Field Mill Sensors Research Articles

Model, design, and experiments of a field mill sensor for measuring high-voltage DC electric fields

Abstract In an attempt to measure the DC field intensity in the space below the high voltage transmission line, based on the principium of electrostatic induction, the DC-induced signal is transformed into an AC signal by continuously changing the relative area of the parallel plate capacitor, and then the signal is filtered and amplified. The measured value of the field to be measured is obtained from the amplitude of the output signal. The influences of the number of openings on the electric field distribution, the induced charge, and the output current in the adjacent space of the capacitive plate are studied by modeling and simulation. An experimental device is built to study the influence of the number of plate openings on the measurement results, and the simulation results are compared and analyzed. The calibration error of the field grinding sensor designed in this paper is about 6%, and the results show that the method can be applicable to the measurement of electric fields in DC transmission engineering.

Differential Structure to Improve Performance of DC Electric Field Sensors

The electric field is an essential electromagnetic environmental parameter in designing and constructing high-voltage direct-current (HVDC) transmission lines. In this paper, a differential structure is proposed to improve the performance of the field mill sensor. Two groups of vanes with the same characteristics generate induced currents with opposite phases, and the difference operation calculates the ground electric field. We calculated the charges and induced currents and optimized the number of vanes of the sensing electrode using the simulation model. Then we designed the I/V circuit and amplifier based on the differential structure and conducted circuit simulation and sensor calibration experiments. Compared with the single input electric field sensor, the noise of the sensor with the differential structure is significantly reduced, and the sensitivity reaches 0.085 V/(kV/m). The results indicate that the field mill sensor with improved differential structure enhances the anti-interference ability and sensitivity.

Integrated Filter Design for Analog Field Mill Sensor Interface

The design process of an integrated bandpass filter targeted for the noise filtering stage of the synchronous demodulation unit of an electric field mill sensor interface is presented. The purpose of this study of filter integration techniques is to avoid the challenging and, in some cases, impossible passive element integration process and to incorporate the final filter design in an entirely integrated field mill sensing system with superior performance and an optimized silicon-to-cost ratio. Four different CMOS filter implementations in the 0.18 μm process of XFAB, using OTA (Operational Transconductance Amplifier)-based configurations for passive element replacement in cascaded filter topologies and leapfrog techniques, are compared in terms of noise performance, total harmonic distortion, dynamic range, and power consumption, as well as in terms of integrability, silicon area, and performance degradation at process corners/mismatches. The optimum filter design performance-wise and process-wise is included in the final design of the integrated analog readout of a field mill sensor, and post-layout simulation results of the total circuit are presented.

Analog Sensor Interface for Field Mill Sensors in Atmospheric Applications

An overview of the electric field mill sensor specifications in applications related to the measurement of the atmospheric electric field was conducted. The different design approaches of the field mill sensor interface are presented and analyzed, while the sensitivity-related parameters of a field mill are discussed. The design of a non-complex analog sensor interface that can be employed for the measurement of the electric field in both fair and foul weather conditions, such as thunderstorms, is implemented using discrete components for experimental validation and is optimized in an integrated version in terms of noise and power consumption. Advanced noise simulations are conducted in a 180 nm CMOS process (XH018 XFAB). The energy-autonomous operation of the sensor for extended periods of time is made feasible due to the low power consumption of the front-end circuitry (165 μW at 3 V) as well as the proposed intermittent style of operation of the motor. The total sensing system is low power, and its realization is simple and cost-effective, while also offering adequate sensitivity (45 mV/kV/m), making it comparable to the existing works.

Graphene electric field sensor for large scale lightning detection network

Graphene is widely used in various real-life applications due to its high sensitivity to the change in the carrier concentration. Here, we demonstrate that graphene can be used for implementing a reliable lightning detection network as it shows excellent sensitivity to the electric field of both positive and negative polarities, with a wide range of magnitude. The lowest electric field detected by our graphene sensor is 67 V/m, which is much smaller than the detection limit of previously reported graphene sensors and comparable to that of field mill and MEMS-based sensors. We also present the results of outdoor experiments where the response of the graphene sensor to the atmospheric electric field on a lightning day was tested and found to be in good agreement with the existing field mill sensor.

An Intelligent Lightning Warning System Based on Electromagnetic Field and Neural Network

Prediction of lightning occurrence has significant relevance for reducing potential damage to electric installations, buildings, and humans. However, the existing lightning warning system (LWS) operates using the threshold method and has low prediction accuracy. In this paper, an intelligent LWS based on an electromagnetic field and the artificial neural network was developed for improving lightning prediction accuracy. An electric field mill sensor and a pair of loop antennas were designed to detect the real-time electric field and the magnetic field induced by lightning, respectively. The change rate of electric field, temperature, and humidity acquired 2 min before lightning strikes, were used for developing the neural network using the back propagation algorithm. After observing and predicting lightning strikes over six months, it was verified that the proposed LWS had a prediction accuracy of 93.9%.

First seasonal and annual variations of atmospheric electric field at a subtropical station in Islamabad, Pakistan

The variation of the atmospheric electric field from the ground is analyzed by using an electric field mill sensor for Islamabad, Pakistan. The first early results of atmospheric electric field are presented in this paper. These results are based on fair-weather days for the diurnal, seasonal, and annual variations in Islamabad from 2015 to 2017. The variation in the values of the atmospheric electric field is studied extensively during the monsoon, the pre-monsoon and the winter season. Minimum values are observed during the monsoon season, and maximum values are observed during winter and spring. The measured values of the atmospheric electric field are also compared with the universal standard values of the Carnegie curve. The trend of the diurnal variation shows a sharp single oscillation in fair-weather with a maximum at ∼ 4:00 UT (universal time), which could be due to the influence of local effects such as aerosol.

Model, Design, and Testing of Field Mill Sensors for Measuring Electric Fields Under High-Voltage Direct-Current Power Lines

High-voltage direct-current (HVdc) transmission lines have been implemented in many countries, including Australia, Brazil, China, and Sweden, and the safety concerns as the result of the high electromagnetic-radiation underneath the HVdc lines have garnered increased public attentions. Here, we report on the model, design, and testing of field-mill electric field sensors to measure the electric field at the ground level under the HVdc transmission lines. This study utilized a finite-element analysis method to establish numerical simulation results based on the electrical and mechanical parameters to achieve optimal designs with experimental calibrations. Afterward, these sensors were successfully tested and utilized at the national high-voltage test base.

Atmospheric Electric Field Sensors Network Integration in Brazil

This paper presents the integration details of an operational Atmospheric Electric Field Mill Sensor (EFM) Network for standardized and continuous operation in the region of Sao Jose dos Campos, State of Sao Paulo, Brazil, in order to collect and transmit real time data for studies of atmospheric electric field and support the development of a Lightning Warning System (LWS). Data collection equipments, including EFM sensors from different manufacturers, datalogger, telecommunication by 3G cellular modem and solar power energy subsystems and software were integrated. A set of graphs obtained by interpolating real time data collected by the integrated EFM network combined with lightning location data detected by the Brazilian Lightning Detection System (BrasilDAT) is also presented.

A new South American network to study the atmospheric electric field and its variations related to geophysical phenomena

In this paper we present the capability of a new network of field mill sensors to monitor the atmospheric electric field at various locations in South America; we also show some early results. The main objective of the new network is to obtain the characteristic Universal Time diurnal curve of the atmospheric electric field in fair weather, known as the Carnegie curve. The Carnegie curve is closely related to the current sources flowing in the Global Atmospheric Electric Circuit so that another goal is the study of this relationship on various time scales (transient/monthly/seasonal/annual). Also, by operating this new network, we may also study departures of the Carnegie curve from its long term average value related to various solar, geophysical and atmospheric phenomena such as the solar cycle, solar flares and energetic charged particles, galactic cosmic rays, seismic activity and specific meteorological events. We then expect to have a better understanding of the influence of these phenomena on the Global Atmospheric Electric Circuit and its time-varying behavior.

Data Transmission System of Rotating Electric Field Mill Network Using Microcontroller and GSM Module

Lightning is an environmental phenomena that cause many fatalities and property destructions in Malaysia since the country is located in the high isokeraunic area. To reduce the fatalities an alert system should be developed. The alert system can consist of several Rotating Electric Field Mill sensors which are installed in spread. Data from the sensors must be gathered in a data centre building for observation, analysis, and triggering an alert signal. Therefore, the objective of this work is to develop a data transmission system by using a wireless method. The wireless data transmission system consists of a microcontroller, voltage divider, and GSM module. Hardware and software development is carried out to achieve the objective. Furthermore, to test the transmission system a function generator is connected to the analog digital converter input of the microcontroller. By varying the magnitude of the function generator output an observation on data transmission is carried out. It is found that the magnitude of receiving data which is displayed on the website is exactly the same with the sent data. In here in lab wireless data transmission system devices and a website to observe the transmitted data from Rotating Electric Field Mill sensors has been successfully developed.

Variations of electric field and electric resistivity of air caused by dust motion

AbstractWe report results of a field campaign conducted in the Nevada desert with a suite of electric field instruments consisting of a field mill (FM) and a short dipole antenna (SDA). Furthermore, we show that a combination of the measurements of these two instruments allows the estimation of the electric resistivity of air, an important quantity that is extremely difficult to measure near the Earth's surface. The electric resistivity of air is found to vary between 1.5 · 1013 and 6 · 1013 Ω m and to correlate with changes in electric field. Vertical DC electric fields with amplitudes up to 6 kV m−1 were observed to correspond to clouds of dust blowing through the measurement site. Enhanced DC and AC electric fields are measured during periods when horizontal wind speed exceeds 7 m s−1, or around twice the background value. We suggest that low‐frequency emissions, below ~200 Hz, are generated by the motion of electrically charged particles in the vicinity of the SDA electrode and propose a simple model to reproduce the observed spectra. According to this model, the spectral response is controlled by three parameters, (i) the speed of the charged particles, (ii) the charge concentration, and (iii) the minimum distance between the particle and the electrode. In order to explain the electric fields measured with the FM sensors at different heights, we developed a multilayer model that relates the electric field to the charge distribution. For example, a nonlinear variation of the electric field observed by the FM sensors below 50 cm is simulated by a near‐surface layer of tens of centimeters that is filled with electrically charged particles that carry a predominantly negative charge in the vicinity of the soil. The charge concentration inside this layer is estimated to vary between 1012 and 5 · 1013 electrons m−3.

Retrieving Storm Electric Fields from Aircraft Field Mill Data. Part II: Applications

Abstract The Lagrange multiplier theory developed in Part I of this study is applied to complete a relative calibration of a Citation aircraft that is instrumented with six field mill sensors. When side constraints related to average fields are used, the Lagrange multiplier method performs well in computer simulations. For mill measurement errors of 1 V m−1 and a 5 V m−1 error in the mean fair-weather field function, the 3D storm electric field is retrieved to within an error of about 12%. A side constraint that involves estimating the detailed structure of the fair-weather field was also tested using computer simulations. For mill measurement errors of 1 V m−1, the method retrieves the 3D storm field to within an error of about 8% if the fair-weather field estimate is typically within 1 V m−1 of the true fair-weather field. Using this type of side constraint and data from fair-weather field maneuvers taken on 29 June 2001, the Citation aircraft was calibrated. Absolute calibration was completed using the “pitch down method” developed in Part I, and conventional analyses. The resulting calibration matrices were then used to retrieve storm electric fields during a Citation flight on 2 June 2001. The storm field results are encouraging and agree favorably in many respects with results derived from earlier (iterative) techniques of calibration.

Retrieving Storm Electric Fields from Aircraft Field Mill Data. Part I: Theory

Abstract It is shown that the problem of retrieving storm electric fields from an aircraft instrumented with several electric field mill sensors can be expressed in terms of a standard Lagrange multiplier optimization problem. The method naturally removes aircraft charge from the retrieval process without having to use a high-voltage stinger and linearly combined mill data values. It allows a variety of user-supplied physical constraints (the so-called side constraints in the theory of Lagrange multipliers) and also helps improve absolute calibration. Additionally, this paper introduces an alternate way of performing the absolute calibration of an aircraft that has some benefits over conventional analyses. It is accomplished by using the time derivatives of mill and pitch data for a pitch down maneuver performed at high (>1 km) altitude. In Part II of this study, the above methods are tested and then applied to complete a full calibration of a Citation aircraft.

Ionization of water clusters by collision with surface

New results of the investigations of the phenomenon of the ion formation and separation at the neutral water cluster scattering by solid surface are reported. First, molecular dynamics simulation has shown the possibility of polar dissociation of water molecules in (H2O)n cluster with n = 34 and 64 during their impact with a rigid surface. Second, the current of ions rebound from target and the current to the target at scattering of (H2O)n clusters (up to n = 50000) by various targets are measured. Third, we have measured the water-cluster-induced electrification of the electric field mill sensor, which has been used for the rocket measurement of mesospheric electric field structure in the vicinity of noctilucent clouds (NLC). A comparison between these and rocket measurements shows that the fluctuations of the field mill signal detected when a rocket was passing the NLC layer is a result of the impact of NLC particles on the field mill electrodes.

Aircraft electric field measurements: Calibration and ambient field retrieval

An aircraft locally distorts the ambient thundercloud electric field. In order to determine the field in the absence of the aircraft, an aircraft calibration is required. In this work a matrix inversion method is introduced for calibrating an aircraft equipped with four or more electric field sensors and a high‐voltage corona point that is capable of charging the aircraft. An analytic, closed form solution for the estimate of a (3×3) aircraft calibration matrix is derived, and an absolute calibration experiment is used to improve the relative magnitudes of the elements of this matrix. To demonstrate the calibration procedure, we analyze actual calibration data derived from a Lear jet 28/29 that was equipped with five shutter‐type field mill sensors (each with sensitivities of better than 1 V/m) located on the top, bottom, port, starboard, and aft positions. As a test of the calibration method, we analyze computer‐simulated calibration data (derived from known aircraft and ambient fields) and explicitly determine the errors involved in deriving the variety of calibration matrices. We extend our formalism to arrive at an analytic solution for the ambient field, and again carry all errors explicitly.