A real-time state-of-charge (SOC) estimator based on the signals obtained from a Fibre Bragg Grating (FBG)-based sensor system is reported. The estimator has used a dynamic time-warping algorithm to determine the best fit, employing previously obtained experimental data. The strain data used were obtained from the optical signal monitored, providing the input to a supervised learning algorithm. The results achieved show a good match with those from conventional techniques, achieving a ~2% accuracy with a ~1% SOC resolution. The system has been successfully applied to a ‘proof of concept’ demonstrator, using a battery-operated train, illustrating as a result the way in which the real-time SOC estimator could be employed to enhance safety in the growing electrical vehicle industry.

In this paper, a multiparameter, multisensor system for comprehensive electrical machine condition monitoring has been developed and the results of an evaluation reported. The fiber Bragg grating-based system developed allows for the simultaneous monitoring of key parameters including machine vibration, rotor speed, torque, spin direction, temperature distribution along the stator windings and on the rotor surface as well as the stator wave frequency. This all-optical sensing solution has been designed to be compatible with being fitted in the tight confines of an electric motor and uses the optical nature of the measurement and the insulating nature of the sensor material to avoid problems of electrical interference. The system reduces the component count over conventional sensor systems, i.e., all sensing elements are contained within the machine and operated by a single sensing interrogation unit, thereby reducing cost and allowing for a convenient interface for the user. The design of the system is presented, as are results on the testing and evaluation of the device the sensing system has been successfully integrated into and tested on a permanent magnet motor prototype.

An operational, Fiber Bragg Grating (FBG)- based sensing system, specifically designed to monitor conditions in a harsh industrial environment is reported. The sensors used were placed inside tanks with high levels of methane (CH4), carbon dioxide (CO2) and hydrogen sulphide (H2S) gases and high relative humidity in the North Head sewage treatment plant in Sydney, Australia. The sensor system was developed primarily to monitor the effect of >98% relative humidity and temperature changes on the corrosion rates of various materials inside the tanks. Data have been obtained from the use of the system for eight months: these have been correlated with key climate data including the changing weather conditions experienced during the continued monitoring activity. The sensor system specifically developed has been shown to be sufficiently robust to work well, and safely, in such a harsh environment (due to the gaseous H2S and CH4 present) with no signs of deterioration of the sensors or of the signals obtained from the system. The remote operation through flexible data transmission has allowed continuous and up-to-date monitoring of the conditions inside the tanks.

This article reports on an extended (20-month) period of monitoring of humidity in situ at two locations in the sewer network operated by Sydney Water using a fibre optic network into which a series of Bragg Grating-based sensors had been installed. The locations (Eustace Street in Manly, Sydney and Old Toongabbie at Oakes Reserve, western Sydney, Australia) both had different operating environments and thus conditions for evaluating the sensor system. It was designed to provide a solution to enable long term, low cost and more reliable monitoring in the harsh conditions of the sewer environments in terms of high relative humidity >95% and a broad range of hydrogen sulfide levels. The results of the study show that even after ~20 months of use, the same sensor is reliably recording humidity and temperature in the sewer environment-overcoming the problems seen with conventional electrical sensors, which typically fail within a couple of weeks of use in this continuous high acid/high humidity environment. The data, recorded constantly from the sensor system, were stable throughout the full monitoring period and further, a comparison with the changing weather conditions was made over the different seasons during the study. The sensor system developed was battery operated and had 4G connectivity for data transfer and debugging. These features have enabled the system to be installed in situations where power is not available and operate successfully with minimal human operation, thus allowing for additional systems to be integrated to the measurement system in the future.

Real-time monitoring of the state of charge (SOC) of the batteries used in a wide variety of applications is becoming increasingly important, especially given the impetus by the current targets towards “net-zero”. In this research, an advanced approach was used involving fiber Bragg grating (FBG)-based sensors that were developed and implemented for the measurement of the key parameters required to ensure optimum battery performance. In this work, one of the biggest challenges to assess (and then map) the data from the sensor system developed is tackled in order to better understand the key parameters of the battery in an efficient and improved way. It is well known that the relationship between the changes in the resonance wavelength of the FBGs used in the sensor system, arising due to change in the electrical parameters of the battery, is complex and dependent on several different factors. In this work, this effect was evaluated by coupling the sensor data to a data-driven regression model approach that was developed for the measurement of the SOC of the batteries used, and this was obtained directly and conveniently from the FBG data. In this comprehensive study, FBG-based sensors were fabricated and then installed onto the battery, which then was subjected to a range of charging–discharging cycles, following which the electrical parameters of the battery were estimated from recorded data using a black-box machine learning (ML) model. Data-driven regression algorithms were employed for the training of the black-box model. The efficiency of the estimation of the SOC of the battery from the FBG-based sensor data was found to be high, at 99.62% (R² values of Estimated SOC and True SOC line), creating a very satisfactory result for this key measurement. Thus, the work shows the robustness of the FBG-based sensor system combined with the neural network algorithm as an effective way to evaluate the electrical parameters of the battery, which is particularly important, as no physical/electrochemical/electrical model of the system is thus required.

This paper proposes a novel highly sensitive humidity sensor with temperature compensation, mainly consisting of a special modal interferometer bonded with thick polyimide (PI) solid films. The modal interferometer is constructed by splicing a special dual-mode fiber (DMF) with two sections of regular single mode fiber (SMF), forming an SDS (SMF-DMF-SMF) structure. Due to the particular design of the refractive index of the DMF, only LP ₀₁ and LP ₀₂ modes are transmitted, which causes a unique wavelength (UWL) to appear in the spectrum. The UWL breaks the periodicity of the conventional interferometric spectrum. More importantly, both sides of UWL respond differently to various measurands, which enables the interferometer to measure dual parameters simultaneously. To achieve a higher humidity sensitivity, the thick PI solid films are used for the first time to manufacture the interferometric humidity sensors. Their thickness is at least one order of magnitude greater than that of the PI coating used in the traditional humidity sensors, which enhances the sensor’s response to humidity variation significantly. The performance of the proposed sensor is further improved with the aid of the varied period Vernier effect by paralleling a bare dual modal interferometer based on the SDS structure as a reference. Similar to the sensing modal interferometric spectrum, the output spectrum of the varied period Vernier effect scheme owns the UWL as well, which makes it easy to distinguish the wavelength shifts of the specific peaks to the measurands. The validity of the proposed scheme is verified by an experimental case, where the humidity sensitivity and the temperature sensitivity are achieved as 1044.26 pm/%RH and 1467.99 pm/°C, respectively.