Data processing: measuring – calibrating – or testing – Measurement system – Measured signal processing
Reexamination Certificate
2000-12-12
2003-10-28
Barlow, John (Department: 2863)
Data processing: measuring, calibrating, or testing
Measurement system
Measured signal processing
C702S002000, C408S008000
Reexamination Certificate
active
06640205
ABSTRACT:
BACKGROUND OF THE INVENTION
The invention relates to a method of and a device for utilizing this method, for investigating and identifying the nature of a material, to be worked, and for making available at least one operating parameter for the optimized pre-setting of a working device.
Different specialized equipment are presently used for optimally working materials such as, e.g. concrete, bricks, tiles, etc., particularly, for producing holes in such materials that are capable of holding dowels. When only one device, e.g. a hammer drill, is used to work on different types of materials, at least some of the equipment parameters, such as the “impact frequency”, the “individual impact energy” and the “rpm” must be adjustable. Furthermore, if the adjustment of at least some of these parameters is to be automatic to facilitate the operation of such working devices, an automatic identification of the material is required.
In the art of material testing, various methods for determining certain material properties are known. Reference is made especially to the subject of the “Non-Destructive Testing of Materials in Construction” in Schickert, G., Presentations and Poster Reports at the International Symposium on Non-Destructive Testing in Construction, Deutsche Gesellschaft für erstörungsfreie Prüfung e.V., Berlin; 1991 and Schickert, G., Wiggenhauser, H., International Symposium Non-Destructive Testing in Civil Engineering (NDT-CE), Deutsche Gesellschaft für erstörungsfreie Prüfung e.V., Berlin; 1995. From the mining sector, a method is known from Aquila Mining Systems Ltd. (www.aquilaltd.com/aquila/aquila.htm), by means of which the nature of the material, which is to be worked, can be determined in real time by an analysis of vibrations. Likewise, a method is disclosed, with which automatic identification of different types of rock is said to be possible by measuring the drilling parameters, such as the torque, the contacting pressure, the rpm and the drilling speed. See Pollitt, M. et al., Lithological interpretation based on monitored drilling performance parameters, CIM Bulletin, Volume 84, No. 985, July 1991, pages 25-29.
In the German patent 3 518 370 (compare to reference Uitto V., Method for Optimizing Impacting Rock Drilling, German Patent 3 518 370, 1985.), a method is described, for which the shock wave is controlled while drilling rock. The measured shock wave or parameters derived therefrom, such as the spectrum, the decay behavior and the amplitude values are compared with a nominal value. By changing one or more of the regulated variables, such as the impact frequency, the impact force, the rpm, the torque and/or the advancing force, the deviation of the quantity measured from the nominal value is kept to a minimum.
Methods are also known from the machinery industry, by which bearing damage can be recognized by analyzing audible sound. Similar methods are used in quality control, for example, for checking flow. See Wagner, J., Automatic Quality Control Systems for the Roof Tile Industry, Keramische Zeitschrift, Volume 47, No. 6, 1995 and Jonuscheit, H., Neuronal Networks in Production, Design & Elektronik.
The aforementioned art have various problems or disadvantages, which the invention overcomes. In particular, the methods, used in testing a material, are expensive, require special test equipment or cannot be automated and/or used online. Moreover, sensing experiments during vibration analysis showed that, in hand-held hammer drilling equipment, for example, identification of the material is not possible on the basis of an analysis of the housing vibrations. Identification by means of an analysis of the tools, such as the drill vibrations, is conceivable. In working equipment of the type under consideration here, particularly, drill hammers, such a measurement can be realized, if at all, only with difficulty. Further, the identification of the material by measurement of the drilling parameters is only possible if all of the mentioned parameters are known, since such parameters have a great mutual effect on one another. Thus, a very extensive sensory analysis is required. Finally, there is a great dependence on the tool used, e.g. on the drill.
SUMMARY OF THE INVENTION
A primary object of the invention is to provide a method of and an apparatus, by which, during or immediately prior to a working process, e.g. a drilling process, the nature of the material to be worked is identified, in order to automatically set, with the help of the data so obtained, at least some of the operating parameters of the working equipment, essential for an optimum working process.
This object is accomplished for a method, described generally above, for investigating and identifying a material, intended to be worked on, due to the fact that prior to or at the beginning and during a working process, a shock wave, generated or induced in a tool of the working equipment, is detected and at least one distinguishing feature, characteristic for the material, is extracted from the shock wave signal so measured and evaluated for classifying the material by means of an algorithm.
The material is identified by an algorithmic analysis of longitudinal waves. These may be, for example, the shock wave measured directly in the tool or the sound waves, particularly, audible sound waves radiating from the tool or the material.
During the classification of the material, for a more accurate evaluation, provisions are made that at least one external force acting on the working device, such as the contacting force, is included in the subsequent signal processing.
The shock wave can be measured by sensors, based on the magneto-elastic (ME) effect, on the basis of expansion strain gauges or on the basis of surface waves. Sound waves, especially, sound waves in the air, are measured, for example, by a microphone.
In the subsequent extraction of distinguishing features, certain properties, such as the decay behavior, the spectra and the energy of the measured signals are calculated by suitable algorithms, as described in the following examples, which are not, however, intended to limit the invention. On the basis of these properties, a decision is made, in the subsequent classification, as to the material that is present in a particular case. Additionally, an externally acting force, especially, the contacting force of the user of the device, can be used as a further auxiliary quantity for this decision. In the simplest case, this auxiliary or additional quantity serves for calculating or evaluating the signal cluster obtained more accurately.
When several distinguishing features are calculated and the results of these calculations are then weighted and combined into an overall decision, such a process is advantageous and improves the accuracy of the material classification appreciably. For this purpose, methods, which are assigned to the field of so-called “artificial intelligence”, such as fuzzy logic systems or neuronal networks, can be used. Table 1 below gives an overview of the different possibilities for detecting signals and extracting distinguishing features during the identification of the material, including the tools used, particularly, the drills used.
TABLE 1
Identification of material and tool (drill)
by measurement and analysis of longitudinal waves
Body sound
Audible sound/shockwave
Measurement with microphones
Measurement with ME sensors
Elongation strain gauges
Surface wave
FFT-based distinguish-
Methods based on auto-
Time domain methods
ing features
regressive (AR) models
Analytical methods
Extreme values
Average value
Damping
Energy quantile
Symmetry of the first
Position of the inherent
inherent frequency
frequencies
Impact length/− decay
Energy
Center of gravity of the
Band pass filtration
spectra
Center of gravity
REFERENCES:
patent: 3464503 (1969-09-01), Houck
patent: 4671366 (1987-06-01), Uitto et al.
patent: 5020378 (1991-06-01), Hesthamer et al.
patent: 5289886 (1994-03-01), Shikata et al.
patent: 6085121 (2000-07-01), Stern
patent: 4334933 (1995-04-01), None
patent: 077161
Bongers-Ambrosius Hans-Werner
Böni Hans
Schaer Roland
Schmitzer Harald
Barlow John
Cherry Stephen
Hilti Aktiengesellschaft
Sidley Austin Brown & Wood LLP
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