Dalian University of Technology Celebrating 75th Anniversary

Dear Colleagues,

Dalian University of Technology (DUT) was founded in April 1949, and 2024 marks its 75th anniversary. It is one of the “211 Project” and “985 Project” universities, with full support for its construction and development provided by the central and local governments of China. DUT has established a comprehensive disciplinary framework, focusing on first-class and high-quality engineering, natural sciences, humanities, and medical sciences research. Additionally, the university has made significant advancements in various fields, including intelligent sensors, aerospace sensors, and optical fiber sensor technology. These innovative sensors have been applied to important projects in civil engineering, aerospace, mechanical manufacturing, and other major fields.

To celebrate the 75th anniversary of DUT, Sensors is proud to announce a Special Issue titled "Dalian University of Technology Celebrating 75th Anniversary". We welcome scholars in the field of sensors to contribute to this Special Issue. Potential topics for submission include, but are not limited to, the following:

• New sensor structure design;
• Novel nanomaterial sensors;
• Environmental monitoring sensors;
• Sensor integration in manufacturing;
• Principles and mechanisms of optical sensing;
• Sensor performance optimization and characterization analysis;
• Wireless sensor networks;
• Sensor data analytics and AI;
• Sensor applications in major engineering projects.

Prof. Dr. Hong-Nan Li
Prof. Dr. Liang Ren
Dr. Xing Fu
Dr. Yang Zhang
Prof. Dr. Yiying Gu
Prof. Dr. Qingchao Sun
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• sensor devices
• sensing principles
• smart/intelligent sensors
• aerospace sensors
• optoelectronic and photonic sensors
• optomechanical sensors
• electronic sensors
• nanomaterial sensors
• wireless sensor networks
• environmental monitoring sensors
• structural health monitoring
• multi-sensor positioning and navigation
• data fusion
• sensor data analytics and AI

Title: Peak searching algorithm based on 2D image morphological processing in fiber-optic low-coherent interferometry
Authors: Tao Liu1, Xuwen Lv2, and Changsen Sun1
Affiliation: 1Dalian university of techincology; 2Goertek Inc.
Abstract: In fiber-optic low-coherent interferometry, the peak recognition is the most important factor that directly determine the accuracy of measurement. In theory, it is well known that the coherence length of light is inversely proportional to the bandwidth of the light source. In pursuing the narrow line width of interference pattern, which can do good for increasing the peak searching accuracy, multiple light sources are consolidated or merged. This consolidation allows for a combined or unified interference pattern to be generated, narrowing the width of interference pattern which can enhance the precision of peak detection. But this can create complex interference fringe with multiple weaker peaks and undermine the peak searching algorithm even to failure. To address this issue, we proposed a robust peaking searching algorithm based on 2D image morphological processing. To verify the effeteness and advantage over other algorithms, the simulation and actual experiment were conducted. Both results demonstrated that the proposed algorithm has good performance in both robustness and accuracy.

Title: Investigating the Breaking Process of Sea Ice and Small Floating Structures by field Observations
Authors: Dayong Zhang
Affiliation: School of Ocean Science and Technology, Dalian University of Technology, Panjin 124221, China
Abstract: The ice load is the predominant load acting on marine structures. The fracture process and interaction characteristics between sea ice and structures are closely associated with the type of structures in question. In this study, based on a prototype test conducted during the winter of 2021-2022 in Baisha Bay, Yingkou, we determined the motion response of small floating body structures under varying environmental conditions. It was observed that there exists a significant periodicity in the interaction between sea ice and small floating bodies. By analyzing data from inclination measurements, vibration responses, and video footage obtained during the prototype test, we were able to reveal the failure process and characteristics of sea ice under different thicknesses and velocities. Additionally, we established a simplified ice force model for both sea ice and small floating structures. Furthermore, it was confirmed that small floating structures can serve as attitude sensors to reflect the ice properties within an icy region.

Title: Electrochemical Sensors Based on Self-Assembling Peptide/Carbon Nanotube Nanocomposites for Sensitive Detection of Bisphenol A
Authors: Yuhang Zhang1§, Tingting Shao1§, Hangyu Zhang1,2*
Affiliation: 1 School of Biomedical Engineering, Faculty of Medicine, Dalian University of Technology, Dalian 116024, China 2 Liaoning Key Lab of Integrated Circuit and Biomedical Electronic System, Dalian University of Technology, Dalian 116024, China
Abstract: Sensors are widely used in medical tests, food analysis, environmental monitoring, industrial process monitoring, and other fields. Currently, the main problems with electrochemical sensors are limited electron transfer rate between the electroactive center and retention of electrical activity. The direction of solving these problems mainly focuses on how to select more suitable substrate materials and how to construct diversified material structures. Here we designed a cationic amphiphilic self-assembling peptide (SAP) Z23 and successfully fabricated a simple bisphenol A (BPA) sensor based on SAP Z23/multi-wall carbon nanotube (Z23/MWCNTs) composite material. The composite material is formed by π-π stacking interaction between the aromatic group on the hydrophobic side of Z23 and the side-wall of WMCNT, with the charged hydrophilic group of Z23 exposed. During the electrocatalytic process of BPA, a synergistic effect was observed between Z23 and MWCNTs. The current response of the sensor based on composite material was 3.24 times that of the MWCNTs-modified electrode, which was much higher than that of the peptide-based electrode. Under optimal conditions, the linear range of the sensor was from 10 nM to 100 μM by amperometric measurement with sensitivity and limit of detection (LOD) at 6.569 μAμM-1cm-2 and 1.28 nM (S/N = 3), respectively.

Title: Automated Visual Inspection for Precise Defect Detection and Classification in CBN Inserts
Authors: Jing Zeng, Feng Wan, Baiyun Zhang, Xu Zhu
Affiliation: Dalian university of technology, Ningbo Institute of Dalian University of Technology, and College of Mechanical and Electrical Engineering.
Abstract: In the high-stakes domain of precision manufacturing, Cubic Boron Nitride (CBN) inserts are pivotal for their hardness and durability. However, post-production surface defects on these inserts can compromise product integrity and performance. This paper proposes an automated detection and classification system using machine vision to scrutinise these surface defects. By integrating an optical bracket, a high-resolution industrial camera, precise lighting, and an advanced development board, the system employs digital image processing to ascertain and categorise imperfections on CBN inserts. The methodology initiates with a high-definition image capture by the imaging platform, tailored for CBN insert inspection. A suite of defect detection algorithms undergoes comparative analysis to discern their efficacy, emphasizing the impact of algorithm parameters and data set diversity on detection precision. The most effective algorithm is then encapsulated into a versatile application, ensuring compatibility with various operating systems. Empirical validation of the system demonstrates a detection accuracy exceeding 90% across multiple defect types, with a notable efficiency of 3 frames per second for flank surface recognition. This breakthrough indicates a scalable, reliable solution for automatically detecting and classifying surface defects on CBN inserts, paving the way for enhanced quality control in automated, high-speed production lines.