility and validity of the electrostatic sensor, and the experiment results provided a useful reference for the identification of abnormal particles as a characteristic of aero-engine faults.

High speed imaging with electrostatic charge monitoring to track powder deagglomeration upon impact

A dry powder inhaler (DPI) is effective in treating respiratory diseases if it can deliver consistent and reliable drug dosage with each actuation. De-agglomeration and subsequent detachment of the drug from the carrier particles upon actuation depends on the interaction forces between particle and wall and particles themselves. The particle surface properties such as roughness and moisture sorption, in turn, determine the extent of the interactions. Via combining high speed imaging with non-intrusive electrostatic measurements in an impaction throat model, the contributions of the electrostatic forces arising from de-agglomeration and impaction behaviours of the rough and smooth particulates could be investigated at 60L/min. Higher flowing charges with limited agglomerate fracture upon impaction were observed for the rough carrier particles while significant agglomerate breakup and ‘plume-like’ re-entrainment behaviour was noted for the smooth ones. Increased moisture sorption on the larger specific surface area of the rough particles could have facilitated the accumulation of surface charges while the higher dispersive surface energy could have increased the cohesiveness of the rough particles. The smooth particles easily broke up upon impaction. High speed imaging with electrostatic monitoring has proved to be useful in investigating the mechanisms of powder de-agglomeration upon impaction.

Applications of Electrostatic Sensor for Wear Debris Detecting in the Lubricating Oil

In this study, an advanced monitoring technology has been presented based on the electrostatic induction principle to monitor timely wear fault on-line. The paper begins with the principle of the electrostatic monitoring technology, then we focus on the electrostatic sensor, the most important component in the electrostatic monitoring system, establish a measurement model for an electrostatic sensor with the given structure parameters. Based on the measurement model, we use the finite element method to analyze the characteristics of an electrostatic sensor for wear debris detecting in lubricating oil. Lastly we build an experiment platform to validate the feasibility of the electrostatic monitoring method. The experiment results show, to some extent, that the electrostatic signal can reflect the relative density of wear debris, and the sensor proposed can satisfy the primary demand of wear debris on-line monitoring.

Electrostatic Precipitator Monitoring System Based on CAN Bus

The hardware and software design are introduced about electrostatic precipitator control system. And this monitoring and control system is based on CAN bus. In this system the basic data acquisition and control functions can be achieved. The work status of precipitator can be collected in real time and fed back to the computer control interface, in order to provide reliable data support for the fault diagnosis of the ESP, so information integration level can be improved and the monitoring system can be optimized. Simple structure, high reliability, communication speed are the characteristics, and it have a wide range of application prospects.