ADC testing using digital stimuli

The Analogue-to-Digital Converter (ADC) is one of the most typical and widely used mixed-signal circuits. They are applied in video, audio, high-speed communications systems and so on. Many ADCs are integrated into platform-based designs, the architecture which normally contains of standard blocks such as memories, digital processors, RF and analogue front-ends. As testing such a system is a complex task, the related test cost of the platforms is a major part of the overall chip costs. The test cost of ADCs has a relatively high percentage of the total test cost of the chips. The major challenges of the ADC production test cost are the expensive test equipment and the long test times. An architecture of an ADC test infrastructure in a platform-based design has been proposed in our research, which consists of the embedded digital processor(s), the ADC under test, aiding digital test stimuli circuits and memory. The embedded processor can generate the test input signal with the aiding circuits and post-process the output data. The aiding circuits adapt the normal digital signal from the processors to be more suitable for ADC testing. The memory can store the conversion output data. In this thesis, we basically propose three novel methods. The first method is using the adaptive pulse wave to test the dynamic parameters. In this method, a number of pulse waves with different duty cycles are applied to the ADC under test as the test stimulus. As the spectrum of a pulse wave is related to its duty cycle, the spectrum of a sine wave is emulated by the spectrum of a number of pulse waves with different duty cycles. In this way, the dynamic parameters of the ADC under test can be calculated. The results can be used to filter out the faulty devices before the ADC under test proceeds to the conventional production testing. In the second method, only a simple pulse wave is applied as the test stimulus. In the post-processing, an unconventional method has been proposed. Signature results are obtained by comparing the similarity of the output waveforms between the golden devices and the device under test (DUT). The signature results can classify the faulty device and the fault-free devices. As the test stimulus is easy to generate and the post-processing is simple, it is very suitable to apply in a multi-site test environment. The method has been proposed as a quick pre-test to …