Application of Neural Networks for Piezoelectric Sensor based Strength Monitoring of Concrete Cube

Artificial Neural Networks (ANN) is an algorithm used in Artificial Intelligence and is used for modeling com- plex data. They have applications in various fields like Com- puter Vision, Self Driving Vehicles, amongst various other fields. In this paper we discuss its uses in Civil Engineering applications. Piezoelectric sensors which are used for Struc- tural Health Monitoring (SHM) are being used to produce data required for ANN. The frequency output response (Im- pedance) of the piezoelectric sensors is obtained using an Impedance Analyzer. We get a characteristic impedance sig- nal which is a function of frequency. This signal comprising of several peaks and valleys varies with change in strength of the concrete cube. The peaks/valleys can shift in amplitude or move left / right in the graph. This forms a preferable envi- ronment for use of neural networks since the variation in data (signal) is a complex function of the inputs. An ANN was constructed and trained on some training data. After this, the trained ANN was used to predict the strength of the cube based on the new signal data obtained from Analyzer, which is un- seen data for ANN. This paper is expected to be useful for application of ANN in new civil engineering field with a good accuracy and efficiency.