There is a rapidly growing demand for signal conditioning ICs in smart devices based on intelligent sensors.
There is a rapidly growing demand for signal conditioning ICs in smart devices based on intelligent sensors. As a result, signal conditioning IC use has rapidly grown in wearables, automotive, Internet of things (IoT) and industrial applications in the past few years.
Here is a projection of the signal conditioners market from 2021-2029; it includes end-user segments, key players, and regions. Source: Maximize Market Research
Expanding use cases
Applications for wearables include medical treatment, health monitoring, real-time tracking, human-machine interface (HMI), smart home, and motion capture.
The challenge with wearables is that the signals monitored by sensors in this segment are typically weak. They are also affected by environmental noise and human motion disruptions. That’s because wearable sensors collect low-intensity, low-frequency, and narrow bandwidth analog signals from human body. Since the signals are weak, they need amplification to increase the raw signal’s amplitude.
In wearables, the signal is typically amplified by transistors. A field effect transistor (FET) is often used in biosensors since flexible, thin, and light components that fit the surface of the body are prevalent. Here, thin film transistors (TFTs), organic thin film transistors (OTFT) and organic electrochemical transistors (OECT) are widely used.
Transistor amplifiers deliver low power consumption, compact size, low power supply voltage and they are resistant to shocks, do not require pre-heating, and are responsive to voltage change. TFTs feature high flexibility and processibility and OTFTs are flexible and printable, which is important for sensors placed directly on human skin.
Data acquisition is critical for wearable sensors, which is mostly performed by modules of probes, signal conditioning, and analog-to-digital conversion (ADC). However, signal conditioning, analog-to-digital conversion, and data transmission until recently took a back seat to probes. This is beginning to change with expanded wearable sensor research and the increased need for signal conditioning.
In vehicles, there is a growing adoption of pressure sensors that are smaller and less expensive. This creates new inroads for signal conditioner ICs that meet both requirements.
Automotive electronic component demand is skyrocketing mainly due to electric vehicles (EVs). These vehicles use more capacitors than the traditional vehicles, which will also drive the use of signal conditioner ICs.
Challenges in this market include harsh automotive environments that require low supply current to reduce power consumption. Here, signal conditioners offer digital compensation for inherent sensor offset, sensitivity, temperature drift, and nonlinearity and can do so over a wide operational temperature range, meeting the AEC-Q100 standard (–40 °C to +150 °C).
Signal conditioning ICs in the automotive segment have multiple diagnostic and monitoring functions that support OEMs and automotive sensor module suppliers. It’s especially important in safety-critical sensor applications for transmission and braking.
Currently, new sensors and signal conditioning ICs are hitting the market with embedded AI and advanced firmware for IoT applications. The IoT-centric signal conditioning requires faster design cycles, improved accuracy, and again, a reduction in system cost.
An example is the ZSSC3281 signal conditioning IC from Renesas. It’s a dual-path signal-conditioning IC for highly accurate amplification, digitization, and sensor-specific correction of sensor signals. Digital compensation of the sensor offset, sensitivity, temperature drift, and non-linearity is provided by a 32-bit ARM M3-based math core running a correction algorithm with calibration coefficients. The programmable, integrated front-end targets the sensors used in a broad range of high-end applications.
Renesas’ Quick-Connect IoT platform offers designers the core software building blocks that reduce coding requirements. Designers only need to graphically select their sensor and write a few lines of code, while integration and setup take place behind the scenes. Consequently, the sensor design process significantly eases the prototyping of IoT system.
Signal conditioner ICs demand in large part is driven by industrial automation. Most signals require manipulation to prepares them for further processing. For example, manipulation to make such analog signals as temperature and vibration intelligible to data acquisition systems and control equipment. If a signal is not optimized for an in-line digitizer using signal conditioning, measurement inaccuracies and suboptimal performance are the result.
Measurement inaccuracies are a potential problem, especially within large plants with long transmission paths. There are many reasons for interference caused by inaccuracies. Field devices often use different signal standards that cannot simply be processed at the control level or cannot always be processed because small PLCs handle limited signal types. The signal conversion function of a signal conditioner converts analog signals into 0/4–20 mA or 0–10 V signals, eliminating the need for expensive input cards for the control panel.
Signal conditioners with a splitting function transmit the measured signal via parallel, galvanically isolated outputs on the control side, ensuring reliable signal forwarding even if faults occur.
The demand for motor drive controllers is influenced by process automation, robotics, elevator control, assembly and packaging, and flight control systems for digitalized output. That, in turn, increases the demand for signal conditioner ICs.
Signal conditioner use on rise
The sensor-centric signal conditioner IC market for all the above-mentioned sectors is expected to grow rapidly. As electronic devices continue to get smaller and cost becomes a major factor, signal conditioner ICs will continue to help reduce the noise signal and increase the efficiency and performance of electronic devices.
This article was originally published on Planet Analog.
Carolyn Mathas has 15 years of journalism experience, the last seven of which have been spent on the EE Times Group’s DesignLines, including PLDesignLine, Network Systems DesignLine, Mobile Handset DesignLine, and her current sites, Industrial Control DesignLine and CommsDesign. Prior to joining UBM in 2005, she was a senior editor at Lightwave Magazine and a correspondent for CleanRooms Magazine. Mathas has a BS in marketing from University of Phoenix and an MBA from New York Institute of Technology. She lives in the Sierra foothills and claims that the pine forest, snow, mountain air, bears, and power outages balance her deadline-packed high-tech career.