Optical accelerometers are high-precision inertial sensors that use optical measurement technology to achieve high-precision and electromagnetic interference-resistant acceleration measurements. With the intensive research and development of optical accelerometers in recent years, their applications in inertial navigation, structural health monitoring, precision vibration isolation systems, wind turbine fault monitoring, earthquake monitoring, and other low-frequency vibration detection have flourished. Optical accelerometers have various schemes; however, their characteristics vary considerably due to different optical modulation schemes. This study aims to address the lack of systematic evaluation of currently available low-frequency optical accelerometers. Optical accelerometers can be classified into four categories in accordance with their optical modulation schemes: optical path-, optical intensity-, optical phase-, and optical wave-length-modulated accelerometers. The typical performance, advantages and disadvantages, and possible application scenarios of various optical accelerometers are summarized. This study also presents the current status and trends of low-frequency optical accelerometers in consideration of the growing demand for high-precision, low-frequency acceleration measurements.

Low-frequency vibration is one of the harmful factors that affect the accuracy of micro-/nano-measuring machines because its amplitude is significantly small and it is very difficult to avoid. In this paper, a low-cost and high-precision vibration generator was developed to calibrate an optical accelerometer, which is self-designed to detect low-frequency vibration. A piezoelectric actuator is used as vibration exciter, a leaf spring made of beryllium copper is used as an elastic component, and a high-resolution, low-thermal-drift eddy current sensor is applied to investigate the vibrator’s performance. Experimental results demonstrate that the vibration generator can achieve steady output displacement with frequency range from 0.6 Hz to 50 Hz, an analytical displacement resolution of 3.1 nm and an acceleration range from 3.72 mm s ⁻² to 1935.41 mm s ⁻² with a relative standard deviation less than 1.79%. The effectiveness of the high-precision and low-cost vibration generator was verified by calibrating our optical accelerometer.

Precision spherical joint is a spherical motion pair that can realize rotation with three degrees of freedom. This joint is widely used in robots, parallel mechanisms, and high-end medical equipment, as well as in aerospace and other fields. However, the rotation orientation and angle cannot be determined when the joint is in passive motion. The real-time determination of the rotation orientation and angle is crucial to the improvement of the motion control accuracy of the equipment where the joint is installed in. In this study, a new measurement method that utilizes eddy current sensors is proposed to identify the special features of the joint ball and realize angle measurements indirectly. The basic idea is to manufacture the specific shape features on the ball without affecting its movement accuracy and mechanical performance. An eddy current sensor array is distributed in the ball socket. When the ball head rotates, the features on the ball opposite to the sensor, as well as the output signal of every eddy current sensor, change. The measurement model that establishes the relationship between the output signal of the eddy current sensor array and the rotation direction and angle of the ball head is constructed by learning and training an artificial neural network. A prototype is developed using the proposed scheme, and the model simulation and feasibility experiment are subsequently performed. Results show that the root mean square angular error of a single axis within a range of ±14° is approximately 20 min, which suggests the feasibility of the proposed method.

The acquisition of rotation angle and pose information of precision spherical joint is of great importance for error motion prediction analysis and motion control. In the early stage, an analytical measurement model based on the equivalent magnetic charge method has been purposed to realize the rotation direction identification and rotation angle measurement. However, several shortcomings were observed such as complicated calculations and time-consuming, and the solution accuracy of the theoretical model was decreasing with the expansion of measurement range. To improve this situation, new modeling methods based on artificial neural network have been researched. This paper employs radial basis function (RBF), extreme learning machine (ELM), and RBF–ELM hybrid neural networks to construct measurement models, then analyzes and compares their effectiveness to obtain the optimal algorithm. Analysis results show that the RBF–ELM hybrid neural network has a better calculation accuracy than the others. Finally, the experimental data are used to train and test the network model, and the error between output angle of the model and the actual measured rotation angle is calculated. The comparison results show that the measurement model based on the RBF–ELM hybrid neural network has a higher calculation accuracy and generalization capability. Within the range of ±20°, the maximum error of rotation angle around the X and Y axes are $9'~48''$ and $6'~55''$ , respectively, and the root mean squared error is $1' 59''$ .

Precision ball hinges are widely applied in parallel mechanisms, robotics, and other areas, but their rotation orientation and angle cannot be obtained during passive motion. The simultaneous clearance error in a precision ball hinge’s motion also can not be determined. In this paper we propose an intelligent ball hinge (IBH) that can detect the rotation angle and moving clearance, based on our previous research results. The measurement model was optimized to promote measurement accuracy and resolution, and an optimal design for the IBH’s structure was determined. The experimental data showed that the measurement accuracy and resolution of the modified scheme were improved. Within ±10° and ± 20°, the average errors of the uniaxial measurements were 0.29° and 0.42°, respectively. The resolution of the measurements was 15″. The source of the measurement errors was analyzed through theory and experimental data and several key error sources were determined. A point capacitance model for measuring the clearance error is proposed, which is useful not only in compensating for the angle measurement error but also in realizing the motion clearance of an IBH in real-time.

A new high-precision and low-frequency three-dimensional (3D) accelerometer that utilizes a symmetrical parallel vibration sensing mechanism and a low cross-axis sensitivity high-precision 3D sensing system is proposed in this study. The parameters of the vibration-sensing mechanism were determined by theoretical modeling and simulation analysis, and the performance of the 3D accelerometer was tested experimentally. The dynamic response characteristics of the accelerometer were first determined using kinetic modeling, which showed reasonable amplitude and phase-frequency characteristics in the frequency range below 10 Hz. The accelerometer was calibrated using the comparison method. The sensitivities of the accelerometer in X-, Y-, and Z-axes are 25.3, 25.3, and 21.1 V/g , respectively, with a cross-axis sensitivity of less than 1%. The resolutions of the accelerometer in the X-, Y-, and Z-axes were 48, 45, and 50 μg, respectively. The proposed accelerometer with high sensitivity and high resolution can be widely used for low-frequency microvibration measurements in engineering applications.