Engineering a Better Golf Swing




Does the perfect golf swing exist? Not unless you’re a robot. In fact, even golf legends have flawed swings

But that might soon change. At least that’s what Greg Brown, a PTC CAD subject matter expert, hopes.

In search of a better swing, Brown developed a demonstration project using data from PTC customer, Mizuno and the internet of things (IoT). Here’s how.

The Mizuno JPX900 Driver. This high-tech beauty was outfitted with sensors in an effort to find the perfect golf swing.

Many golf clubs include adjustable counterweights to help improve accuracy and overcome inherent problems with your swing.

A few tracks/channels run along the bottom of the Mizuno JPX900 Driver. Weights attached at different locations along the tracks result in changes to the club’s center of gravity and mass distribution. Take a look:

 

Place counterweights at different locations in the tracks to alter the club head’s center of gravity.

Replacing Assumptions with Facts

So how do golfers know where to put the weights? Normally, they rely on imperfect trial and error. Move the weight, test your swing, move the weight again, test your swing again, and so on.  

Brown thought he could do better. He set out to determine if he could use sensors and Creo to find the optimal position for his club’s counterweights.

“In Creo, I have a solid model,” says Brown. “I know the model’s center of mass and I know how it changes if I move any of the weights—based on the density and volume.”

Others (before Brown) have affixed sensors to golf clubs. That isn’t new. However, those sensors measured the trajectory of the golfer’s hands, which indicates the quality of their swing. Instead, Brown wanted to use sensors to optimize the impact of changes to the golf club head’s center of gravity—the result of moving the counterweights.

Counterweight modeled in Creo Parametric.

 

How It Works

Brown outfitted the center track of the golf club head with accelerometer and gyroscope. A cable runs from the sensors, along the track, up the club’s shaft and into Brown’s wrist.

 

A golf club head outfitted with accelerometer and gyroscope (next to the blue counterweight), which generate data related to a golfer’s swing.

The swing data travels via Bluetooth to ThingWorx and it eventually ends up in Creo Product Insight Extension where calculations are performed

In order to use the data in Creo Parametric, a sensor “part” is added to the Creo model. Then, the parameters of the sensor are associated with the data stream. Here’s how it all looks:

The sensor part shown in Creo Parametric. 

A set of 6 data points tell what the club head is doing at the moment when it strikes the golf ball.

For himself, Brown noticed that his typical swing is not quite centered. “So, if I move the counterweights, the center of gravity is in a better position for my typical swing,” he said.

More Data Driven Decisions

Again, Brown says a better golf swing wasn’t really the point of his project. He wanted to encourage design engineers to start thinking about the IoT in new innovative ways. What can sensor data can teach you about your models? Your product? Your service?  

Bring Your Best Game with Creo

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