Desktop calibration of automatic transmission for passenger vehicle

Desktop calibration of automatic transmission(AT) is a method which can reduce cost, enhance efficiency and shorten the development periods of a vehicle effectively. We primary introduced the principle and approach of desktop calibration of AT based on the condition of coupling characteristics between engine and torque converter and obtained right point exactly. It is shown to agree with experimental measurements reasonably well. It was used in different applications abroad based on AT technology and achieved a good performance of the vehicle compared with traditional AT technology which primary focuses on the drivability, performance and fuel consumption.

Searching for an Optimized Single-objective Function Matching Multiple Objectives with Automatic Calibration of Hydrological Models

In the calibration of hydrological models, evaluation criteria are explicitly and quantitatively defined as single-or multi-objective functions when utilizing automatic calibration approaches.In most previous studies, there is a general opinion that no single-objective function can represent all important characteristics of even one specific hydrological variable(e.g., streamflow).Thus hydrologists must turn to multi-objective calibration.In this study, we demonstrated that an optimized single-objective function can compromise multi-response modes(i.e., multi-objective functions) of the hydrograph, which is defined as summation of a power function of the absolute error between observed and simulated streamflow with the exponent of power function optimized for specific watersheds.The new objective function was applied to 196 model parameter estimation experiment(MOPEX) watersheds across the eastern United States using the semi-distributed Xinanjiang hydrological model.The optimized exponent value for each watershed was obtained by targeting four popular objective functions focusing on peak flows, low flows, water balance, and flashiness, respectively.Results showed that the optimized single-objective function can achieve a better hydrograph simulation compared to the traditional single-objective function Nash-Sutcliffe efficiency coefficient for most watersheds, and balance high flow part and low flow part of the hydrograph without substantial differences compared to multi-objective calibration.The proposed optimal single-objective function can be practically adopted in the hydrological modeling if the optimal exponent value could be determined a priori according to hydrological/climatic/landscape characteristics in a specific watershed.

Contact High-Temperature Strain Automatic Calibration and Precision Compensation Research

Automated control and calibration are important components in industrial process and in artificial intelligence system and robotics.In order to solve the problem of contact high-temperature strain precision measurement,this paper established an automatic calibration device for high-temperature strain gauges.The temperature of the high-temperature furnace is automatically controlled by the temperature control device.The electric cylinder is driven by the servo motor to apply the load to the calibration beam.The output signal of the high-temperature strain gauge,the thermocouple signal,and the displacement signal of the grating ruler are collected at the same time.The deformation measurement results obtained after temperature correction are used to calculate the theoretical mechanical strain,which are fed back to control the loading action to complete the automatic calibration process.Based on the above calibration device,the hightemperature strain measurement accuracy correction software is developed to calibrate the high-temperature strain gauge with multiparameters,and the curves of sensitivity coefficient,thermal output,zero drift,and creep characteristics with temperature are obtained,and a strain measurement accuracy compensation model is established.The high-temperature strain measurement experiment is carried out to verify that the modified model can meet the requirements in each temperature range.

Design of Automatic Batch Calibration and Correction System for IMU

Thanks to its light weight,low power consumption,and low price,the inertial measurement units(IMUs)have been widely used in civil and military applications such as autopilot,robotics,and tactical weapons.The calibration is an essential procedure before the IMU is put in use,which is generally used to estimate the error parameters such as the bias,installation error,scale factor of the IMU.Currently,the manual one-by-one calibration is still the mostly used manner,which is low in efficiency,time-consuming,and easy to introduce mis-operation.Aiming at this issue,this paper designs an automatic batch calibration method for a set of IMUs.The designed automatic calibration master controller can control the turntable and the data acquisition system at the same time.Each data acquisition front-end can complete data acquisition of eight IMUs one time.And various scenarios of experimental tests have been carried out to validate the proposed design,such as the multi-position tests,the rate tests and swaying tests.The results illustrate the reliability of each function module and the feasibility automatic batch calibration.Compared with the traditional calibration method,the proposed design can reduce errors caused by the manual calibration and greatly improve the efficiency of IMU calibration.

Automatic calibration for wobble errors in shallow water multibeam bathymetries

The wobble errors caused by the imperfect integration of motion sensors and transducers in multibeam echo-sounder systems(MBES)manifest as high-frequency wobbles in swaths and hinder the accurate expression of high-resolution seabed micro-topography under a dynamic marine environment.There are many types of wobble errors with certain coupling among them.However,those current calibration methods ignore the coupling and are mainly manual adjustments.Therefore,we proposed an automatic calibration method with the coupling.First,given the independence of the transmitter and the receiver,the traditional georeferenced model is modified to improve the accuracy of footprint reduction.Secondly,based on the improved georeferenced model,the calibration model associated with motion scale,time delay,yaw misalignment,lever arm errors,and soundings is constructed.Finally,the genetic algorithm(GA)is used to search dynamically for the optimal estimation of the corresponding error parameters to realize the automatic calibration of wobble errors.The simulated data show that the accuracy of the calibrated data can be controlled within 0.2%of the water depth.The measured data show that after calibration,the maximum standard deviation of the depth is reduced by about 5.9%,and the mean standard deviation of the depth is reduced by about 11.2%.The proposed method has significance in the precise calibration of dynamic errors in shallow water multibeam bathymetrie s.

An Automatic Optimization Technique for the Calibration of a Physically Based Hydrological Rainfall-Runoff Model

Models are tools widely used in the prediction of hydrological phenomena. The present study aims to contribute to the implementation of an automatic optimization strategy of parameters for the calibration of a hydrological model based on the least action principle (HyMoLAP). The Downhill Simplex method is also known as the Nelder-Mead algorithm, which is a heuristic research method, is used to optimize the cost function on a given domain. The performance of the model is evaluated by the Nash Stucliffe Efficiency Index (NSE), the Root Mean Square Error (RMSE), the coefficient of determination (R2), the Mean Absolute Error (MAE). A comparative estimation is conducted using the Nash-Sutcliffe Modeling Efficiency Index and the mean relative error to evaluate the performance of the optimization method. It appears that the variation in water balance parameter values is acceptable. The simulated optimization method appears to be the best in terms of lower variability of parameter values during successive tests. The quality of the parameter sets obtained is good enough to impact the performance of the objective functions in a minimum number of iterations. We have analyzed the algorithm from a technical point of view, and we have carried out an experimental comparison between specific factors such as the model structure and the parameter’s values. The results obtained confirm the quality of the model (NSE = 0.90 and 0.75 respectively in calibration and validation) and allow us to evaluate the efficiency of the Nelder-Mead algorithm in the automatic calibration of the HyMoLAP model. The developed hybrid automatic calibration approach is therefore one of the promising ways to reduce computational time in rainfall-runoff modeling.

QA/QC Procedures for <i>in-Situ</i>Calibration of a High Altitude Automatic Weather Station: The Case Study of the AWS Pyramid, 5050 m asl, Khumbu Valley, Nepal

In-situ calibrations of weather stations are usually performed by positioning standard instruments close to the station under calibration and comparing the obtained results. This procedure could be useful to evaluate the proper functioning of the monitoring equipments, but do not allowed the determination of a calibration curve that allow the corrections of the acquired parameters. Thus, the development of a dedicated facility for in-situ calibration of weather stations, enabling simultaneous generation of a wide range of temperatures and pressures could offer important improvements in this framework, particularly if this facility is applied to high mountains monitoring stations where the weather stations calibrations could be very difficult. This paper will present the calibration chamber developed in the framework of the EMRP-METEOMET (Metrology for Meteorology) Project, which aims is to bring metrological traceability to high altitude meteorological instruments and through this experience will provide a general overview on the importance of the application of this methodology at different levels.

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）.

Automatic calculation of the magnetometer zero offset using the interplanetary magnetic field based on the Wang-Pan method

The space-borne fluxgate magnetometer(FGM)requires regular in-flight calibration to obtain its zero offset.Recently,Wang GQ and Pan ZH(2021a)developed a new method for the zero offset calibration based on the properties of Alfvén waves.They found that an optimal offset line(OOL)exists in the offset cube for a pure Alfvén wave and that the zero offset can be determined by the intersection of at least two nonparallel OOLs.Because no pure Alfvén waves exist in the interplanetary magnetic field,calculation of the zero offset relies on the selection of highly Alfvénic fluctuation events.Here,we propose an automatic procedure to find highly Alfvénic fluctuations in the solar wind and calculate the zero offset.This procedure includes three parts:(1)selecting potential Alfvénic fluctuation events,(2)obtaining the OOL,and(3)determining the zero offset.We tested our automatic procedure by applying it to the magnetic field data measured by the FGM onboard the Venus Express.The tests revealed that our automatic procedure was able to achieve results as good as those determined by the Davis-Smith method.One advantage of our procedure is that the selection criteria and the process for selecting the highly Alfvénic fluctuation events are simpler.Our automatic procedure could also be applied to find fluctuation events for the Davis-Smith method.

Development of calibration system for transmission control unit of AT based on XCP

To guarantee control system＇s performance and shorten the development cycle during the development process of hydraulic automatic transmission, a calibration system on CAN for high-pow- er AT ECU is designed based on XCP. In this system, it is possible that the master dynamically searching the slaves available on bus and data synchronization between master and slave is also achieved. Real-time measurement and on-line calibration can be executed during the running process of transmission control unit, so the calibration result is displayed in time. Calibration by true value and physical value are both available. Experimental results showed that this system operated stably and reliably and had strong timeout handling ability.

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.

Reducing Item Exposure in Computerized Adaptive Testing Systems Using Automatic Item Generation

This paper studies the technics of reducing item exposure by utilizing automatic item generation methods. Known test item calibration method uses item parameter estimation with the statistical data, collected during examinees prior testing. Disadvantage of the mentioned item calibration method is the item exposure; when test items become familiar to the examinees. To reduce the item exposure, automatic item generation method is used, where item models are being constructed based on already calibrated test items without losing already estimated item parameters. A technic of item model extraction method from the already calibrated and therefore exposed test items described, which can be used by the test item development specialists to integrate automatic item generation principles with the existing testing applications.

Easy calibration method of vision system for in-situ measurement of strain of thin films

An easy calibration method was presented for in-situ measurement of displacement in the order of nanometer during micro-tensile test for thin films by using CCD camera as a sensing device. The calibration of the sensing camera in the system is a central element part to measure displacement in the order of nanometer using images taken with the camera. This was accomplished by modeling the optical projection through the camera lens and relative locations between the object and camera in 3D space. A set of known 3D points on a plane where the film is located on is projected to an image plane as input data. These points, known as a calibration points, are then used to estimate the projection parameters of the camera. In the measurement system of the micro-scale by CCD camera, the calibration data acquisition and one-to-one matching steps between the image and 3D planes need precise data extraction procedures and repetitive user's operation to calibrate the measuring devices. The lack of the robust image feature extraction and easy matching prevent the practical use of these methods. A data selection method was proposed to overcome these limitations and offer an easy and convenient calibration of a vision system that has the CCD camera and the 3D reference plane with calibration marks of circular type on the surface of the plane. The method minimizes the user's intervention such as the fine tuning of illumination system and provides an efficient calibration method of the vision system for in-situ axial displacement measurement of the micro-tensile materials.

Prototyping low-cost automatic weather stations for natural disaster monitoring

Weather events put human lives at risk mostly when people might occupy areas susceptible to natural disasters.Deploying Professional Weather Stations(PWS)in vulnerable areas is key for monitoring weather with reliable measurements.However,such professional instrumentation is notably expensive while remote sensing from a number of stations is paramount.This imposes challenges on the large-scale weather station deployment for broad monitoring from large observation networks such as in Cemaden—The Brazilian National Center for Monitoring and Early Warning of Natural Disasters.In this context,in this paper,we propose a Low-Cost Automatic Weather Station(LCAWS)system developed from Commercial Off-The-Shelf(COTS)and open-source Internet of Things(IoT)technologies,which provides measurements as reliable as a reference PWS for natural disaster monitoring.When being automatic,LCAWS is a stand-alone photovoltaic system connected wirelessly to the Internet in order to provide real-time reliable end-to-end weather measurements.To achieve data reliability,we propose an intelligent sensor calibration method to correct measures.From a 30-day uninterrupted observation with sampling in minute resolution,we show that the calibrated LCAWS sensors have no statistically significant differences from the PWS measurements.As such,LCAWS has opened opportunities for reducing maintenance costs in Cemaden's observational network.

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.

全自动免疫组织化学染色与手工染色在胃肠道肿瘤患者中的应用价值比较

目的比较全自动免疫组织化学染色与手工染色在胃肠道肿瘤患者中的应用价值。方法选取2022年1月至12月宝鸡市中医医院收治的300例胃肠道肿瘤患者为研究对象。所有患者各采集病灶组织2份,分别采用全自动免疫组化仪染色(自动组)和手工染色(手工组)。比较不同染色方式的染色质量、切片背景着色、边缘着色发生率、阳性细胞检出率、染色时间及染色方式满意度。结果自动组的染色质量优良率高于手工组,差异具有统计学意义(P<0.05)。自动组的切片背景着色、边缘着色发生率低于手工组,阳性细胞检出率高于手工组,差异具有统计学意义(P<0.05)。自动组的人力工作时间、步骤完成时间短于手工组,差异具有统计学意义(P<0.05)。自动组的显色情况、染色结果、诊断结果及应用价值满意度评分高于手工组,差异具有统计学意义(P<0.05)。结论全自动免疫组织化学染色在胃肠道肿瘤患者中应用的价值优于手工染色,其可提高染色质量、阳性细胞检出率、染色效率与染色满意度。

基于半自动分割技术的膝关节有限元建模

背景:膝关节有限元建模可以深入了解膝关节力学,但其复杂的图像分割工作对于研究人员来说较为困难。随着深度学习技术的发展,深度学习技术已经广泛应用于膝关节有限元建模中。目的:使用3D Swin UNETR结合统计形状模型半自动分割技术来代替膝关节有限元建模中人工分割的步骤。方法:基于MR建立手动(人工)膝关节有限元模型和3D Swin UNETR+统计形状模型分割的半自动膝关节有限元模型,对2个模型施加相同的载荷与边界条件,通过计算Dice相似系数、平均距离以及比较2个模型的等效应力峰值、最大主应力和最大剪切应力来进行验证。结果与结论:①半自动分割模型股骨和胫骨的Dice相似系数均超过98%,平均距离均≤(0.35±0.08)mm;②对手动和半自动有限元模型股骨顶端施加纵向荷载750 N及10 Nm内翻力矩,手动有限元模型半月板等效应力峰值、最大主应力、最大剪切应力为14.12,18.54,7.35 MPa;股骨软骨等效应力峰值、最大主应力、最大剪切应力为2.22,2.15,1.18 MPa;胫骨软骨等效应力峰值、最大主应力、最大剪切应力为2.50,1.91,1.41 MPa;半自动有限元模型半月板等效应力峰值、最大主应力、最大剪切应力为14.93,18.53,7.75 MPa;股骨软骨等效应力峰值、最大主应力、最大剪切应力为2.26,2.18,1.20 MPa;胫骨软骨等效应力峰值、最大主应力、最大剪切应力为2.60,1.91,1.46 MPa;手动和半自动有限元模型等效应力峰值、最大主应力和最大剪切应力之间基本一致,差异无显著性意义(P>0.05);③此次研究所提出的半自动分割技术在创建准确的膝关节有限元模型方面可代替人工分割。

翻斗式径流泥沙半自动监测设备的误差及校准分析

[目的]分析翻斗式径流泥沙半自动监测设备在野外实际应用下的误差规律,构建径流量和泥沙量校准模型,为径流泥沙半自动监测设备的应用提供依据。[方法]采用天然降雨径流泥沙监测数据,对翻斗式径流泥沙半自动监测设备的径流量和泥沙量测量值的误差进行分析,基于人工模拟径流冲刷试验初步构建了径流量和泥沙量的校准函数,结合自然降雨试验数据构建了7个径流小区径流泥沙半自动监测设备的径流量和泥沙量校准模型,并验证校准模型的可行性。[结果](1)翻斗式径流泥沙半自动监测设备得到的径流量和泥沙量与实测值存在一定误差,次降雨条件下各径流小区径流量和泥沙量相对误差分别介于0.03%~139.52%和0.32%~346.19%,且误差均随径流量和泥沙量的增大而减小;年尺度上径流量和泥沙量的误差分别介于2.23%~45.03%和-10.38%~103.26%,径流量的自动测量数据总体偏大,而泥沙量没有明显规律,但半自动监测设备次降雨尺度监测结果的误差大于年尺度的误差。(2)翻斗式径流泥沙半自动监测设备的监测数据可以用线性函数方程进行校准,通过径流模型、泥沙模型校准后,径流量和泥沙量均方根误差均大幅下降,相对误差分别介于-0.01%~0.68%和0.00%~3.52%,能够达到径流泥沙监测数据误差均小于5%的相关要求。[结论]虽然径流泥沙半自动监测设备的使用对加快水土流失监测自动化进程、提升数据获取效率具有重要意义,但设备安装后需要进行进一步校准,采用自然降雨真实径流数据建立的校准模型,校准结果更佳。