Absolute Noise Corrupts Absolutely

Since Most Wiring Is Fixed in Place, Varying Currents Are The Usual Cause of Magnetic Coupling

By Mike Bacidore, managing editor

To be fully functional, data might need a little help. Information can be manipulated or reconstructed via signal processing, but nothing corrupts data like electrical noise and interference.

We normally break down interference or electrical noise into two categories—radio frequency interference (RFI) and electromagnetic interference (EMI). Their effects can cause unpredictable errors in instrumentation, system inefficiencies, poor product quality and equipment failure.

A noise source, an affected receiving device and a coupling channel between the source and receptor are required for noise or EMI problems to exist, says Bill McGovern, sales manager at Dataforth. “The aim in electromagnetic compatibility is to minimize, divert or eliminate one of these elements,” he adds.

A good design rejects as much noise as possible, says Helge Hornis, manager, intelligent systems, at Pepperl+Fuchs. “For data networks, this is done by using symmetrically designed electronics and floating signals, possibly combined with shielding,” he adds. “Floating signals in symmetric designs have the great virtue that typical noise is canceled by the receiver circuit. Shielding adds a layer of protection, making it harder for noise to penetrate the cables. Improperly executed shielding might increase the noise the hardware must deal with.”

Whether the cable is shielded or not, the channel can give rise to coupling, so preventive measures are needed. Any equipment or wiring can develop an electric charge, adds McGovern. If this charge changes, a changing electric field is generated that can couple capacitively to other devices. “An easy, effective way to minimize capacitively coupled interference is to use cable shielding,” he says. “The shield is a Gaussian or equi-potential surface where electric fields can terminate and return to ground without affecting the internal conductors.”

However, when a cable carries current, a magnetic field is generated. A changing magnetic field induces currents in stationary conductors. “Since most wiring is fixed, varying currents are the usual cause of magnetic coupling,” adds McGovern. “This is more difficult than capacitive coupling because magnetic fields can penetrate conductive shields. Twisted-pair wires are the simplest way to reduce magnetic interference, and they work for shielded and unshielded cables and for interference caused by shield currents or other sources.”
Signal conditioners can ensure accuracy by providing isolation, amplification, filtering and linearization of analog signals. Experts say a high-quality signal conditioner also should include a low-pass filter to prevent noise from causing errors to the measurement system. “Both analog and digital isolation can use components such as transformers and optocouplers for the separation of unwanted signals,” says Derek Sackett, lead interface marketing specialist at Phoenix Contact. “Transformers are a little more electrically rugged and can handle larger transient voltage spikes than optocouplers. Transformers also run faster, up to 1 GHz, while optocouplers are limited to less than 10 MHz.”

Frequency resolution, or resolution bandwidth, is a common concern when applying a fast Fourier transform (FFT)-based algorithm to estimate a power spectrum for an acquired signal, according to Sam Shearman, senior product manager, signal processing software, at National Instruments. It determines frequency measurement accuracy of spectral peaks and sets minimum spacing to distinguish between two closely spaced peaks. “Acquisition parameters are key to determining expected frequency resolution,” he explains. “Consider that FFT-based algorithms operate on discrete values representing continuous/analog signals. More accurately, an FFT is an efficient implementation of a discrete Fourier transform (DFT), an operation that results in an array of discrete time, Fourier transform (DTFT) samples.”

A successful implementation must detect data corruption and assure that intended information gets through, adds Hornis. “This is where error detection combined with automatic transmission retries come into play,” he says. “Many solutions exist, including long checksums, signal shape monitoring and simple parity bit checks.”

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