Acoustic emission as a tool for prediction of nugget diameter in resistance spot welding

Abstract

Acoustic emission monitoring has been successfully employed in different application areas such as monitoring of fatigue loaded bridges and pressure testing of vessels. However, application of this technology on resistance (spot) welding processes yielded limited results. Existing literature only mentions the detection of certain defects such as expulsion and cracked welds. Detecting nugget nucleation and growth, to allow prediction of nugget diameter, has never been proven to be feasible based on acoustic emission signals. This work contains experiments based on varying as well as constant nominal welding parameter sets, where acoustic emission waveforms were collected during the welding process. A methodology is described, revealing a correlation between certain frequencies present in the acoustic emission signal and physical events occurring during welding. Based on these frequencies, a model is constructed for predicting the nugget diameter of resistance spot welds based on acoustic emission measurement data.

Orta Frekans Doğru Akım Direnç Nokta Kaynak Sistemlerinde Kullanılan Evirici Topolojilerinin İncelenmesi

“…Endüstride bir otomobil veya panel radyatör binlerce nokta kaynağından oluşur. DNK, otomatikleştirilebilir, pratik yapısı sayesinde, bu tür metal plakalardan oluşan ürünlerin eklemlerini birleştiren seri üretim tesisleri için temel yöntem olarak karşımıza çıkar [9]. DNK, düşük gerilimli yüksek elektrik akımı kullanır.…”

Real-time prediction model of welding temperature based on LSTM

“…Nomura K et al [7] used the optical image of the top layer of the welding pool to predict the depth of the gap fluctuation gas metal arc welding pool, and the estimation accuracy of more than 95% was less than 1mm. Dejans et al [8] explored the correlation between some of the acoustic waves and the physical events that occurred in the welding through the sound waves collected in the welding. Sarkar et al [9] proposed a machine learning-based -multiple linear regression (MLR) to predict and transient temperature in SAW.…”

Magneto-Optical Imaging of Arbitrarily Distributed Defects in Welds under Combined Magnetic Field

“…This method has great application prospects and needs to be further studied. At present, the non-destructive testing methods of spot welding are radiographic testing [15], acoustic emission testing [16], ultrasonic testing [17][18][19], infrared thermography testing [20,21], dynamic resistance testing [22,23], eddy current testing [24,25], magnetic flux leakage testing [26,27], and so on.…”

“…Moreover, because X-rays are harmful to the human body, the application of the radiographic inspection of solder joint quality in actual production is limited [15]. Many studies show that acoustic emission testing is only suitable for on-line detection and early damage prediction at present [16]. Due to the weak acoustic emission signal of some materials in actual production and the sound signal being easily affected by the environment, it is very difficult to detect the defects, and other detection methods are needed.…”