P.M. Bravo

The application of a two-step AI model to an automated pneumatic drilling process

Real-world processes may be improved through a combination of artificial intelligence and identification techniques. This work presents a multidisciplinary study that identifies and applies unsupervised connectionist models in conjunction with modelling systems. This particular industrial problem is defined by a data set relayed through sensors situated on a robotic drill used in the construction of industrial storage centres. The first step entails determination of the most relevant structures in the data set with the application of the connectionist architectures. The second step combines the results of the first one to identify a model for the optimal working conditions of the drilling robot that is based on low-order models such as black box that approximate the optimal form of the model. Finally, it is shown that the most appropriate model to control these industrial tasks is the Box–Jenkins algorithm, which calculates the function of a linear system from its input and output samples.

Determination of the Plastic Collapse Load for Wire-Wound Pressure Vessels

This paper is focused on determining the plastic collapse load of vessels which consist of an inner cylinder prestressed by a surrounding winding. This winding consists of a wire helically wound edge-to-edge in pretension in a number of layers around the outside of the inner cylinder. As a consequence, compression stresses are introduced in the cylinder, and the fatigue life of the vessel can be greatly increased. The ASME code, Section VIII - Division 3, provides the analytical equations for the stress calculation in wire-wound vessels under linear-elastic conditions (ASME, 2007). However, to obtain the plastic collapse load of the vessel, finite element method should be used. In this way, the main aim of this paper is to present a numerical procedure for the FE simulation of wire-wound vessels. For this simulation, it must be taken into account that the wire winding is a continuous process where every new layer is coiled around all previous deformed layers. Hence, a layer-by-layer numerical procedure which takes into account this continuous process during winding has been developed. Some examples are given to demonstrate the applicability of the procedure. Once the numerical procedure was validated, it was used to obtain (i) the maximum circumferential stress after winding, (ii) the initial plastic load, and (iii) the plastic collapse load. To obtain the plastic collapse load, an elastic perfectly-plastic material behaviour has been considered. Finally, the numerical results obtained for the plastic collapse load were obtained as a function of several ratios over a wide range, which take into account the cylinder thickness, the wire-wound thickness, the wire-wound pretension and the yield limit of the material.Copyright

A Cooperative Unsupervised Connectionist Model to Identify the Optimal Conditions of a Pneumatic Drill

A novel connectionist method to feature selection is proposed in this paper to identify the optimal conditions to perform drilling tasks. The aim is to extract information from complex high dimensional data sets. The model used is based on a family of cost functions which maximizes the likelihood of identifying a specific distribution in a data set. It employs lateral connections derived from the Rectified Gaussian Distribution to enforce a more sparse representation in each weight vector. The data investigated is obtained from the sensors allocated in a robot used to drill and build industrial warehouses. It is hoped that in classifying this data related with the strength, the water volume for refrigerating, speed and time of each sample, it will help in the search of the best conditions to perform the drilling of reinforce concrete slabs. This would produce a great saving for the company which owns the drilling robot.