FORMULATION OF MATHEMATICAL MODEL FOR MAINTENANCE COST OF A STONE CRUSHING PLANT BASED ON DIMENSIONAL ANALYSIS AND MULTIPLE REGRESSION

2013 ◽  
pp. 1-6
Author(s):  
PROF. ANJALI J. JOSHI ◽  
DR. JAYANT P. MODAK
Keyword(s):  
Mathematical Model ◽  
Multiple Regression ◽  
Dimensional Analysis ◽  
Least Square Method ◽  
Least Square ◽  
Maintenance Cost ◽  
Design Data ◽  
Static And Dynamic Analysis ◽  
Dimensionless Equation ◽  
Crushing Plant

This paper presents the approach for the mathematical modeling of maintenance cost for the set up of new Stone Crushing Plant based on the dimensional analysis and multiple regression. Presented maintenance cost mathematical model is derived based on the generated design data. Design data is generated from actual design of all stone crushing plants followed by static and dynamic analysis. Estimation of design data is carried out based on the assumed plant layout. Dimensional analysis is used to make the independent and dependent variables dimensionless and to get dimensionless equation. Later, multiple regression analysis is applied to this dimensionless equation to obtain the index values based on the least square method. The mathematical model of maintenance cost is formulated using these obtained index values. Finally, the formulated model is evaluated on the basis of correlation and root mean square error between the computed values by model and the estimated values.

scholarly journals FORMULATION OF MATHEMATICAL MODEL FOR PRODUCTION TURNOVER OF BIODIESEL PLANT BASED ON DIMENSIONAL ANALYSIS AND MULTIPLE REGRESSION

2012 ◽  
pp. 268-276
Author(s):  
ASHWIN S. CHATPALLIWAR ◽  
DR. VISHWAS S. DESHPANDE ◽  
DR. JAYANT P. MODAK ◽  
DR. NILESHSINGH V. THAKUR
Keyword(s):  
Mathematical Model ◽  
Multiple Regression ◽  
Dimensional Analysis ◽  
Least Square Method ◽  
Least Square ◽  
Design Data ◽  
Dimensionless Equation ◽  
Set Up ◽  
The Mathematical Model ◽  
Data Design

This paper presents the approach for the mathematical modeling of production turnover for the set up of new Biodiesel plant based on the dimensional analysis and multiple regression. Presented production turnover mathematical model is derived based on the generated design data. Design data is generated from the estimated design data. Estimation of design data is carried out based on the assumed plant layouts of different capacities. Dimensional analysis is used to make the independent and dependent variables dimensionless and to get dimensionless equation. Later, multiple regression analysis is applied to this dimensionless equation to obtain the index values based on the least square method. The mathematical model of production turnover is formulated using these obtained index values. Finally, the formulated model is evaluated on the basis of correlation and root mean square error between the computed values by model and the estimated values.

Research on Generator Excitation Parameter Identification - PSS Low-Pass Link Parameter Identification

2013 ◽  
Vol 805-806 ◽  
pp. 716-720
Author(s):  
Tao Xu ◽  
Tian Long Shao ◽  
Dong Fang Zhang
Keyword(s):  
Mathematical Model ◽  
Parameter Identification ◽  
Least Squares Method ◽  
Least Square Method ◽  
Least Square ◽  
National Standards ◽  
Matlab Software ◽  
Low Pass ◽  
Newton Iterations ◽  
The Mathematical Model

Combined with the contents of the study-PSS low-pass link parameter identification. Least-squares method is selected. Using least-square method for PSS low-pass link mathematical model are also deduced. For the results, because of the mathematical model is solving nonlinear equations, cannot used by the Newton method directly. So we choose to use Newton iterations, with this feature, choose to use MATLAB software to solve the equation. Identification of the use of MATLAB software lags after the PSS parameters obtained recognition results compared with national standards, identifying and verifying the practicability.

Displacement Analysis of the 3SPS-3CCS Mechanism Based on Hyper-Chaotic Damp Least Square Method

2011 ◽  
Vol 55-57 ◽  
pp. 2092-2098
Author(s):  
You Xin Luo ◽  
Qi Yuan Liu ◽  
Xiao Yi Che ◽  
Bin Zeng
Keyword(s):  
Mathematical Model ◽  
Real Number ◽  
Matrix Method ◽  
Parallel Mechanism ◽  
Least Square Method ◽  
Least Square ◽  
Forward Displacement ◽  
Displacement Analysis ◽  
Chaotic Sequences ◽  
Chaos System

The forward displacement analysis of parallel mechanism is attributed to find the solutions of complicated nonlinear equations and it is a very difficult process. Taking chaotic sequences as the initial values of the damp least square method, we can find all the solutions of equations quickly. Making use of existing chaos system and discovering new chaos system to generate chaotic sequences with good properties is the key to the damp least square method based on Chaos sequences. Based on utilizing hyper-chaotic Hénon mapping to obtain initial points, a new method of finding all real number solutions of the nonlinear questions is proposed. Using cosine matrix method, the author established the mathematical model of forward displacement for the generalized 3SPS-3CCS parallel robot mechanism and a numerical example is given. Compared to the quaternion method building mathematical model, the result shows cosine matrix method building mathematical model and hyper-chaotic damp least square method to find solution is brief and high calculation efficiency as the calculation is done in real number range. The proposed method has universality which can be used in forward displacement of other parallel mechanism.

Machining Efficiency Model Based on the Multiple Regression Theory in Turning Glass Ceramics

2012 ◽  
Vol 201-202 ◽  
pp. 1092-1095
Author(s):  
Lian Jie Ma ◽  
Ai Bing Yu ◽  
Ya Dong Gong
Keyword(s):  
Prediction Model ◽  
Multiple Regression ◽  
Removal Rate ◽  
High Reliability ◽  
Cutting Speed ◽  
Glass Ceramics ◽  
Least Square Method ◽  
Least Square ◽  
Feed Speed ◽  
Tools Wear

The materials removal rate (V/VB) was selected to be objective function. It is comprehensive parameter about materials and tools wear. Through turning glass ceramics experimentation, the materials removal influence of cutting speed, cutting depth and feed speed were study. Based on least square method, the multiple regression prediction model of materials removal rate was built. And the model was tested. It was applied to predictive and control. The results indicated: this model was well to express materials removal law in turning glass ceramics. The multiple regression prediction model is high remarkable. The prediction value was coincident with measure value. This model is high reliability. So, expect materials removal rate can been obtained by this model, and choosing the technological parameter can been guided.

Railroad track modeling based on the results of mobile laser scanning

2018 ◽  
pp. 408-413
Author(s):  
Elena Lenchenkova
Keyword(s):  
Mathematical Model ◽  
Laser Scanning ◽  
Dimensional Space ◽  
Practical Importance ◽  
Three Dimensional ◽  
Least Square Method ◽  
Least Square ◽  
Railroad Track ◽  
Railway Line ◽  
Type Data

Objective: To develop a mathematical model of the railroad track based on the initial progressive-type data (laser scanning) in railroad design. Methods: Regression analysis (least-square method), as well as coordinate methods of calculating point position in space were applied. Results: The mathematical model, which could describe the position of the railroad track in three-dimensional space by means of mathematical relations, was obtained. Applicability of approximating models was established. The models make it possible to provide smoothing of laser survey data. Regularization and globalization algorithms of initial data were developed. Practical importance: The introduced model is universal when describing the position of the track at all stages of life cycle of the railway line. It is reasonable to apply the presented model in design engineering in order to balance survey errors, maintain the track in coordinates, as well as to calculate design and profile parameters.

Error Model and Calibration Analysis of the Flexible Coordinate Measuring Machine

2011 ◽  
Vol 121-126 ◽  
pp. 3273-3277 ◽  
Author(s):  
Fang Li ◽  
Shu Gui Liu ◽  
Lei Zhao
Keyword(s):  
Mathematical Model ◽  
Coordinate Measuring Machine ◽  
Least Square Method ◽  
Coefficient Matrix ◽  
Error Model ◽  
Least Square ◽  
Parameter Calibration ◽  
Measuring Machine ◽  
Improving Accuracy ◽  
The Mathematical Model

A new 5-DOF flexible coordinate measuring machine (CMM) is introduced in this paper, which uses REVO system produced by Renishaw. According to the D-H method, the mathematical model is built, and then the error model of the flexible CMM is derived. The parameter calibration based on the nonlinear least square method is analyzed theoretically. Due to the disadvantages of Gauss-Newton method, LM method is researched, which improved the singularity of the coefficient matrix. The calibration analysis is a basis for improving accuracy of the flexible CMM.

scholarly journals A Mathematical Model for Predicting the Winnowing Efficiency of Bambara Groundnut Sheller

2020 ◽  
Vol 5 (2) ◽  
pp. 225-228
Author(s):  
Inimfon Samuel Ossom ◽  
Akindele Folarin Alonge ◽  
Kingsley Charles Umani ◽  
Edidiong J. Bassey
Keyword(s):  
Experimental Data ◽  
Mathematical Model ◽  
Moisture Content ◽  
Model Equation ◽  
Model Simulation ◽  
Least Square Method ◽  
Bambara Groundnut ◽  
Least Square ◽  
Predicted Model ◽  
Experimental Values

A mathematical model for predicting the winnowing efficiency of bambara groundnut sheller was developed. The regression equation for model simulation was developed using Least Square Method. The model was verified and validated by fitting it into established experimental data from winnowing efficiency of already existed Bambara groundnut sheller. The result revealed that the fitted model correlated well with the experimental data with R-square value of 0.99. The winnowing efficiency obtained from the predicted model was approximately the same values with the experimental values. Therefore, the model equation was considered to be reasonably good for predicting the winnowing efficiency of bambara groundnut sheller for known values of moisture content and blower speed.

MICROCONTROLLER-BASED FOR SYSTEM IDENTIFICATION TOOLS USING LEAST SQUARE METHOD FOR RC CIRCUITS

2015 ◽  
Vol 77 (28) ◽  
Author(s):  
Ang Jia Yi ◽  
M. S. Abdul Majid ◽  
Azuwir M. N. ◽  
S. Yaacob
Keyword(s):  
Mathematical Model ◽  
System Identification ◽  
Least Square Method ◽  
Least Square ◽  
Real Time System ◽  
System Identification Method ◽  
Identification Method ◽  
Verification Methods ◽  
Identification Technique ◽  
Rc Circuit

System identification is one of the method to construct a plant mathematical model from experimental data. This method has been widely applied in the automatic control, aviation, spaceflight medicine, society economics and other fields more. With the rapid growth of the science and technology, the system identification technique has increasingly grown in various applications. Since most of the system identification devices are off-line base, this means that the system identification can only be done after collecting the data and process through a computer devices. This paper will show how to process system identification method with real-time system. This method required a microcontroller as the medium to perform. That’s why the system identification method will be programmed into a microcontroller, based on Least Square Method. Later, the system will be tested on a RC circuit to see the effect of the signal and the mathematical model obtained. The data will undergo the system identification toolbox for process using ARX and ARMAX model. On the other hand, the data will also be collected using the microcontroller created for analysis purpose. To ensure the validity of the model some verification methods are performed. Results show that the Least Square Method using Microcontroller base has the capability to work as a system identification tools.

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