Diagnostics of Advanced Power Intensive Power Sources Based on the Acoustic Spectroscopy Method

Objective of this article is to develop a method for lithium chemical current sources diagnostics, which would ensure high reliability in assessing their technical state (primarily, the discharge degree) close to potentially achievable introduction of the acoustic spectroscopy method. Today, microcalorimetric studies and methods of impedance and noise spectroscopy make it possible to predict the lithium chemical current sources service life. However, implementation of the microcalorimetric studies result requires a lot of time accompanied by using stationary and large-size equipment, which is practically impossible in the autonomous conditions. Application of the impedance spectroscopy method provides satisfactory results only with high degrees of discharge. In the range of 0--30 %, it is very difficult to determine the discharge degree, since noticeable alteration in the correlate within its deviation from the mean value is missing. In this regard, it is proposed in order to provide diagnostics of the lithium chemical current sources in the region of initial degrees of discharge to introduce the noise diagnostics method. In order to increase reliability of the diagnostic estimates, it is advisable to use acoustic spectroscopy as a physically independent method in diagnosing the state of lithium chemical current sources. Results of the preliminary measurements analysis confirm the prospects of using the acoustic spectroscopy method in assessing the current state of primary lithium chemical current sources. Experimental studies of the lithium chemical current sources response to acoustic (mechanical) action made it possible to determine a set of parameters characterizing the proposed methodological approach. This provided a possibility to search for correlation dependences of the lithium chemical current sources spectral characteristics on the degree of their discharge. This makes it possible to use the method of acoustic spectroscopy in prompt and reliable diagnostics of the primary current sources in the region of low discharge degrees

Detection of Noise Signal in the Additive Mixture Based on the Second-Order Cumulant

In order to determine the technical condition of energetic objects with the objective of ensuring their operational reliability, durability and safety, systems of noise diagnostics, which are based on the analysis of acoustic diagnostic signals. A promising area of noise diagnostics are cumulant methods, based on cumulant analysis, which involves the use of cumulants and cumulant coefficients. In known literature no characteristics of detection of a signal within an interference-containing additive mixture with the use of a second-order cumulant (variance) can be found. That is why the objective of the paper is to study the use of cumulant method on the basis of point estimations of variance for a sample of momentary values for detection of an acoustic signal against the background of noise interference. The research was carried out by way of modeling the additive mixture of signal and interference using the MATLAB® software package. Interference is a model of a noise acoustic signal, which accompanies the operation of properly functional equipment. Signal is a model of an acoustic signal which is created with the occurrence of a malfunction. Signal and interference are independent random variables, so the property of additivity of cumulants was used – the variance of a mixture equals the sum of variances of signal and interference. The decision about the presence of a signal was made on the basis of testing two statistical hypotheses. The null hypothesis – the signal is absent, variance equals to the variance of the interference. The first hypothesis – the signal is present, variance equals to the variance of the mixture. Additional parameters: probability of a Type I error 0,01, probability of correct determination 0,99. The relative error of estimation determined the minimal sample size. These values allowed for the calculation of the threshold value, upon the exceeding of which by the variance estimation, the decision on the presence of signal is made. For each sample, assessments of variance were made. Experimental probability of correct determination is calculated as a total number of decisions taken regarding the presence of a signal, divided by the number of realizations, and corresponds to the value of the specified probability of correct determination. Its relative error was calculated in order to control the validity of the results. Also, kernel density estimation of the probability of the variance assessment for the case of a signal with normal distribution. As shown by the graphs, the assessments have a distribution that is close to normal. The conducted study proves that a variance -based cumulant method allows to detect a signal against the background of noise interference. The necessary sample size, which shows the number of the necessary momentary values, is given in the paper. That is to say that with the help of the frequency of an analogue digital converter the needed duration of the recording of a real for assessment of its variance can be obtained, and the decision on the presence or absence of a signal is to be made on the basis of the specified threshold values. The results of the study can be added to the known sample sizes and threshold values for the coefficients of asymmetry and excess with different distributions. Application of the described method requires additional testing on real acoustic signals and has the areas of use in systems of noise diagnostics.

Noise diagnostics of graphene interconnects for atomic-scale electronics

Graphene nanogaps are considered as essential building blocks of two-dimensional electronic circuits, as they offer the possibility to interconnect a broad range of atomic-scale objects. Here we provide an insight into the microscopic processes taking place during the formation of graphene nanogaps through the detailed analysis of their low-frequency noise properties. Following the evolution of the noise level, we identify the fundamentally different regimes throughout the nanogap formation. By modeling the resistance and bias dependence of the noise, we resolve the major noise-generating processes: atomic-scale junction-width fluctuations in the nanojunction regime and sub-atomic gap-size fluctuations in the nanogap regime. As a milestone toward graphene-based atomic electronics, our results facilitate the automation of an optimized electrical breakdown protocol for high-yield graphene nanogap fabrication.