# A Displacement Controlled Fatigue Test Method for Additively Manufactured Materials
## 4 Experimental Setup  
### Mini Fatigue Testing Machine  
The mini fatigue testing machine consists of six major parts: (i) an electromagnetic actuator, (ii) a non-contact displacement sensor, (iii) a load cell, (iv) a controller, (v) a power amplifier or driver, and (vi) a test bench. The voice coil of a subwoofer was used as the actuator. The sub-woofer behaves as a low audio frequency shaker. The mathematical model of an electrodynamic shaker and a sub-woofer is relatively similar though the moving elements of a shaker are more rigid than a subwoofer. Higher rigidity multiplies the power requirements. To design a low power system, a soft mechanical suspension of the sub-woofer was implemented to transfer maximum energy to the specimen. The actuator is made of a high Curie temperature ferrite magnet with a cast aluminum frame of 10 inches diameter. The larger diameter of the voice coil (3 inches) than the length (1 inch) of the specimen supports the one-dimensional movement. The dust cap of the voice coil was replaced with a plastic flange. A load cell was mounted in-line between the central clamp and the flange to measure the tensile and compressive force. To measure the displacement of the specimen, a high-speed non-contact laser displacement sensor was fixed with a guide rail. Figure 5 illustrates the test bench setup. First, the specimen was clamped at the center. The specimen sits on the bearings at both ends as shown in Figure 5. Spacers were used at both ends to ensure no preload on the specimen. Then, the other bearing holders were placed and clamped using heavy load toggle clamps on top. To ensure line contact at both ends, bearings were used. Bearings also minimize the friction during the simply supported vibration test. By sliding the displacement sensor using the guide rail, the sensor was pointed at the center of the specimen. The displacement measured by the sensor was processed using a microcontroller to determine the amplitude and mean of the displacement. The data was sent to a computer from the microcontroller using a serial port. An adaptive controller was implemented in  
\begin{table}
\begin{tabular}{l c c c c c c c c c c c} \hline \hline
**Material** & **C** & **Mn** & **Si** & **S** & **P** & **Cr** & **Ni** & **Cu** & **Mo** & **Co** & **N** & **O** \\ \hline Wrought & 0.023 & 1.69 & 0.43 & 0.020 & 0.034 & 18.10 & 8.02 & 0.63 & 0.24 & 0.15 & 0.084 & - \\ Powder & 0.015 & 1.40 & 0.63 & 0.004 & 0.012 & 18.50 & 9.90 & \(<\)0.1 & - & - & 0.090 & 0.02 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Chemical properties (wt%) of 304L stainless steel powder and bulk 304 stainless steel.  
\begin{table}
\begin{tabular}{l c c c c c c} \hline \hline
**Parameter** & **Power** & **Hatch Space** & **Point Distance** & **Exposure Time** & **Energy Density** & **Raster Rotation** \\
**Set** & **(watt)** & **(μm)** & **(μm)** & **(millisecond)** & **(MJ/m\({}^{3}\))** & **(degree)** \\ \hline Nominal & 200 & 85 & 60 & 75 & 58.8 & 67 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Parameters used to build additively manufactured part using selective laser melting (SLM) process.  
the Python development environment to estimate the required amplitude of the sinusoidal control signal. The signal from the computer was sent to a waveform generator via Ethernet. A linear power amplifier connected with the waveform generator drives the actuator. All process and manipulated variables were stored for further analysis to identify the nucleation and propagation phase.