Simulation of non-stationary random vibrations has motivated Packaging vibration testing for decades. Often, an event-detection algorithm decomposes Road vehicle vibrations when analyzing the recorded series. However, heuristics and subjective justifications are often in the papers, whereby the foremost concern is the validation of the non-stationarity of simulated signals. Furthermore, if a changepoint detection is inherent to the procedure, it is recommended to calibrate the detector. The current paper concerns the Receiver operating characteristics (ROC) of two novel algorithms and provides contextual support by Segment length distributions (SLD).

Research on the non-stationary nature of road vehicle vibrations (RVV) led to advances in simulating such processes. Contemporary methods introduced for the analysis of RVV primarily aimed at partitioning the signal in the time- or time − frequency domain, providing differing segments of a signal. However, a degree of dissimilarity, or conversely similarity, is still challenging to find. Hereunder we argue that in some cases, merely a statement of dissimilarity between neighbouring segments within a signal might be well-enough, though from a broader perspective, the assessment of the similarity of discrete Fourier transforms (DFT) may be the next practical step forward. For this reason, the current paper presents the hierarchical clustering of elements of the short-time Fourier transform (STFT) plane from an RVV measurement; secondly, it introduces a clustering validation metric to arrive at an optimum distance metric and a threshold to use in binary hierarchical clusters.

Non-stationary random vibrations gained increasing interest in vibration testing. Often, a changepoint detection procedure handles the decomposition of Road vehicle vibrations (RVV) when analysing the recorded series. Unfortunately, only subjective justifications support the proposed methods, and mainly the validation of the non-stationarity of simulated signals is concerned. Thus, if a detector is inherent to the procedure, it is also recommended to calibrate it. The current paper concerns the Receiver operating characteristics (ROC) of a CUSUM-type algorithm and supplies contextual support by Segment length distributions (SLD).

Vibration testing procedures relying solely on a Fourier profile can introduce only stationary random vibrations. It is in contrast with the non-stationary and non-Gaussian nature of the Road vehicle vibrations (RVV). The following procedure segments the first four spectral moments of the time-frequency domain of RVV, constructs probability density arrays per frequency bins, and perform simulations according to random segment lengths and -root mean squares, yielding more realistic representations of RVV. The distribution of time- and frequency domain moments and normalized spectral entropies are confronted. The Probability-based spectrogram synthesis (PBSS) offers a data-driven stochastic modelling framework for simulating non-stationary RVV.

Road-induced vibrations are in the scope of various environmental testing protocols, e.g., for packaging vibration testing (PVT) purposes. This field matures with well-understood methods for analyzing amplitude-type non-stationarity (NS) in road vehicle vibrations (RVV). Albeit frequency-type NS is well known, only suggestions are provided for processing the phenomenon in PVT. Both types of NS can be jointly investigated in the time-frequency domain; thus, the current study initiates the investigation of spectral non-stationarities (SNS) in RVV. Three vibration series were recorded from 118 km traveled distance supplying an empirical insight.

Goods transported on wheeled vehicles are subjected to road-induced vibrations. Verification of protective packaging is accompanied by random vibration testing in standard procedures, which utilize power spectral density (PSD). Since PSD is time-invariant, it produces stationary Gaussian signals; however, stationarity is hardly the case in road vehicle vibrations (RVV). Various attempts had been presented on nonstationary vibration simulations and unique signal segmentation methods are presented to understand the real nature of RVV.

Segmentation of road vehicle vibration (RVV) signals can occur by the need to analyse or synthesise vibrations obtained in passenger cars or on the stowage of vans, trucks. A general and widely used measure to quantify RVV signals is its description via power spectral density (PSD). From a given PSD a Gaussian signal can be generated in a shaker testing laboratory. However, actual RVVs tend to have a non-Gaussian and nonstationary nature, which can be modelled as a composition of different segments, each with a different length and RMS content. For simulation purposes of nonstationary vibration signals, different approaches have been introduced yet each with its unique signal segmentation approaches. The current paper proposes a signal segmentation method implemented in the time-frequency domain in order to find segments within an RVV signal, where each segment has similarity in-between and is dissimilar to neighbouring segments. For this purpose, multiple comparison tests had been utilised between the Short-time Fourier transforms (STFT) applied on given fractions of an RVV. Different countermeasures had been applied against the Type I. error inflation.

Records of search queries can often be exported from scientific databases, most of them contain the record of citations, as well. However, it is ineffective to register the citation relationships among publications manually, so the reader might lean on the number of citations when looking for leading publications. One can be interested in trend-setting publications or the primary columns of the discipline in terms of publications. Beneath the conventional literature reviews, helpful solutions are available to assist the reader in similar questions. Network visualizations in bibliographic analyses have long-established practices, offering appealing tools to visualize complex connection systems constituted by different bibliometric couplings. The current paper investigates the direct citation network of a sample drawn from the Web of Science scientific database in the relation of a particular research field concerning road induced vibrations from a packaging testing perspective. The sample consists of 46 publications embracing 28 years as of date. Core publications are identified first, supplemented by qualitative contextual reviews, followed by main path analysis. The assays attempt to estimate the main research topics of the investigated discipline by the given sample.