Evidence map›Paper›PMID 33105794›Full record

ArticleSensors (Basel, Switzerland)2020

Assessment of the Road Surface Condition with Longitudinal Acceleration Signal of the Car Body.

Krzysztof Prażnowski, Jarosław Mamala, Michał Śmieja, Mariusz Kupina

RetractedAbstract readRetracted Publication
In one paragraph

Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Self-Reported Musculoskeletal Disorder Symptoms among Bus Drivers in the Taipei Metropolitan Area.International journal of environmental research and public health · 2022
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Krzysztof PrażnowskiDepartment of Vehicle, Faculty of Mechanical Engineering, Opole University of Technology, 45-271 Opole, Poland.
Jarosław MamalaDepartment of Vehicle, Faculty of Mechanical Engineering, Opole University of Technology, 45-271 Opole, Poland.
Michał ŚmiejaFaculty of Technical Sciences, University of Warmia and Mazury in Olsztyn, 10-710 Olsztyn, Poland.
Mariusz KupinaDepartment of Mechanics and Structural Engineering, Faculty of Civil Engineering and Architecture, Opole University of Technology, 45-061 Opole, Poland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

On the basis of road tests, the authors assessed the feasibility of the vehicle body acceleration values for the purposes of assessing road surface characteristics in terms of its roughness. Short-term Fourier Transform (STFT) was used for the analysis of the recorded signal. The spectra obtained in successive frequency bands demonstrate the amplitudes originating from the natural vibrations of the rolling wheel and forces resulting from the interaction with the road roughness. The article focuses on the relationships between the road roughness and the ratios of individual amplitudes in a specific frequency band of the vehicle body acceleration values. Amplitude values derived on the basis of successive windows were averaged for analogous, arbitrarily assumed local frequency bands. The value characterizing the road surface condition provided the information regarding the mean amplitude value in specific frequency ranges depending on the instantaneous velocity of the car body and the condition of the road surface on which it was moving. In cases where the road was free of any visible roughness, the obtained mean amplitude value in the analyzed spectrum window, for the adopted vehicle velocity range from 50 km h to 100 km/h, did not exceed 0.02 m/s

Indexed as

pavements classificationroad surfacevehicle vibration

Identifiers

PMID33105794
PMCPMC7660092

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.