Microelectronics world news

Infineon Technologies AG of Munich, Germany says that radiation-hardened (rad-hard) devices from its IR HiRel (high-reliability) division supported the electronic backbone — from critical power supply and control systems to data communications — were at the heart of the Orion capsule of NASA’s Artemis II mission, which recently returned from its 10-days around the Moon (reaching the furthest distance from Earth ever achieved by crewed spaceflight)...

Nuvoton Technology of Kyoto, Japan has announced the start of mass production of the KLC434FL01WW high-power violet laser diode (402nm, 4.5W), which achieves what is claimed to be industry-leading optical output in a 9.0mm-diameter TO-9 CAN package, for continuous-wave (CW) operation at a case temperature (Tc) of 25°C. Due to the proprietary device structure and heat-dissipation design technology, the new product achieves 1.5 times the 3.0W optical output of the firm’s conventional 402nm product in a TO-9 CAN package (the KLC432FL01WW), contributing to improved production throughput in optical equipment such as maskless lithography systems. Furthermore, adding this product to the firm’s lineup enables the product portfolio to support major photosensitive materials used in advanced semiconductor packaging...

Automated test equipment (ATE) supplier Teradyne is bolstering its test solutions for semiconductor design by acquiring TestInsight, a provider of test program creation, pattern conversion, and pre-silicon validation tools used across ATE platforms and semiconductor design environments.

By acquiring a supplier of semiconductor test development, validation, and conversion software, Teradyne aims to scale its next generation of pre-silicon validation and automated pattern generation technologies. That strengthens Teradyne’s ability to support semiconductor design-in activities to accelerate time-to-market in the emerging AI and data center markets.

Here is how pattern conversion across multiple cores and CPUs accelerates the test program. Source: TestInsight

Greg Smith, president and CEO of Teradyne, calls TestInsight’s tools foundational to modern test program development. “By integrating the TestInsight team into Teradyne, we enhance our ability to help customers achieve silicon readiness faster and with greater confidence.”

The acquisition will allow Teradyne to combine its ATE platforms with TestInsight’s tightly integrated design-to-test workflow, thereby reducing debug cycles, improving coverage, and enabling earlier test program readiness. In short, the acquisition of a design-to-test software firm will help Teradyne close the gap between design and test in semiconductor design environments.

TestInsight announced that it will continue to support its existing customers across all ATE platforms.

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The post Teradyne snaps up TestInsight to boost ATE for semiconductors appeared first on EDN.

Aliasing is thankfully becoming a less frequent problem due to improved instrument designs. Users should still be aware of it to prevent time- and money-costly errors.

Aliasing is an ever-present potential problem in sampled data acquisition systems. It occurs when input signals are sampled at a sample rate that is too low. If you haven’t been bamboozled by an aliased signal, you are extremely lucky.

Sampled data instruments, such as digitizers and digital oscilloscopes, must sample their input signals at a rate greater than twice the highest frequency component present in the input signal. If this criterion is not met, then aliasing can occur. Figure 1 shows an example of aliasing.

Figure 1 In this example of aliasing, a 50MHz sine wave was acquired at sampling rates of 1 Giga samples per second (GS/s) and 55 Mega samples per second (MS/s). The 55 MS/s acquisition is aliased and displayed as a 5 MHz waveform.
Source: Art Pini

A 50 MHz sine wave was acquired at both 1 GS/s and 55 MS/s. The waveform acquired at 1 GS/s has the correct frequency of 50 MHz as shown in the frequency parameter P1. The waveform acquired at 55 MS/s is aliased and has a frequency of 5 MHz as reported in parameter readout P2. The alias waveform will appear as having a different frequency than the correctly sampled waveform. This can be a significant problem that can be costly if not addressed carefully.

Let’s look into aliasing and learn how to deal with it. Sampling is a mixing process. When you apply an input signal to a sampler, the resulting output from the sampler contains the original waveforms, the sampling waveform, and the sum and difference frequencies, including the harmonics of the sampling signal. This is illustrated in Figure 2.

Figure 2 Sampling is a mixing or multiplicative process. The baseband frequency spectrum of the acquired signal appears as the upper and lower sidebands about the sampling frequency and all its harmonics.
Source: Art Pini

A correctly sampled waveform will have more than two samples per cycle at the bandwidth limit. In the sampler output, the baseband frequency spectrum of the input signal will appear as upper and lower sidebands about the sampling frequency and its harmonics. The right-hand graphs show the output spectrum of the sampler for the correct sampling rate (upper) and the undersampled case (lower). As the sampling frequency is decreased below twice the input signal bandwidth, the lower sideband of the sampling frequency interferes with the baseband signal, resulting in aliasing.

In the time-domain view (left-hand graphs), the aliased signal lacks sufficient time resolution to track the input waveform. Returning to the example in Figure 1, the 50 MHz input sampled at 55 MS/s will result in sum and difference image frequencies that are above and below the 55 MS/s sampling frequency. The lower sideband image falls into the baseband region of the spectrum and is the source of the 5 MHz alias signal.

Current digital instrument designs generally use sampling rates much higher than the instrument’s analog bandwidth. Some instruments may use sharp-cutoff anti-aliasing low-pass filters to limit the input bandwidth and control the instrument’s frequency response. These techniques, combined with long acquisition memories, also minimize this classic problem.  Still, users should be aware of aliasing.

Recognizing Aliasing

It is good practice to determine the frequency of the measured signal and verify that it has not been aliased. If the characteristics of the input signal are unknown, it is good practice to view the signal at the highest available sample rate, then decrease the sampling rate as needed. If aliasing occurs, you will see the signal’s frequency change as you select a lower sampling rate.

Another hint that a signal is an alias is that it will appear to have an unstable trigger and will jump erratically in time. This occurs because the instrument is triggered by the signal, and the alias, with fewer samples, may not display the trigger point. The instrument displays the nearest sample, which varies from one acquisition to the next, causing instability.

Aliasing can also be recognized by observing the effect on the input signal’s frequency-domain spectrum as the signal’s frequency is varied. A spectral component that shows a decrease in frequency when the input signal’s frequency is increased, a reversal of direction, is an alias. As the frequency of a sine wave increases, the spectral line corresponding to that sine wave will move to the right until it hits the Nyquist frequency of one-half the sample rate.

As the frequency increases above Nyquist, an aliased image from the lower sideband about the sampling frequency will fold back into the baseband spectrum, moving downward in frequency. The lower-sideband images for each harmonic of the sampling frequency show this reversal. Upper sideband images will move in the correct direction. This phenomenon is called spectral folding.

A helpful technique to view an aliased signal

If the signal is a relatively simple periodic waveform, such as the example sine wave, then enabling infinite display persistence will show the underlying waveform, as shown in Figure 3.

Figure 3 The aliased signal (upper trace) and the same signal displayed with infinite persistence turned on (lower trace). The persistence display accumulates all the sample values showing the original 50 MHz waveform.
Source: Art Pini

All sample points in the aliased waveform are real. If infinite persistence is enabled, all samples are accumulated on the persistence display, and the original unaliased waveform is eventually recovered. This technique won’t work for complex signals such as non-return-to-zero (NRZ) data or broadband signals.

Using aliased waveforms

Given that aliased signals are made up of real samples, an aliased signal can be used in measurements, as long as the signal’s frequency is not being measured. Consider measuring the output of a remote keyless entry transmitter. This device outputs a pulse-modulated RF signal with a carrier frequency of 433MHz. This signal has a relatively narrow bandwidth about the carrier frequency. The information being transmitted is encoded in a 400 ms pulse pattern.

Two measurement scenarios are needed. The first is to characterize the RF signal. Parameters like frequency. Also, the shape of the RF envelope affects the purity of the transmitted signal. The second measurement would involve decoding the information content. Using an oscilloscope with a 20 Mega sample (MS) memory at a horizontal scale setting of 100 ms per division (1 second acquisition time), the sampling rate would be 20 MS/s. Figure 4 shows the two measurement processes for both the RF and Data decoding measurements.

Figure 4 Measurements on a remote keyless entry transmitter use an aliased signal to decode digital data.
Source: Art Pini

The traces on the left side of the screen show the RF measurements. The signal is acquired at 20 GS/s, and its leading edge is captured. The oscilloscope measures the RF carrier frequency at 433.9 MHz. The envelope of the RF carrier is extracted by applying the absolute value function, followed by a low-pass filter to create a peak detector. Trace F1 (bottom) shows the envelope. A copy (Trace F3) of the Envelope is also overlaid on a horizontally expanded zoom view (Trace Z1) of the leading edge of the signal. The envelope can be used to measure the envelope’s rise time.

The right side of the display shows the data decoding process. The entire data packet is acquired on a 100-ms-per-division horizontal scale. The sampling rate is 20 MS/s. The RF carrier is aliased down to 6.13 MHz as measured in parameter P2. The aliased frequency of the carrier is the result of mixing the twenty-second harmonic of the sampling rate with the 433.9 MHz carrier. The same envelope detection technique is applied to the entire packet, rendering the data content as an NRZ signal. Aliasing has enabled the acquisition of the entire signal data packet.

Conclusion

Aliasing in digital instruments is a digitizer characteristic that is becoming less frequent a problem due to improved instrument designs, including anti-aliasing filters, oversampling, and very long acquisition memories. Users should still be aware of aliasing to prevent errors that cost time and money.

Arthur Pini is a technical support specialist and electrical engineer with over 50 years of experience in electronics test and measurement.

Related Content

• Sampling and aliasing
• Using oscilloscope filters for better measurements
• Combating noise and interference in oscilloscopes and digitizers
• Building a low-cost, precision digital oscilloscope—Part 1
• Building a low-cost, precision digital oscilloscope – Part 2

The post Aliasing, the bane of sampled data systems appeared first on EDN.

It is 3-rd LCD panel in a month with the same issue, backlight stopped working, there was one resistor still measuring 270 Ohm so we know what it should be, all others are open circuit or in xx MOhm range. No signs of corrosion or overheating anywhere, just crappy components, never have seen this issue. It is planned obsolence or bad combination of materials in resistor. Share your experience with similar cases. submitted by /u/Al3x_Y [link] [comments]