Sripati Sah

An adaptive sampling scheme for improved energy utilization in wireless sensor networks

This paper presents the design and evaluation of a novel adaptive sampling algorithm for reducing energy consumption in data acquisition and communication subsystems of a wireless sensor node. The algorithm uses isochronous measurements of the frequency content of the signal as the basis for adaptively varying the sampling rate. This allows signal acquisition at the minimum rate without sacrificing signal quality. Simulation results indicate that the algorithm dynamically responds to changes in the frequency content by adjusting the sampling rate, thus achieving a significant reduction in the energy consumed in acquisition and communication, with only a minimal loss in signal fidelity.

Pressure and Draw-In Maps for Stamping Process Monitoring

This paper presents two tooling-integrated sensing techniques for the in situ measurement and analyses of pressure distribution at the tool–workpiece interface and material draw-in during the stamping processes. Specifically, the contact pressure distribution is calculated from the measurements by an array of force sensors embedded in the punch, whereas sheet draw-in is measured by custom-designed thin film sensors integrated in the binder. Quantification of the pressure distribution from spatially distributed sensors has been investigated as a regularization problem and solved through energy minimization. Additionally, a Bayesian framework has been established for combining finite-element analysis (FEA) based estimates of the pressure distribution with experimentally measured evidence, to achieve improved spatiotemporal resolution. A new data visualization technique termed pressure and draw-in (PDI) map has been introduced, which combine spatiotemporal information from the two sensing techniques into an illustrative representation by capturing both the tool–workpiece interaction (dynamic information) and resulting workpiece motion (kinematic information) in a series of time-stamped snap shots. Together, the two separate yet complementary process-embedded sensing methods present an effective tool for quantifying process variations in sheet metal stamping and enable new insight into the underlying physics of the process.

Spatial Blending Functions for Improved Estimation of Contact Pressure Distribution at the Tool-Workpiece Interface

On-line measurement of contact pressure distribution (CPD) at the tool-workpiece interface during sheet metal stamping processes plays a critical role in tool wear and product quality monitoring and control. Realizing such measurement poses a significant challenge, due to the severe operating conditions at the contact interface. Since the number of sensors that can be integrated into a tooling structure is limited by concerns of structural integrity, a mathematical framework is needed for estimating the contact pressure distribution measured by sparse sensors. This paper investigates a new technique termed the Spatial Blending Functions (SBF), which provides an improved estimate of the contact pressure distribution by merging measurements from tooling-embedded sensors with simulation results from Finite Element modeling. The effectiveness of the SBF-based merging technique is demonstrated for the case of a panel stamping operation through Finite Element simulations and experiments performed on a stamping press with a tooling-integrated sensing system. Analysis of the results demonstrates that the SBF-based CPD estimation is more accurate than classic numeric surface interpolation methods, thus enhances contact pressure distribution estimation for stamping process monitoring.Copyright

Integrated Sensing of Pressure Distribution at the Workpiece-Tool Interface in Sheet Metal Stamping

To improve process monitoring in the sheet metal stamping process, it is of interest to measure the contact pressure distribution at the workpiece-tool interface. This paper presents the design and performance evaluation of a tooling integrated sensing method that estimates the pressure distribution on the contact interface through an array of force sensors embedded in the stamping tool. Experiments were conducted to evaluate two techniques for integrating force sensors into the tool structure. The spatially discrete nature of the sensor measurements necessitates the use of a numerical interpolation model to construct continuous pressure distribution maps from the discrete sensing locations. Experiments conducted on a customized panel stamping test bed confirmed the effectiveness of the tooling-integrated sensing method for improving the observability of the process with benefits to process designers.Copyright