Peter Lindahl
Massachusetts Institute of Technology
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Publication
Featured researches published by Peter Lindahl.
IEEE Transactions on Instrumentation and Measurement | 2016
Ryan Zachar; Peter Lindahl; John S. Donnal; William Cotta; Christopher Schantz; Steven B. Leeb
This paper presents a vibration measurement and analysis technique for use during a machines spin-down procedure. During spin-down, the machines operation covers a continuous wide frequency band, from operating speed to standstill, which allows the estimation of the machines vibration transfer function (VTF). This transfer function is rich in information for detecting and differentiating not only machinery pathologies but also problems with vibrational mounts. Utilizing a back-electromotive force sensor to infer rotor speed and a single-axis accelerometer for vibration measurements, this technique allows minimally intrusive estimation of a machines VTF. Data collected in laboratory and field tests aboard U.S. Navy ships are presented to demonstrate the usefulness of this monitoring technique.
autotestcon | 2016
Peter Lindahl; Steven B. Leeb; John S. Donnal; Greg Bredariol
Modernization in the U.S. Navy and U.S. Coast Guard includes an emphasis on automation systems to help replace manual tasks and reduce crew sizes. This places a high reliance on monitoring systems to ensure proper operation of equipment and maintain safety at sea. Nonintrusive Load Monitors (NILM) provide low-cost, rugged, and easily installed options for electrical system monitoring. This paper describes a real-world case study of newly developed noncontact NILM sensors installed aboard the USCGC SPENCER, a Famous class (270 ft) cutter. These sensors require no ohmic contacts for voltage measurements and can measure individual currents inside a multi-phase cable bundle. Aboard the SPENCER, these sensors were used to investigate automated testing applications including power system metric reporting, watchstander log generation, and machinery condition monitoring.
static analysis symposium | 2017
Joshua C. Nation; Andre Aboulian; Daisy H. Green; Peter Lindahl; John S. Donnal; Steven B. Leeb; Greg Bredariol; Kevin Stevens
This paper presents a case study applying nonintrusive load monitoring (NILM) for fault detection and isolation (FDI) of automated shipboard systems. A NILM system installed on an engine room subpanel of U.S. Coast Guard (USCG) Cutter SPENCER collected aggregated power consumption data for ten automated systems. A correlation-based transient identifier is used to disaggregate this data, identifying specific automated load events, including on/off events of the gray water disposal pump. A two-parameter model is calculated from these events and used for fault detection. Data collected during two operational periods of the SPENCER demonstrate the effectiveness of this model in identifying a pump sensor fault previously undetected by the crew. Early identification of such malfunctions prevents costly wear on the gray water disposal system pumps and avoids eventual catastrophic failure.
IEEE Transactions on Power Electronics | 2014
John J. Cooley; Peter Lindahl; Clarissa L. Zimmerman; Matthew Cornachione; Grant Jordan; Steven R. Shaw; Steven B. Leeb
This paper presents a multisource, multiconverter power system for electrically propelled unmanned aerial vehicles (UAVs) with a focus on promoting fuel cell health. Linearized multiconverter system analysis and the two extra element theorem (2EET) inform a system design for fuel cell current buffering and integral diagnostics. Integral diagnostics is in situ impedance spectroscopy achieved by controlling the power system to superpose a frequency-swept excitation current at the fuel cell terminals. An experimental system demonstrates hybridization of a solid-oxide fuel cell (SOFC) with a lead-acid battery having suitable current buffering and integral diagnostics performance under UAV load profiles. Experimental behavior is demonstrated with an electrically emulated SOFC stack or “reference simulator.” Impedance spectroscopy data measured during run-time clearly indicate both degradation and recovery phenomena in the SOFC.
static analysis symposium | 2017
John Donnai; Christopher Schantz; Jinyeong Moon; Peter Lindahl; Steven B. Leeb
This paper provides a survey of example sensors that can be implemented with nonintrusive electromagnetic measurements. Stray electric and magnetic fields exist around many important components in commercial and industrial processes. For example, power cables operate surrounded by magnetic and electric fields. Flow meters operate with cyclically-varying magnetic fields. And stray electromagnetic fields can serve as an energy source for powering sensors wirelessly. These stray fields provide remarkable opportunities for nonintrusive sensing of industrial processes. Sensed information can be used to establish monitoring in new or retrofit systems, or can be used as a backup or redundant source to verify the operation of an installed sensor network. Three different example sensors are presented in this paper for power monitoring, fluid flow tracking, and electromechanical vibration monitoring. All three sensors make use of a common set of circuits for electric and magnetic field sensing. They illustrate approaches that could be applied for many other sensing applications.
IEEE Sensors Journal | 2017
John S. Donnal; Peter Lindahl; David Lawrence; Ryan Zachar; Steven B. Leeb
Electromagnetic field sensors provide an electronic “stethoscope” that can determine the current and power flowing in the wire without ohmic contact and without the need to physically separate conductors. Isolation is inherent, and non-contact monitors can be installed without special safety precautions. However, the process of reconstructing the detailed conductor currents is an inverse problem subject to subtle and severe complications in real environments. Interference from nearby conductors, incorrect or unconventional wiring, ground leakage, and three-wire connections complicate the interpretation of electric and magnetic fields to infer line currents. Over a year of field monitoring has been conducted to demonstrate signal processing and physical approaches for untangling these problems to produce accurate and reliable multi-phase power measurements with non-contact sensors.
autotestcon | 2016
Jinyeong Moon; Peter Lindahl; John S. Donnal; Steven B. Leeb; Lt. Ryan Zachar; Lt. William Cotta; Christopher Schantz
This paper presents a nonintrusive and electromagnetically self-powered embedded system with vibration sensor for condition monitoring of electromechanical machinery. This system can be installed inside the terminal block of a motor or generator and supports wireless communication for transferring data to a mobile device or computer for subsequent performance analysis. As an initial application, the sensor package is configured for automated condition monitoring of resiliently mounted machines. Upon detecting a spin-down event, e.g. a motor turnoff, the system collects and transmits vibration and residual backemf data as the rotor decreases in rotational speed. This data is then processed to generate an empirical vibrational transfer function (eVTF) rich in condition information for detecting and differentiating machinery and vibrational mount pathologies. The utility of this system is demonstrated via lab-based tests of a resiliently mounted 1.1 kW three-phase induction motor, with results showcasing the usefulness of the embedded system for condition monitoring.
IEEE Transactions on Instrumentation and Measurement | 2016
Peter Lindahl; Al-Thaddeus Avestruz; William Thompson; Elizabeth George; Brian R. Sennett; Steven B. Leeb
Human occupancy detection and localization are important in a variety of smart building applications including building security, assisted living monitors, and energy-efficient heating ventilation and air cooling and lighting. Current implementation of such systems is limited by motion-sensor technologies, e.g., passive infrared (PIR) and ultrasonic sensors, which substitute as occupancy detectors but ultimately suffer from an inability to detect stationary objects. Capacitive sensing can detect stationary objects, but the technology has almost exclusively been developed for short-range human detection and localization, e.g., touch-screen human interfacing of smart devices. This paper presents a transmitter-receiver platform for research and development of capacitive sensing for long-range human occupancy detection and localization. During testing, the system revealed a detection range of 3.5 m, a typical room dimension in homes. Further, tests of a multitransmitter single-receiver system in a 3.2 m × 3.2 m space showed the systems potential for occupant localization. Ultimately, this system represents an alternative to PIR and ultrasonic motion sensors, and has the potential to increase smart building system implementation.
applied power electronics conference | 2018
Manuel Gutierrez; Peter Lindahl; Arijit Banerjee; Steven B. Leeb
IEEE Transactions on Instrumentation and Measurement | 2018
Peter Lindahl; Steven R. Shaw; Steven B. Leeb