When looking at reducing product noise, there are changes that can be made to assist with this. For example, from the design side we can start by looking at structure, EMAG and control.
(Mechanical design); design of the rotor and stator with appropriate structural vibration characteristics and material selection.
We gain a lot of insights through simulation, however when testing products in the real world for noise pollution, it can prove to be highly complex. Once we have created a product and tested it thoroughly, we start to get noise data that can be analysed.
(Electro-Magnetic); the magnetic design i.e., the structure of the flux pattern and strength, which is controlled by parameters such as pole ratio, magnetic material selection, pole shaping and air gap.
Design and tuning of the control software to avoid adding noise to the drive current, or purposefully integrating algorithms to remove noise.
Transmission path
How we mount the motor onto the product and how noise propagates through the product.
Sound quality
We now have tools for sound quality assessment and optimisation, based largely on customer feedback.
Motor design
Magnets, pole tips, mechanical interactions and materials, software, etc.
The Fisher & Paykel Technologies Sound Room is a purpose-built soundproof environment used to test sound emissions from products. The latest industry standard sound measurement software suite is used for this purpose. The room features soundproofed walls, except for one hard wall and a hard floor. This specific set-up is designed for the testing of products such as refrigerators and rangehoods – appliances that would typically be set against a wall.
Microphones can be positioned according to the standards for noise measurement and software is used for recording the noise emissions. Algorithms break it down into various structures e.g., standard sound, sound pressure measurements and sound power measurements.
Investigative parameters like order analysis help to break down a noise problem into the various sources of noise within the product.
A mannequin with microphones in the ears is used to simulate sound pressure at ear level. Various algorithms are then used to break down the sound into quality metrics such as sharpness, loudness, roughness, and fluctuation. Another algorithm will boil that information down to a value that can be used to represent what a user might perceive.