Data fusion is a topic which is currently causing much interest. In NDT, the combining of data from a number of independent sources related to the same test component can provide a more complete and accurate assessment of any flaws present. Ultrasonic testing, radiographic and eddy current inspection, as well as other methods, can provide the required diversity of information. However, in order to obtain meaningful results, techniques must be used which go beyond the simple addition or superimposing of the various data sources. Within this context this book by Xavier Gros is very timely, as it provides an opportunity for those interpreting NDT data to obtain an insight into data fusion methods.
Overall it is a very useful and interesting book containing many suggestions for data fusion which can form the basis of further study, and very complete reference sections at the end of each chapter. Whilst this is a major strength, it also a weakness in that individual chapters appear isolated and do not form part of a coherent whole. This is particularly true in the early review chapters where different topics appear as a list of items rather than as a properly argued line of thought. This also results in a number of repetitions in different chapters concerning POD and ROC curves as well as Bayesian inference.
The first two chapters introduce the subject of data fusion and provide a mathematical framework on the subject independently of the NDT context. Based on probability theory, conditional probabilities are used to characterize the various sensors. For example, for eddy current depth measurement, given a flaw of a certain depth, what is the probability of detecting a signal of a particular value? The application of Bayesian inference techniques and Dempster - Schafer evidential reasoning allows the combination of various probabilities associated with different measurements in order to obtain a higher level of confidence in the parameter of interest, in this case depth. The information given in this chapter is comprehensive and well presented. My only criticism is that it tends to presuppose a background knowledge of probability resulting in gaps in the development of the theory which requires further study. It would have been helpful to include more basic introductory material and examples, if only for revision purposes.
The third chapter contains a very basic introduction to a wide range of NDT methods including liquid penetrant testing and acoustic emission. These and other examples are not relevant to the data fusion cases discussed in the book and no real insight is obtained as to how such sources of information can be used in a data fusion scheme. The material is well known to the NDT practitioner and tends to detract from the natural progress of the book. On the other hand, the following chapter on scientific visualization is a very good introduction to the subject with important aspects such as visualization tools and colour maps being highlighted. It includes the important point that different colour scales, thresholds and representations of the same data can produce remarkably different images. The user has to discover how to get the most from the data. Again visualization is considered separately from data fusion and it is only when the case studies are presented do we see its real relevance. In fact it is very important for showing the results of the fusion process especially when fusing data at the pixel level from 2D scanned images.
The case studies given in the last two chapters, are used to illustrate the application of data fusion to NDT data taken from both real and artificial flaws. In the first example the binary decision of a defect being present or not present is demonstrated with impact-damaged composite material used in helicopter blades. Although a number of NDT techniques applicable to composite inspection is described along with the types of damage encountered, the data fusion mainly relates to data taken from eddy current systems. A particularly nice example of eddy current data taken from a scan over a composite plate is given in terms of a visualized 2D image. In this case the raw data map is compared with that of a conditional probability map showing the probability of a defect being present given that a particular level of signal is being observed. The resulting image shows a considerable improvement over crude averaging in removing noise and in distinguishing two clear defective areas. Although the technique depends on knowing the probability of a defect being present and the conditional probability of observing a particular signal when a defect is present, there is insufficient detail given to obtain a full understanding of how these a priori probabilities were derived.
The second example is a comprehensive study of data fusion applied to weld specimens examined using eddy current, ultrasonic and radiographic methods. In this case data fusion is used to estimate both the depth and length of a series of representative flaws including both artificial slots and real flaws such as lack of sidewall fusion, slag line and crack defects.
Much detail is given including the importance of deriving prior probability distributions for the sensors used. For eddy current crack depth measurement a series of calibrations slots is used and the results compared to Gaussian normal distributions. The same approach is taken for characterizing ultrasonic probes of different angles used to size linear flaws for length. I was somewhat disturbed to see the suggestion that for sensor calibration, slots could safely be incorporated in the parent metal of welded components since it was unlikely that cracking would occur in this region due to external loading.
As to the data fusion itself a number of different scenarios are presented including the use of Bayesian theory to improve the results from one eddy current and multiple eddy current sensors. Whilst a very useful and interesting section the description of the different probability terms being used is somewhat difficult to follow. Of particular interest are sections dealing with the fusion of data to determine the accurate length of a flaw. The outputs used included data taken from ultrasonic probes of different angles and also data taken from ultrasonic, eddy current and radiographic systems. However the important point is made that fusing data from different techniques does not necessarily increase the belief in a particular measurement, since limited prior information on a given NDT method will only increase the uncertainty in the results obtained from the overall fusion process.
The chapter concludes with a very interesting discussion on pixel-level fusion of both eddy current images related to surface flaws such as HAZ cracks, and ultrasonic C-Scan images of internal flaws such as slag lines. Gros demonstrates that naive arithmetic operations do not really work on pixel data, but that a priori information to weight images prior to addition, multiplication and subtraction can produce dramatically improved results in the separation of real features from non-relevant ones. In addition, the use of complementary techniques such as the ones above can be used to form composite images revealing both surface and internal features.
I would certainly recommend this book to engineers and scientists interested in applying data fusion methods to NDT, since it contains lots of options for data fusion, which genuinely give small improvements in accuracy or confidence limits. My only reservation is that for some methods such as ultrasonic testing, obtaining sufficient a priori information on representative flaws may in fact be difficult.