CLASSIFICATION OF STEEL

Abstract: A steel specimen is presented to coils (7, 8) to provide inductive coupling between the primary coil (7) and the secondary coil (8). The primary coil (7) is excited by a plurality of frequencies by current from a signal generator (10) and the induced signals, measured in a high impedance load connected across the secondary coil (8), are representative of the induction values of the specimen at those frequencies. A grade classification is then given to the specimen on the basis of these induction values. The measurements may be facilitated by the use of a digital voltmeter (11) a mini-computer (12) and a cathode ray oscilloscope (20).

Description: CLASSIFICATION OF STEEL Technical Field This invention relates to methods and apparatus for identifying and classifying steels. Background Art In a modern steel works producing a wide range of steel products of differing steel grades, it is important to be able to carry out non-destructive testing of steel specimens to establish their correct grades. One current method, known as the "Forster" method, relies on a comparison between the magnetic properties of a steel specimen to be tested and a "standard" sample which has been chemically analysed. The test specimen and the standard sample are inserted into separate coils, each having primary and secondary windings. The primary windings of the two coils are subjected to a common energizing current of fixed frequency and a comparison is made between output signals induced in the secondary windings t of the two coils. The output signals may be applied to a comparison circuit which generates a display on a screen. The Forster method of steel classification has several limitations and problems in practice. These include: 1. A highly trained operator is required to interpret the trace or screen display to enable satisfactory information to be gained. 2. Since the operator must visually access a visual display, estimating the amplitude and shape of a wave form generated by the test sample, only a qualitative idea is obtained of possible differences between successive samples being tested. 3. Since the test method is not quantitative and since there are always some variations in the physical and chemical properties even within a given grade of steel, it is very difficult to be certain whether an observed changed in the display constitutes a real change in grade or only a variation explainable by within grade variations. 4. The method is very sensitive to variations in temperature between the test specimen and the standard sample. 5. Results depend on chemical analysis of the initial standard sample. Once it is considered that a change in grade has occurred the new grade cannot be determined without further recourse to sampling and subsequent chemical analysis. The present invention has arisen from work aimed at developing an improved magnetic testing method which will enable a more accurate and convenient testing procedure. Disclosure of Invention The invention provides a method of classifying a steel specimen comprising: ' presenting the specimen to a coil means having a primary winding and a secondary winding such that the specimen contributes to an inductive coupling between the primary winding and the secondary winding; applying an excitation current to the primary winding at each of a plurality of excitation frequencies whereby to induce in the secondary winding for each excitation frequency a signal indicative of an induction value of the specimen; and determining a grade classification of the specimen dependent on the induction values obtained at said excitation frequencies. The primary and secondary windings of the coil means may be generally co-axial and spaced apart in the axial direction and the specimen may be positioned so as to extend into both windings. Alternatively, the primary and secondary windings may be disposed about a coupling member defining a coupling gap and the specimen may be position so as to provide an inductive coupling across said gap. Preferably, the critical frequencies at which signals induced in the secondary winding are exactly out of phase with the excitation current are also determined and the determination of the grade classification is also /dependent on those critical frequencies. Preferably further, the grade classification is determined according to the value of a discriminant function of the form aα+b8+cγ+....... where α,β,γ are attributes of the specimen comprising said induction values and a,b,c are coefficients reflecting the degree to which the respective attributes are effective to discriminate between steel grades. ■> Preferably said attributes also comprise said critical frequencies. The invention also provides apparatus for c'lassifying steel specimens, comprising: coil means having a primary winding and a secondary winding to be inductively coupled via a steel specimen to be classified; excitation means for applying an excitation current to the primary winding at each of a plurality of / excitation frequencies whereby to induce in the secondary winding for each frequency an output signal indicative of an induction value of the specimen; and signal processing means to receive the output signals indicative of the induction values at said frequencies and to determine a grade classification of the specimen dependent on those values. Brief Description of Drawings In order that the invention may be more fully explained, the operation of one particular form of equipment, and the results obtained, will be described in detail with reference to the accompanying drawings in which: Figure 1 is a circuit diagram of conventional equipment operating on the "Forster" method; Figures 2, 3 and 4 illustrate equipment operable in accordance with the present invention; Figure 5 is a canonical variable plot for various steel grades; Figure 6 is a diagram showing the skin effect for steel specimens at varying excitation frequencies; Figure 7 illustrates the relationship between the indudtion and cross-sectional area of the specimens; Figure 8 illustrates the relationship between the induction and the measured surface area of the r specimens; Figure 9 is a plot of the shape factor of various specimens against a breaόVth/thickness ratio; and Figure 10 is a graph showing a correlation between the decarburisation depth and measured inductions at various frequencies. Mode for carrying out the Invention Apparatus conventionally used for classifying specimens by the "Forster" method is shown in Figure 1. Two independent coils 1, 2 are used and comparisons are made between a chemically analysed sample 3 inserted into coil 1 and the test sample 4 inserted into coil 2. The primary winding ' s of the coils are connected to a 50 hz signal source 6 so that the same current (I) flows through the primaries (P) of both coils and a comparison is made between the two secondaries (S). If the samples are the same, a balanced condition is effectively contained between Si and S2. A change in magnetic properties of the test sample causes an imbalance in the electrical circuit, resulting in a change to the visual display pattern on the screen of the cathode ray tube instrument 5. One apparatus for testing in accordance with /the present invention is illustrated in Figures 2 and 3. In this apparatus two coils 7, 8 are strapped together with their axes aligned, to enable a steel specimen 9 to be inserted through both coils. An excitation current delivered from a signal generator 10 is applied to the ends of the primary winding of the first coil 7 and the induced EMF is measured in a high impedance load (10 M.ohms) connected to the secondary winding of the second coil 8. The secondary winding of the first coil (Si) and the primary winding of the second coil (P2) are not used. It is possible to use one coil only by using the primary as driver and secondary as receiver, but the induced voltages from the primary which occur even without a sample threading the coil is sufficient to reduce the sensitivity to a large extent. The output (secondary) from coil 8 is measured on a digital voltmeter 11 in parallel with a coaxial connection to a mini-computer 12. The input and output signals are displayed on a cathode ray oscilliscope 20. The computer, a MINC-11 (DEC) has an input keyboard 13, performs an analog to digital conversion on the as received signal and displays an output on a V.D.U. display screen 14. Instead of using two coils each with primary and secondary windings, it would be possible to employ a single coil with primary and secondary windings spaced apart in the axial direction and arranged so that the steel specimens can be inserted through both. Figure 4 illustrates an alternative coil arrangement for dealing with specimens which are too large to be accommodated within the confines of a coil. In this arrangement primary and secondary coil windings 15, 16 are dispersed on a horseshoe-shaped coupling member 17, the ends of which define a coupling gap which, in use of the apparatus, bridged by a steel test specimen 18 so that the specimen contribute to the inductive coupling between the primary and secondary windings. The method of classifying steel specimens according to their grade type in accordance with the invention is based on a statistical procedure known as Linear Discriminant Analysis. Computer software packages that perform this statistical technique are available for a range of computer operating systems. One particular pfrogram suitable for this purpose is program P7M of the BMDP package (Bio Medical Statistical Programs issued by the Regents of the University of California) running on a PDP 11/70 computer using the RSX - 11M operating system. This program determines the minimum number of variables which will achieve the optimum statistical separation of the known steel grades types. Data from a large number of steel specimens of various grade types are collectively called a "learning set". Each specimen (or case) in the learning set has been processed using the coil arrangement to obtain quantitative induction data at various frequencies. These calculated variables as well as grade code (a convenient numerical identifier corresponding to the alpha-numeric grade name), are used as input to the P7M program. All steel specimens of a particular grade code are grouped together by the program. Variables that show merit in separating grade groupings on a quantitative statistical basis then become part of the linear discriminant equation. At each step, one variable will enter or be removed from the current list of optimum variables. The linear discriminant function that uses the chosen variables will differ between grade codes by the coefficient and constant terms applied. That is, each grade will have an equation, comprised of differing coefficients applied to the same chosen variables. For any specimen the numerical value of its known variables may be substituted into the. equation for each grade code, to generate a numerical result. The particular equation that achieves the highest numerical r result is deemed, on a statistical basis, to show which of the grade types known to the program most closely resembles the specimen in question. In order to test the reliability of the procedure, the discriminant equations can be used to classify each of the steel specimens that form the learning set. The calculated grade may be compared with the known grade to report the percentage of agreements. To test specimens on-line, or in the field, the values of the variables, viz. the inductions of various frequencies, are obtained, and fed into those same discriminant equations that were calculated off line. However, in the on-line case, the grade is unknown, and so the grade name whose equation gives the highest result, is classed as the grade of the unknown specimen. In a series of classification tests on steel specimens a sampling time of two seconds (2 sees) was used in order to capture the signal induced by each specimen and the RMS signal strength was calculated for each current frequency applied to the input primary coil (from the signal generator). A series of applied current frequencies were used viz; 5, 10, 50, 500, 5000, 10000 hertz. ' In addition to these direct inputs to the MINC-11 via the A to D interface, additional information was supplied via the keyboard. This information en.itsisted of: (i) The section (diameter of steel specimen) (ii) The natural frequency (in hertz) (iii) The coil frequency (in hertz) The natural and coil frequency values were measured *by connecting the input (driving) current to the X channel of a cathode ray oscilloscope (CRO) and the output signal to the Y channel. If the frequency of the exciting current is slowly increased from zero (by rotating the frequency control potentiometer of the signal generator), the relative phase relationship between the two can be monitored. At a limited number of critical frequencies (determined by the coil design) the input and output signals are exactly out of phase (180°). The introduction of a steel specimen into the coils changes the frequency at which this out of phase condition occurs. The lower frequency measured is called the "natural" frequency and the higher frequency, the "coil" frequency. These two values were entered manually to the MINC-11. However, with more sophisticated equipment this information may be automatically measured by a sweep frequency technique when the sample is first presented to the coil. The computer presents the actual RMS inductions in the secondary at the frequency values used to excite the primary coil and the ACTUAL GRADE CODE it has determined the sample to be. The samples used were all obtained from the laboratory sampling room in the as-rolled condition. All specimens were rounds or rods and in the aage 5.5 mm - 20 mm the upper limit being dictated by the coil size. The samples were examined and tested in the as received condition (usually slightly convex in shape with some minor scale present on the surface). The resistance of the primary coil .was not matched to that of the signal generator output resistance and consequently the available current into the primary coil varied to a large degree depending on the frequency of the applied current. In order to ensure that the measurements obtained resulted from the effects of inserting the sample, and not from the induction between the coils, the induced EMF when no sample was present was measured for the frequencies of interest. These values were referred to as the background values and were subtracted from the appropriate induction values obtained during the testing of the samples. I = T - B Induction at 50hz = Total Induction at 50hz - Background (at 50 due to sample measured Induction (Relative) (Absolute) 5 (Sample inserted) (No sample) Table 1 of the Appendix shows a computer summary sheet for a portion of the information collected during this investigation. Column 1 of this table indicates the as received sample identification number, 2 0 the section diameter which is entered via the computer keyboard and columns 3 to 8 refer to the induction (I) at the frequencies indicated. The natural frequency (in hertz) is shown in column 9 and the coil frequency in 10. Column 11 is the actual grade of steel of the specimen. 5 Tables 2 and 3 show the chemical analysis, the inductions and the computed grade classification for a few of the samples tested. The program which collects the voltage waveform from the output coil is also responsible for managing the 0 data whidh is used for recording new sample, information * and also for testing specimens on-line. The data file from this program was transferred to a main processing r computer, for analysis by the BMDP discriminant analysis program (P7M)-. This program is effective to choose which 5 of the pieces of information collecting during testing, known as "attributes", will be most useful in describing the differences between individual specimens classified into their actual grades. For example, the measured induction values at 5,000 hertz may not discriminate well 0 between two particular grade codes whereas the program may find significant differences between the induction values at 5 hertz. It therefore uses the I ς value in preference to the I-.,, value to separate these two grades. In reality (with 8 attributes and hundreds of samples) the simple two-dimensional separation mentioned above translates into 8th dimensional space. The program uses a weighting procedure to emphasize the extent to which each attribute will be used to get the maximum separation that is possible (i.e. the best discrimination one grade from another) from the supplied data. The output of the programme results from the following types of equation. A variable X * = aα+bβ+cγ+ Where α,β,γ are attributes and a,b,c are constants determined from the statistical analysis. e.g. X = 23 x I 50> + 49 ^sooo 5 + 526 (I 5 ) 8 terms In the case above it has calculated that I 5 is very important to the discriminant procedure with L fl( . fl less so (49 526) and I 5Q even less so (23 49 526). A look up table of X values then will yield the grade. e.g. after a learning set has been input to the computer. Value Range Grade X 5 - 90 WK1082 91 - 200 WK1072 201 - 400 WK1057 etc. If X is in range specified print out grade code. e.g. X calculated = 300 PRINT "GRADE IS WK1057" a,b,c once calculated on a reasonable large machine can be entered into a smaller (e.g. MINC - 11 machine) ready for the testing of new samples. e.g. Result of main P7M run a = ' 15.2 g = 29.6 b = 9.7 h = 393.1 c = 23.5 d = -5.2 e = 7.5 f = 5.1 Placing a NEW sample to be identified into the coil .- the small computer sets up the equation to be solved as follows: X = 15.2 (I 5 ) + 9.7 (I 10 ) + 23.5 (I 5Q ) - 5.2 (I 500 ) + 7.5 (I 5000 ) + 5.1 (I 10000 ) - 29.6 (Natural freq. value) + 393.1 (Coil. freq. value) - ready for the sample to be processed - when the sample is processed and the inductions and frequency values determined the simple linear equation is solved. e.g. 2.3 ""5000 23.5 10 3.5 I 10000 30.2 '50 5.0 Nf 50 500 6.5 Cf 30000 Then X = 15.2 x 2.3 + 9.7 x 3.5 + 23.5 x 5.0 + etc, X table is searched for the value of X calculated and the grade outputted. The data from the classification tests was grouped together by using a grade code variable to be the independent variable. Some initial restructuring of the / data was necessary for two reasons: (i) Although 50 grade codes were available from the samples, many were represented by only one or two cases. Some grades are closely similar and were grouped together (e.g. the silicon grades WK22 and R207). Such grades were classified as one code or "generic" name. (ii) A reduction in the number of codes available (generic-names) was made necessary because of limitations to the available memory which restricted the total number of cases available for analysis. This upper limit was r dependent on the number of groups (grade codes), and variables which were chosen for inclusion in the program's control language. The program P7M, performs stepwise so that, for each step, the variable which allows the best discrimination (grade separation) is entered. Each equation, one for each grade is a linear function of the chosen variables. For each specimen tested the most probable grade was determined by the linear discriminant function which has the maximum value. The probability that the specimen is each of the grade codes represented was calculated from the discriminant equations. The BMDP result file, containing the classification function coefficients was transferred, via floppy diskette, to the MINC-11. The output grade is one of the "generic" grades inputted to the program. For example a sample whose actual grade specification is AS 1302, would be classified to the generic code of SF2 (see Figure 4c, / Case No. 36) . The BMDP statistical package outputs its results in the form of a classification matrix. This tabulated information is read as follows: Example 1 Assume that 50 samples are to be classified into five categories or grades (Categories A,B,C,D and E). If classification is perfect, the following computer result would be obtained: Computer Result A B C D E A 100% 7 0 0 0 0 B 100% 0 10 0 0 0 Actual C 100% 0 0 12 0 0 Grade D 100% 0 0 0 13 0 E 100% 0 0 0 0 8 100% The actual grade of the specimen (as determined by chemical analysis) is shown in the first column and the grade calculated by the BMDP programme is shown across the top row of the output. The entries (elements) of the table indicate the number of occasions where the actual grade (row on entry) and the computed grade (column of entry) are recorded. When classification is correct on all occasions, all samples (entries) fall along the major diagonal of the table from top left to bottom right. I this case there were seven (7) cases of grade A, all 'classified correctly into the computer entry. Similarly there were 10 cases of grade B, 12 of C, 13 of D and 8 of E. In a more realistic case where the classification is less than perfect, entries appear at locations other than on the major diagonal. Example 2 Computer Result A B C D E A 71.4 5 2 0 0 0 B 70.0 2 7 1 0 0 Actual C 83.3 1 1 10 0 0 Grade D 92.3 0 0 0 12 1 E 100.0 0 0 0 0 8 84.0 In this case, the seven cases of Grade A, five have been correctly classified as A, and two incorrectly as grade B. The percentage correct is. 5_ x 100 = 71. 4% 7 Of the 10 cases of grade B, 7 are correct, 2 are misclassified as grade A, and one case (1) misclassified as grade C. The overall percentage correct for this example (those along major diagonal = 42) is then % correct = Number along major diagonal x 100 = 42 x 100 = 84 Total number 5U The actual grade codes for the samples tested and their average chemical analysis are given in Table 4 '-of the Appendix. As can be seen, the grades display a considerable range in carbon analysis, and include rim, semi-killed and fully killed steels (R * = rim, CS,S,WS = Semi-killed, K,WK,XK = Fully Killed). Table 5 shows the actual matrix obtained as a summary of the results of grade classification on steel rounds (5.5 mm - 20 mm). Another method BMDP uses to describe the results obtained from its statistical analysis is to generate a canonical variable plot. This graph is a two dimensional representation of the relative placement and separations between individual groups (grades). This graph is shown as Figure 5. It can be seen that in the far top left of the graph the lowest carbon steels are represented. As the carbon level increases the" grades are represented by locations towards the top centre of the graph and finally towards the top right for high carbon grades. Higher manganese steels WK22, XK1320, XK1340 are shown as a band extending to the right at a lower position on the graph. Spring steel grades XK5155, - XK9261 are shown on the far right and far right bottom respectively indicating the relative ease of separation or classification which can be made for these grades, based on their magnetic properties. At low frequencies (5,10 hz) the current traverses the entire cross-section of a steel specimen inserted into the coils. The intensity of the current induced is therefore directly related to the cross-sectional area of the specimen (the volume or mass per unit length). At high frequencies (greater than 500 hertz) the current flow is confined almost entirely to the surface or skin of the conductor, as illustrated in Figure 6. There is a tendency for a varying electric current in a conductor to concentrate in the outer part, or "skin", rather than be distributed uniformly over the cross-section of the conductor. This "skin" effect arises from the increase of internal self inductance of the Conductor with the depth below the surface of the conductor; In consequence, the magnitude of the effect increases with the rate of change (frequency) of the current, the diameter of the conductor and the magnetic permeability of the conductor material. By concentrating the current towards the outside of the conductor, skin effect increases the alternating current or skin resistance, and the energy dissipation within the conductor compared with when it is carrying a steady direct current. Generally, the skin or penetration depth from the conductor's surface is given by: d = 1/ / ( U 0 fs) ,d being the depth at s * which the current has fallen to 1/e of its surface value. μ = permeability of free space μ = permeability of the material f = the frequency of the applied current s = conductivity of the material All of the samples tested and computer classified were rounds (rods and rounds) between 5.5 and ,20 mms in diameter. In order to investigate the * behaviour of specimens with other sections, pieces of angles and flats of various dimensions were tested. The results of these tests are tabulated in Table 6. The most significant differences relate to the ratio of surface area of the specimens compared with their mass (volume). For rounds, the surface" area per unit length is; S = 1TD where D is the diameter and the volume per unit length is; For a flat with thickness T and width W S = 2 (T + W) C = TW If we calculate an "aspect ratio" or shape factor which involves the square of the surface area divided by the volume, weObtain for a round. S 2 - τr 2 p 2 = 4π C D 2 /4 which is not dependent on the section of the steel specimen. For a square we have; S 2 = 2 2 (T+W) 2 now T = W C TW which is also independent of section size. For sections with large elongations (width/thickness ratio), the shape factors are much larger. e.g. flat 10 mms x 100 mms , S 2 = (110 x 2) 2 = (220) 2 = 48.4 C 1000 1000 It is possible to measure the relative volume (low frequency induction) to surface area (high frequency induction) of any specimen placed inside the coils by measuring the inductions induced at different applied current frequencies. In this manner it is possible to estimate the approximate section or shape being presented to the computer for grade analysis, thus avoiding the more obvious human entry errors of incorrect section input via the computer keyboard. For the particular coils used it was found that the induction did not increase linearly with cross sectional area (at low frequencies) but conformed to a curvilinear relationship as shown in Figure 7. The induced voltage was almost but not quite linear with the measured surface area of the specimens as shown in Figure 11. From Figures 7 and 8 it is possible to estimate the shape factor of the. specimen under test. For example the following values are measured for a specimen whose section has been INCORRECTLY typed in as a ROUND, prior to grade identification. 5 hz 500 hz I = 80.0 1150 millivolts The computer would check the shape factor as follows: 80.0 = 590 mm 2 = C (Figure 10), Mass (Volume) 1150 = 200 mm = S (Figure 11), Surface Area Now shape factor = S_ .2 = 200 x 200 = 67.8 C 590 and therefore by referring to Figure 9, with the above shape factor the breadth to thickness ratio is about 18 to 1, clearly indicating the sample is not a ROUND. Since the volume is (approximately since it 2 depends on grade) 590 mms (cross section) the specimen is either a flat or angle (or channel) with a width/thi-ckness ratio of 18/1 or 104 x 5.8 mms for a typical structural grade of steel. Information can be gathered on other sections to form the basis for extending the method to all steel shapes produced at a particular steelworks where testing is to be conducted. Problems relating to the surface •decarburisation of steel occur quite frequently. In order to examine the possible use of the method of this invention for detecting the presence and extent of decarburisation, several steel specimens of a A grade prone to loss of carbon at the surface was examined. Eight pieces of as rolled 20 mm round K1045 were taken and treated as follows: (i) Samples 1 and 2 were left at 20 mms and used for comparison purposes. (ii) The remaining samples were turned down to 18 mms in diameter to remove any decarburisation skin initially present on their surfaces. (iii) Samples were heat treated individually, with slowly increasing oxidising conditions applied to the samples. (Details are given in Table 7 of the Appendix), (iv) Metallographic examination was performed to define the extent of decarburisation of each specimen. The ratio of the induction at 500 hertz (surface induction) to that obtained at 5 hertz •{volumetric induction) is called RATIO 1. The correlation between the ratio and the reported decarburisation depth is demonstrated by Figure 10. As can be seen the decarburised skin led to an increased induction on the surface of the specimen as expected. Table 8 of the Appendix lists classification function coefficients actually determined for a wide range of steel grades and Tables 9, 10 and 11 show how these were used to classify three separate steel samples of unknown grade. The first sample was a 5.5 mm round section and as indicated in Table 9 each measured variable of the sample, was multiplied by the appropriate coefficient and the result summed for all variables. This sum is calculated for all the possible grades and the grade whose sum is the maximum value is deemed to be the actual grade of the specimen. In Table 9 the highest value of 12072.895 was obtained from the coefficients for the grade WS1014 which was therefore determined as the appropriate grade. Table 10 shows the results obtained from a second specimen which was 10 mm round. The maximum sum value of 12175.711 was obtained from the coefficients for the grade WS1014 and this specimen was also of that grade. In the case of Table 11, howe ver, the maximum sum value of 13534.500 was obtained from the coefficients for the grade WK1082 which was therefore determined as the appropriate grade. The third specimen was 10 mm round and the first row of figures relating to section isn the same for Tables 10 and 11. Industrial Applicability From the above results it will be appropriate that the method of the present invention in which the absolute induction of a steel sample is measured at various applied frequencies is capable of classifying the Specimen into a GRADE CODE which is the primary method of steel identification used both within steelworks and by customers. It allows a rapid means of steel identification and avoids most of the current limitations of the Forster instrumentation. 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H « *N M WU » u •> UUΌ ω -o oo — u ■« «. •- UI o- in 3--3 22 2 5S2225SS 2S222 ©©5 s2 5 5SSSS ©©--- 55S5SS 5 SBSS M !! s SSaε « " δ SϊSI-sssss ββ 888" « -" w ss6 β °s° 6£000/98_lV/lDd I66W/98 OA\ ήπ-lw- i _ 0.09X C 1.32X Hn 0.710X 81 0.01X Cr Grade coda • βrada n__« i WK22 Cl ewiricaUon I UK 22 C 100 X 3 8F2 C 0 X 3 C*»u « 3 Seaμlv t 3133.0 Abfcυlule 3.073 26.891 118.697 339.692 3.935 522.882 100.3 32320.0 Swi.' tlun 3,3 a* Relative 2.386 24.427 92.104 186.209 3.173 233.024 Ariϋl wkik 0.32X C 0.94X Hn 0.021X 81 0.01X Cr βrada coda t 3 βrade namit : US1033 0 X 3 C -w * 4 S.a lw * 53614.0 Ab.olute 21.992 106.834 364.146 809.678 38.844 1045.274 33.0 29465.0 Section 16.0 _• Relative 21.305 104.370 337.533 636.193 38.063 735.416 Aπ.lu_i_ 0.19X C 1.S2X Hn 0.210X 81 0.01X Cr Orada coda * βrada πa>« t XK1320 Cle.-i. icaliur. i XK1320 C 100 X 3 SF2 C 0 Cat.* • 3 Seaμli. I 3138.0 Absolute 1.375 13.044 88.044 305.227 2.541 458.668 447.0 33040.0 Sec tion 5.5 aa Relative 0.688 10.580 61.451 131.744 1.761 168.810 ήneluei . 0.73X C 0.70X Hn 0.180X Si 0.01X Cr θrada coda • 1 Orada naaa 1 UK1072 0 3 Cat,* » 6 6*».-ltt • 3192,0 Absolute 4.304 40.871 173.038 469.393 8.736 664.842 110.0 31520.0 Swellun 5.3 aa Relative 3.817 38.407 146.443 296.112 7.937 374.984 nr.-l-k.i_ 0.10X C 1.32Z Hn 0.780X Si 0.01X Cr Orada coda • Grade naaa t UK22 Cl__-lfi_βtl_ι. ( UK22 C 100 X 3 8F2 C 0 X TABLE 3 3. Hz 90. Hz 300. Hz 3000. Hz 10. Hz 10000. Hz Natural Coil Background level 0.687 2.464 26.393 173.483 0.780 289.838 % AnelUbl . 0.83X C 0.74X Hn 0. 190X 81 0.01X C :rr βrada code • 13 Orade neaβ I UK1082 Clari f icat ion ! UK1082 C 100 X 3 UK 1072 C 0 X Saβfle • 66430.0 Abkulute 10.272 38.371 212.709 528.837 19.125 737.551 36.0 30500.0 Section 10.0 aa Relative 9.385 36.107 186.117 353.334 18.345 447.693 C 0.73X Hn 0.016X Si 0.01X Cr βrada code • 12 βrade neββ { A81302 1 SF2 C 98 X 3 C81030 C 2 .0 Abkulute 17.927 87.686 308.810 716.378 31 .933 1018.136 36.0 29930.0 aa Relative 17.240 83.222 282.217 543.093 31 .173 728.298 Analysis 0.23X C 0.80X Hn 0.035X Si 0.01X Cr βrada code • 16 Orade naae X SF2 9 X 3 Cake • 38 Eaaple • 33669.0 Abaolute 3.402 45.118 167.027 413.232 10.372 600.079 79.5 31630.0 Section 13.0 aa Relative 4.713 42.654 140.434 241.749 9.792 310.221 ήnalwkik 0.34X C 0.83X Hn 0.210X 81 0.82X Cr Orade coda • 17 Orade naae J XK3133 Cl*k>iricatlon t XK3133 C 100 X 3 UK1082 C 0 X 3 Cake « 39 Saβt-le • 39030.0 Absolute 8.443 61.026 219.961 342.180 16.010 736.396 61 .0 31000.0 Section 13.0 aa Relative 7.736 38.362 193.360 368.697 13.231 466.730 Analwkik 0.40X C 1.61X Hn 0.260X SI 0.02X Cr Orade code • 18 Orade naae t XK1340 Classification « XK1340 C 100 X 3 UK1082 C 0 3 Case * 40 8eaι » le t 33704.0 Absolute 8.438 73.332 302.391 727.534 16.586 1172.740 106.0 29800.0 Section 13.0 aa Relative 7.751 72.868 275.798 354.031 15.807 882.882 Analwkik 0.38X C 0.B3X Hn 2.130X 81 0.20X Cr Orade code ♦ 19 Orade naae t XK9261 Classification t X 9261 C 100 X 3 XK1340 C 0 X 3 Case • 41 S.at-le * 398.0 Abkulute 22.382 104.106, 339.137 774.016 39.400 1076.582 34.5 29150.0 Section 16.0 aa Relative 21.695 101.642 332.363 600.333 -38.621 786.724 Analwkik 0.00Z C 0.00X Hn 0.000X 61 0.00X Cr Orade code 0 20 βrade naae I A81442 Classification t XK1320 C 100 X 3 8F2 C TABLE 4 CHEMICAL ANALYSIS OF GRADES EXAMINED Grade Name Mn Si Cr N72 06 .37 .007 .01 R1010 10 .45 .007 .01 K22 10 1.32 .75 .01 S1013 09 .32 .10 .01 WS1014 11 .40 .04 .01 SF2 22 .79 .03 .01 CS1030 27 .76 .03 .01 XK1320 20 1.50 .22 .01 XK1340 39 1.60 .24 .01 S1045 45 ■ .77 .02 .01 XK5155 53 -.85 .20 .85 XK9261 57 .83 2.00 .20 K1057 57 . .70 .17 .01 K1072 74 .72 .18 .01 WK1082 84 .72 .18 .01 sυ BST TUTE SHEET TABLE 5 CLASSIFICATION MATRIX GROUP PERCENT NUMBER OF CASES CLASSIFIED INTO GROUP - 1 S1045 100.0 0 0 0 0 0 0 0 0 0 8 0 0 XK5155 100.0 0 0 0 0 • 0 0 0 0 0 0 4 0 XK9261 100.0 0 0 0 0 0 0 0 0 0 0 0 2 WK1057 100.0 0 0 0 0 0 0 0 0 0 0 0 0 K1072 66.7 0 0 0 0 0 0 0 0 0 0 0 0 WK1082 80.0 0 0 0 0 0 0 0 0 0 0 0 0 TOTAL 90.2 11 9 3 38 87 15 3 7 12 8 4 2 WK1057 WK1072 WK1082 N72 100.0 0 0 0 R1010 80.0 0 0 0 WK22 100.0 0 0 0 WS1013 80.5 0 0 0 WS1014 94.4 0 0 0 SF2 93.3 0 0 0 CS1030 100.0 0 0 0 XK1320 100.0 0 0 0 XK1340 92.3 1 0 0 S1045 100.0 0 0 0 XK5155 100.0 0 0 0 XK9261 100.0 0 0 0 WK1057 100.0 4 0 0 WK1072 66.7 1 10 4 W 10Θ2 80.0 0 1 4 TOTAL 90.2 6 11 8 - 28 - TABLE 6 SAMPLE NO SECTION 5 10 SO 100 500 S/C . Indue olta (at the indicatad Irequancy) aa.-l DIMENSIONS CROSS SECT SURFACE S"S/C ana. aq.aaa . ■as. 1 ROUND 8.3 14.4 57.0 79. 0 108 0.73 5.S 23.76 17.28 12.57 1.0 2 • • 12. β 22.0 72.0 95. 0 145 0.62 6.5 33.18 20.42 12.57 1.0 1 20.2 33.2 93.0 125. 0 188 0.50 8.0 SO.26 25.13 12.57 1.0 f 4 29. β 4S.4 116.0 155. 0 255 0.40 10.0 78.54 31.42 12.57 1.0 c (t SI ANCLE 39.1 67.0 272.5 415 625 0.64 3.3x2S.βx2S. .8 170.0 109. 70.66 5.6 DO S2 53.2 92.8 380.0 596 885 0.63 3.3x39.7x39. .7 262.0 165. 104.42 8.3 <Λ S3 • • 63.7 111.2 462.0 725 1135 0.65 3.2x50.1x51. .3 324.5 209. 134.87 10.7 S4 82.2 135.7 570.0 837 1265 0.43 4.85x64.1x64. .2 622.2 266. 113.97 9.C H SS 64.2 111.7 380.0 532 900 0.34 6.25x39.9x40. .1 500.0 172. 59.51 4.7 H S6 • • 86.4 140.7 471.0 6S6 1145 0.33 6.55x44.0x44, .0 576.4 189. 62.04 4.9 C S7 130.7 195.2 628.0 909 1565 0.22 10.00x65.0x66, .5 1315.0 283 60.90 4.8 H Sβ FLAT 92.2 149.2 483.0 686 1175 0.26 8.3x86 717.9 189, 50.07 .. . PI S9 • • 72.7 116.2 325.0 452 765 0.24 lO.lxSO.6 511.1 121. 28.84 2.2 ω S10 * • 47.7 76.2 212.0 298 495 0.25 12.0x23.8 285.6 71. 17.95 1.4 Sll • • 24.2 36.2 104.0 137 262 0.39 10.2x10.2 104.0 40.8 16.00 l.: x SI- , , 58.7 77.7 209.0 285 445 0.23 12.0x32.5(S1040) 390.0 89.0 20.31 l.» m S l l PI PE 49 . 0 82 . 9 2 30 . 0 294 405 0 . 35 27 . 0 (OD ) , 20 . 5 ( I D ) 242 . 5 84.8 29.65 q - 29 - TABLE 7 DECARBURISATION TEST- -K1045 SAMPLE SECTION HEAT FREQUENCIES IN HERTZ FREQ. RATIO FREQ. RATIO FREQ. RATIO DECARBURISATION DEPTH NO. mms. TREATMENT 5 50 500 5000 1 2 3 mms. A 20 AS rolled 46.5 238 837 1460 18.0 31.4 5.12 N.D. B 20 As rolled 50.0 245 840 1465 16.8 29.3 4.90 N.D. 1 18 20mins @ 950* 49.5 244 821 1375 16.6 27.8 4.93 0.07 2 18 30min @ 950 42.5 209 701 1261 16.5 29.6 4.92 0.11 3 18 60min @ 950 41.0 208 756 1425 18.4. 34.8 5.07 0.15 4 18. ,2 120min @ 950 37.0 206 767 1448 20.7 39.1 5.57 0.18 (0 5 18. ,2 240min @ 950 37.5 223 907 1578 24.2 42.1 5.95 0.25 c 6 18. ,2 120min @1000 42.5 253 1045 1659 24.6 39.0 5.95 .30-0.35 or ■ H K1030 18 As rolled 44.5 204 673 1161 15.1 26.1 4.58 N.D. (Comparison) H sample C FREQ. RATIO Induction at 500 hertz/Induction at 5 hertz -H FREQ. RATIO Induction at 5k hertz/Induction at 5 hertz PI FREQ " . RATIO Induction at 50 hertz/Induction at 5 hertz *Sample 1 was wrapped in steel sheet ω to prevent surface oxidation The DECARBURISATION was determined by metallographic x examination PI Samples 1 - 6 were turned down to approx. 18mms PI to remove any decarburisation present on the H surface of the rounds prior to heat treatment TABLE 8 COLUMN 1 Group = N72 ROW 1 Variable 2 Name SECTION Coeff 705.0402 ROW 2 Variable 3 Name 5 HZ Coeff -τ42.0238 ROW 3 Variable 5 Name 50 HZ Coeff 16.8402 ROW 4 Variable 17 Name RATI05 Coeff 85.6796 ROW 5 Variable 18 Name RATIOll Coeff -0.7523 ROW 6 Variable 19 Name ALPHA Coeff 0.0650 ROW 7 Variable 20 Name AREA5 Coeff 335.5944 ROW 8 Variable 21 . Name ARE 500 Coeff -6.8365 ROW 9 Variable 22 Name AREACOIL Coeff 0.5511 Const = -12284.6943 COLUMN 2 Group = Iαoio ROW 1 Variable 2 Name SECTION Coeff — 704.4084 ROW 2 Variable 3 Name 5 HZ Coeff = -45.1489 ROW 3 Variable 5 Name 50 HZ Coeff = 17.9221 ROW 4 Variable 17 Name RATIOS Coeff = 86.2930 ROW 5. Variable 18 • Name RATIOll Coeff - -0.7499 ROW 6 Variable 19 Name ALPHA Coeff = 0.0645 ROW 7 Variable 20 Name AREA5 Coeff = 333.0164 ROW 8 Variable 21 Name AREA500 Coeff = -6.2416 ROW 9 Variable 22 Name AREACOIL Coeff 0.5518 Const -12387.9267 COLUMN 3 Group = WK22 ROW 1 Variable 2 Name SECTION Coeff = 714.2988 ROW 2 Variable 3 Name 5 HZ Coeff = -48.8604 ROW 3 Variable 5 Name 50 HZ Coeff = 16.9853 ROW 4 Variable 17 Name RATI05 Coeff = 91.1654 ROW 5 Variable 18 Name RATIOll Coeff = -0.9640 ROW 6 Variable 19 Name ALPHA Coeff r_ 0.0737 ROW 7 Variable 20 Name AREA5 Coeff = 318.0666 ROW 8 Variable 21 Name AREA500 Coeff = -6.1173 ROW 9 Variable 22 Name AREACOIL Coeff 0.5500 Const -12431.2314 COLUMN Group = WS1013 ROW 1 Variable 2 Name SECTION Coeff = 703.4184 ROW 2 Variable 3 Name 5 HZ Coeff = -43.5756 ROW 3 Variable 5 Name 50 HZ Coeff = 17.0363 ROW 4 Variable 17 Name RAT105 Coeff = 85.7004 ROW 5 Variable 18 Name RATIOll Coeff = -0.7541 TABLE 8 (CONTINUED) ROW 6 Variable 19 Name ALPHA Coeff = 0.0645 ROW 7 Variable 20 Name AREA5 Coeff = 327.2436 ROW 8 Variable 21 Name AREA50Q Coeff = -6.1879 ROW 9 Variable 22 Name AREACOIL Coeff = 0.5494 Const = -12240.8066 COLUMN 5 Group = WS1014 ROW 1 Variable 2 Name SECTION Coeff 703. 7175 ROW 2 Variable 3 Name 5 HZ Coeff -42.1316 ROW 3 Variable 5 Name 50 HZ Coeff 16.7537 ROW 4 Variable 17 Name RATI05 Coeff 85. 3400 ROW 5 Variable 18 ame RATIOll Coeff -0.753 ROW 6 Variable 19 Name ALPHA Coeff 0. 064 ROW 7 Variable 20 Name AREA5 Coeff 320 .126 ROW 8 Variable 21 Name AREA500 Coeff -6.392 ROW 9 Variable 22 Name AREACOIL Coeff 0.550 Const -12204. 541 COLUMN 6 Group = SF2 ROW 1 Variable 2 Name SECTION Coeff = 706.808 ROW 2 Variable 3 Name 5 HZ Coeff = -46.950 ROW 3 Variable 5 Name 50 HZ Coeff = 17.510 ROW 4 Variable 17 Name RATI05 Coeff = 88.309 ROW 5 Variable 18 Name RATIOll Coeff = -0.844 ROW 6 Variable 19 Name ALPHA Coeff = 0.067 ROW 7 Variable 20 Name AREA5 Coeff = 313.343 ROW 8 Variable 21 Name AREA500 Coeff • = -6.941 ROW 9 Variable 22 Name "AREACOIL Coeff 0.549 Const -12157.760 COLUMN 7 Group = C :S103 0 ROW 1 Variable 2 Name SECTION Coeff _s 717.461 ROW 2 Variable 3 Name 5 HZ Coeff = -43.770 ROW 3 Variable 5 Name 50 HZ Coeff = 16.309 ROW 4 Variable 17 Name RATI05 Coeff = 88.686 ROW 5 Variable 18 Name RATIOll Coeff = -0.822 ROW 6 Variable 19 Name ALPHA Coeff = 0.066 ROW 7 Variable 20 Name AREA5 Coeff = 315.324 ROW 8 Variable 21 Name AREA500 Coeff = -6.95 ROW 9 Variable 22 Name AREACOIL Coeff 0.55 Const -12352.09 SUBSTITUTE SHEET TABLE 8 (CONTINUED) COLUMN 8 Group = XK1320 ROW 1 Variable 2 Name SECTION Coeff 703.4089 ROW 2 Variable 3 Name 5 HZ Coeff -58.9975 ROW 3 Variable 5 Name 50 HZ Coeff 22.4087 ROW 4 Variable 17 Name RATI05 Coeff 93.5601 ROW 5 Variable 18 Name RATIOll Coeff -0.9344 ROW 6 Variable 19 Name ALPHA Coeff 0.0720 ROW 7 Variable 20 Name AREA5 Coeff 328.5123 ROW 8 Variable 21 Name AREA500 Coeff -8.5696 ROW 9 Variable 22 Name AREACOIL Coeff 0.5480 Const -12265.7666 COLUMN 9 Group = XK1340 ROW 1 Variable 2 Name SECTION Coeff 761.1804 ROW 2 Variable 3 Name 5 HZ Coeff -58.4867 ROW 3 Variable 5 Name 50 HZ Coeff 18.6741 ROW 4 Variable 17 Name RATIOS Coeff 97.5701 ROW 5 Variable 18 Name RATIOll Coeff -0.9801 ROW 6 Variable 19 Name ALPHA Coeff 0.0775 ROW 7 Variable 20 Name AREA5 Coeff 337.8048 ROW 8 Variable 21 Name AREA500 Coeff -9.0274 ROW 9 Variable 22 Name AREACOIL Coeff 0.5741 Const -13477.8554 COLUMN 10 Group = S1045 ROW 1 Variable 2 Name SECTION Coeff 755.3459 ROW 2 Variable 3 Name 5 HZ Coeff -47.9695 ROW 3 Variable 5 Name 50 HZ Coeff 14.4255 ROW 4 Variable 17 Name RATI05 Coeff 92.7199 ROW 5 Variable 18 Name RATIOll Coeff -0.8878 ROW 6 Variable 19 Name ALPHA Coeff 0.0725 ROW 7 Variable 20 Name AREA5 Coeff 326.5255 ROW 8 Variable 21 Name AREA500 Coeff -7.6645 ROW 9 Variable 22 Name AREACOIL Ceoff 0.5649 Const -13004.0673 COLUMN 11 Group = XK5155 ROW 1 Variable 2 Name SECTION ROW Coeff 806.0668 2 Variable 3 Name 5 HZ -57.5713 ROW Coeff 3 Variable 5 Name 50 HZ .-- ROW Coeff 16.7942 4 Variable 17 Name RATIOS 101.2814 ROW Coeff 5 Variable 18 Name RATIOll ROW Coeff -0.9883 6 Variable 19 Name ALPHA ROW Coeff 0.0777 7 Variable 20 Name AREA5 ROW Coeff 345.5113 8 Variable 21 Name AREA500 ROW Coeff -9.0901 9 Variable 22 Name AREACOIL Coeff 0.6000 Const = -14723.1298 SUBSTITUTE SHEET TABLE 8 (CONTINUED) COLUMN 12 Group - XK9261 ROW 1 Variable 2 Name SECTION Coeff = 742.841 ROW 2 Variable 3 Name 5 HZ Coeff — -83.520 ROW 3 Variable 5 Name 50 HZ Coeff — 28.880 ROW 4 Variable 17 Name RATI05 Coeff — 103.056 ROW 5 Variable 18 Name RATIOll Coeff — -1.337 ROW 6 Variable 19 Name ALPHA Coeff — 0.117 ROW 7 Variable 20 Name AREA5 Coeff — 399.504 ROW 8 Variable 21 Name AREA500 Coeff — -14.194 ROW 9 Variable 22 Name AREACOIL Coeff 0.570 Const = -14100.033 COLUMN 13 Group = WK1057 ROW 1 Variable 2 Name SECTION Coeff = 745.094 ROW 2 Variable 3 Name 5 HZ Coeff = -47.033 ROW 3 Variable 5 Name 50 HZ Coeff = 16.246 ROW 4 Variable 17 Name RATIOS Coeff = 98.745 ROW 5 Variable 18 Name RATIOll Coeff — -1.077 ROW 6 Variable 19 Name ALPHA Coeff = 0.075 ROW 7 Variable 20 Name AREA5 Coeff = 324.761 ROW 8 Variable 21 Name AREA500 Coeff = -8.851 ROW 9 Variable 22 Name AREACOIL Coeff 0.567 Const • = -13087.950 COLUMN 14 Group = WK1072 ROW 1 Variable 2 Name SECTION Coeff = 761.747 ROW 2 Variable 3 Name 5 HZ Coeff = -50.541 ROW 3 Variable 5 Name 50 HZ Coeff = 16.949 ROW 4 Variable 17 Name RATI05 Coeff - 99.632 ROW 5 Variable 18 Name RATIOll Coeff = -1.046 ROW 6 Variable 19 Name ALPHA Coeff = 0.076 ROW 7 Variable 20 Name AREA5 Coeff = 331.752 ROW 8 Variable 21 Name AREAS00 Coeff = -9.218 ROW 9 Variable 22 Name AREACOIL Coeff = 0.578 Const = -13573.817 COLUMN 15 Group = WK1082 ROW 1 Variable 2 Name SECTION Coeff __ 763.970 ROW 2 Variable 3 Name 5 HZ Coeff = -51.227 ROW 3 Variable 5 Name 50 HZ Coeff — 17.061 ROW 4 Variable 17 Name RATIOS Coeff — 97.811 ROW 5 Variable 18 Name RATIOll Coeff = -0.984 ROW 6 Variable 19 Name ALPHA Coeff = 0.073 ROW 7 Variable 20 Name AREAS Coeff = 328.055 ROW 8 Variable 21 Name AREA500 Coeff = -8.876 ROW 9 Variable 22 Name AREACOIL Coeff 0.580 Const -13626.978 flute ■ SHS** sυβsτ TABLE 9 N72 R1010 ' WK22 WS1013 WS1014 SF2 CS103C No Variable Value 2 SECTION 5.500 3877.722 3874.247 3928.644 3868.802 3870.447 3877.449 3946.035 3 5 HZ S.160 -216.843 -232.968 -252.120 -224.850 -217.399 -242.265 -225.858 5 50 HZ 37.918 638.547 679.572 644.049 645.983 635.267 663.978, 618.428 17 RATIOS 11.219 961.199 968.080 1022.742 961.432 957.389 990.703 994.936 18 RATIOll 9.884 -7.436 -7.412 -9.528 -7.454 -7.445 -8.345 -8.131 19 ALPHA 6529.901 424.574 421.766 481.841 421.766 420.264 440.703 431.431 20 AREA5 5.160 1731.667 1718.365 1641.224 1688.577 1651.854 1616.852 1627.076 21 AREA500 105.864 -723.747 -660.766 -647.606 -655.078 -676.786 -734.851 -736.309 22 AREACOIL 32050.000 17664.037 17686.150 17628.781 17609.553 17643.846 17604.104 17752.816 Constant -12284.694 -12387.927 -12431.231 -12240.807 -12204.541 -12157.761 -12352.096 Equation Totals 12065.026 12059.106 12006.796 12067.924 12072.895 12060.567 12048.328 XK1320 XK1340 S1045 XK5155 XK9261 WK1057 WK1072 WK1082 No Variable Value 2 SECTION S.500 3868.749 4186.492 4154.403 4433.368 4085.627 4098.021 3 5 HZ 4189 .608 4201.836 5.160 -304.427 -310.791 -247.523 -297.068 -430.967 -242.694 5 SO HZ -260.792 -264.334 37.918 849.693 708.087 546.989 636.804 1095.081 616.041 642.710 17 RATI05 646.946 11.219 1049.606 1094.593 1040.181 1136.228 1156.143 1107.781 1117.727 1097.296 18 RATIOll 9.884 -9.236 -9.687 -8.775 -9.769 -13.217 -10.646 -10.342 -9.726 19 ALPHA 6529.901 470.545 506.133 473.679 507.830 764.521 492.550 20 ARBA5 ! 499.015 483.017 S.160 1695.124 1743.073 1684.872 1782.839 21 AREA500 2061.446 1675.767 1711.841 1692.764 105.864 -907.219 2 -955.678 -811.402 -962.320 -1502.671 -937.066 α 22 AREACOIL -975.946 -939.724 32050.000 17565.322 18400.545 18107.930 19232.244 18276.512 18202.477 18541.566 18616.564 ca Constant', -12265.767 -13477.855 -13004.067 -14723.130 -14100.033 -13087.950 -13573.817 -13626.979 Equation Totals 12012.392 11893.910 11936.286 11737.028 11392.441 11914.282 11881.571 11897.660 m o Pl r, v.i - 35 - «4 TABLE 10 ϊ*i N72 R1010 WK22 WS1013 WS1014 SF2 CS1030 φ No Variable Value 2 SECTION 10.000 7050.403 7044.084 7142.988 7034.185 7037.176 7068.088 7174.610 3 5 HZ 16.802 -706.084 -758.592 -820.953 -732.159 -707.896 -788.864 -735.440 ψϊ 5 50 HZ 73.032 1229.874 1308.890 1240.472 1244.196 1223.556 1278.855 1191.124 «« 17 RATIOS 8.399 719.661 724.813 765.739 719.836 • 716.809 741.751 744.921 18 RATIOll 1.964 -1.478 -1.473 -1.893 -1.481 -1.479 -1.658 -1.616 19 ALPHA 7837.768 509.612 506.241 578.349 506.241 504.439 528.971 517.841 20 AREA5 4.874 1635.786 1623.220 1550.350 1595.082 1560.392 1527.328 1536.986 21 AREAS00 120.205 -821.790 -750.277 -735.334 -743.818 -768.467 -834.399 -836.054 22 AREACOIL 26912.727 14832.681 14851.250 14803.076 14786.929 14815.725 14782.353 14907.229 Constant -12284.694 -12387.927 -12431.231 -12240.807 -12204.541 -12157.761 -12352.098 Equation Totals 12163.972 12160.231 12091.563 12168.203 12175.711 12144.665 12147.504 XK1320 XK1340 S1045 XK5155 XK9261 WK1057 WK1072 WK1082 No Variable Value 2 SECTION 10.000 7034.089 7611.804 7553.459 8060.669 7428.413 7450.949 7617.470 7639.703 3 5 HZ 16.802 -991.277 -982.694 -805.985 -967.314 -1403.316 -790.259 -849.191 -860.726 5 50 HZ 73.032 1636.553 1363.811 1053.529 1226.518 2109.181 1186.527 1237.892 1246.050 17 RATIOS 8.399 785.853 819.535 778.796 850.708 865.618 829.409 836.856 821.559 18 RATIOll 1.964 -1.835 -1.925 -1.744 -1.941 -2.626 -2.116 f 2.055 -1.933 19 ALPHA 7837.768 564.789 607.505 568.552 609.543 917.646 591.203 598.962 579.760 20 ARE 5 4.874 1601.266 1646.560 1591.581 1684.124 1947.304 1582.981 1617.057 1599.037 21 AREA500 120.205 -1030.116 -1085.140 -921.320 -1092.682 -1706.231 -1064.007 -1108.153 -1057.025 22 AREACOIL 26912.727 14749.789 15451.134 15205.421 16149.520 15346.981 15284.813 15569.551 15632.526 Constant -12265.767 -13477.855 -13004.067 -14723.130 -14100.033 -13087.950 -13573.817 -13626.979 Equation Totals 12083.345 11952.736 12018.222 11796.015 11402.938 11981.552 11944.573 11961.973 - 36 - . TABLE 11 N72 R1010 WK22 WS1013 WS1014 SF2 CS1030 No Variable Value 2 SECTION 10.000 7050.403 7044.084 7142.988 7034.185 7037.176 7068.088 7174.610 3 5 HZ 3.763 -158.136 -169.895 -183.862 -163.975 -158.542 -176.675 -164.710 5 50 HZ 35.462 597.188 635.555 602.333 604.142 594.120 620.971 578.372 17 RATIOS 15.409 1320.244 1329.696 1404.776 1320.564 1315.011 1360.769 1366.584 18 RATIOll 22.323 -16.793 -16.740 -21.520 -16.835 -16.815 -18.848 -18.364 19 ALPHA ' 8176.804 S31.656 528.140 603.366 528.140 526.259 551.852 540.241 ω 20 ARE 5 1.092 366.353 363.539 347.219 357.237 349.468 342.063 344.226 c 21 AREA500 60.184 -411.453 -375.648 -368.166 -372.414 -384.756 -417.766 -418.595 ro 22 AREACOIL 29603.637 16315.749 16336.175 16283.185 16265.423 16297.098 16260.389 16397.750 ω H Constant -12284.694 -12387.927 -12431.231 -12240.807 -12204.541 -12157.761 -12352.098 Equation Totals 13310.517 13286.979 13379.089 13315.660 13354.479 13433.083 13448.016 c -I PI XK1320 XK1340 S1045 XK5155 XK9261 WK1057 WK1072 WK1082 No Variable Value x n 2 SECTION . 10.000 7034.089 7611 .804 7553.459 8060.669 7428.413 7450.949 7617.470 7639. 703 3 5 HZ 3.763 -222.008 -220.086 -180.510 -216.641 -314.289 -176.988 -190.186 -192. 770 5 50 HZ 35.462 794.658 662.223 511.560 595.558 1024.151 576.139 601.081 605.042 17 RATI05 15.409 1441.675 1503.465 1428.729 1560.654 1588.007 1521.580 1535.242 1507.178 18RATI011 22.323 -20.860 -21.879 -19.820 -22.063 -29.850 -24.045 -23.357 -21.966 19 ALPHA 8176.804 589.220 633.784 593.145 635.910 957.340 616.776 624.871 604.838 20 AREA5 1.092 358.622 368.766 356.453 377.179 436.121 354.527 362.159 358.123 21 AREA500 60.184 -515.758 -543.307 -461.286 -547.083 -854.274 -532.726 -554. 829 -534.237 22 AREACOIL 29603.637 16224.569 16996.039 16725.758 17764.254 16881.473 16813.090 17126.297 17195.568 Constant -12265.767 -13477.855 -13004.067 -14723.130 -14100.033 -13087.950 -13573. 817 -13626.979 Equation Totals 13418.442 13512.955 13503.425 13485.308 13017.059 13511.354 13524.931 13534.500

Claims: CLAIMS 1. A method of classifying a steel specimen . comprising: presenting the specimen to a coil means having a primary winding and a secondary winding such that the specimen contributes to an inductive coupling between the primary winding and the secondary winding; applying an excitation current to the primary winding at each of a plurality of excitation frequencies whereby to induce in the secondary winding for each excitation frequency a signal indicative of an induction value of the specimen; and determining a grade classification of the specimen dependent on the induction values obtained at said excitation frequencies. 2. A method as claimed in Claim 1, wherein the specimen is positioned so as to extend into both windings. 3. A method as claimed in Claim 2, wherein the primary and secondary windings of the coil means are generally co-axial. 4. A method as claimed in Claim 1, wherein the primary and secondary windings of the coil means are disposed about a coupling member defining a coupling gap and the specimen is positioned so as to provide an inductive coupling across said gap. 5. A method as claimed in any one of the preceding claims, wherein the critical frequencies at which signals induced in the secondary winding are exactly out of phase with the excitation current are also determined and the determination of the grade classification is also dependent on those critical frequencies. 6. A method as claimed in any one of the preceding claims, wherein the grade classification is determined according to the value of a discriminant function of the form aα+bβ+cγ+ where α, 8, γ, are attributes of the specimen comprising said induction values and a,b,c are coefficients reflecting the degree to which the respective attributes are effective to discriminate between steel grades. 7. A method as claimed in any one of Claims 1 to 5, wherein the grade classification is determined by deriving for each of a plurality of possible grades the value of a discriminant function of the form aα+bg+cγf where <_v β, γ, ....;.. are attributes of the specimen comprising said induction values and a,b,c are predetermined coefficients reflecting fehe degree to which the respective attributes are effective to discriminate that possible steel grade from the others and determining which of the possible grades correlates with a maximum discriminant function value. 8. A method as claimed in Claim 7, wherein said coefficients are predetermined by measuring the values of said attributes in a set of steel samples of all the possible grades. 9. _ A method as claimed in Claim 7 or Claim 8, wherein the critical frequencies at which signals induced in the secondary windings are exactly out of phase with the excitation current are also determined and said attributes also comprise said critical frequencies. 10. Apparatus for classifying steel specimens, comprising: coil means having a primary winding and a secondary winding to be inductively coupled via a steel specimen to be classified; excitation means for applying an excitation current to the primary winding at each of a plurality of excitation frequencies whereby to induce in the secondary winding for each frequency an output signal indicative of an induction value of the specimen; and signal processing means to receive the output signals indicative of the induction values at said frequencies and to determine a grade classification of the specimen dependent on those values. 11. Apparatus as claimed in Claim 10, wherein the primary and secondary windings are generally co-axial and arranged so that a specimen to be classified may be extended into both windings. 12. Apparatus as claimed in Claim 11, wherein the primary and secondary windings are disposed about a coupling member defining a coupling gap to be bridged by a specimen to be classified. 13. Apparatus as claimed in any one of Claims 10 to 12, wherein the signal processing means is operative to derive for each of a plurality of possible grades the value of a discriminant function of the form aα+bβ+cγ+ where α, β, γ are attributes of the specimen comprising said induction values and a,b,c are predetermined coefficents reflecting the degree to which the respective attributes are effective to discriminate that possible steel grade from the others and to determine which of the possible grades correlates with a maximum discriminant function value. Ϊ4. Apparatus as claimed in Claim 13, wherein the signal processing means is able to determine and store values of said coefficients for each of the possible steel grades on presentation to the apparatus of a set of steel samples of all the possible grades.

Inventors: KEMLO KENNETH GARRY, KEMLO, KENNETH, GARRY
Applicants: BROKEN HILL PTY CO LTD, THE BROKEN HILL PROPRIETARY COMPANY LIMITED
Application year: 1986
Main classification: G01N27
IPC codes: G01N27, G01N33