Dual Capacitive Linearization Circuit for MEMS Sensors
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Solution Overview
Problem
Current MEMS sensors using variable capacitors for capacitive sensing are inherently non-linear, requiring up to 20 parameters for correction and experiencing poor performance in high g acceleration environments due to nonlinearity and vibration rectification error.
Innovation Solution
A micro-electro-mechanical system (MEMS) design incorporating a proof mass, anchor, amplifier, and sense elements with feedback elements, where the proof mass moves between sense elements in a half-Wheatstone bridge configuration, generating a linear output by eliminating non-linear terms through a dual capacitive linearization circuit.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If variable capacitors are used for capacitive sensing, then the sensor can convert mechanical displacement into electrical signal, but the output is inherently non-linear requiring up to 20 parameters of correction
Solution Approach 1:
The patent implements a feedback mechanism where the output signal is fed back through feedback capacitors to the proof mass. This feedback loop automatically compensates for non-linearities in the capacitive sensing elements, producing a linear output without requiring complex correction parameters. The feedback capacitors are configured to counteract the non-linear response of the sense capacitors, thereby linearizing the overall system response.
Solution Approach 2:
The patent changes the electrical parameters of the system by introducing feedback capacitors with specific capacitance values that are designed to counterbalance the non-linear characteristics of the sensing capacitors. By carefully selecting and adjusting these feedback capacitor parameters, the system achieves linear output characteristics without requiring multiple correction parameters in the signal processing chain.
2Measurement precision
If non-linear correction is applied, then linear output can be achieved, but performance in high g acceleration environment deteriorates due to vibration rectification error
Solution Approach 1:
The feedback mechanism actively compensates for non-linearities in real-time, including those caused by high g acceleration and vibration. By continuously adjusting the feedback signal based on the actual proof mass position, the system maintains linear output characteristics even under extreme acceleration conditions, thereby improving reliability in high g environments.
Solution Approach 2:
The feedback capacitors are pre-configured to counteract the expected non-linear effects before they manifest in the output. The feedback network is designed to anticipate and compensate for non-linearities including vibration rectification errors, thereby preventing performance degradation in high g acceleration environments before it occurs.
3Length of moving object
If proof mass travel is increased, then sensing range is improved, but non-linearity increases
Solution Approach 1:
The feedback capacitors are designed to provide linearizing feedback over the extended proof mass travel range. As the proof mass moves through a larger displacement, the feedback mechanism dynamically adjusts to maintain a linear relationship between input acceleration and output signal, enabling both increased travel distance and maintained linearity.
Solution Approach 2:
The system employs dynamic feedback where the feedback capacitor configuration can adapt to the proof mass position and velocity. This dynamic adjustment allows the system to maintain linear response characteristics across a wider range of proof mass displacements, effectively decoupling the trade-off between travel range and linearity.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This design reduces nonlinearity, increases proof mass travel, and improves sensor performance by eliminating total harmonic distortion, enabling better performance at large sound levels and larger sensing ranges.
Implementation Method 1
Current state-of-the-art MEMS sensors use variable capacitors (capacitive sensing) as a transduction method between the electrical and mechanical domains of the MEMS sensor converting mechanical displacement into an electrical signal
Implementation Method 2
The first feedback element is connected between the proof mass and the output signal and generates a signal responsive to proof mass displacement. The second feedback element is connected between the proof mass and the output signal and generates a signal in response to proof mass displacement
Implementation Method 3
The anchor coupled to the proof mass via a spring
Data Source
AI summary
A MEMS system includes a proof mass, an anchor, an amplifier, first and second sense elements and their corresponding feedback elements. The proof mass moves responsive to a stimulus. The anchor coupled to the proof mass via a spring. The amplifier receives a proof mass signal from the proof mass and amplifies the signal to generate an output signal. The first sense element is connected between the proof mass and a first input signal and the second sense element is connected between the proof mass and a second input signal. The second input signal has a polarity opposite to the first input signal. The first feedback element is connected between the proof mass and the output signal and its charges change responsive to proof mass displacement. The second feedback element is connected between the proof mass and the output signal and its charges change in response to proof mass displacement.