Descriptive IoT Based Design and Implementation of a 3-Input Automatic Transfer Switch with Data Logging Features

Electricity is crucial for critical sectors such as banking, healthcare, education, and business. However, in developing nations like Cameroon, persistent power fluctuations and outages present significant challenges, leading to communication disruptions, food spoilage, water supply interruptions, and financial losses. This study proposes a novel solution: a three-input automatic transfer switch integrated with Internet of Things (IoT) and data logging capabilities. The system automatically switches between three independent power sources based on priority and availability, employing electromechanical contactors, relays, and timers for seamless switching. It incorporates ATMEGA328P microcontrollers, a GSM module for communication, and an SD card module for efficient data logging. Safety measures, such as miniature circuit breakers, voltage monitoring relays, and proper grounding, ensure user protection and system integrity. A user-friendly mobile application enables remote manual switching and real-time system information requests, while SMS notifications inform consumers about power source changes. The system has a power rating of 4.752 kW, accommodating a maximum continuous load of the same value. Voltage dividers provide a reliable 3.37 VDC output from a 12 VDC input, and data logging operates effectively by storing system data onto an SD card every 1.5 seconds. Comprehensive testing validates the system’s performance, with an average percentage error of 2.31% compared to actual values, falling within an acceptable range. This solution distinguishes itself by incorporating modern technologies like data logging and IoT, addressing the limitations of existing alternatives.

Preliminary Study on the Differences between Automatic-observed and Manual-observed Wind Speed and Its Correction

Comparing and analyzing the difference between automatic-observed and manual-observed wind speed based on the wind speed parallel observations in two methods, we find that many elements can influence the difference between automatic-observed and manual-observed wind speed, including the levels of speed wind, observation instruments and different regions. According to these elements, correction has been conducted, and find that the correction according to the level of wind speed has the best correction effect.

Comparison of Manual and Automatic Methods for Measurement of Methane Emission from Rice Paddy Fields

S The methane emission flux from rice paddies was simultaneously measured with automatic and manual methods in the suburban of Suzhou. Both methods were based on the static chamber/GC-FID techniques. Detail analysis of the experimental results indicates: a) The data of methane emission measured with the automatic method is reliable. b) About 11 or 19 o′clock of local time is recommended as the optimum sampling time for the manual spot measurement of methane emission from rice paddies. The methane emission fluxes measured by manual sampling at local time other than the optimum time have to be corrected. The correction coefficient may be determined by automatic and continuous measurement. c) In order to get a more accurate result, an empirical correction factor, such as 18%, is recommended to correct the seasonally total amount of measured methane emission by enlarging the automatically measured data or reducing the manually measured ones.

Enhancing manual P-phase arrival detection and automatic onset time picking in a noisy microseismic data in underground mines

Accurate detection and picking of the P-phase onset time in noisy microseismic data from underground mines remains a big challenge. Reliable P-phase onset time picking is necessary for accurate source location needed for planning and rescue operations in the event of failures. In this paper, a new technique based on the discrete stationary wavelet transform （DSWT）and higher order statist!cs, is proposed for processing noisy data from underground mines. The objectives of this method are to （1） Improve manual detection and tPicking of P-phase onset; and （ii） provide an automatic means of detecting and picking P-phase onset me accurately. The DSWT is first used to filter the signal over several scales. The manual P-phase onset detection and picking are then obtained by computing the signal energy across selected scales with frequency bands that capture the signal of interest. The automatic P-phase onset, on the other hand, is achieved by using skewness- and kurtosis-based criterion applied to selected scales in a time-frequency domain. The method was tested using synthetic and field data from an underground limestone mine. Results were compared with results obtained by using the short-term to long-term average （STA/LTA） ratio and that by Reference Ge et al. （2009）. The results show that the me!hod provides a more reliable estimate of the P-phase onset arrival than the STA]LTA method when the signal to noise ratio is very low. Also, the results obtained from the field data matched accurately with the results from Reference Ge et al. （2009）.

Design and Simulation of an Audio Signal Alerting and Automatic Control System

A large part of our daily lives is spent with audio information. Massive obstacles are frequently presented by the colossal amounts of acoustic information and the incredibly quick processing times. This results in the need for applications and methodologies that are capable of automatically analyzing these contents. These technologies can be applied in automatic contentanalysis and emergency response systems. Breaks in manual communication usually occur in emergencies leading to accidents and equipment damage. The audio signal does a good job by sending a signal underground, which warrants action from an emergency management team at the surface. This paper, therefore, seeks to design and simulate an audio signal alerting and automatic control system using Unity Pro XL to substitute manual communication of emergencies and manual control of equipment. Sound data were trained using the neural network technique of machine learning. The metrics used are Fast Fourier transform magnitude, zero crossing rate, root mean square, and percentage error. Sounds were detected with an error of approximately 17%;thus, the system can detect sounds with an accuracy of 83%. With more data training, the system can detect sounds with minimal or no error. The paper, therefore, has critical policy implications about communication, safety, and health for underground mine.

Method of Predicting Water Content in Crude Oil Based on Measuring Range Automatic Switching

Water content in output crude oil is hard to measure precisely because of wide range of dielectric coefficient of crude oil caused by injected dehydrating and demulsifying agents.The method to reduce measurement error of water content in crude oil proposed in this paper is based on switching measuring ranges of on-line water content analyzer automatically.Measuring precision on data collected from oil field and analyzed by in-field operators can be impressively improved by using back propogation （BP） neural network to predict water content in output crude oil.Application results show that the difficulty in accurately measuring water-oil content ratio can be solved effectively through this combination of on-line measuring range automatic switching and real time prediction,as this method has been tested repeatedly on-site in oil fields with satisfactory prediction results.

Fabrication of automatic switch for AC-DC completely automated measurement system at NIS

A fast automatic AC-DC switch is designed and fabricated mainly by a microcontroller and three double poles single throw reed relays.This new switch is introduced to establish a fully automated system for AC-DC measurements through ACDC transfer standards for the first time at the National Institute for standards(N IS)in Egypt.The implemented circuit of theautomatic AC-DC switch and its protection are presented in details.An AC voltage source is calibrated against DC voltagesource by using the demonstrated automatic switch as an application The calibrated voltage ranges are2V,6V,20V and60V as examples.The uncertainty budget is also evaluated for the calibrated values.

Towards Increasing Data Availability for Meteorological Services: Inter-Comparison of Meteorological Data from a Synoptic Weather Station and Two Automatic Weather Stations in Kenya

Meteorological data is useful for varied applications and sectors ranging from weather and climate forecasting, landscape planning to disaster management among others. However, the availability of these data requires a good network of manual meteorological stations and other support systems for its collection, recording, processing, archiving, communication and dissemination. In sub-Saharan Africa, such networks are limited due to low investment and capacity. To bridge this gap, the National Meteorological Services in Kenya and few others from African countries have moved to install a number of Automatic Weather Stations (AWSs) in the past decade including a few additions from private institutions and individuals. Although these AWSs have the potential to improve the existing observation network and the early warning systems in the region, the quality and capacity of the data collected from the stations are not well exploited. This is mainly due to low confidence, by data users, in electronically observed data. In this study, we set out to confirm that electronically observed data is of comparable quality to a human observer recorded data, and can thus be used to bridge data gaps at temporal and spatial scales. To assess this potential, we applied the simple Pearson correlation method and other statistical tests and approaches by conducting inter-comparison analysis of weather observations from the manual synoptic station and data from two Automatic Weather Stations (TAHMO and 3D-PAWS) co-located at KMD Headquarters to establish existing consistencies and variances in several weather parameters. Results show there is comparable consistency in most of the weather parameters between the three stations. Strong associations were noted between the TAHMO and manual station data for minimum (r = 0.65) and maximum temperatures (r = 0.86) and the maximum temperature between TAHMO and 3DPAWS (r = 0.56). Similar associations were indicated for surface pressure (r = 0.99) and RH (r > 0.6) with the weakest correlations occurring in wind direction and speed. The Shapiro test for normality assumption indicated that the distribution of several parameters compared between the 3 stations were normally distributed (p > 0.05). We conclude that these findings can be used as a basis for wider use of data sets from Automatic Weather Stations in Kenya and elsewhere. This can inform various applications in weather and climate related decisions.

Discuss of Key Issue for Automatic BATS Control in Regional Power Grid

Busbar Automatic Transfer Switch (BATS) is very important for power distribution reliability. However, BATS can’t consider whether it cause overloading of devices after it acts. In this paper, we introduce the design principle of Automatic BATS control from whole architecture including its function, strategy and a rule of on-off. On the other hand, the running experience and effect is also introduced. Site operation shows that the proposed method is feasible and it can ensure power grid reliability.

基于变分模态分解和改进灰狼算法优化深度置信网络的自动转换开关故障识别

自动转换开关(ATSE)是保证系统连续供电的设备,对其进行健康监测和故障诊断对系统的稳定运行具有重要意义。为了实现对ATSE的非侵入式故障识别,该文提出一种基于电流信号变分模态分解(VMD)的特征提取和改进灰狼算法(IGWO)优化深度置信网络(DBN)相结合的故障诊断方法。该方法首先利用样本熵确定VMD分解次数并对故障电流进行分解;其次对分解后得到的本征模态函数进行小波包能量的提取,并利用IGWO对DBN网络结构参数进行优化;最后通过DBN将电流能量特征与ATSE的故障类型建立起映射关系从而完成最终的故障识别。所提IGWO采用了分段调节与非线性递减的衰减因子相结合的策略,以平衡算法全局搜索和局部搜索能力;并采用莱维飞行更新探狼的移动位置,来避免算法陷入早熟收敛。实验结果表明,该算法不仅能显著提高前期对参数寻优的训练速度,后续泛化实验的故障分类准确率也有98.78%的良好表现。

不同核酸提取方法对HBV-DNA检测性能验证情况分析

目的评估2种乙型肝炎病毒(HBV)-DNA提取方法及2家检测试剂的性能,有助于选择优化提取试剂和检测试剂。方法2023年4月采用达安全自动核酸提取仪提取法(磁珠法)和手工提取法(一步法),并用达安和圣湘2种HBV-DNA试剂检测,对其进行精密度、正确度、线性范围、检出限及抗干扰能力等性能进行验证和评价。结果达安全自动核酸提取仪提取达安试剂检测、手工提取达安试剂检测和手工提取圣湘试剂检测在精密度、正确度、线性范围、检出限方面验证结果均达标;达安全自动核酸提取仪提取圣湘试剂检测在低值检测中变异系数大于5%,最低检测限验证不合格;抗干扰能力方面,全自动核酸提取仪提取的2.0 g/dL血红蛋白浓度的样本用达安和圣湘试剂检测结果均不受影响。手工提取甘油三酯浓度达3000 mg/dL的样本用达安和圣湘试剂检测的结果均不受影响。结论不同厂家的提取和检测试剂避免混用,达安和圣湘试剂对HBV-DNA定量检测的结果均符合要求。

自动滴定仪测定土壤有机碳及其组分的方法优化

土壤有机碳及其组分(颗粒有机碳、矿物结合态有机碳等)是反映土壤质量的关键性指标,开展准确高效地测定这些指标对相关研究具有重要意义。自动滴定仪与传统人工滴定相比,人员工作强度低,检测准确,但检测效率不及人工滴定的30%。为解决此问题,本文探讨了4种氧化剂加入量对测定有机碳的影响,研究了提前预加滴定液对检测效率提高的效果。最终优选氧化剂加入量为2mL,预加滴定液量以空白样滴定量的1/3计,建立了用于测定土壤有机碳的自动滴定仪法。采用有机碳不同水平的土壤样品和标准物质对方法进行验证,并与人工滴定进行比较,结果表明,自动滴定仪法与人工滴定法无显著性差异,方法的相对标准偏差(RSD,n=6)在2.10%~12.96%,加标回收率在93.37%~98.06%,标准物质相对误差为4.31%~4.79%;优化后的自动滴定法单个试样滴定用时由11min缩短到3.5min,整体检测效率高于人工滴定,而试剂耗用量仅是人工滴定法的40%。自动滴定仪法显著提升了有机碳的检测能力。

触发开关自动化装配与调测系统设计

在触发开关生产过程中,实现自动化和智能化是提升产能保证装调质量的先决条件。针对触发开关自动装调和检测的问题,设计一套触发开关自动化装调系统,提出一种动作过载调测自主学习算法,实现触发开关螺钉拧紧距离的自动调测。利用机器视觉方法对装配过程中的关键部件进行缺陷检测,以快速完成装配质量检测。该系统可实现触发开关的自动装配、铆接、检测、调测、灌封和固化等功能。

自动粪便分析仪与人工复核法检测粪便结果的比较分析

目的比较自动粪便分析仪与人工复核法两种粪便检测方法的检验效果。方法收集2022年9月—2023年8月三明市第二医院就诊患者的9402份新鲜粪便标本,分别使用FA160自动粪便分析仪和人工复核法检测粪便有形成分(白细胞、红细胞、脂肪球、真菌)和隐血,记录两种方法的检测结果并进行统计学分析。结果自动粪便分析仪检测白细胞、红细胞、脂肪球、真菌和隐血的阳性检出率分别为4.90%、2.67%、6.31%、4.54%、25.34%,人工复核法阳性检出率分别为4.17%、2.22%、5.55%、5.29%、25.23%,自动粪便分析仪对粪便有形成分的阳性检出率除真菌略低于人工复核外,其他各项指标均高于人工复核,且差异均有统计学意义(均P<0.05),而粪便隐血试验的阳性检出率比较差异无统计学意义(P>0.05)。以人工复核法为标准,自动粪便分析仪检测白细胞、红细胞、脂肪球、真菌、隐血的阳性符合率分别为91.07%、96.17%、94.83%、78.07%、98.19%;阴性符合率分别为98.85%、99.46%、98.90%、99.56%、99.25%;阳性预测值分别为77.44%、80.08%、83.47%、90.87%、97.77%;阴性预测值分别为99.61%、99.91%、99.69%、98.79%、99.39%。结论自动粪便分析仪与人工复核法的检测结果虽然符合率较高,但还存在漏检和误检。因此对自动分析结果必须进行人工复核,提高检测结果的准确性,为临床提供可靠的参考依据。

软式内镜管道自动清洗装置与手工操作清洗在消化内镜管道刷洗中的消毒质量对比

目的:观察软式内镜管道自动清洗装置与手工操作清洗在消化内镜管道刷洗中的消毒质量。方法:选取2022年10月—2024年2月江苏省中医院消化内镜中心70条次消化内镜为研究对象,以随机数表法分成观察组(n=35)与对照组(n=35)。观察组采用软式内镜管道自动清洗装置清洗消化内镜,对照组采用手工操作清洗消化内镜。比较两组内镜清洗质量、清洗前后内镜微生物与芽孢水平。结果:两组内镜表面及阀门目测法清洗合格率均为100%。两组三磷酸腺苷(ATP)生物荧光测定法表面、阀门清洗合格率比较,差异无统计学意义(P>0.05);观察组ATP生物荧光测定法管道清洗合格率高于对照组(P=0.046)。清洗前,两组菌落单位(CFU)、相对光单位(RLU)、芽孢水平比较,差异无统计学意义(P>0.05);清洗后,观察组CFU、RLU、芽孢水平低于对照组(P<0.05)。结论:软式内镜管道自动清洗装置与手工操作清洗对消化内镜表面及阀门的清洗效果相当,但软式内镜管道自动清洗装置对消化内镜管道的清洗质量更佳,能有效清除内镜微生物与芽孢。

一种拓展数据采集系统动态范围的方法研究

针对当前台站需要使用两套采集系统分别监测记录微弱信号与大地震信号这一问题,提出一种自动切换采集模式的数据采集方法。在正常情况监测微弱信号时,采集系统使用小信号通道ADC分级采样,而当发生大震、巨震时,系统自动切换使用大信号通道ADC采样。实验表明,采集系统单个AD数据采集模式在100 Hz采样时,动态范围达128 dB,而使用双AD数据采集模式在100 Hz采样时,动态范围可达158 dB。改进后的数据采集方法可有效提高地震信号采集动态范围,在不增加硬件成本情况下,能在一定程度上改善数据采集系统的性能。

一种有源天线温度试验自动测试系统设计

某型有源天线批生产产品数量多,由于温度试验周期长,温度试验成为天线均衡高效生产的一个瓶颈环节。为解决生产需求,研制一种天线专用温度测试系统。分析了天线温度试验测试项目和测试原理,梳理现有测试设备测试效率低下的原因,集中讨论了研制设备硬件组成、测试功能、软件设计和自动化要求,重点研究了屏蔽装置以及对接工装的设计。研制的测试系统基于VS2015软件,通过上位机控制电源切换单元、波控切换单元和射频切换单元完成产品分时自动测试。研制屏蔽装置,不仅完成了天线在温箱内接收和发射功能测试,还保证了测试结果的真实有效。设计对接夹具,方便产品对接和更换。该温度测试系统具有测试时间短、测试产品多、自动化程度高的优点,在生产线投入使用后,效果良好,解决了天线温度生产瓶颈。

继电保护测试仪自动检测系统设计

继电保护测试仪是对继电保护装置调试和检验的重要仪器。为了进一步提高继电保护测试仪的检测精度、稳定性和检测效率,设计了基于LabVIEW的继电保护测试仪自动检测系统。该系统采用LabVIEW模块化的编程思想,实现继电保护测试仪的自动检测、手动检测、保存报告等功能。为了解决继电保护测试仪的输出为三相,而万用表和示波器仅支持单相测试的问题,设计了输出转换装置。基于转换装置,可以在测试开始前一次性完成所有接线,并在测试过程中根据不同校准项目进行测试回路自动切换。功能测试结果表明,该系统能满足检验标准化、报告标准化和闭环自动测试要求。该系统对其他二次测量设备的自动检测校准有一定的借鉴意义。

基于潜蛟P100的渔网缝补机械臂设计

为解决传统手工修补渔网效率低下且成本较高的问题,设计了一种可自动缝补渔网的机械臂。该机械臂以STM32F103C8T6为主控制器,通过红外传感器、电机执行器和通信模块实现其功能。红外传感器模块负责检测渔网破损位置,电机执行器模块驱动6个轴上的电机使机械臂能灵活地将缝补装置送到预设节点处,通信模块负责将检测的渔网破损信息传输给控制器进行处理。实验测试结果表明,所设计的机械臂通过六自由度的旋转,实现每分钟4~5个简单破损网孔的修补。与传统的手工修补方法相比,提高了渔网修补效率和质量、降低了人工成本,具有明显优势.

花瓣型配电网区域备自投系统控制策略优化研究及应用

针对花瓣型配电网发生故障后,若故障无法被保护可靠隔离时会导致区域备自投系统无法实现“花瓣”恢复供电的问题,基于控制策略对等式的思想,提出一种新型区域备自投系统控制策略。新型控制策略主动进行故障隔离并通过相邻开关房的信息交互,实现“花瓣”的恢复供电及恢复供电后线路过载时各开关房中负荷的智能选切功能,通过信息交互也确保了安全稳定系统切负荷功能的有效性;同时提出了经主保护闭锁的后备保护,解决了“花瓣”内合环运行时后备保护定值整定配合困难和工作量大的技术问题。现场应用结果验证了新型控制策略的有效性,对其他配电网区域备自投系统控制策略的研究具有一定的借鉴意义。