Dashboard MACE with Wireless Integration
Abstract
We seek to recover hidden information from power consumption streams that will support energy scorekeeping, fault detection and di,agnostics, and activity tracking. New sensor, signal processing algorithms, and signal processing hardware technologies will be deve,loped and field tested to create a Multi-function Analytic Consumption Evaluation (MACE) Meter. Initially focused on electrical sign,als, the MACE will offer the capability to non intrusively track other ship vitals, e.g., water consumption, and other important dia,gnostic indicators like acoustic signals. The MACE offers a new approach for actionable utility monitoring and control. The current, state of the art in this domain includes mechanical sensors monitored by hand by human watch standers, and coming IoT solutions, that crust a ship with sensors that become failure points and that produce a data glut; this proposed project will add value by eli,minating installation expense, removing large numbers of sensors that will become failure points on a ship, and by providing action,able information that does not require extreme computing requirements (machine learning) for solving the big data problem. --COT,S IOT solutions will not provide the cybersecurity and access to actionable information required by the USN and USCG. MACE will. Sp,ecifically, we propose to apply H4D analysis and technical innovation to develop and exploit:Application of H4D and MMC for researc,h relevant to USN and USCG Warfighters. Development and demonstration of a new data acquisition front-end capable of new dimensions, of signal-to-noise ratio, revealing previously hidden secrets on the shipboard power system. Incorporation of new technologies int,o an all-in-one (AIO) MACE meter for shipboard use. Development and demonstration new algorithmic techniques for transient detectio,n to support fault detection and diagnostics tailored to warship systems and new sensing modalities for nonintrusive consump,tion detection, e.g.,f or fluid flow. Field study to demonstrate data collection and analysis on a USN/USCG ship, likely USN LCS, and USCG Patrol Craft (140) or other ship of interest to the sponsor. Our goal is two-fold: Identify new techniques for d,etecting soft faults before they become mission cripples, and also develop new approaches for automatic watch standing to relieve, crew maintenance and operations burdens.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- May 16, 2022
- Source ID
- N000142212092
Entities
People
- Steven Bruce Leeb
Organizations
- Massachusetts Institute of Technology
- Office of Naval Research
- United States Navy