Fiber-Optic Point-Based Sensor Using Specklegram Measurement

Orbital angular momentum mode fiber force sensing technology based on intensity interrogation

Micromanipulation and biological, materials science, and medical applications often require controlling or measuring the forces exerted on small objects. Based on the high linearity and sensitivity of OAM beams in the sensing field, this article proposes for the first time to apply OAM beams to force sensing. In this paper, a fiber optic force sensing technology based on the intensity distribution change of orbital angular momentum (OAM) mode is proposed and realized. This technique detects the magnitude of the external force applied to the fiber by exciting the OAM mode with a topological charge 3, thereby tracking changes in light intensity caused by mode coupling. Applying this technique to force measurement, we have experimentally verified that when the sensor is subjected to a force in the range of 0mN to 10mN, the change in speckle light intensity at the sensor output has a good linear relationship with the force. Meanwhile, theoretical analysis and experimental results indicate that compared with previous force sensing methods, this sensing technology has a simple structure, is easy to implement, has good stability, and has practical application potential.

A Machine Learning Specklegram Wavemeter (MaSWave) Based on a Short Section of Multimode Fiber as the Dispersive Element

Wavemeters are very important for precise and accurate measurements of both pulses and continuous-wave optical sources. Conventional wavemeters employ gratings, prisms, and other wavelength-sensitive devices in their design. Here, we report a simple and low-cost wavemeter based on a section of multimode fiber (MMF). The concept is to correlate the multimodal interference pattern (i.e., speckle patterns or specklegrams) at the end face of an MMF with the wavelength of the input light source. Through a series of experiments, specklegrams from the end face of an MMF as captured by a CCD camera (acting as a low-cost interrogation unit) were analyzed using a convolutional neural network (CNN) model. The developed machine learning specklegram wavemeter (MaSWave) can accurately map specklegrams of wavelengths up to 1 pm resolution when employing a 0.1 m long MMF. Moreover, the CNN was trained with several categories of image datasets (from 10 nm to 1 pm wavelength shifts). In addition, analysis for different step-index and graded-index MMF types was carried out. The work shows how further robustness to the effects of environmental changes (mainly vibrations and temperature changes) can be achieved at the expense of decreased wavelength shift resolution, by employing a shorter length MMF section (e.g., 0.02 m long MMF). In summary, this work demonstrates how a machine learning model can be used for the analysis of specklegrams in the design of a wavemeter.

Design Study of Broadband and Ultrahigh-Resolution Imaging Spectrometer Using Snapshot Multimode Interference in Fiber Bundles

Imaging spectrometry plays a significant role in various scientific realms. Although imaging spectrometers based on different schemes have been proposed, the pursuit of compact and high-performance devices is still ongoing. A compact broadband and ultrahigh-resolution imaging spectrometer (CBURIS) is presented, which comprises a microlens array, multiple fiber bundles, a microscope, and a two-dimensional detector array. The principle of the device is to spatially sample and integrate the field information via the front microlens array and then further process with the fiber bundles and imaging system based on the multimode interference theory. From both the theoretical and numerical analysis, this CBURIS design is a superior concept that not only achieves a 0.17° spatial resolution and ultrahigh spectral resolution (resolving power exceeds 2.58 × 106 at 1.55 µm) from the visible to mid-infrared region but also has the advantages of snapshot measurement, thermal stability, and a compact footprint compared with most existing imaging spectrometers.

Intermodal fiber interferometer with frequency scanning laser for sensor application

An intermodal fiber interferometer with an optical frequency scanning light source is considered to attain two main goals: signal fading elimination and achieving a linear response to external fiber perturbations. It is demonstrated that the interferometric signal traces repeatedly generated by the laser frequency scans can be used to average the target signal by calculating their autocorrelation function. A correlation approach is studied for signal processing, and various correlation function modifications are proposed and theoretically analyzed to achieve complete signal reconstruction. In particular, the relation between the autocorrelation function and the averaged amplitude characteristic is demonstrated. The efficiency of the proposed interferometer's scheme and the correlative signal processing are confirmed experimentally for the case of a sine-shaped fiber length modulation. We believe that the proposed method will be useful in real-time sensing applications.