GENERAL DESCRIPTION

The AD7686 is a 16-bit, charge redistribution, successive approximation, analog-to-digital converter (ADC) that operates from a single 5 V power supply, VDD. It contains a low power, high speed, 16-bit sampling ADC with no missing codes, an internal conversion clock, and a versatile serial interface port. The part also contains a low noise, wide bandwidth, short aperture delay track-and-hold circuit. On the CNV rising edge, the AD7686 samples an analog input IN+ between 0 V to REF with respect to a ground sense IN?. The reference voltage, REF, is applied externally and can be set up to the supply voltage. Power dissipation scales linearly with throughput. The SPI-compatible serial interface also features the ability, using the SDI input, to daisy-chain several ADCs on a single, 3-wire bus or provides an optional busy indicator. This device is compatible with 1.8 V, 2.5 V, 3 V, or 5 V logic, using the separate supply VIO. The AD7686 is housed in a 10-lead MSOP or a 10-lead QFN (LFCSP) with operation specified from ?40°C to +85°C.

FEATURES

16-bit resolution with no missing codes

Throughput: 500 kSPS

INL: ±0.6 LSB typical, ±2 LSB maximum (±0.003 of FSR)

SINAD: 92.5 dB @ 20 kHz

THD: ?110 dB @ 20 kHz

Pseudo differential analog input range 0 V to VREFwith VREFup to VDD

No pipeline delay

Single-supply 5 V operation with 1.8 V/2.5 V/3 V/5 V logic interface

Serial interface SPI?-/QSPI?-/MICROWIRE?-/DSP-compatible

Daisy-chain multiple ADCs and busy indicator

Power dissipation

3.75 μW @ 5 V/100 SPS

3.75 mW @ 5 V/100 kSPS

Standby current: 1 nA

10-lead MSOP (MSOP-8 size) and 3 mm × 3 mm, 10-lead QFN (LFCSP) (SOT-23 size)

Pin-for-pin-compatible with 10-lead MSOP/QFN PulSAR? ADCs

APPLICATIONS

Battery-powered equipment

Data acquisitions

Instrumentation

Medical instruments

Process controls

AD7946屬于集成電路（IC） > 模數轉換器（ADC）。亞德諾半導體技術有限公司制造生產的AD7946模數轉換器（ADC）模數轉換器（ADC、A/D 或 A 轉 D）對模擬信號進行采樣，例如由麥克風采集的聲音或傳感器的輸出，然后將其轉換為數字信號。一般來說，數字輸出是二進制補碼二進制數，與輸入成比例。輸入類型可能是差分、偽差分或單端輸入。模數轉換器可按照位數、采樣率、輸入數、接口、轉換器數和架構（例如自適應增量、雙斜率、折疊、流水線、SAR、三角積分、兩步式）進行選擇。