Abstract: A dynamic intelligent prediction control system is built in slender cylindrical grinding.
Elman network is used in the dynamic size prediction control model, and the first and the second
derivative of the actual amount removed from the workpiece are added into the network input,
which can greatly improve the size dynamic prediction accuracy. Moreover, a surface roughness
equation with vibration data is proposed. Based the equation, the surface roughness dynamic fuzzy
neural network prediction subsystem is built. Experiment verifies that the developed prediction
control system is feasible and has high prediction and control accuracy.
Abstract: Based on systematic engineering theory and method, interpretative structural model of
ceramic grindability system was set up. Property parameters, grinding parameters and grindability
indexes were selected as system elements. The adjacency matrix between system elements was
constructed. The reachability matrix was calculated according to adjacency matrix. By calculation
of reachability matrix and classification, interpretative structural model of the ceramic grindability
system was obtained. The system model could describe the relationship between the ceramic
grindability and system elements. The grindability system model also provides a fundamental
theoretical reference for the research on the grindability of ceramic materials. The weight of each
influencing factor of ceramic grindability can be calculated by applying the system model. The
grindability of ceramic materials can be evaluated objectively and comprehensively.
Abstract: A grinding trouble on-line monitoring mode is presented based on the nonlinear building
mode principle of neural network. The input units were the peak of the FFT, the peak of RMS, and
the standard deviation of AE signals. The outputs were the troubles of the grinding burning,
grinding chatter, and grinding wheel dull. The structure of neural network is established by
self-configuration method. The network mode is trained and tested by using the experiment data,
and the results indicate that the neural network mode obtained by self-configuration method has
high recognize rate for grinding troubles, and can be used to monitor grinding troubles on-line.
Abstract: To overcome the acceleration discontinuity and feed fluctuation of the conventional
five-axis grinding interpolator, a jerk-limited acceleration is utilized and two aspects of constraints is
taken into account: (1) the machining dynamics, including the constraints of power, velocity,
acceleration and jerk represented by upper bounds for each axis (2) the contour constraints of linear
segments, including the linear distance of the segment and sharp corner at the segment junctions.
With the analysis of these constrains, the optimal feed for each segment and the joint feed at the
segment junctions is derived. The corresponding adjusted interpolation algorithm with jerk-limited
acceleration is presented such that a smooth motion during the machining can be maintained. The
presented algorithm is demonstrated by the simulation result.
Abstract: The thermal error model of the 5-axis grinding machine tool was acquired by the
homogeneous coordinate transformation, including 17 thermal error components. The thermal
volumetric error real time compensation model was built by using the multiple regression analysis.
The thermal error compensation control system and the temperature sensing system were developed
and used as real-time compensation for the 5-axis grinding machine tool.
Abstract: The operation principle of SFD and the center moving orbit of grinding wheel spindle
which under the operation of SFD are studied. Based on the theoretical research, the experiment is
studied and analyzed. The study results show that the application of SFD technology can effectively
restrain vibration which is caused by the imbalance quality when the grinding wheel spindle turning
at ultrahigh speed. And it can remarkably improve the working quality and work efficiency of ultra
Abstract: Spindle thermal deformation is the main error source of many precision profile grinders.
In this paper, the relationship between spindle temperature and either radial or axial thermal
deformation is studied based on experiments. The placement and amount of temperature sensors are
optimized. Then a kind of thermal error modeling method based on support vector machine is
presented and applied in the modeling of thermal error of profile grinding. The result shows the
model is robust and the on-line accurate prediction of grinding thermal error is realized based on
monitoring of temperature rise of spindle. Finally, the error compensation strategy is discussed for
further application of thermal error modeling.
Abstract: The grind-hardening process integrates heat treatment processing into the production line,
reduces the number of producing procedures, shortens machining period and lowers the cost.
Meanwhile, grind-hardening machining doesn’t use cutting fluid. So the grind-hardening process is
a green manufacturing method with an extending application in future. Grinding hardening is an
effective method in machining SKD-11 hardened steel due to its good quenched property. In this
paper, the grind-hardening characteristics of SKD-11 hardened steel are discussed, and the impacts
on the hardened surface layer varying with the grinding parameters are also studied. Optimization
of grinding parameters of SKD-11 hardened steel is conducted based on the study.
Abstract: In this study, a number of experiments on surface grinding of nanostructured WC/12Co
(n-WC/12Co) coatings were conducted on a precision surface grinding machine with a horizontal
axis and rectangular worktable. The residual stresses in the as-sprayed and ground n-WC/12Co
coatings were measured with the X-ray diffraction method. According to the experimental study and
theoretical analysis, this paper investigates the influences of grinding parameters, such as depth of
cut, feedrate of workpiece, abrasive grit size and wheel bond type on residual stresses precision
grinding of n-WC/12Co coatings.
Abstract: This paper aims to evaluate the surface and sub-surface integrity of optical glasses which
were correspondingly machined by coarse and fine-grained diamond grinding wheels on Tetraform
‘C’ and Nanotech 500FG. The experimental results show that coarse-grained diamond grinding
wheels are capable of ductile grinding of optical glasses with high surface and sub-surface integrity.
The surface roughness values are all in nanometer scale and the sub-surface damages are around
several micros in depth, which is comparative to those machined by fine-grained diamond wheels.