MEMS inertial-sensors technology has been driven by automotive safety systems; as such, the technology has been applied to several high-volume applications. The large volumes associated with automotive safety systems have enabled substantial investment in MEMS manufacturing technology, packaging concepts, quality assurance systems, and innovative design approaches.

This has resulted in cost-effective, reliable solutions that are gaining interest in many other market segments as well. These include gaming consoles (Wii Remote) and a variety of mobile-handset applications.

In addition, MEMS sensors are finding their way into an increasing number of industrial applications, including workplace safety systems. Equipment position sensing, impact detection, and roll-over prevention for lift trucks are examples of workplace safety systems that benefit from MEMS accelerometers.

Workplace safety systems are tasked with detecting potentially dangerous operating conditions without impacting normal operation. One of the primary factors in this process is the accuracy of the sensing solution used to detect the dangerous operating conditions. As with most technology solutions, MEMS accelerometers have a trade-off relationship between cost and performance.

For applications such as automotive and commercial, adequate performance at the lowest cost possible is sufficient. But industrial applications, such as workplace safety systems, require higher accuracy. In such cases, reliability, convenience, and component costs of these solutions are critical.

With the introduction of higher integration and more accurate accelerometer products, system designers still have a need to understand how parts are calibrated; this allows them to decide whether to purchase this capability or develop their own calibration routines. This article outlines the calibration process used for a dual-axis accelerometer and highlights its most common error sources.

CALIBRATION " PURPOSE AND VALUE For many MEMS inertial sensor consumers, calibration provides opportunity to trade system cost for improved accuracy in their sensing solutions, as shown in Figure 1. While the relationship in this graph is generic, the performance goals are generally driven by end-system performance requirements that add value for the customer.

For example, greater accuracy means the roll-over prevention system does not need to overcompensate when determining the limits on a lift truck. Optimized accuracy levels can enable a crane to serve a larger area, or handle heavier loads, without the threat of tipping. The bottom line is that optimizing performance in safety sensing systems will add to the value to the overall solution.

The cost increase associated with calibration includes both direct material costs (ADC, microcomputer, extra PCB complexity, labor), and investment costs (calibration fixtures, R&D engineering) that can be amortized over the anticipated volume of systems produced. The obvious goal of any calibration process is to achieve valuable performance levels, while managing the associated costs.

The difference between a well-executed calibration process and a less-effective one is illustrated in the performance vs. cost curves shown in Figure 1. Diligence in identifying and mitigating risk will determine what a given level of performance improvement will cost. It only takes one mistake to move from blue to red!

Developing a MEMS calibration solution can broken down into four simple steps: 1. Establish performance goals. 2. Determine calibration requirements. 3. Design calibration process. 4. Implement correction formulas.