Tool wear and chatter detection using the coherence function of two crossed accelerations

Tool wear and chatter have been found to be the main causes of rejects in the machining of super alloys. A novel detection technique to identify both tool wear and chatter in turning a nickel-based super alloy is introduced. It uses the coherence function between two crossed accelerations from the bending vibration of the tool shank. The value of the coherence function at the chatter frequency reaches unity at the onset of chatter. Its values at the first natural frequencies of the tool shank approach unity in the severe tool wear stage. The results are interpreted using the analysis of the coherence function for a single input-two output model. The advantage of using this method is that the thresholds for detecting severe tool wear and chatter can be easily set, since values of coherence function are normalized to a range of between zero and unity, and are also not so susceptible to changing cutting conditions, because the value of the coherence function is close to unity at the onset of chatter and severe tool wear.     

A novel AR-based robot programming and path planning methodology

This paper discusses the benefits of applying Augmented Reality (AR) to facilitate intuitive robot programming, and presents a novel methodology for planning collision-free paths for an n degree-of-freedom (DOF) manipulator in an unknown environment. The targeted applications are where the end-effector is constrained to move along a visible 3D path/curve, which position is unknown, at a particular orientation with respect to the path, such as arc welding and laser cutting. The methodology is interactive as the human is involved in obtaining the 3D data points of the desired curve to be followed through performing a number of demonstrations, defining the free space relevant to the task, and planning the orientations of the end-effector along the curve. A Piecewise Linear Parameterization (PLP) algorithm is used to parameterize the data points using an interactively generated piecewise linear approximation of the desired curve. A curve learning method based on Bayesian neural networks and reparameterization is used to learn and generate 3D parametric curves from the parameterized data points. Finally, the orientation of the end-effector along the learnt curve is planned with the aid of AR. Two case studies are presented and discussed.     

A surface blending approach for displacement features on freeform surfaces

Embedding a number of displacement features into a base surface is common in industrial product design and modeling, where displaced surface regions are blended with the unmodified surface region. The cubic Hermite interpolant is usually adopted for surface blending, in which tangent plane smoothness across the boundary curve is achieved. However, the polynomial degree of the tangent field curve obtained symbolically is considerably higher, and the reduction of the degree of a freeform curve is a non-trivial task. In this work, an approximation surface blending approach is proposed to achieve tangential continuity across the boundary curve. The boundary curve is first offset in the tangent field with the user-specified tolerance, after which it is refined to be compatible with the offset curve for surface blending. Since the boundary curve is offset in a three-dimensional (3D) space, the local self-intersection in the offset curve is addressed in a 2D space by approximately mapping the offset vectors in the respective tangent planes to the parameter space of the base surface. The proposed algorithm is validated using examples, and the normal vector deviation along the boundary curve is investigated.     

Registration using natural features for augmented reality systems

Registration is one of the most difficult problems in augmented reality (AR) systems. In this paper, a simple registration method using natural features based on the projective reconstruction technique is proposed. This method consists of two steps: embedding and rendering. Embedding involves specifying four points to build the world coordinate system on which a virtual object will be superimposed. In rendering, the Kanade-Lucas-Tomasi (KLT) feature tracker is used to track the natural feature correspondences in the live video. The natural features that have been tracked are used to estimate the corresponding projective matrix in the image sequence. Next, the projective reconstruction technique is used to transfer the four specified points to compute the registration matrix for augmentation. This paper also proposes a robust method for estimating the projective matrix, where the natural features that have been tracked are normalized (translation and scaling) and used as the input data. The estimated projective matrix will be used as an initial estimate for a nonlinear optimization method that minimizes the actual residual errors based on the Levenberg-Marquardt (LM) minimization method, thus making the results more robust and stable. The proposed registration method has three major advantages: 1) It is simple, as no predefined fiducials or markers are used for registration for either indoor and outdoor AR applications. 2) It is robust, because it remains effective as long as at least six natural features are tracked during the entire augmentation, and the existence of the corresponding projective matrices in the live video is guaranteed. Meanwhile, the robust method to estimate the projective matrix can obtain stable results even when there are some outliers during the tracking process. 3) Virtual objects can still be superimposed on the specified areas, even if some parts of the areas are occluded during the entire process. Some indoor and outdoor experiments have been conducted to validate the performance of this proposed method.     

General Liability Insurance Coverage for Mold Claims

Although humans and mold have coexisted for centuries, the effects of mold on health and property have recently received considerable attention. Members of the construction industry and commercial property owners are, with increasing frequency, finding themselves defending claims of property damage or personal injury due to indoor mold growth. These designers, builders, and property owners frequently turn to their general liability insurance carriers for defense and indemnification without having a full understanding of the protections afforded by their commercial general liability policies. This article provides an introduction to the typical coverages and exclusions applicable to mold related claims submitted for general liability coverage. This article also discusses maximizing the potential for coverage by notifying and cooperating with one’s insurer and provides guidance on the avoidance of indoor mold growth and claims. Questions concerning the meaning and effect of particular insurance policy provisions and the availability of additional or alternative coverages should be directed to one’s insurance professional or coverage attorney.     

Feature-based design in a distributed and collaborative environment

In this paper, a client/server framework has been developed to enable a dispersed team to accomplish a feature-based design task collaboratively. A manipulation client+modelling server infrastructure has been proposed to facilitate consistent primary information modelling for multiple users and adaptability of the system. Based on feature-to-feature relationships, a distributed feature manipulation mechanism has been proposed to filter the varied information of a working part during a co-design activity to avoid unnecessary re-transferring of the complete large-size CAD files each time when any interactive operation is imposed on the model by a client. In the distributed environment, a design task and the engaged clients are organised and connected through working sessions generated and maintained dynamically with a collaborative server. The environment is open to downstream manufacturing analysis modules to achieve distributed concurrent engineering.     

Hybrid Approach to Modeling the Process of Convective Radiative Heat and Mass Transfer in Closed Differentially Heated Cavities

Journal of Engineering Physics and Thermophysics - A hybrid model has been developed for the analysis of the process of combined mass and heat transfer in closed rectangular cavities under the...     

Human Endothelial Progenitor Cells Protect the Kidney against Ischemia-Reperfusion Injury via the NLRP3 Inflammasome in Mice

Ischemia-reperfusion injury (IRI) is a major cause of acute kidney injury (AKI) and progression to chronic kidney disease (CKD). However, no effective therapeutic intervention has been established for ischemic AKI. Endothelial progenitor cells (EPCs) have major roles in the maintenance of vascular integrity and the repair of endothelial damage; they also serve as therapeutic agents in various kidney diseases. Thus, we examined whether EPCs have a renoprotective effect in an IRI mouse model. Mice were assigned to sham, EPC, IRI-only, and EPC-treated IRI groups. EPCs originating from human peripheral blood were cultured. The EPCs were administered 5 min before reperfusion, and all mice were killed 72 h after IRI. Blood urea nitrogen, serum creatinine, and tissue injury were significantly increased in IRI mice; EPCs significantly improved the manifestations of IRI. Apoptotic cell death and oxidative stress were significantly reduced in EPC-treated IRI mice. Administration of EPCs decreased the expression levels of NLRP3, cleaved caspase-1, p-NF-κB, and p-p38. Furthermore, the expression levels of F4/80, ICAM-1, RORγt, and IL-17RA were significantly reduced in EPC-treated IRI mice. Finally, the levels of EMT-associated factors (TGF-β, α-SMA, Snail, and Twist) were significantly reduced in EPC-treated IRI mice. This study shows that inflammasome-mediated inflammation accompanied by immune modulation and fibrosis is a potential target of EPCs as a treatment for IRI-induced AKI and the prevention of progression to CKD.