Low Speed Operation Research Articles

Water Desalination Plant Fault Detection using Artificial Neural Network

<p>Water famine is very cruel. The desalination plant was brought in to alleviate the water shortage. A desalination plant has been set up in many places around the world. In the view of expanding worldwide need of fresh water, the usage of desalination plant becomes more common. There are more than twenty-five thousand desalination plants around the world. Many industries require treated water for production, water treatment, and other functions. Water quality is occasionally insufficient or does not satisfy the quality criteria for manufacturing causes. So, the enterprises utilize desalination systems to purify water for their own usage. It makes the water safe to drink as well as suitable for a variety of industrial applications. The fault occurring in the desalination plant, it slows down the processing the speed and reduce the output rate. In this study, focuses on the faults like not under system control, electrical fault, pump fault, control valve fault, inaccurate signal, old data fault, derived fault and transmitter fault. The proposed artificial neural network with the single and double component fault (ANN S-DCF) is introduced to detect the faults occurring in the desalination plant. The faults are splitted into two catagories and characteristics of each fault are trained in the artificial neural network. The result of this work achieves the best accuracy comparing to the existing techniques of SVR (support vector regression), PCA (principal component analysis) and DPLS (dynamic partial least square) method. This study achieves the accuracy rate of 96%, precision rate of 93% and sensitivity rate of 95% respectively with low complexity and high operational speed.</p>

High-Frequency Square Wave Injection Sensorless Control Method of IPMSM Based on Oversampling Scheme

In view of the disadvantages of the traditional high-frequency square wave signal injection method in the low-speed operation of high-power interior permanent magnet synchronous motor (IPMSM), such as the large error of rotor position calculation and delay of position update, a method based on high-frequency square wave signal injection is proposed to obtain an effective vector action current through oversampling. When the vector is zero, the current changes to not zero, but when the vector is effective, the current changes greatly. In the traditional sampling and calculation methods, the change of the zero-vector is ignored, resulting in errors, especially in the case of small power, and the errors are more obvious. Through the method of oversampling the current of the effective vector, the high-frequency response current of the effective vector is obtained. Through the reasonable demodulation method, the high-frequency response current of the effective vector is extracted, and then the rotor position information is obtained through the phase-locked loop. On this basis, the influence of the inherent nonlinear characteristics of the motor system and the sampling delay on the calculation of the rotor position is analyzed, and the error is compensated to obtain a more accurate rotor position.

Druggable protein prediction using a multi-canal deep convolutional neural network based on autocovariance method

Drug targets must be identified and positioned correctly to research and manufacture new drugs. In this study, rather than using traditional methods for drug expansion, the drug target is determined using machine learning. Machine learning has generated significant interest and desire in recent years and extensive research due to its low cost and speed of operation. As a result, it is critical to develop an intelligent classification system for drug proteins. This study proposes two distinct models for the prediction of druggable protein classes based on the deep learning method. The translation of drug-protein sequences is based on six physicochemical properties of amino acids. Following the application of the autocovariance method, converted sequences are used as fixed-length input vectors in deep stacked sparse auto-encoders (DSSAEs) network. The coded protein sequences are also considered and utilized as a six-channel input vector for the deep convolutional neural network model. The experimental results contributing to the deep convolution model are more efficient than previous studies for classifying druggable proteins. The proposed approach achieved a sensitivity of 96.92%, a specificity of 99.51%, and an accuracy of 98.29%.

Clamping Modulation Scheme for Low-Speed Operation of Three-Level Inverter Fed Induction Motor Drive With Reduced CMV

This article introduces a family of carrier-based pulse width modulation (PWM) schemes for three-level (3 L) inverter fed motor drive for low-speed operation. The proposed PWM in dual-inverter topology (DIT) simultaneously clamps two phases of each inverter throughout the fundamental cycle, which reduces the switching transition in the pole voltage and common-mode voltage (CMV). Four PWM variants in the family (i.e., PWM-1–PWM-4) are discussed and compared with conventional discontinuous PWM schemes. A mapping of the gating pulse is derived to extend the proposed PWM to a classical 3 L inverter fed star-connected motor drive. The gating pulses are generated using triangular carrier comparison with synchronous sampling. The steady-state and dynamic performances of PWM are validated both in DIT fed open-end winding induction motor (IM) drive and neutral point clamped (NPC) inverter fed star-connected IM drive. It is observed that the proposed PWM gives inherent capacitor voltage balance in the NPC topology. PWM-1 has a higher linear modulation range than conventional zero clamp PWM and leads to reduced CMV in the NPC topology. PWM-2 and PWM-3 give reduced CMV in DIT. PWM-4 has fault tolerance to single-phase open-switch and short-switch failure in DIT.

Research on displacement fluctuation reduction for hydrostatic lead screw feed system at low-speed operation under variable loads

This study proposes a method to reduce the displacement fluctuation of hydrostatic lead screw feed systems under ultralow velocity and subjected to different loads by means of a dual-drive hydrostatic screw-nut pair (DDHSNP). The differential compound principle of DDHSNP and the wedge-shaped oil film gap are used to generate the hydrodynamic effect of lubricating film while ensuring the worktable is fed at extremely low speed. After that, the model of the DDHSNP, considering the pitch errors and nut posture errors, is established based on the equation of motion, the Reynolds equation, and the Euler equation. Finally, a comparative experiment is conducted to demonstrate the effectiveness of the proposed method. The results indicate that: (a) The nut's posture errors have little effect on the displacement fluctuation of the hydrostatic lead screw feed system. (b) The DDHSNP can significantly reduce the displacement fluctuation of the hydrostatic lead screw feed system under variable loads and low speeds. This research is an excellent improvement for the superior motion characteristics of the hydrostatic lead screw at low speed.

Surface Permanent Magnet Synchronous Motors’ Passive Sensorless Control: A Review

Sensorless control of permanent magnet synchronous motors is nowadays used in many industrial, home and traction applications, as it allows the presence of a position sensor to be avoided with benefits for the cost and reliability of the drive. An estimation of the rotor position is required to perform the field-oriented control (FOC), which is the most common control scheme used for this type of motor. Many algorithms have been developed for this purpose, which use different techniques to derive the rotor angle from the stator voltages and currents. Among them, the so-called passive methods have gained increasing interest as they do not introduce additional losses and current distortion associated instead with algorithms based on the injection of high-frequency signals. The aim of this paper is to present a review of the main passive sensorless methods proposed in the technical literature over the last few years, analyzing their main features and principles of operation. An experimental comparison among the most promising passive sensorless algorithms is then reported, focusing on their performance in the low-speed operating region.

Investigating the Pollutants of Marine Shipping Emissions Along the East China Sea by Combining in-situ Measurements and Automatic Identification System

Marine shipping emissions have important impacts on air quality and climate. This type of anthropogenic emission remains largely unclear due to complex vessel types and activities. A coastal site near the Ningbo-Zhoushan port along the East China Sea was selected for this study, representing one of the hotspot regions globally with the most intensive shipping activities, in combination with vessels for both domestic and international transportation. Long-term temporal variations in key gaseous and particulate pollutants were obtained at the site using in-situ measurements, and the vessel speed associated with each classified vessel type was obtained according to the automatic identification system (AIS). In combination of backward trajectories, we were able to identify the periods predominated by the surrounding vessel emissions (in warm seasons, dominated by vessels in full operation or idle mode) or influenced by continental outflow (in cold season). We found that emissions of sulphur dioxide (SO2), nitrogen oxides (NOx), and black carbon (BC) aerosol were highly correlated with high-speed vessels, whereas carbon monoxide (CO) was likely related to lower operation speed. The total particulate matter (PM) was not directly linked to vessel activities. The enhancement factor in operation mode compared to that in idle mode was approximately 1-4 for most pollutants. This direct ambient observation of the emissions from a range of mixed vessel types may provide a basis for evaluating the shipping emission inventory.

Elimination of Dead Time Effects on Common Mode Voltage in an Open-End Winding Induction Motor Drive Under Low Speed Operation Using a Simplified Model Predictive Control

In this article, a simplified model predictive current control (MPCC) for a three-level open-end winding induction motor drive mitigating the dead time effects on common mode voltage (CMV) in the low speed operation of the motor is proposed. The traditional current based objective function is replaced with an equivalent voltage based objective function, and an additional term indicating the nonzero CMV during dead time is added to achieve complete CMV elimination. Further, a sector-based selection of candidate switching states is employed to reduce the computational burden. It is also shown that the constraint on eliminating the dead time effect on CMV heavily deteriorates the performance of the drive at higher speeds and a smooth transition with and without the constraint is also demonstrated. The envisaged MPCC is simulated in MATLAB and is experimentally verified using TMS320F28377S launchpad. The proposed MPCC gives a massive reduction in the computational burden compared to the conventional MPCC without sacrificing the motor drive performance.

An Algorithm for Offline Measurement of Motor Stator Resistance and Voltage Drop Across Inverter Switches for Washing Machine Drives

The knowledge of the exact value of motor phase resistance is extremely important for modern electrical drives, which use it for tuning of current controllers, position estimators, temperature monitoring, and so on. At the same time, the value of voltage drop across inverter switches is necessary for providing proper and efficient control, especially in the low-speed region, where the impact of system nonlinearities is significant. This article proposes a novel algorithm for the offline measurement of motor resistance and voltage drop across inverter switches, which significantly improved the performance of washing machines in open-loop starting and low-speed operation. The proposed technique uses two step injection of dc current into stator windings, which provides data for the estimation of resistance and voltage drop. This article describes traps and pitfalls on the way of implementation and tuning and provides recommendations on avoiding them. After analysis of detailed experimental results, the author gives recommendation on a selection of algorithm parameters in order to provide low estimation errors. Following successful implementation and a series of tests, this technique has been accepted for mass production and has become an inevitable part of the control system of washing machines.

An Unequal Split Dual Three-Phase PMSM With Extended Torque-Speed Characteristics for Automotive Application

High gradability and wide operating speed range are critical requirements for heavy-duty trucks and off-road electric vehicles. The motor power rating used for such applications can be reduced by selecting a motor with a wide constant power speed range (CPSR). However, permanent magnet synchronous motors (PMSMs) with wide CPSR have limited overloading capability. The operating speed range, as well as the overloading capability, can be improved by increasing the base speed of a low CPSR three-phase PMSM, which results in overdesign. Further, using multigear transmission to achieve a wide operating speed range with a low power motor increases system weight, drivetrain complexity, and maintenance requirement. This article proposes a dual three-phase interior PMSM with an unequal split winding configuration and zero degree winding displacement (uneq0-PMSM) to extend the constant power region and improve the overloading capability without any machine overdesign. The winding split ratio for the proposed configuration is decided to achieve the desired torque-speed characteristic shape for a given requirement. Further, a transition algorithm for smooth changeover between two-winding operation during low-speed and one-winding operation for high-speed is also proposed. The proposed concepts are experimentally validated on a 1.5-kW uneq0-PMSM with 1:3 winding split ratio.

Faster Measurement for Formaldehyde Emissions from Veneered Particleboard Based on the Standardized Desiccator Method

Desiccator method is a fast and effective way to measure formaldehyde emissions from wood-based panels. This method is popular in the Chinese furniture industry and testing institutions. It is also an important method for production control due to its characteristics of low cost, fast speed, and simple operation. In order to further increase the measurement speed of the desiccator method, this study focuses on the impact of temperature and time conditions in regard to standard GB/T 17657-2013. The corresponding relationships for the measurement of formaldehyde emissions between the standardized desiccator method and those under different temperature and time conditions were studied. Four different experimental conditions were used: 60 °C for 6 h, 40 °C for 6 h, 43 °C for 4 h, and 45 °C for 4 h. The results showed that under 40 °C for 6 h the formaldehyde emissions measured using desiccator method were about twice as much as those under 20 °C for 24 h, at a correlation coefficient of R = 0.820. Under 45 °C for 4 h, the formaldehyde emissions measured using desiccator method were almost near equilibrium to emissions under 20 °C for 24 h, which was supported by a correlation coefficient of R = 0.955. A corresponding relationship between the formaldehyde emissions measurement results under these two conditions and those under the standardized conditions was observed. This relationship can be applied in the actual production control in the furniture industry in order to shorten the formaldehyde measurement time from 24 h to 6 h and 4 h, which can greatly improve measurement efficiency.

Hybrid Pulse High-Frequency Voltage Injection Control Algorithm of Sensorless IPMSM for Vehicles

A hybrid pulse vibration high-frequency voltage signal injection method is proposed to solve the problems that the conventional sensorless control algorithm of vehicle IPMSM may generate a large estimated rotor position error and opposite directions in identifying the polarity of magnetic poles under zero-speed and high-torque starting and low-speed operation. The magnetic pole polarity is identified by the saturation effect of the flux chain by injecting a high-frequency sinusoidal voltage signal and opposite pulse voltage signal into the axis of the assumed coordinate system simultaneously. Subsequently, the position relationship between the assumed axis and the actual d axis is studied in accordance with the amplitude of response current to acquire the rotor position and speed information. The simulation and experimental results suggest that the algorithm is capable of accurately identifying the magnetic pole polarity and estimating the rotor position at zero speed and low speeds, starting the motor smoothly at zero speed, and then operating the motor stably at low speeds.

Noise analysis of MoTe2-based dual-cavity MOSFET as a pH sensor

Field-effect transistor (FET) pH sensors have been studied for a long time because of their low cost, sound sensitivity, and high operational speed. Recently, transition metal dichalcogenides (TMD) materials such as MoTe2, MoS2, among others, have emerged as promising channel materials for developing energy-efficient electronic devices. TMD-based sensors have shown excellent results because of the high surface area–volume ratio and better bio-specific interaction. This paper proposes and analyzes a MoTe2 channel–based dual-cavity (DC) accumulation metal oxide semiconductor field effect transistor (MOSFET) as a pH sensor. For a comprehensive study, a pH-FET noise model has been considered to investigate the amount of noise associated with the proposed FET under various ionic concentrations and device dimensions. The electrolytic semiconductor has been modeled based on ion dynamics for the simulation study. A site-binding model has been incorporated to capture the surface charge density fluctuations at the interface of electrolyte and gate oxide for different pH values. The effect of gate length scaling on the device performance is studied to comprehend its scalability. With this MoTe2-based DC accumulation MOSFET sensor, a peak threshold sensitivity of 77 mV pH−1 has been achieved. To provide a comparative performance analysis of the proposed work, a benchmarking figure is included and a detailed fabrication methodology is also presented in this paper. All simulations are performed with an experimentally calibrated setup in SILVACO Technology Computer Aided Design (TCAD).

Research on robust control of continuous rotary electro-hydraulic servo motor based on AdaBoost prediction

A robust control strategy based on Adaboost prediction was proposed for the effects of dynamic uncertainty, parameter perturbation and nonlinear factors such as friction and leakage on the robustness and low-speed performance of the electro-hydraulic servo system. Based on the establishment of the Pol-Ind friction model, according to the mathematical model of the continuous rotary electro-hydraulic servo motor, the structural uncertainty model of the system under parameter perturbation and external perturbation and the generalized state equation of the system are established. The robust controller is designed according to the [Formula: see text] control theory. The system feedback mechanism is designed by using the AdaBoost based on the RBF neural network algorithm. The real-time input and output of the system are used as the training sample set for repeated training, and the multiple weak neural network predictors obtained by training are used to form a strong predictor to calculate the forecast output and error of the electro-hydraulic servo system, and the robust controller was used for real-time control. Simulation and experiment show that: compared with the wavelet neural network control, the robust controller based on AdaBoost prediction has a good tracking performance to the slope signal with an input signal of 0.001°/s, and has a high response speed to sinusoidal signal. Under the condition of satisfying the requirement of double 10 index, the maximum response frequency reaches 15 Hz. It can effectively improve the low-speed performance and anti-interference ability of the electro-hydraulic servo system, greatly improve the robustness of the system and expand the frequency band of the system.

Mode transition analysis of a turbine-based combined-cycle considering ammonia injection pre-compressor cooling and variable-geometry ram-combustor

Mode transition (MT) is a significant process in the turbine-based combined-cycle (TBCC) involving the co-operation of high-speed and low-speed channels. To improve the thrust pinch caused by the deviation of the turbine and ramjet from the design point, a novel TBCC engine with ammonia mass injection pre-compressor cooling (Ammonia MIPCC) and variable-geometry ram-combustor (VGRC) is used to extend the operation envelope of the MT. CFD simulations and shock loss calculations are used to construct combined dual-channel inlet model. Through simulation, we find that the Ammonia MIPCC can reduce the pre-compressor temperature, improve the compressor efficiency, and increase the turbine's specific thrust. Meanwhile, increasing the ramjet combustor expansion ratio (CER) helps to alleviate the inlet unstart and extend the low-speed operating boundary of the ramjet. Furthermore, the extension of the operating envelope for TBCC under the effects of ammonia injection and CER is investigated. Based on specific thrust and specific impulse, the optimal starting Mach number field for MT process is studied, and the corresponding TBCC thrust is given. Overall, the results show that the optimal starting Mach number field for the MT of the proposed TBCC is 2.85–3.2, and two-stage sub-engines have high thrust performance in this range.

A modified CPS-PWM for capacitor voltage reduction of MMC based variable speed drive

<span>In recent years, modular multilevel converters (MMC) have become one of the most popular multilevel converter topologies. Despite its growing popularity, MMC is still less widespread in variable speed drives (VSDs) applications. The reason for this is that the voltage ripple of the MMC submodules (SM) increases during the low-speed constant torque operation. In this paper, carrier phase shift-pulse width modulation (CPS-PWM) is modified to reduce the average voltage of SM and thus accommodate more ripples without exceeding the maximum SM voltage. The proposed method does not involve the injection of circulating current components, thereby resulting in less power loss. In addition to that, the necessity for increasing the SM capacitor rating during low-speed operation is not required. Extensive simulation has been conducted under various speed commands to validate the effectiveness of this method.</span>

Dynamic Response of HTS Pinning Maglev System Under High Frequency Excitation

The full-size high temperature superconducting (HTS) pinning magnetic levitation (maglev) prototype train was launched in SWJTU, Chengdu, China in 2021. This prototype has shown the basic load and low speed operation capacity of HTS pinning maglev train. Hence, the next important issue should be its dynamical performance under high-speed. Moreover, in the same track condition, higher speed usually brings higher frequency excitation, which becomes the major vibration cause of the HTS pinning maglev system. Therefore, this paper will mainly focus on this point to study the dynamic response of the HTS pinning maglev system under high frequency. Initially, an experiment is designed to measure the vibration response signal under the external excitation in different directions. Secondly, the responses of the system in each direction under different excitation frequencies are compared. Finally, the vertical, lateral and coupling response of the system under high frequency in different field cooling height (FCH) are analyzed. The result verifies that the HTS pinning maglev can effectively isolate the high frequency vibration. And compared to the vertical excitation, the lateral excitations can affect the dynamic performance of the system to a greater extent. This study suggests the smoothness requirement of the operating line in high-speed, as well as providing references for future dynamic studies and design of HTS pinning maglev system.

Low power high-speed CNFET-based full adder

This study proposes a 1-bit Full Adder using Carbon Nanotube-FET (CNFET) with low power, fast speed, and excellent performance for a range of electrical applications. The suggested Full Adder has two elements: sum and cout (FA). This design likewise exploits the advantagesof the unique characteristics ofmetal oxide-FETs like CNFETs. These CNFETs have the ability to change their threshold voltage by altering the diameter of carbon nanotubes to obtain their required voltage levels and great performance. The simulations presented in this paper use 32-nm CNFET technology in the Cadence Virtuoso EDA tool. When compared to the classical Si MOSFET-based Full Adder, simulation outcomes demonstrate the suggested design is better in aspects of speed, power, and energy.

Experimental assessment and feedforward control of backlash and stiction in industrial serial robots for low-speed operations

ABSTRACT Serial robots have been successful in numerous applications; however, their limited motion accuracy hinders the potential for high precision robotic machining. Among the many sources of error in robot movement, non-linearities at robot joints, namely backlash and stiction/friction, are yet to be thoroughly investigated and addressed. When a robot joint reverses, backlash-induced excitation switches direction and stiction induces localized errors that occur over a short duration. Together, backlash and stiction from joint reversal lead to significant positional errors. This paper closes the research gap by proposing feedforward backlash and stiction compensation with a focus on suppressing errors during joint reversals. The controllers are designed using experimental studies of robot joints and the nominal tool centre point (TCP) trajectories. Based on the robot kinematics, the strategy interpolates the nominal trajectories to ensure accurate identification of joint reversals along the path, and therefore provides optimal error compensation with minimum latency. The performance of the controller is evaluated in single axis tests for suppressing backlash in static conditions and in multi-axis path tests for suppressing backlash and stiction in continuous motions. The experimental results show that the feedforward compensation greatly improves the robot accuracy during joint reversal, reducing errors by more than 70%.

Low-voltage IPMSM sensorless control strategy based on high-frequency square-wave injection

Aiming at the low power supply voltage of 12 V and 24 V, low-salience and low-speed performance of parts such as water pumps and fans in the automotive field, to improve the accuracy of angle and speed identification, a sensorless control strategy based on the high-frequency square-wave injection is introduced. The control and angle signals are demodulated by two consecutive samples at the adjacent times, which effectively avoids the use of filters, greatly improves the bandwidth of double closed-loop control, simplifies the signal demodulation process, and carries out verification and analysis through the MATLAB/Simulink simulation model.