d73347bb132bc6b1b1f69ea285eec223 futureinternet-16-00474-v2.pdf fce09dce8d86bfff61b6779302837cb108ca8f69 futureinternet-16-00474-v2.pdf 197715c08b19c02df1a2fb1fb17a236548fae4da2b6219b5ca0dd3afb298cf96 futureinternet-16-00474-v2.pdf Title: Thermoelectric Generator-Powered Long-Range Wireless Real-Time Steam Leak Detection in Steam Traps Subject: This paper introduces a novel thermoelectric generator (TEG)-powered Industrial Internet of Things (IIoT) device that addresses key limitations in the detection of steam leaks in industrial steam pipelines, particularly in steam traps. Existing solutions often rely on battery-powered or wired sensors, which are limited by high maintenance costs, short lifespans, or significant infrastructure investments. The proposed device operates without batteries, using waste heat to provide continuous power, and leverages LoRaWAN for long-range wireless communication, minimizing reliance on costly internal infrastructure. Additionally, the device integrates temperature differential (T) and ultrasonic sensors with edge computing capabilities to enhance real-time leak detection and reduce dependency on cloud computing. By enabling precise, low-maintenance monitoring of steam systems in energy-intensive industries (e.g., petrochemical, pharmaceutical), this technology can significantly reduce energy losses, operational costs, and greenhouse gas emissions. Initial testing demonstrates the device’s ability to detect leaks accurately under varying industrial conditions, offering a robust, scalable solution for Industry 4.0 applications. Keywords: steam trap; battery-less; TEG; LoRaWAN Author: Raúl Aragonés, Joan Oliver and Carles Ferrer Creator: LaTeX with hyperref Producer: pdfTeX-1.40.25 CreationDate: Sat Dec 21 08:20:57 2024 CET ModDate: Sat Dec 21 08:27:29 2024 CET Custom Metadata: no Metadata Stream: no Tagged: no UserProperties: no Suspects: no Form: none JavaScript: no Pages: 19 Encrypted: no Page size: 595.276 x 841.89 pts (A4) Page rot: 0 File size: 8869174 bytes Optimized: no PDF version: 1.7 name type encoding emb sub uni object ID ------------------------------------ ----------------- ---------------- --- --- --- --------- MQFYIK+VnURWPalladioL-Bold Type 1 Custom yes yes yes 10 0 PPTNWJ+URWPalladioL-Bold Type 1 Custom yes yes yes 16 0 QBKUKX+URWPalladioL-Roma Type 1 Custom yes yes yes 22 0 ZCDXNL+URWPalladioL-Ital Type 1 Custom yes yes yes 27 0 MPUDFL+PazoMath Type 1 Builtin yes yes yes 32 0 BMWNIW+VnURWPalladioL Type 1 Custom yes yes yes 37 0 MJSSOL+CMSY10 Type 1 Builtin yes yes yes 67 0 JDMFEP+Symbol 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TrueType WinAnsi yes yes no 617 0 JDMDPH+PalatinoLinotype,Italic TrueType WinAnsi yes yes no 620 0 Jhove (Rel. 1.28.0, 2023-05-18) Date: 2025-02-17 16:57:33 CET RepresentationInformation: futureinternet-16-00474-v2.pdf ReportingModule: PDF-hul, Rel. 1.12.4 (2023-03-16) LastModified: 2025-02-12 12:26:32 CET Size: 8869174 Format: PDF Version: 1.7 Status: Well-Formed and valid SignatureMatches: PDF-hul MIMEtype: application/pdf PDFMetadata: Objects: 761 FreeObjects: 1 IncrementalUpdates: 0 DocumentCatalog: PageLayout: SinglePage PageMode: UseNone Outlines: Item: Title: Introduction Destination: section.1 Item: Title: Steam Trap Study Destination: section.2 Children: Item: Title: Steam Processes Destination: subsection.2.1 Item: Title: Steam Trap Operation Destination: subsection.2.2 Item: Title: Steam Trap Failures Destination: subsection.2.3 Item: Title: Steam Leak Cost Estimation Destination: subsection.2.4 Item: Title: Present Technology Scenario Destination: section.3 Children: Item: Title: Detection of Steam Losses in Steam Traps Destination: subsection.3.1 Item: Title: Actual Sensing Devices Destination: subsection.3.2 Item: Title: Steam Leak Detection Destination: section.4 Children: Item: Title: TEG Design Destination: subsection.4.1 Children: Item: Title: Thermal Model Destination: subsubsection.4.1.1 Item: Title: Electronic Design Destination: subsubsection.4.1.2 Item: Title: IIoT Module Destination: subsection.4.2 Children: Item: Title: Wireless Protocol Comparison Destination: subsubsection.4.2.1 Item: Title: Hardware Implementation Destination: subsubsection.4.2.2 Item: Title: Firmware Process Destination: subsubsection.4.2.3 Item: Title: Main Implementation and Results Destination: section.5 Children: Item: Title: Thermoelectric Module Characterization Destination: subsection.5.1 Item: Title: Device Characterization in an Uncontrolled Environment Destination: subsection.5.2 Item: Title: Data Analysis Destination: subsection.5.3 Children: Item: Title: Use of Temperature to Determine the State of the Steam Trap Destination: subsubsection.5.3.1 Item: Title: Use of Ultrasound to Determine the State of the Steam Trap Destination: subsubsection.5.3.2 Item: Title: Background and Related Work Destination: subsection.5.4 Item: Title: Conclusions Destination: section.6 Item: Title: References Destination: section.7 Info: Title: Thermoelectric Generator-Powered Long-Range Wireless Real-Time Steam Leak Detection in Steam Traps Author: Raúl Aragonés, Joan Oliver and Carles Ferrer Subject: This paper introduces a novel thermoelectric generator (TEG)-powered Industrial Internet of Things (IIoT) device that addresses key limitations in the detection of steam leaks in industrial steam pipelines, particularly in steam traps. Existing solutions often rely on battery-powered or wired sensors, which are limited by high maintenance costs, short lifespans, or significant infrastructure investments. The proposed device operates without batteries, using waste heat to provide continuous power, and leverages LoRaWAN for long-range wireless communication, minimizing reliance on costly internal infrastructure. Additionally, the device integrates temperature differential (T) and ultrasonic sensors with edge computing capabilities to enhance real-time leak detection and reduce dependency on cloud computing. By enabling precise, low-maintenance monitoring of steam systems in energy-intensive industries (e.g., petrochemical, pharmaceutical), this technology can significantly reduce energy losses, operational costs, and greenhouse gas emissions. Initial testing demonstrates the device’s ability to detect leaks accurately under varying industrial conditions, offering a robust, scalable solution for Industry 4.0 applications. 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