Signal Based Fault Detection and Diagnosis for Rotating Electrical Machines: Issues and Solutions - Complex System Modelling and Control Through Intelligent Soft Computations - page 274

The proposed data-driven algorithms for FDD based on MVSA and MCSA are
tested by several simulations and experimentations in order to verify the effec-
tiveness of the proposed methodologies.
The chapter will be organized in the following sections. In Sect. 2 the FDD
algorithm based on Motor Current Signature Analysis is discussed with focus on
Quality Control scenario. Experimental tests on real motors are reported in Sect. 3 .
The FDI algorithm based on vibration signals is described in Sect. 4 . Experimental
tests on real motors are reported in Sect. 5 . Comments on the performances of the
proposed solutions are reported in Sect. 6 .

2 Electric Motor FDD by MCSA in Quality Control
Scenario

In industry, QC is a collection of methods that are able to improve the quality and
ef

ciency in processes, productions and in many others industry aspects. In 1924,
Walter Shewhart designed the first control chart and gave a rationale for its use in

process monitoring and control (Stuart et al. 1995 ). The main concept of QC is the
“

”

that ensures the product quality, processes and signals monitoring
to detect when they

proactiveness

. In the last years, manufacturing industries
are paying attention and efforts for the introduction of QC in the production lines.
Large volumes of low-tech products involve many investigations on the ef

“ go out of control ”

cient

introduction of QC in production lines.
One of the major problems, in which these manufacturing industries are
involved, is the customers satisfaction, because they usually purchase a lot of
products with some unwanted defective component. In order to satisfy customers,
manufacturing industries carry out some spot checks at the end of production lines.
This method does not ensure the quality of products and total defective products
removal. A desirable QC solution for these manufacturing industries should be
minimally invasive, effective and with a low payback period. In addition, tests
should be performed in a systematic way using a low-cost system based on a
reduced set of sensors embedded in the test bench.
The proposed FDD system acquires sensor measurements and detects defective
products. Moreover, by isolating and identifying the defective type, the FDD
procedure helps to estimate in which subprocess the defect is introduced and allows
to remove the defective products, improving the processes quality. The tests, per-
formed at the end of production lines, allow to improve the quality of processes as
proactive measures for the QC methodology.