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Applied Sciences
Volume 12
Issue 10
10.3390/app12105182
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Article
Peer-Review Record

An Automatic Fault Diagnosis Method for the Reciprocating Compressor Based on HMT and ANN

Appl. Sci. 2022, 12(10), 5182; https://doi.org/10.3390/app12105182
by Qian Lv 1, Liuxi Cai 2,*, Xiaoling Yu 2, Haihui Ma 1, Yun Li 2 and Yue Shu 3
Reviewer 1: Anonymous
Reviewer 2:
Vinay Vakharia
Appl. Sci. 2022, 12(10), 5182; https://doi.org/10.3390/app12105182
Submission received: 25 April 2022 / Revised: 10 May 2022 / Accepted: 19 May 2022 / Published: 20 May 2022
(This article belongs to the Special Issue Compressors and Their Systems: Energy, Flow and Mechanical Systems)

Round 1

Reviewer 1 Report

The paper is interesting and can be read and understood easily.

However, I would recommend presenting more recent research in the Introduction. Describe the current state of research in the area and how innovative your approach is. Most cited references are older than 5 years.

Indicate what type of ANN was used in your case, were different types of ANN tested? Describe the ANN type used in more detail.

What type of pressure sensor (line 205) was used?

Text in lines 127 and 130 are missing resp. not displayed correctly.

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Reviewer 2 Report

Authors presented an automatic fault diagnosis method for the reciprocating compressor based on digital image processing.After reading manuscript,comments are as follows :
1. Title of manuscript is journal.It should include certain words and methodology adopted by authors so that reader can get idea about the work.For example :  Hit-or-miss transform can be included.

2. Authors extracted features from images.It is recommended to kindly include the features name in separate table which was extracted for fault diagnosis purpose .

3. It is always recommended to compare the results of ML algorithms.Authors presented fault diagnosis results with ANN only.Kindly compare the results with other ML algorithms like Random forest,SVM,1D CNN etc. and include necessary description in revised manuscript.

4. There are some already published literature related to fault diagnosis of reciprocating compressor which are as follows :

a. https://asmedigitalcollection.asme.org/SMASIS/proceedings-abstract/SMASIS2013/56048/V002T05A002/282040

b. https://www.mdpi.com/1424-8220/19/5/1041

c. https://journals.sagepub.com/doi/10.1177/0954406217740929

It is suggested to prepare a comparison table which highlights the utility of authors proposed methodology as compared to existing literature.

5. In pg.12,line 334 authors mention that the gradients of the compression and expansion curves and the fluctuation of the discharge curve are sensitive in the faulty cases. What is the reason of this sensitivity.

6. Kindly include the relevant literatures in references.

Author Response

Please see the attachment.

Author Response File: Author Response.docx

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