Deterioration and defects in building components are key aspects to consider when assessing buildings’ conditions, as they may influence the building’s functionality. The typical defects include cracking, moisture, dampness, and architectural defects. This paper aims to evaluate the defects in a building using a non-destructive testing (NDT), which is the Infrared Thermography (IRT) method. A visual inspection method is then conducted to verify the results of the IRT method. The combination of IRT and visual inspection methods can identify the type of defect and level of severity more accurately. In both methods, ratings or scores are given to the collected defect data to determine the consistency between them. Two (2) buildings were selected as case studies; AA1 and BB2 are multistorey buildings. From those, 51 and 67 spots were taken from the IRT method and further verification process, respectively. Among the defects that were found were moisture, dampness, cracking, staining, chipping, and flaking paint. From all the findings, IRT was found to be comparable with the visual inspection results for serious defects such as cracking and flaking paint. However, IRT was believed to underestimate the architectural defects of staining and chipping. Even so, serious defects such as dampness were also underestimated in IRT due to the fact that the temperature difference between different ratings will not differ much. In conclusion, the IRT method has the potential to be used as a tool for building condition rating. However, it should be assisted with a visual inspection, and more research needs to be conducted for its practicality.

Surface roughness parameter prediction and evaluation are important factors in determining the satisfactory performance of machined surfaces in many fields. The recent trend towards the measurement and evaluation of surface roughness has led to renewed interest in the use of newly developed non-contact sensors. In the present work, an attempt has been made to measure the surface roughness parameter of different machined surfaces using a high sensitivity capacitive sensor. A capacitive response model is proposed to predict theoretical average capacitive surface roughness and compare it with the capacitive sensor measurement results. The measurements were carried out for 18 specimens using the proposed capacitive-sensor-based non-contact measurement setup. The results show that surface roughness values measured using a sensor well agree with the model output. For ground and milled surfaces, the correlation coefficients obtained are high, while for the surfaces generated by shaping, the correlation coefficient is low. It is observed that the sensor can effectively assess the fine and moderate rough-machined surfaces compared to rough surfaces generated by a shaping process. Furthermore, a linear regression model is proposed to predict the surface roughness from the measured average capacitive roughness. It can be further used in on-machine measurement, on-line monitoring and control of surface roughness in the machine tool environment.

A computer measurement system, designed and built by authors, dedicated to location and description of partial discharges (PD) in oil power transformers examined by means of the acoustic emission (AE) method is presented. The measurement system is equipped with 8 measurement channels and ensures: monitoring of signals, registration of data in real time within a band of 25–1000 kHz in laboratory and real conditions, basic and advanced analysis of recorded signals. The basic analysis carried out in the time, frequency and time-frequency domains deals with general properties of the AE signals coming from PDs. The advanced analysis, performed in the discrimination threshold domain, results in identification of signals coming from different acoustic sources as well as location of these sources in the examined transformers in terms of defined by authors descriptors and maps of these descriptors on the side walls of the tested transformer tank. Examples of typical results of laboratory tests carried out with the use of the built-in measurement system are presented.