scholarly journals Double B-Spline Curve-Fitting and Synchronization-Integrated Feedrate Scheduling Method for Five-Axis Linear-Segment Toolpath

2020 ◽  
Vol 10 (9) ◽  
pp. 3158 ◽  
Author(s):  
Xiangyu Gao ◽  
Shuyou Zhang ◽  
Lemiao Qiu ◽  
Xiaojian Liu ◽  
Zili Wang ◽  
...  
Keyword(s):  
Curve Fitting ◽  
Rotary Motion ◽  
Linear Segment ◽  
B Spline ◽  
Feedrate Scheduling ◽  
Fitting Method ◽  
Scheduling Method ◽  
Tip Position ◽  
Curve Fitting Method ◽  
Fitting Error

The discontinuities of a five-axis linear-segment toolpath result in fluctuation in the feedrate, acceleration and jerk commands that lead to machine tool vibration and poor surface finish. For path smoothing, with the global curve-fitting method it is difficult to control fitting error and the local corner-smoothing method has large curvature extreme. For path synchronization, the parameter synchronization method cannot ensure smooth rotary motion. Aiming at these problems, this paper proposes a double B-spline curve-fitting and synchronization-integrated feedrate scheduling method. Two C2-continuous and error-bounded B-spline curves are produced to fit tool-tip position and tool orientation, respectively. The fitting error is controlled by locally refining the curve segments that exceed the fitting tolerance. The tool-tip position trajectory is firstly planned to address axial kinematic constraints in the feedrate scheduling process. Then the feedrate is deformed for the tool orientation to guarantee smooth rotary motion as well as to share the same motion time with the tool-tip position segment by segment. The feasibility and effectiveness of the proposed method have been validated by simulations and experiments on the S-shape test piece. Simulations show that the proposed curve-fitting method can generate smooth toolpath and constrain fitting error. The proposed feedrate scheduling method can guarantee smooth rotary motion and keep axial motions under kinematic limits, compared with the method that does not consider axial kinematic constraints and the parameter synchronization method. Experimental results verify that the proposed curve-fitting method can generate smooth tool path under fitting tolerance, and the proposed feedrate scheduling method can produce smooth and restricted axial motions.

An additional branch free algebraic B-spline curve fitting method

2010 ◽  
Vol 26 (6-8) ◽  
pp. 801-811 ◽  
Author(s):  
Mingxiao Hu ◽  
Jieqing Feng ◽  
Jianmin Zheng
Keyword(s):  
Curve Fitting ◽  
B Spline ◽  
Spline Curve ◽  
Fitting Method ◽  
Additional Branch ◽  
Curve Fitting Method

scholarly journals An evaluation of the BFD curve based upon wood crib fires performed in an ISO 9705 room

2010 ◽  
Vol 14 (2) ◽  
pp. 521-531 ◽  
Author(s):  
Qiang Xu ◽  
Gregory Griffin ◽  
Yong Jiang ◽  
Cong Jin
Keyword(s):  
Empirical Model ◽  
Curve Fitting ◽  
Zone Model ◽  
Wood Crib ◽  
Fitting Method ◽  
Curve Fitting Method ◽  
Temperature Time ◽  
Fitting Error

The BFD curve fitting method of Barnett is adopted to study the compartment temperature-time curves for a series of wood crib fires in an ISO 9705 room. The nominal fire sizes were 0.15 MW, 0.25 MW, 0.5 MW, and 1.0 MW. The cribs were positioned at the corner or the center of the floor of the room. The temperatures within the compartment were measured using two thermocouple trees with 10 thermocouples on each tree; these measured the compartment temperature from floor to ceiling. No flashover occurred during the tests, and the compartment temperature can be well described by a two-zone model. BFD curve fitting was performed for all 20 temperature-time curves in the upper and lower zones of the compartment for each test. The fitting error is evaluated for all tests. This empirical model needs more tests to verify and optimize.

Using A Segmented Voltage Sweep Mode and A Gaussian Curve Fitting Method to Improve Heavy Metal Measurement System Performance

2012 ◽  
Vol 19 (2) ◽  
pp. 381-394
Author(s):  
José Pereira ◽  
Octavian Postolache ◽  
Pedro Girão
Keyword(s):  
Heavy Metals ◽  
Heavy Metal ◽  
Measurement System ◽  
Curve Fitting ◽  
System Performance ◽  
Redox Potentials ◽  
Voltage Sweep ◽  
Gaussian Curve ◽  
Fitting Method ◽  
Curve Fitting Method

Using A Segmented Voltage Sweep Mode and A Gaussian Curve Fitting Method to Improve Heavy Metal Measurement System PerformanceThis paper presents a voltammetric segmented voltage sweep mode that can be used to identify and measure heavy metals' concentrations. The proposed sweep mode covers a set of voltage ranges that are centered around the redox potentials of the metals that are under analysis. The heavy metal measurement system can take advantage of the historical database of measurements to identify the metals with higher concentrations in a given geographical area, and perform a segmented sweep around predefined voltage ranges or, alternatively, the system can perform a fast linear voltage sweep to identify the voltammetric current peaks and then perform a segmented voltage sweep around the set of voltages that are associated with the voltammetric current peaks. The paper also includes the presentation of two auto-calibration modes that can be used to improve system's reliability and proposes the usage of a Gaussian curve fitting of voltammetric data to identify heavy metals and to evaluate their concentrations. Several simulation and experimental results, that validate the theoretical expectations, are also presented in the paper.

Evaluation of a predictive curve-fitting method for processing data from flow systems

1993 ◽  
Vol 272 (1) ◽  
pp. 125-134 ◽  
Author(s):  
James M. Jordan ◽  
Michael D. Love ◽  
Harry L. Pardue
Keyword(s):  
Curve Fitting ◽  
Processing Data ◽  
Fitting Method ◽  
Flow Systems ◽  
Curve Fitting Method

A Curve Fitting Method for Detecting Valve Stiction in Oscillating Control Loops

2007 ◽  
Vol 46 (13) ◽  
pp. 4549-4560 ◽  
Author(s):  
Q. Peter He ◽  
Jin Wang ◽  
Martin Pottmann ◽  
S. Joe Qin
Keyword(s):  
Curve Fitting ◽  
Control Loops ◽  
Fitting Method ◽  
Valve Stiction ◽  
Curve Fitting Method

scholarly journals A Fast Haar Classifier based Gesture Recognition using camShift algorithm and Curve Fitting Method

2012 ◽  
pp. 295-299
Author(s):  
Bhavish Sushiel Agarwal ◽  
Jyoti R Desai ◽  
Snehanshu Saha
Keyword(s):  
Human Computer Interaction ◽  
Gesture Recognition ◽  
Curve Fitting ◽  
Lead Point ◽  
Hand Gestures ◽  
Curve Fit ◽  
Camshift Algorithm ◽  
Fitting Method ◽  
Wide Range ◽  
Curve Fitting Method

The use of hand gestures opens a wide range of application for human computer interaction. The paper makes use of haar classifiers and camShift algorithm to track the movement of hand. Parallelism is introduced at every step by segmenting the data from camshaft into an NxN grid. Every block of the grid now represents a lead point which is calculated from mean of all the points belonging to the particular grid. Now we have only N2 points to recognize the curve that was performed by the user in his action. Finally the fit that was found is compared to pre-defined curve fit data to find out the curve using Mahalanobis equation. Parallelism used in reducing the number of points to be fitted allows the recognition to be faster.

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