Christopher Laughman

Detection of Rooftop Cooling Unit Faults Based on Electrical Measurements

Nonintrusive load monitoring (NILM) is accomplished by sampling voltage and current at high rates and reducing the resulting start transients or harmonic contents to concise “signatures.” Changes in these signatures can be used to detect, and in many cases directly diagnose, equipment and component faults associated with rooftop cooling units. Use of the NILM for fault detection and diagnosis (FDD) is important because (1) it complements other FDD schemes that are based on thermo-fluid sensors and analyses and (2) it is minimally intrusive (one measuring point in the relatively protected confines of the control panel) and therefore inherently reliable. This paper describes changes in the power signatures of fans and compressors that were found, experimentally and theoretically, to be useful for fault detection.

Diagnostic indicators for shipboard systems using non-intrusive load monitoring

Field studies have demonstrated that the non-intrusive load monitor (NILM) can effectively evaluate the state of many electromechanical systems by analyzing the electrical power that they draw. This paper discusses NILM applications in the marine environment. Machinery power data collected from USCGC SENECA (WMEC-906), a 270-foot U.S. Coast Guard cutter, indicates that the NILM can successfully diagnose the failure of flexible couplings and the presence of leaks in cycling systems. This paper discusses both of these shipboard problems, and it details the methodology used to develop the metrics that diagnose them.

A power quality prediction system

This paper describes two hardware prototypes and estimation schemes for determining the parameters of a simple, physically based, point-of-use electric utility model using transient measurements. Parameters of the utility model are estimated using data collected by the prototypes. Frequency-dependent effects observed in previous work in this area are modeled. Performance of the techniques given is demonstrated by comparison of measured and predicted line voltage distortion during current transients created by several loads.

Fault detection and diagnostics for non-intrusive monitoring using motor harmonics

Harmonic analysis of motor current has been used to track the speed of motors for sensorless control. Algorithms exist that track the speed of a motor given a dedicated stator current measurement, for example [1–5]. Harmonic analysis has also been applied for diagnostic detection of electro-mechanical faults such as damaged bearings and rotor eccentricity [6–17]. This paper demonstrates the utility of harmonic analysis for fault detection and diagnostics in non-intrusive monitoring applications, where multiple loads are tracked by a sensor monitoring only the aggregate utility service. An optimization routine is implemented to maintain accuracy of speed estimation while using shorter lengths of data.

A Method for Nonlinear Least Squares With Structured Residuals

This note develops a modification of standard nonlinear least squares methods with reduced sensitivity to the quality of the initial guess. The technique is presented in the context of least squares fitting of dynamic system models, but may apply to other kinds of problems. The performance of the technique is compared to standard methods for a variety of test problems

Optimization of circuitry arrangements for heat exchangers using derivative-free optimization

Abstract Optimization of the refrigerant circuitry can improve a heat exchangers performance. Design engineers currently choose the refrigerant circuitry according to their experience and heat exchanger simulations. However, the design of an optimized refrigerant circuitry is difficult. The number of refrigerant circuitry candidates is enormous. Therefore, exhaustive search algorithms cannot be used and intelligent techniques must be developed to explore the solution space efficiently. In this paper, we formulate refrigerant circuitry design as a binary constrained optimization problem. We use CoilDesigner, a simulation and design tool of air to refrigerant heat exchangers, in order to simulate the performance of different refrigerant circuitry designs. We treat CoilDesigner as a black-box system since the exact relationship of the objective function with the decision variables is not explicit. Derivative-free optimization (DFO) algorithms are suitable for solving this black-box model since they do not require explicit functional representations of the objective function and the constraints. The aim of this paper is twofold. First, we compare four mixed-integer constrained DFO solvers and one box-bounded DFO solver and evaluate their ability to solve a difficult industrially relevant problem. Second, we demonstrate that the proposed formulation is suitable for optimizing the circuitry configuration of heat exchangers. We apply the DFO solvers to 17 heat exchanger design problems. Results show that TOMLAB/glcDirect and TOMLAB/glcSolve can find optimal or near-optimal refrigerant circuitry designs after a relatively small number of circuit simulations.

A comparison of transient heat pump cycle models using alternative flow descriptions

This article compares the effects of two different refrigerant flow modeling assumptions on the transient performance of vapor-compression heat pump cycles. This comparison is done on a dynamic system-level model of a flash tank vapor injection cycle that includes finite-volume heat exchanger models. The effect of the flow assumptions and specific slip ratio correlations on both the equilibrium operating point and the transient behavior of the cycle are demonstrated through both simulations and experiments. It is shown that equivalent simulations with different slip ratio correlations each have different equilibrium mass inventories and that some aspects of the dynamic system behavior, such as the suction superheat or pressure transients, exhibit significant differences both in simulations and in comparison to experimental data.

Proportional-integral extremum seeking for vapor compression systems

In this paper, we optimize vapor compression system power consumption through the application of a newly-developed proportional-integral extremum seeking controller (PI-ESC) that converges at the same timescale as the process. This method modifies the control law to include terms proportional to the estimated gradient, but this modification of the control law requires a more sophisticated gradient estimator in order to avoid bias. We develop a PI-ESC for which this bias is eliminated. PI-ESC is applied to the problem of compressor discharge temperature setpoint selection for a vapor compression system where setpoints are automatically determined so that power consumption is minimized. The vapor compression system operates with a regulating feedback controller configured to drive the compressor discharge temperature to setpoints selected by the PI-ESC, and we use a physics-based simulation model to demonstrate that power consumption is minimized dramatically faster than by traditional perturbation-based methods.

Improving the efficiency of residential HVAC systems using computer-based power-electronic controls

Space heating and cooling are responsible for about 43% of energy consumption in the average American home [1]. That number can be reduced significantly through the use of a computer-based power-electronic control system. This paper describes one proposed solution, which uses a PC to control the motors in the system. The central PC uses wireless communications to coordinate fan and compressor speeds. The paper describes some new control concepts designed to implement demand-side management, and it shows how the system can be operated in a diagnostic mode that regularly checks for increased energy consumption resulting from degrading equipment conditions.

Model Predictive Control of Multi-zone Vapor Compression Systems

While the previous chapter presented modeling and control strategies for vapor compression systems in general, in this chapter, a model predictive controller is designed for a multi-zone vapor compression system. Controller requirements representing desired performance of production-scale equipment are provided and include baseline requirements common in control literature (constraint enforcement, reference tracking, disturbance rejection) and also extended requirements necessary for commercial application (selectively deactivating zones, implementable on embedded processors with limited memory/computation, compatibility with demand response events.). A controller architecture is presented based on model predictive control to meet the requirements. Experiments are presented validating constraint enforcement and automatic deactivation of zones.