Gerry Nagel
Adjunct Assistant Professor Milwaukee School of Engineering
- Milwaukee WI
Gerry Nagel is a Principal Software Engineer leveraging experience in software and systems.
Milwaukee School of Engineering
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Education, Licensure and Certification
B.S.
Electrical Engineering
Milwaukee School of Engineering
1989
M.S.
Engineering Management
Milwaukee School of Engineering
2000
Biography
Areas of Expertise
Social
Patents
Method and apparatus for detection of drive misconfiguration in a multi-axis configuration
US9148042B2
2015-09-29
A system for detecting a mismatch between how a motor drive is connected electrically and how it is configured for operation is disclosed. The motor drive may either be connected in a stand-alone mode to control operation of a motor from an AC source without connection to another motor drive or be connected electrically to other motor drives, for example, in a paralleled mode, shared DC bus mode, or a combination thereof. A parameter identifies the expected electrical configuration of the motor drive. The power transferred to the DC bus is compared to the power transferred from the DC bus in the motor drive. If the difference between the power transferred to the DC bus and the power transferred from the DC bus exceeds a predetermined threshold, the motor drive detects the mismatch between how a motor drive is connected electrically and how it is configured for operation.
Error diagnostics and prognostics in motor drives
US9207671B2
2015-12-08
An automation network that utilizes motor drives to diagnose faults, and provide potential solutions to a user. The fault status and/or diagnostic remedies may be displayed via a user display integrated with (e.g., in a single cabinet with) the motor drives and/or coupled to (e.g., in an external device separate from) the motor drives. As such, a logic process or other algorithm may be executed by the motor drive to determine a potential set of solutions for any given fault, based on, for example, determined errors and likelihood of causes for presentation to a user. In this manner, motor drives may allow for user corrective actions to be communicated to a user.
Sizing and tuning methodology for optimized motion control components and energy efficiency
US9354651B2
2016-05-31
Aspects of the present invention provide a tool for simulating a motion control system that simulates performance and energy for a given configuration. The simulation analysis considers a motion profile and one or more corresponding performance parameters, and the resulting configuration provides hardware elements, such as drives and motors, and settings of those elements. The simulation allows optimization for energy efficiency, as opposed to only speed or accuracy.
Automatic network discovery in precision time protocol networks
US9288112B2
2016-03-19
Aspects of the present invention provide systems and methods using precise timing relationships between nodes in computer networks to generate mappings depicting the physical arrangement or ordering of nodes in the computer networks. The technical effect is by tracking the timing delays between nodes as observed by an individual node, and collecting such information together for subsequent processing, nodes may receive and/or construct an entire physical network topology using an algorithm accordingly.
Method and system for real-time anomaly detection in a motor drive
US10879831B1
2020-12-29
A system and method for real-time detection of anomalies in a motor drive includes a controller receiving one or more signals corresponding to real-time operation of a controlled system. The controller samples the real-time signal during operation of the controlled system and maintains a moving window of the sampled data. A signature of the sampled data within the moving window is then generated. Each signature corresponds to operation of the controlled system within the period of time defined by the moving window. An identifier and a number of occurrences of each signature may be stored with the signature. An initial table of expected signatures may be generated, for example, by executing a training, or learning, period within the control system. The controller compares each real-time signature against the table of expected signatures to detect the occurrence of an anomaly.
