State Space Modeling of Sheet Metal Assembly for Dimensional Control

1999 ◽  
Vol 121 (4) ◽  
pp. 756-762 ◽  
Author(s):  
Jionghua Jin ◽  
Jianjun Shi
Keyword(s):  
State Space ◽  
Sheet Metal ◽  
State Space Model ◽  
Measurement Information ◽  
Dimensional Control ◽  
Locating Error ◽  
Variation Propagation ◽  
Space Modeling ◽  
State Space Modeling ◽  
Sheet Metal Assembly

In this paper, a state space modeling approach is developed for the dimensional control of sheet metal assembly processes. In this study, a 3-2-1 scheme is assumed for the sheet metal assembly. Several key concepts, such as tooling locating error, part accumulative error, and re-orientation error, are defined. The inherent relationships among these error components are developed. Those relationships finally lead to a state space model which describes the variation propagation throughout the assembly process. An observation equation is also developed to represent the relationship between the observation vector (the in-line OCMM measurement information) and the state vector (the part accumulative error). Potential usage of the developed model is discussed in the paper.

Modeling Variation Propagation Based on State Space and its Application to Dimensional Variation Prediction in Shipbuilding

2011 ◽  
Vol 291-294 ◽  
pp. 2889-2892
Author(s):  
Xiang Rui Liu ◽  
Zhi Ying Zhang
Keyword(s):  
State Space ◽  
Assembly Process ◽  
Accuracy Control ◽  
Dimensional Control ◽  
Shipbuilding Industry ◽  
Locating Error ◽  
Variation Propagation ◽  
Dimensional Variation ◽  
Block Construction ◽  
Stream Model

Dimensional control is one of the most important challenges in shipbuilding industry. In order to predict assembly dimensional variation in block construction of shipbuilding, a variation stream model based on state space is presented in this paper, which can be further applied to accuracy control. Both locating error and welding deformation are taken into consideration in this model, and variation propagation mechanisms and accumulative rule in the assembly process are analyzed, then, a model is developed to describe the variation propagation throughout the assembly process, finally, an example of flat block construction is given to provide this method is effective and useful.

Hybrid State Space Modeling of a Spark Ignition Engine for Online Fault Diagnosis

2017 ◽  
Vol 140 (4) ◽  
Author(s):  
E. P. Nadeer ◽  
Amit Patra ◽  
Siddhartha Mukhopadhyay
Keyword(s):  
State Space ◽  
Gasoline Engine ◽  
State Space Model ◽  
Control Unit ◽  
Spark Ignition ◽  
Spark Ignition Engine ◽  
Intake Manifold ◽  
Hybrid State ◽  
Space Modeling ◽  
State Space Modeling

In this work, a nonlinear hybrid state space model of a complete spark ignition (SI) gasoline engine system from throttle to muffler is developed using the mass and energy balance equations. It provides within-cycle dynamics of all the engine variables such as temperature, pressure, and mass of individual gas species in the intake manifold (IM), cylinder, and exhaust manifold (EM). The inputs to the model are the same as that commonly exercised by the engine control unit (ECU), and its outputs correspond to available engine sensors. It uses generally known engine parameters, does not require extensive engine maps found in mean value models (MVMs), and requires minimal experimentation for tuning. It is demonstrated that the model is able to capture a variety of engine faults by suitable parameterization. The state space modeling is parsimonious in having the minimum number of integrators in the model by appropriate choice of state. It leads to great computational efficiency due to the possibility of deriving the Jacobian expressions analytically in applications such as on-board state estimation. The model was validated both with data from an industry standard engine simulation and those from an actual engine after relevant modifications. For the test engine, the engine speed and crank angle were extracted from the crank position sensor signal. The model was seen to match the true values of engine variables both in simulation and experiments.

State-Space Modeling and Control of Acoustic Systems

2001 ◽  
Author(s):  
Reza Kashani ◽  
Asim S. Mohammad
Keyword(s):  
State Space ◽  
State Space Model ◽  
Feedback Controller ◽  
Mode Shapes ◽  
Acoustic System ◽  
Modeling And Control ◽  
Space Modeling ◽  
State Space Modeling ◽  
Space Formulation ◽  
And Control

Abstract Synthesis and analysis of model-based controllers for an acoustic system require the state-space formulation of the system. The use of modal data, i.e. resonant frequencies, model damping ratios, and mode shapes, in constructing state-space model of an aoucstic system is described in this paper. Moreover, a simple, low-order feedback controller for adding damping to and/or cancelling offending noise in an acoustic system is introduced. State-space modeling, as well as the effectiveness of the proposed feedback controller are demonstrated through numerical and experimental, illustrative examples.

scholarly journals Representation of multi-connected system of Fuzzy State Space Modeling (FSSM) in potential method based on a network context

2017 ◽  
Vol 13 (4) ◽  
pp. 711-716 ◽  
Author(s):  
Jibril Aminu ◽  
Tahir Ahmad ◽  
Surajo Sulaiman
Keyword(s):  
State Space ◽  
State Space Model ◽  
Type A ◽  
Potential Method ◽  
Network System ◽  
Space Model ◽  
Space Modeling ◽  
State Space Modeling ◽  
Fuzzy State

The complexity of a system of Fuzzy State Space Modeling (FSSM) is the reason that leads to the main objective of this research. A multi-connected system of Fuzzy State Space Model is made up of several components, each of which performs a function. These components are interconnected in some manner and determine how the overall system operates. In this study, we study the concept of graph, network system and network projections which are the requisite knowledge to potential method. Finally, the multi-connected system of FSSM of type A namely feeder, common feeder and greatest common feeder are transformed into potential method using various method of transformation.

Tolerance Allocation and Maintenance Optimal Design for Fixture in Multi-Station Panel Assembly Process

2010 ◽  
Vol 34-35 ◽  
pp. 1039-1045 ◽  
Author(s):  
An Cui ◽  
Hai Peng Zhang
Keyword(s):  
Sheet Metal ◽  
Optimization Model ◽  
Manufacturing Systems ◽  
State Space Model ◽  
Tolerance Allocation ◽  
Vehicle Body ◽  
Type Model ◽  
Assembly Process ◽  
Variation Propagation ◽  
Sheet Metal Assembly

Traditionally, tolerance and maintenance designs have been studied separately in manufacturing systems. An integration optimization model of tolerance and maintenance for multi-station sheet metal assembly was presented in this work. Based on the variation propagation state space model, a quality loss model of multi-station assembly processes was built. This model considered the effect of process loss. It built the function of fixture tolerance, replacement cycle and total cost. The nonlinear tolerance optimization of locating holes (slots) in multi-station sheet metal assembly was achieved. The optimization model was calculated with practical data in a vehicle body side assembly. Compared with the same type model, it’s verified correct and rational of the model in multi-station sheet metal assembly process quality control.

Sign in / Sign up

Export Citation Format

Share Document