ArticleSensors (Basel, Switzerland)2018
Temperature Compensation of Elasto-Magneto-Electric (EME) Sensors in Cable Force Monitoring Using BP Neural Network.
Article in Sensors (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- An Improved IHBA-BP Neural Network for Temperature Compensation of Load Cells.Sensors (Basel, Switzerland) · 2026Article
- Investigation and Prediction of Nano-Silver Line Quality upon Various Process Parameters in Inkjet Printing Process Based on an Experimental Method.3D printing and additive manufacturing · 2024Article
- Temperature Compensation of Laser Methane Sensor Based on a Large-Scale Dataset and the ISSA-BP Neural Network.Sensors (Basel, Switzerland) · 2024Article
- Analyzing the Relationship among Social Capital, Dynamic Capability, and Farmers' Cooperative Performance Using Lightweight Deep Learning Model: A Case Study of Liaoning Province.Computational intelligence and neuroscience · 2023Article
- Comprehensive Indicators for Evaluating and Seeking Elasto-Magnetic Parameters for High-Performance Cable Force Monitoring.Sensors (Basel, Switzerland) · 2022Article
- Research on Temperature Compensation of Multi-Channel Pressure Scanner Based on an Improved Cuckoo Search Optimizing a BP Neural Network.Micromachines · 2022Article
- Investigation of the Temperature Compensation of Piezoelectric Weigh-In-Motion Sensors Using a Machine Learning Approach.Sensors (Basel, Switzerland) · 2022Article
- Verification of Tensile Force Estimation Method for Temporary Steel Rods of FCM Bridges Based on Area of Magnetic Hysteresis Curve Using Embedded Elasto-Magnetic Sensor.Sensors (Basel, Switzerland) · 2022Article
- The Use of BP Neural Network Algorithm and Natural Language Processing in the Impact of Social Audit on Enterprise Innovation Ability.Computational intelligence and neuroscience · 2022Article
- Application of Three-Stage DEA Model Combined with BP Neural Network in Microfinancial Efficiency Evaluation.Computational intelligence and neuroscience · 2022Article
- A General Grid-Less Design Method for Location and Pressure Sensors with High Precision.Sensors (Basel, Switzerland) · 2020Article
- Compensation of Rotary Encoders Using Fourier Expansion-Back Propagation Neural Network Optimized by Genetic Algorithm.Sensors (Basel, Switzerland) · 2020Article
- Outage Probability Performance Prediction for Mobile Cooperative Communication Networks Based on Artificial Neural Network.Sensors (Basel, Switzerland) · 2019Article
- BBS Posts Time Series Analysis based on Sample Entropy and Deep Neural Networks.Entropy (Basel, Switzerland) · 2019Article
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4 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Techniques based on the elasto-magnetic (EM) effect have been receiving increasing attention for their significant advantages in cable stress/force monitoring of in-service structures. Variations in ambient temperature affect the magnetic behaviors of steel components, causing errors in the sensor and measurement system results. Therefore, temperature compensation is essential. In this paper, the effect of temperature on the force monitoring of steel cables using smart elasto-magneto-electric (EME) sensors was investigated experimentally. A back propagation (BP) neural network method is proposed to obtain a direct readout of the applied force in the engineering environment, involving less computational complexity. On the basis of the data measured in the experiment, an improved BP neural network model was established. The test result shows that, over a temperature range of approximately −10 °C to 60 °C, the maximum relative error in the force measurement is within ±0.9%. A polynomial fitting method was also implemented for comparison. It is concluded that the method based on a BP neural network can be more reliable, effective and robust, and can be extended to temperature compensation of other similar sensors.
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