Application skills of ultrasonic flaw detection for forgings and castings

Forgings and castings are important blanks of various mechanical equipment and boiler pressure vessels.
I Ultrasonic flaw detection of castings
Due to the coarse grain, poor sound permeability and low signal-to-noise ratio of the casting, the flaw detection is difficult. It uses the sound beam with high-frequency sound energy to reflect when it encounters the internal surface or defects in the propagation of the casting. The reflected sound energy is a function of the directivity and nature of the inner surface or defect and the acoustic impedance of this reflector. Therefore, the sound energy reflected by various defects or inner surfaces can be used to detect the location, wall thickness or depth of defects under the surface. As a widely used nondestructive testing method, ultrasonic testing has the following main advantages: high detection sensitivity and can detect small cracks; It has large penetration ability and can detect thick section castings. Its main limitations are: it is difficult to interpret the reflection waveform of disconnected defects with complex contour size and poor directivity; Undesirable internal structures, such as grain size, microstructure, porosity, inclusion content or fine dispersed precipitates, also hinder waveform interpretation; In addition, it is necessary to refer to the standard test block during testing.
II Ultrasonic flaw detection of forgings
（1） Forging processing and common defects
Forgings are made of hot steel ingots by forging deformation. The forging process includes heating, deformation and cooling. Forging defects can be divided into casting defects, forging defects and heat treatment defects. Casting defects mainly include shrinkage cavity residue, porosity, inclusion, crack, etc. Forging defects mainly include folding, white spots, cracks, etc. Heat treatment defects are mainly cracks.
Shrinkage cavity residue is the residual of shrinkage cavity in ingot due to insufficient head cutting during forging, which is mostly found at the end of forging.
Porosity refers to the non compactness and holes formed during solidification and shrinkage of the ingot. During forging, it is not fully dissolved due to insufficient forging ratio, which mainly exists in the center and head of the ingot.
Inclusions include internal inclusions, foreign non-metallic inclusions and metal inclusions. The internal inclusions are mainly concentrated in the center and head of the ingot.
The cracks include casting cracks, forging cracks and heat treatment cracks. The axial intergranular crack of austenitic steel is the crack caused by casting. Improper forging and heat treatment will form cracks on the surface or center of the forging.
The white spot is the cracking caused by excessive stress due to the high hydrogen content of forgings, too fast cooling after forging and too little time for the dissolved hydrogen in the steel to escape. The white spots are mainly concentrated in the center of the large section of the forging. White spots always appear in groups in steel.
（2） Overview of flaw detection methods
According to the classification of flaw detection time, flaw detection of forgings can be divided into raw material flaw detection, flaw detection in manufacturing process, product inspection and in-service inspection.
The purpose of raw material flaw detection and flaw detection in the manufacturing process is to find defects as soon as possible, so as to take timely measures to avoid scrapping caused by the development and expansion of defects. The purpose of product inspection is to ensure product quality. The purpose of in-service inspection is to supervise the defects that may occur or develop after operation, mainly fatigue cracks.
1. Flaw detection of shaft forgings
The forging process of shaft forgings is mainly based on drawing, so the orientation of most defects is parallel to the axis. The detection effect of this kind of defects is the best from the radial direction with the longitudinal wave straight probe. Considering that the defects will have other distribution and orientation, the flaw detection of shaft forgings should also be supplemented by straight probe axial detection, angle probe circumferential detection and axial detection.
2. Flaw detection of cake and bowl forgings
The forging process of cake and bowl forgings is mainly upsetting, and the distribution of defects is mainly parallel to the end face. Therefore, using a straight probe to detect defects on the end face is the best method to detect defects.
3. Flaw detection of barrel forgings
The forging process of barrel forgings is upsetting first, then punching, and then rolling. Therefore, the orientation of defects is more complex than that of defects in shaft forgings and cake forgings. However, since the central part with the worst quality in the ingot has been removed during punching, the quality of barrel forgings is generally better. The main orientation of the defect is still parallel to the outer circular surface of the cylinder, so the flaw detection of cylinder forgings is still mainly based on the outer circular surface of straight probe, but for cylinder forgings with thick wall, angle probe must be added.
（3） Selection of detection conditions
1. Probe selection
In ultrasonic flaw detection of forgings, longitudinal wave straight probe is mainly used, and the wafer size is Φ 14～ Φ 28mm, common Φ 20mm。 For small forgings, small wafer probe is generally used considering the reasons of near-field region and coupling loss. Sometimes, in order to detect defects with a certain inclination angle to the detection surface, an angle probe with a certain K value can also be used for detection. For short-range defects, due to the influence of the blind area and near-field area of the straight probe, the double crystal straight probe is often used for detection.
The grains of forgings are generally small, so a higher flaw detection frequency can be selected, usually 2.5 ~ 5.0mhz. For a few forgings with coarse grains and serious attenuation, in order to avoid "forest echo" and improve the signal-to-noise ratio, a lower frequency should be selected, generally 1.0 ~ 2.5MHz.