Purpose In the case of machines, structures and assemblies, the crack generation and propagation is becoming a great concern, especially in airplane wings, turbine blades and such other applications. This is because these parts are very large in size and the crack size is very small, i.e. in microns. Hence, there is an important need to locate the crack and to find its severity before it starts to propagate and also to detect these parameters by on-site non-destructive testing methods. This paper aims to develop and test the methodology to locate an unknown single open crack in steel cantilever beam along with its severity. Design/methodology/approach This study covers analytical, numerical and experimental analysis for healthy and cracked beams. Vibration-based approach and finite element analysis (FEA) approach is used for analytical and numerical study respectively. Own designed and dedicated experimental set-up is used for testing purpose along with fast fourier transform analyzer. An anti-resonance technique is used to locate and to find the severity of unknown crack. The statistical approach helps to validate the results. Findings The comparison of the natural frequency of healthy and cracked steel cantilever beam shows that the crack in the beam reduces its natural frequency. The accuracy of results is achieved by finding actual density and Young's modulus of steel specimen under consideration. It is helpful to verify the health of the non-cracked beam by applying dye testing. The study of natural frequency and anti-resonance gives the location of crack and its depth also. The FEA approach proved to be an important tool for numerical analysis of cracked beam. Research limitations/implications The research is limited to steel material and surface cracks only. Practical implications Practically, this study highlights how to locate a surface crack in steel beam along with its depth, i.e. severity with great accuracy. Identification of the factors such as location and depth of a crack provide the severity of damage in airplane wings, turbine blades, bridges and many more, and thereby, it helps in safety at working vicinity. Social implications The identification and solutions of current research helps to predict the operational life of machine elements such as airplane wings, turbine blades, bridges and many more, and thereby, it helps in the safety of people in working vicinity of such structures. Originality/value The work presented, is based on original research and experimentation. This work is valued contribution in the field of methodologies applied for fault detection in structures and also determining its correctness by numerical and experimental work.