A method is proposed to determine lifetime of luminescent emissions based on the phase shift measurement employing the digitalized Lissajous representation: this diagram has been typically used with analogical algorithms, whereas the proposed method is performed in digital domain, showing an improved accuracy and repeatability. The procedure is studied and tested with two different oxygen sensors that show different sensitivities and signal levels in order to confirm the no influence of the signals intensity on the calibration process. The computational cost of the proposed method is low, which makes it possible to monitor in real time luminescence sensors based on reversible quenching with a potential low cost system based on a digital signal processor (DSP).
Technological research assigns many resources to the development of sensors for a specific purpose, which is providing more independency to the products and systems that improve human quality of live. Nowadays, smart cities require the information of sensors of different types to enhance the performance of the urban services, reducing cost and pollution as well as using natural resources more efficiently [
Therefore, it is important to have sensors able to measure distinct physical or chemical magnitudes. Furthermore, each type of sensor needs a processing unit that can register and monitor the transduction between the measurement and the parameter recorded by the sensor. This step can be as critical as the sensor construction itself and determines drastically the whole performance of the system. In this context, optical fiber sensors show a relevant potential due to the advantages of using optical fiber against electric cables in several scenarios [
Luminescent sensors register the emission of a specific material when it is illuminated with a light source at a certain wavelength. The transduction takes place when the target magnitude modifies the properties of the sensing material emission, for example, its intensity [
There are approaches that analyze other parameters in order to overcome this problem: lifetime is an interesting alternative because it is a temporal parameter and therefore it is not affected by signal level fluctuations [
In this paper, a fluorescence lifetime system is proposed based on phase shift measurement, so it is independent on the light intensity. A specific algorithm has been developed to calculate the phase shift: it works with the Lissajous curve in the digital domain and it handles the low level signal emitted by the sensing material; it improves the results obtained by traditional methods such as Fast Fourier Transform (FFT) or zero crossing. Moreover, the calculations are done entirely in the digital domain, highlighting the originality of the work, because these techniques were traditionally employed in the analog domain. Therefore, the whole signal processing (even the modulation of the interrogating signal) can be performed by a single embedded system such as DSP without any signal conditioning in the analogic domain. The proposed method is focused on obtaining lifetime measurements independent of artifacts under conditions where the signal level is low and noisy. The algorithm has been optimized in terms of standard deviation (measured in degrees) following five different implementations. The procedure has been applied to two different optical fiber sensors with different sensitivities to measure distinct oxygen concentrations: although one of them showed a significantly lower signal, they both were correctly calibrated in the 0–20% oxygen range, which verifies the robustness of the proposed method.
In this work, two sensors with a different behavior have been implemented and studied, providing two scenarios well differentiated. They have been prepared with the same sensing material, which was platinum tetrakis pentafluorophenyl porphine (Pt-TFPP). When this product is illuminated with a light source centered on 395 nm, it shows a luminescent emission located at 650 nm. Furthermore, due to its chemical structure, the compound is not soluble in water. The lifetime of this emission depends on the environmental oxygen concentration by a quenching effect, which is reversible [
Two oxygen sensors were implemented with the same sensing material, but using distinct supporting matrices to attach it onto the optical fiber. All the chemical compounds employed were bought from Sigma Aldrich but the Pt-TFPP from Frontier Scientific: all of them were used without any purification. Before the deposition of the sensing material, the fibers were cleaned with a 1 M potassium hydroxide (KOH) aqueous solution.
The supporting matrix used to implement the first probe, named Sensor A, was a plastic one; specifically, polyvinyl chloride (PVC) was used as polymer [
The second sensor was prepared following Layer-by-Layer (LbL) method. Briefly, this procedure is based on the assembly of polymer chains with an electrical charge by electrostatic forces [
The experimental set-up can be divided into three main blocks: the first one is related to the optical fiber sensor; the second one includes the electronic devices required to modulate the excitation signal and conditioning the emitted one; the third one is formed by the valves and the system that sets the different oxygen concentrations. A scheme of the whole set-up is shown in Figure
Experimental set-up used for the experiments. The three main blocks are surrounded by colored dotted lines: (red) optical fiber sensor configuration; (green) oxygen flow system; and (purple) electronic devices used for signal modulation and conditioning. The whole system is controlled by a personal computer.
The fiber used to prepare the sensors is Plastic Cladding Silica (PCS), whose core has a diameter of 1000
The excitation signal was modulated at a frequency of 500 Hz with a wave generator Tektronix CFG280 by a 1 V peak to peak sinusoidal signal (to modulate the intensity of the LED emission) with a +
The gas flow used to interrogate the sensors was a mixture of gaseous oxygen and nitrogen. The flow rate was similar for all the experiments, and it was set at 250 mL/min. The composition of the flow (expressed in oxygen %) was controlled with
The objective of the procedure is to determine the phase shift between the exciting and the luminescent signals and then use this parameter to estimate the lifetime emission. Both the excitation and luminescent signals were analyzed by averaging 30 cycles in each case. The number of averaged cycles was optimized by considering a different number of cycles (from 1 up to 55) evaluating the resulting standard deviation for each case. The luminescent signal was chosen to estimate the optimal number of cycles to be sampled because it is weaker than the exciting one. It was found that the standard deviation reached a minimum for 30 sampled cycles, and its value was slightly increased of a higher number of averaged samples (as it can be observed in Figure A1 in Supplementary Material available online at
The description of the proposed method is based on the signals registered from Sensor A at room conditions (21% oxygen concentration) and they are displayed in Figure
(a) Excitation signal (blue) and luminescent signal before (red) and after weighing it (green) so both of them show a similar RMS value. (b) Standard deviation expressed in mV for each sample of the signals under study. The values corresponding to the maximum, minimum, and zero crossing for each signal are pointed for each signal.
The proposed method to measure the phase shift between the excitation signal and the luminescent one is based on the Lissajous curve, which is firstly applied for this type of sensors [
In our scenario,
The representation
The noise present in the signals is supposed to be Gaussian: therefore, it was decided to evaluate the root mean square (RMS) of both digitalized signals, using the 30 sampled cycles to calculate it (this number period is enough to minimize the noise effect over the RMS value). Once these parameters were obtained, the luminescent signal was weighed in order to adjust its RMS value to the one of the excitation signal. The resulting signal is displayed in Figure
Taking into account that the excitation signal shows a lower noise level at the maximum and minimum points, the parametric equations can be rewritten considering
At this point, the signals are sinusoidal and with the same RMS value, so that it can be assumed that both of them have the same maximum amplitude neglecting the Gaussian noise effect from the sensing signal. Therefore, if the phase shift is obtained from the ratio between the maximum and minimum of both signals, the precision of the phase shift estimation would be improved. The digitalized Lissajous curve obtained from the signals with the same RMS value is displayed in Figure
Lissajous parametric representation for excitation and weighed luminescent signal. The distances required to calculate the phase shift are indicated.
Equation (
Mathematical expressions to determine the phase shift by the proposed methods based on the Lissajous curve.
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The results for the distinct methods just described for Sensor A at room conditions are around 72°. The phase shift has an offset component due to time delay produced by the high pass filter, the photo multiplier, and the electronic instrumentation: this parameter has to be measured and compensated from the measurements in order to get the shift produced by the quenching effect and, in this manner, calculate the lifetime of the emission. To get this baseline, the excitation signal was allowed to pass through the filter, and a naked fiber optic pigtail was used as sensor. In this manner, it was possible to measure the phase shift induced by the circuit in the excitation signal, which is 67° (this parameter was obtained with the method that has shown the best performance, which will be indicated later). Thus, this value was subtracted from the measured values, which allowed the real phase shift to be calculated.
In order to evaluate the different methods, Sensor A was exposed to distinct oxygen concentrations, specifically 0%, 2%, 7.5%, 15%, 60%, and 100%. The most critical conditions were under a 100% oxygen concentration because the luminescence signal got highly quenched. The registration and processing of the signals were performed by a Labview virtual instrument: in this manner, the value of the phase shift between signals was determined on real time by the different methods while the working conditions changed. Each concentration was kept for 5 minutes, and the phase shift was calculated every second. The average and standard deviation values while the concentration was constant were used to evaluate the proposed methods. The results obtained are plotted in Figure
Phase shift calculated with the different Lissajous based methods in terms of averaged value and standard deviation.
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0% | 9.02 | 0.23 | 9.07 | 0.12 | 9.05 | 0.17 | 9.17 | 0.29 | 9.01 | 0.09 |
2% | 8.44 | 0.21 | 8.60 | 0.21 | 7.97 | 0.23 | 8.33 | 0.31 | 8.23 | 0.11 |
7.5% | 6.68 | 0.18 | 7.33 | 0.14 | 6.82 | 0.24 | 7.24 | 0.26 | 6.87 | 0.11 |
15% | 5.46 | 0.16 | 6.23 | 0.13 | 4.78 | 0.26 | 5.66 | 0.28 | 5.42 | 0.11 |
60% | 3.62 | 0.21 | 4.52 | 0.16 | 3.71 | 0.28 | 4.10 | 0.36 | 3.86 | 0.15 |
100% | 2.63 | 0.34 | 2.60 | 0.31 | 3.56 | 0.52 | 2.07 | 0.59 | 3.09 | 0.13 |
(a) Temporal response from Sensor A when exposed to different oxygen concentrations in terms of the phase shift calculated with the proposed methods based on Lissajous representation. (b) Standard deviation for each method at the different concentrations.
In Figure
To verify the validity of the proposed method, two different experiments were carried out: the first one consists of the calibration of Sensor A and Sensor B following zero crossing approach and 1
The response of the sensors was analyzed for oxygen concentrations between 0% and 20%, where the sensitivity was higher for both of them. The registered data were processed following the zero crossing approach and the 1
Comparison between the lifetime parameter estimated with zero crossing and
In light of these results, it can be inferred that when the signal level is high enough, although both methods offer similar values, the proposed one yields a higher accuracy; moreover, when the amplitude of the sensor signal is low, the zero crossing method is not reliable, whereas 1
Luminescent sensors can be characterized by means of light intensity and luminescence lifetime: both types of measurements were carried out and compared because if both of them are correct, their calibration curves must be similar and agree with the Stern-Volmer equation:
In order to validate the proposed method, the sensors under study were calibrated in terms of (
The calibration lines obtained for each device following Stern-Volmer equation are plotted in Figure
Comparison between the calibration expressions for both sensors using intensity and lifetime information.
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Stern-Volmer representation of the estimated lifetime parameter calculated with method
As the signal from Sensor A was higher, it was decided to calibrate it attenuating the LED source in order to check if the intensity level of the signal has no effect on the lifetime measurements. To verify this point, a filter which induced 70% intensity losses was placed after the light source. The sensor was exposed again to different oxygen concentrations as in previous experiments. Regarding the calculated lifetime emission, the results matched the ones obtained with the higher signal level: it can be checked in Figure
Stern-Volmer calibrations obtained for the same sensor working at different signal levels.
An improved method has been proposed to characterize luminescence based sensors in terms of the phase shift between the exciting signal and the luminescent emission from the sensor, and this parameter was used to estimate the emission lifetime. Phase shift parameter is obtained by digital signal processing of both signals at the points that show a lower noise deviation: this information is processed in the digital domain to get the best accuracy and precision. In this manner, the modulation, acquisition, and processing of the different signals could be embedded in a single system to enhance the features of the proposed approach.
The Lissajous parametrical representation in the digital domain is employed to estimate the phase shift, using the points that show the smallest deviation. Compared with traditional approaches, the proposed procedure offers better results in terms of accuracy and precision. What is more important, in the case of the sensors with low signal level, 1
The authors declare that they have no competing interests.
This work was supported in part by the Spanish Ministry of Economy and Competitiveness FEDER TEC2013-43679-R.