Mojdeh Shakeri

Bio: Mojdeh Shakeri is an academic researcher from MathWorks. The author has contributed to research in topics: Computational complexity theory & Lagrangian relaxation. The author has an hindex of 15, co-authored 25 publications receiving 1014 citations. Previous affiliations of Mojdeh Shakeri include University of Connecticut & Mansfield University of Pennsylvania.

Multi-signal flow graphs: a novel approach for system testability analysis and fault diagnosis

Abstract: In this paper, we present a comprehensive methodology for a formal, but intuitive, cause-effect dependency modeling using multi-signal directed graphs that correspond closely to hierarchical system schematics and develop diagnostic strategies to isolate faults in the shortest possible time without making the unrealistic single fault assumption A key feature of our methodology is that our models lend naturally to real-world necessities, such as system integration and hierarchical troubleshooting >

Sequential testing algorithms for multiple fault diagnosis

Abstract: We consider the problem of constructing optimal and near-optimal test sequences for multiple fault diagnosis. The computational complexity of solving the optimal multiple-fault isolation problem is super exponential, that is, it is much more difficult than the single-fault isolation problem, which, by itself, is NP-hard. By employing concepts from information theory and AND/OR graph search and by exploiting the single fault testing strategies of Pattipati et al. (1990), we present several test sequencing algorithms for the multiple fault isolation problem. These algorithms provide a trade-off between the degree of suboptimality and computational complexity. Furthermore, we present novel diagnostic strategies that generate a diagnostic directed graph, instead of a traditional diagnostic tree, for multiple fault diagnosis. Using this approach, the storage complexity of the overall diagnostic strategy reduces substantially. The algorithms developed herein have been successfully applied to several real-world systems.

Distributed model compilation

Abstract: Methods and systems are provided for partitioning and distributing the model processing of a graphical model to provide an executable form of the graphical model. The methods and systems determine tasks of the model processing that can be processed separately and concurrently from other tasks. A distribution scheme for distributing the model processing tasks is determined that considers the characteristics of the model processing tasks in view of the characteristics of available computing resources. Variations of partitioning and distributing the model processing tasks can be determined to provide for distributed processing in an optimized or desired manner. The results of the distributed processing of the model processing tasks are obtained and combined to provide an executable form for the graphical model.

Optimal and near-optimal test sequencing algorithms with realistic test models

Abstract: In this paper, we first present the formulation and solution of the basic test sequencing problem. We then consider generalized test sequencing problems that incorporate various practical features such as precedence constraints and setup operations for tests, multi-outcome tests, modular diagnosis, and rectification. We develop various AO/sup */ and information heuristic-based algorithms to solve these practical test sequencing problems. We also discuss the issues involved in implementation of the test sequencing algorithms for solving large problems efficiently, and show that our preprocessing techniques result in considerable speed-ups.

A system and method for using execution contexts in block diagram modeling

Abstract: A method of controlling the conditional execution of elements and subsystems in a block diagram is disclosed. Data structures known as Execution Contexts are created and associated with individual block diagram elements and subsystems. The Execution Contexts allow execution of the associated element or subsystem upon satisfaction of a specified pre-condition. The Execution Contexts may be inherited by other elements and subsystems in the block diagram and propagated programmatically throughout the block diagram. The use of the Execution Contexts allows for efficient code generation and block diagram execution, as well as supporting modular design concepts.

Smart building manager

Abstract: A building manager includes a communications interface configured to receive information from a smart energy grid. The building manager further includes an integrated control layer configured to receive inputs from and to provide outputs to a plurality of building subsystems. The integrated control layer includes a plurality of control algorithm modules configured to process the inputs and to determine the outputs. The building manager further includes a fault detection and diagnostics layer configured to use statistical analysis on the inputs received from the integrated control layer to detect and diagnose faults. The building manager yet further includes a demand response layer configured to process the information received from the smart energy grid to determine adjustments to the plurality of control algorithms of the integrated control layer.

Automated fault detection and diagnostics in a building management system

Abstract: Systems and methods for building automation system management are shown and described. The systems and methods relate to fault detection via abnormal energy monitoring and detection. The systems and methods also relate to control and fault detection methods for chillers. The systems and methods further relate to graphical user interfaces for use with fault detection features of a building automation system.

Multi-signal flow graphs: a novel approach for system testability analysis and fault diagnosis

Abstract: In this paper, we present a comprehensive methodology for a formal, but intuitive, cause-effect dependency modeling using multi-signal directed graphs that correspond closely to hierarchical system schematics and develop diagnostic strategies to isolate faults in the shortest possible time without making the unrealistic single fault assumption A key feature of our methodology is that our models lend naturally to real-world necessities, such as system integration and hierarchical troubleshooting >

Building management system with fault analysis

Abstract: A controller for a building management system is configured to analyze faults in the building management system. The controller detects a fault in the building management system by evaluating data of building management system using a system of rules. The controller determines a conditional probability for each of a plurality of possible fault causes given the detected fault. The controller determines the most likely fault cause by comparing the determined probabilities and electronically reports the most likely fault cause.

Systems and methods for detecting changes in energy usage in a building

Abstract: A computer system for use with a building management system for a building includes a processing circuit configured to automatically identify a change in a building's energy usage model based on data received from the building management system. The processing circuit may be configured to communicate the identified change in the static factor to at least one of (a) a module for alerting a user to the identified change and (b) a module for initiating an adjustment to the energy model for a building in response to the identified change.