Soft Measurements Research Articles

Analyze Soft Measurement Technology Based Intelligent Algorithm in Sewage Treatment

On the basis of introduction to soft sensing technology, the paper comprehensively discusses the research present situation and the application characteristics of Genetic Algorithm、Artificial Neural Networks、and Support Vector Machine.After comparison and analysis, this paper presents a high quality research strategy of on-line real-time control.

Multi-mode acid concentration prediction models of cold-rolled strip steel pickling process

In the steel strip pickling process, the control of the acid concentration is an important part for ensuring the strip surface quality. Now only X-ray method is used to detect the acid concentration online, but the price is very high and the maintenance is very hard. The acid concentration is not measured in most of the steel strip pickling lines online. In this paper, a soft measurement of acid concentration is developed. The pressure differential, conductivity and temperature are used to calculate the acid concentration including ferrous chloride (FeCl2) and hydrogen chloride (HCl) concentration. The real pickling process is under a multi-mode condition. First, the spectral clustering based on geodesic distance is used to cluster the data into some groups. There are clearly linear relationship between the condition variables and the acid concentration. Then, orthogonal signal correction-iteratively reweighted least squares (OSC-IRLS) models based on the cluster data set are built to predict the acid concentration. The real field data set from cold-rolled strip steel pickling process is used to validate the model. The results demonstrate that the clustering method can improve the prediction result.

A fast time-response bolometer for soft X-ray radiation energy measurements in a high-current Z-pinch

A high-sensitivity bolometer with a short time response to heating with external radiation has been developed. It is intended for measuring the integral parameters of soft X-ray radiation of liner plasma. The bolometer is adapted to the conditions of explosion experiments with an increased level of electromagnetic pickups at facilities that are based on magnetic-explosion generators with megaampere currents. The bolometer has a metal casing for improving the noise immunity of measurements. A 2-μm-thick nickel foil is used as the material for the resistive element of the working substance of the bolometer. The choice of the material and the geometrical dimensions of the bolometer working elements were analyzed. The ultimate thermal load on the bolometer was determined. A technique for calibrating the working elements using a pulse current was developed. The working capacity, good noise immunity, and a high sensitivity of the bolometer were demonstrated in experiments. The dynamic range in measurements of the surface energy density of X rays is 0.03–0.3 J/cm2.

Fuzzy least squares support vector machine soft measurement model based on adaptive mutative scale chaos immune algorithm

In order to enhance measuring precision of the real complex electromechanical system, complex industrial system and complex ecological & management system with characteristics of multi-variable, non-liner, strong coupling and large time-delay, in terms of the fuzzy character of this real complex system, a fuzzy least squares support vector machine (FLS-SVM) soft measurement model was established and its parameters were optimized by using adaptive mutative scale chaos immune algorithm. The simulation results reveal that fuzzy least squares support vector machines soft measurement model is of better approximation accuracy and robustness. And application results show that the relative errors of the soft measurement model are less than 3.34%.

Exploring new ways to ensure interoperability under the Digital Agenda

Purpose – This article seeks to analyze the initiative of the European Commission that studied the feasibility of measures that would lead significant market players to license their interoperability information under the Digital Agenda. Design/methodology/approach – The significance of the abuse of dominance regime and the electronic communications framework in ensuring access to interoperability information in the ICT sector is studied by way of analyzing legislation and case law. Against the background of these two existing regulatory regimes, the proposals that the Commission made in its recently published Staff Working Document are evaluated. Findings – The Microsoft case illustrates that the abuse of dominance regime under European competition law is not very effective to remedy interoperability issues in a structural way. An ex ante regime will enable the ICT industry to reap the full benefits of interoperability on a broader scale. Since the Commission's initiative seems to target interoperability among software products, the electronic communications regime is not applicable. A new regulatory regime should therefore be established. As the desirability of a mandatory regime can be questioned, the adoption of soft law measures seems to be the preferred option. Originality/value – By putting the initiative of the Commission to examine measures that promote access to interoperability information under the Digital Agenda into its broader regulatory context, the article contributes to the discussion on the possible ways to ensure interoperability in the ICT sector.

Multivariate Methods Based Soft Measurement for Wine Quality Evaluation

Soft measurement is a new, developing, and promising industry technology and has been widely used in the industry nowadays. This technology plays a significant role especially in the case where some key variables are difficult to be measured by traditional measurement methods. In this paper, the quality of the wine is evaluated given the wine physicochemical indexes according to multivariate methods based soft measurement. The multivariate methods used in this paper include ordinary least squares regression (OLSR), principal component regression (PCR), partial least squares regression (PLSR), and modified partial least squares regression (MPLSR). By comparing the performance of the four methods, the MPLSR prediction model shows superior results than the others. In general, to determine the quality of the wine, experienced wine tasters are hired to taste the wine and make a decision. However, since the physicochemical indexes of wine can to some extent reflect the quality of wine, the multivariate statistical methods based soft measure can help the oenologist in wine evaluation.

Not Too Little, Not Too Much and Shortcut: A Review on the Effectualness of Per Capita Pollutant Discharge Indicators

In the fields of wastewater treatment planning, institutional and governance aspects are sometimes emphasised in developing and middle-developed countries. This paper summarises some important technical issues for the stakeholders of municipal wastewater treatment and water environment management. Pollutant removal efficiencies at wastewater treatment plants (WWTPs) are important but effluent water quality is sometimes emphasised. To achieve high pollutant removal efficiencies, maintaining a certain level of pollutant concentrations in the influent, or “Not Too Little” pollutant, is necessary. The second point is pollutant discharge from the river catchment should be “Not Too Much”. Excess and rapid pollutant discharge increase in the catchment results in high costs and lengthy time periods for the river water environment to recover the original water environment conditions. The third point is that developing and middle-developed countries can use a shortcut or technological bypass by use of existing hard and soft measures to facilitate environmental improvements. This can be done with appropriate financial mechanisms. Pollutant discharge per capita (PDC) and pollutant load per capita flowing into water body (PLCwb) are effective and efficient indicators that can be used to address these three concepts.

The Study of the Relationships among Psychological Factors, Acceptable Walking Distance, and Reported Walking Distance for Shopping Trips

The purpose of this study is to examine the relationship between psychological factors and walking behavior in order to provide evidence supporting the implementation of measures for behavioral change for the success of urban planning initiatives. The acceptable walking distance is selected as an intermediate variable between psychological factors and actual walking distance. The results indicate that increasing the acceptable walking distance has the potential to stimulate pedestrians to increase the amount of walking. Also, an ordered probit model has indicated that psychological factors have a significant influence on the acceptable walking distance. It is able to identify a sequence of cause and effect where psychological factors would first influence acceptable walking distance and then the acceptable walking distance would influence pedestrian walking distance. A policy of applying soft measures such as psychological strategies to increase the pedestrian output is supported by the findings of this project work.

Study on Applied Technology with Soft Measurement for Lance Position Based on MLR and PCR

Because the lance position of oxygen-enriched air and top-blown furnace is affected by lance pressure, melt temperature, melt furface,the type of slag and other factors, it is difficult accurately measured. Firstly, processing informations(excluding data,analysis correlation) to the production data.Then identified the main auxiliary variables of soft measurement model and established MLR and PCR soft prediction model of the lance position.Secondly,according to production data,through fitting and forecasting of these models, the results show that the PCR model's forecasting ability is better than the MLR model.Finally, the obtained model is embedded in WinCC software platform and further verify the feasibility of the model.The research may guide the production and lay theoretical foundations for the lance position control

Clinical effect of tip-edge plus appliance in children with angle II1 malocclusion

The effects of Tip-Edge plus appliance in the treatment of Angle II(1) malocclusion and the mechanism were investigated. Fifty-two Angle II(1) children, aged from 12.3-14.2 years, with mandibular retrusion in permanent dentition were selected and treated with Tip-Edge plus appliance. Lateral cephalometric films taken before and after treatment were analyzed. The arithmetic mean and standard deviation were calculated for each variable. Paired t-test was performed to evaluate the significant treatment change. Results showed that the average treatment time was 16 months. Normal overjet and overbite were established with retroclination of upper incisors and proclination of lower incisors. U1-NA was decreased by 15.4° (P<0.01). ANB and Y axial angle were decreased significantly (P<0.05). Soft tissue measurements showed that FCA and UL-E were decreased dramatically (P<0.05), and LL-E was increased significantly (P<0.05). Remarkable soft tissue change was noted after the treatment and convex facial profile changed to the straight profile. In conclusion, Tip-Edge plus technique can quickly and efficiently correct anterior bite and lateral outlook.

Kinetic Modeling and Parameter Estimation for Competing Reactions in Copper Removal Process from Zinc Sulfate Solution

In zinc hydrometallurgy, an advanced copper removal process purifies zinc sulfate solution through a series of chemical reactions with recycled underflow by using zinc powder in zinc hydrometallurgy. This paper focuses on the kinetic modeling of the competitive-consecutive reaction system in the copper removal process, and proposes an adaptive parameter optimal selection strategy for different industrial conditions. In the system model, copper cementation, one of the removal reactions, is described by a surface controlled pseudo-first-order rate equation; cuprous oxide precipitation, the other removal reaction, is described by a shrinking core model of a noncatalytic fluid–solid reaction. Because there are several kinetic parameters in the system model, parameter estimation plays an essential role. Because of the complexity and variation in the practical removal process, the kinetic parameters are usually sensitive to alterations in the process conditions. This work solves the parameter estimation problem using an optimal selection strategy. In the strategy, the industrial conditions are classified adaptively according to the system model performance, then the kinetic parameters are selected optimally by evolutionary and particle swarm optimization algorithms for different industrial conditions. Three different representative industrial data sets are used to test the effectiveness and flexibility of the proposed modeling and parameter optimal selection approach in various situations. Finally, the kinetic model is applied to the soft measurement of the practical copper removal process with underflow, and the results demonstrate that the model effectively captures the trends of the removal reactions.

Evaluation of the soft measures' effects on ambient water quality improvement and household and industry economies

Abstract Various ecological footprint calculators, carbon footprint calculators and water footprint calculators have been developed in recent years. The basic concepts of ecological behaviour record notebooks and of carbon dioxide emission calculators have been developed since the late 20th century. The first carbon dioxide emission calculator was developed in 1991. Likewise, water pollutant discharge calculators have been developed to estimate the effects of soft measures introduced into households to reduce pollutant discharge since 2004. The soft measures which have been developed in Japan may consist of a wider framework, household sustainable consumption, which has been developed in Europe, and can be referred to cleaner consumption. In this research, summarisation of the short history of ecological behaviour record notebooks and ecological footprint calculators in Japan since the 1980s was conducted, and the soft measures in households to reduce pollutant discharge were evaluated for their effects on ambient water quality improvement as well as household and industry economies. Effects of the soft measures on related industry economies were investigated using an Input–Output Table analysis and the effects of the imported goods were evaluated with an import effect matrix, which was developed in this research. The effects of the soft measures on household expenditures were estimated to be a decrease by 2.5% or USD 285 person −1 year −1 in 2003–2006. The results show that the soft measures positively affect the chemical fibre industry and significantly affect the detergent industry. Analysis of the import effect matrix proved that the six industries were tightly related through extensive amounts of imported goods. The soft measures in households may lead to household sustainable consumption and thus reduce disadvantageous human impacts on water environments. The effects of the measures introduced to improve the environment should be qualitatively and quantitatively evaluated to avoid redundant concerns and discord between the environment and the economy, which may be worried when the relationship is not well understood.

Method for detecting free fiber ends in tissue paper

Softness is one of the major properties of tissue paper. Tissue softness can be divided into bulk and surface softness. The bulk softness can be measured quite reliably by measuring the thickness and elasticity of a sheet. However, the measurement of surface softness is not straightforward. One significant factor influencing surface softness is the fibers extending from the surface of the tissue paper. This paper presents a novel imaging method to detect the amount of such fibers on the tissue paper. The method is based on the detection of shadows caused by the free fiber ends. The shadows cannot be detected as such from the reflectance image of the sheet because of the wavy surface of tissue paper. Thus, the 3D information of the surface was estimated based on the photometric stereo, and the intensity variations caused by the wavy surface were filtered out. The method has the advantages over previous methods of improved accuracy and the possibility of implementation in a running paper machine.

A GPVSC Controller for Batch Dyeing Process Based on Integrated Model

Traditional textile dyeing industry, which is always based on open-loop control strategy, has the problem of high energy consumption and serious pollution because it is difficult to deal with the direct control problem of the dyeing process. Based on the multi-variable dyeing uptake rate integration model, this paper proposed a closed loop control system using Generalized Prediction Variable Structure Control (GPVSC) algorithm. The integrated model is used as the soft measurement method of the whole closed loop control system, which can solve the problem that it is hard to measure dyeing uptake rate directly during the batch dyeing process. In the aspect of control algorithm, the Generalized Prediction Controller (GPC) was combined with Variable Structure Control (VSC), where the temperature was selected as the control variable, which achieved the control of the dyeing uptake rate during the batch dyeing process. Simulation results show that the algorithm could exactly track and control the dyeing uptake rate during the batch dyeing process.

Propensity for Voluntary Travel Behavior Changes: An Experimental Analysis

In this paper we analyze individual propensity to voluntary travel behavior change combining concepts from theory of change with the methodologies deriving from behavioral models. In particular, following the theory of voluntary changes, we set up a two-week panel survey including soft measure implementation, which consisted of providing car users with a personalized travel plan after the first week of observation (before) and using the second week to monitoring the post-behavior (after). These data have then been used to estimate a Mixed Logit for the choice to use a personal vehicle or a light metro; and a Multinomial Logit for the decision to change behavior. Results from both models show the relevance of providing information about available alternatives to individuals while promoting voluntary travel behavioral change.

Soft Measurement Technology and Implementation Based on PSO-SVR

Aiming at the important parameters of industrial process can not be online measured by sensors, this paper proposes a soft sensor modeling method based on PSO-SVR, and analyzes the technical bottleneck of the soft measurement model applied in engineering, designs the online application system of soft-sensing model with OPC technology. This paper discusses in detail the implementation steps of exchanging data between MATLAB algorithm model and WinCC industrial control configuration platform with OPC technology. The method has the advantages of simple integration and easy to implement, has certain application value.

Structural view independence: A criterion for judging the objectivity of economic parameters measured by opinion survey

Economic measurements have a great influence over all our lives, but as with other soft measurements, significant effort is needed to ensure their objectivity. This is particularly true of the process of consolidating into a single representative figure different people’s valuations of a non-market good (“views”), as measured by opinion survey. Sometimes the views are transformed and averaged before being returned to the original domain as the back-transformed mean. Examples are the geometric mean resulting from a logarithmic transformation and the root-mean-squared (r.m.s.) value from a square transformation. Such transformations are tested for objectivity using the new criterion of structural view independence. It is shown that an analyst using any general, nonlinear, increasing and differentiable transformation other than the linear transformation can know at the outset that he is giving greater weight to views of his choosing, meaning that he has no claim to objectivity. Of all such transformations, only the linear transformation possesses the desirable property of structural view independence. The resultant sample mean is objective and the only consolidated figure recommended for human views.

Soft Measurement of Heat Flux for TEC Based Dynamic Thermal Management

Heat flux measurement is important for dynamic thermal management (DTM) since it can provide more predicted information. Commercial heat flux sensors are too expensive and fragile for practical applications. Thermoelectric Cooler (TEC) based DTM provides the possibility of measuring the heat flux without additional heat flux sensor. Soft measurement of TEC heat flux has been presented via Neural Network (NN), which is suitable for identifying TEC model. NN models have been proposed by combing the classical TEC model together. The soft measurement performances with different NN models have been reported and analyzed in terms of accuracy, efficiency, and generalization capability.

Soft Measures to Improve the Wind Speed Prediction Capability in Wind Farm

For decreasing the error of wind speed prediction in wind farm, improvements from the aspects of arithmetic, space and time has been proposed based on the soft sensor. Support Vector Machine as the basic prediction method is used to analyze. MRA-SVM testify the improvement of algorithm can increase the performance targets.The modified model about meteorological information achieves the space continuity and the cascading of turbines profits the time continuity. Based the actual measured data, the calculated result shows that it is feasible to improve the wind speed prediction from the aspects of algorithm, space and time.

Data De-noising Based on PCA-KNN Algorithm in Billet Surface Temperature Measurement

This paper first analyzes the soft-sensor technology and temperature measurement technology used in recent soft measurements, focuses on the accuracy and efficiency requirements of soft measurement in slab surface temperature detection. In this paper, we collects images noise processes of continuous casting slabs, and uses component-based OTSU segmentation method to extract the slab area and then implements Hough transform for edge correction; then measures the selected regions of interest in pixels and extracts color features using PCA for feature reduction; we extracts the improved data set with KNN algorithm for noise reduction, and the removal of contradictory data; the final regression models are used in prediction.