INTRODUCTION
Austenitic stainless steels are widely used as structural materials in power, chemical, petrochemical, nuclear and other industries, because of high level of fabricability and excellent corrosion resistance. In these steels, due to plastic deformation or working, the unstable austenite transforms to martensite in a diffusionless manner. In case of operating components made of austenetic stainless steels, e.g. AISI type 304, AISI type 316, local plastic deformation associated with fatigue damage in components operating at room temperature (300K) and below may lead to precipitation of martensite. Detection and characterisation of small amounts of martensite in such steels is very useful for early detection of fatigue damage and hence for evaluation of in-service degradation
X-ray diffraction is used for quantification of martensite. Since marteniste is a magnetic phase in a non-magnetic austenite matrix, it is possible to exploit the magnetic methods of NDE for characterisation of martensite. A few such methods reported in the literature include eddy current test, hystetisis, and equivalent delta-ferrite based Ferritescope method [1, 2]. Superconducting QUantum Interference Device (SQUID) is an ultrasensitivie magnetic sensor, which typically has resolution of 10-14 T [3]. In recent years, SQUID sensors have formed the basis for several new magnetic non-destructive evaluation (NDE) methods and these methods have been applied to variety of applications [4-10]. Similarly, MBN methods are being increasingly applied for characterisation of microstructures in a variety of materials [2]. We have applied SQUID and MBN methods for characterisaiton of martensite in cold worked AISI type 304 stainless steel. This paper describes the details of the experimental set up developed and discusses the results of characterisation of marteniste. The sensitivity of the SQUID method is compared with MBN, delta ferrite, eddy current, and hysterisis methods. For the benefit of readers in NDE, detailed descriptions of operating principles of SQUIDs, different SQUID systems and interesting applications of SQUIDS to NDE are also given in the paper.
SUPER CONDUCTING QUANTUM INTERFERENCE DEVICE (SQUID)
Superconductivity
Superconductivity is a unique thermodynamic state characterised by the condensation of the conduction electrons into pairs featuring opposite momentum and spin (Copper spins) [3]. At absolute temperature (0K) all the conduction electrons of the superconducting material are condensed into these pairs. At elevated temperatures, an increasing number of excitations occur (pair breaking), leading to a number of phi-0;quasi-particles; (electrons with a missing counterpart) in addition to the pair condensate. At a critical temperature Tc, all pairs break and superconductivity ceases. Tc values of some important materials are given in Table-I.
Table-I Important superconducting materials
SQUID Principles
A SQUID essentially consists of a superconducting ring (in practice any shape, provided that the superconducting material completely surrounds a void) interrupted at one or two positions by a Josephson junction. The operation of SQUID sensor is based on two effects namely flux quantisation and Josephsen effects, observable only in the presence of superconductivity; Flux quantisation dictates that the flux inside the SQUID ring due to an external magnetic field can not change continuously, but only in multiples of , the flux quantum (phi-0= h/2e = 2.7 x 10-15 Tesla/m2). The Josephsoneffect states that a superconducting current can cross the Josephson junction, which consists of a weak link between two superconductors, up to a limit known as the critical current. These properties cause the SQUID impedance, measured after inductively coupling to arf current bias, to be a periodic function of the magnetic flux threading the SQUID. The net result is that the SQUID works as a flux-to-voltage converter with unparalleled sensitivity [4]. SQUID is the most sensitive magnetic sensor to date. It can detect changes in magnetic field of several femtotesla (10-15T).
SQUIDs with one junction are called rfSQUIDs and those with two junctions are called DC SQUIDs, because of different types of electronic read-out commonly used. Generally to reduce the influence of magnetic signals from unwanted sources, the SQUID itself is placed inside a superconducting shield, while the signal of interest is transformer-coupled to the SQUID through a small opening in the shield. If the SQUID is unshielded or if there is only a simple pick-up coil for the section of the transformer outside the shield, then the SQUID gives a measure of the magnetic field, and functions as a magnetometer. If more complex external coil structures are used, such as two axial coils wound in opposite directions and separated by a distance relatively large compared to the distance of one of the coils to the signal source, then the system functions as a magnetic gradiometer. This gradiometer coil configuration effectively serves to nullify a uniform background without having much influence on the signal from the nearby source of interest [5]. The pickup coil configurations for magnetometer and gradiometer are shown in Fig.1(a). In order to compensate for the electromagnetic disturbances from surroundings, second order gradiometers are used. Figure 1(b) illustrates how the pickup coil loops are flux transformer coupled to the SQUID loops.
SQUIDs were first developed using low temperature superconductivity (LTS) materials in the 1960s and became available commercially in the early1970s as relatively crude Nd devices with single Josephson junctions formed by a mechanical point contact between a screw and bulk material. The reliability of this design was limited and in the early 1980s thin film devices fabricated with microelectronic film deposition and photolithographic patterning processes superseded it. The technology of superconducting devices was advanced in 1986 by the discovery of the high temperature superconductivity (HTS) materials, principally YBa2Cu3O7-x which superconductsupto 92K. Through this is still a low temperature in everyday terms, the ability to use liquid nitrogen for cooling led to the belief that many previously impractical applications, including NDE, would become practical. Significant progress has been made by many industrial and academic groups to realise simple, portable HTS SQUID systems for NDE research.
SQUID Configurations and Systems
Most commercial SQUID systems have high sensitivity from DC to 10 kHz. They have a linear response and a wide dynamic range. When used with gradiometer pick-up coils, they can easily reject distant magnetic noise sources or ambient background magnetic fields. Typical sensitivities for LTS commercial SQUIDs above 1 Hz are in the range of 1-10 fT, while HTS commercial SQUIDs are limited to the range of 30-300 fT. Nevertheless, even HTS SQUIDs are more sensitive than any other magnetic sensor technology. Relatively simple fluxgate magnetometers have sensitivities in the range of 1 nanotesla (10-9T) - 1 picotesla (110-12T). If the magnetic signal to be monitored is sufficiently large, high sensitivity systems are not required. Detection of a localised defect using a SQUID pick up coil is approximately limited by the a) diameter of the pick-up coil and b) lift-off between the coil and the signal source. Here, the lower HTS stand-offs as compared to those of LTS, compensate for the lower sensitivity of HTS SQUIDs. The most important drawback of SQUIDs is that they work only at low temperatures; -269 deg. C for LTS alloys and 197 deg. C for HTS ceramics.
SQUID Applications in NDE
For aircraft NDE, while ECT methods are among the better techniques available, they are not effective beyond a depth of a few millimeters. However, using multi-sensor LTS SQUIDs detection of simulated cracks and corrosion damage in hidden layers has been demonstrated [5, 6, 8]. By raster scan imaging of the SQUID gradiometer over the object surface, an electromagentic microscope has been realised and scans of aircraft fuselage and wheels have been produced to demonstrate the advantages of SQUID over conventional NDE techniques [5]. LTS SQUID systems are not well suited for practical use because of the sophisticated and expensive cryogenics involving liquid He. Further the SQUID systems have to be mobile and capable of operating without any magnetic shielding e.g. in aircraft maintenance hangers where the level of electromagnetic disturbances is very high (up to the micro-Tesla range).
With the availability of high temperature superconductivity (HTS) materials, new avenues have been opened up for SQUID sensors and they are being used in a variety of NDE applications [4-10]. Some of them include detection of defects in carbon steels [7] and aluminium alloys [5, 8], detection of buried steel pipelines, detection of gross flaws in sub-sea steels structures, and fatigue damage assessment in austenitic stainless steel [9]. Because steel provides its own ferromagnetic signal, or is easily magnetised, SQUIDs make excellent detectors of discontinuities in steels. Remote detection of defects in stainless steel pipe walls in chemical industry and in nuclear rectors is possible by using SQUIDs. Similarly, measurement of magnetic field at the surface of a stressed steel structure provides a very sensitive information of microscopic mechanical behaviour, which is generally not observed via traditional stress strain measurements [6]. SQUIDs are being explored for early detection of defects or microstructural degradations in civil and military aircraft. There are continuous attempts to find a niche for NDE SQUID applications.
MAGNETIC BARKHAUSEN NOISE (MBN) METHOD
Magnetic flux perturbation occurs when an induced magnetic field in ferromagnetic materials is swept in a hysteresis loop and as a result what are known as Barkhausen noise emissions are produced. These are due to the result of discrete changes in magnetisation caused mainly by the irreversible motion of the 180° domain walls during the sweeping of the magnetic field. NDE method that involves measurement of these perturbations for characterisation of materials is known as Magnetic Barkhausen Noise (MBN) method. The perturbations are measured by using a pick up coil and analysed as MBN signals. The nucleation and movement of magnetic domain walls directly depends on various microstructural features such as cavities, grain boundaries, precipitates, cracks etc. MBN parameters such as Mmax(the maximum value of MBN signal generated during a hysteresis cycle), Hcm(the magnetic field at which the maximum MBN occurs), number of signal counts, and rms voltage of MBN signal have been used to characterise these microstructural features. Typical successful applications of MBN method include microstructural characterisation, characterisation of post weld heat treatment in weld joints, assessment of creep and fatigue damage, and measurement of residual stresses. A more detailed description of the MBN method and its applications can be found elsewhere.
EXPERIMENTAL SET UP
Arf-HTS SQUID magnetometer system shown in Fig.2 has been used in the present study. The SQUID is made of YBa2Cu3O7-x or 1-2-3 compound. Liquid Nitrogen is used as coolant for maintaining temperature. This SQUID system has sensitivity better than 5 x 10-15 Tesla/ÖHz at 1 Hz. Because of very high sensitivity, SQUID is not used directly to measure the magnetic fields. Rather, it is encapsulated in a superconducting shield, with the magnetic signal coupled to it by a flux transformer [10]. The flux transformer consists of a primary (magnetometer) coil placed nearer to the measurement position and a secondary (input) coil coupled to the SQUID, inside the shield, as shown in Fig. 1 (b). Scanning is performed so that external magnetic field from the specimens induces voltage in the primary coil and the current in the primary coil generates a magnetic field in the SQUID through the input coil. The SQUID output in multiples of phi-0 is digitised and stored in the computer. Software written in Labview; is used for controlling the scanner as well as the data acquisition. This software also consists of provision for filtering to remove background noise and to process the acquired signals. During measurements using SQUIDs, proper magnetic shielding is ensured to avoid the background field pick-up, which many a times buries the magnetic field produced by the desired variables in specimens, e.g. martensite in austenitic stainless steel. Averaging has been performed on the SQUID data to enhance the signal-to-noise by approximately three times.
For MBN experimental studies 3MA system developed by IZFP has been used.MBN measurements have been made using sinusoidal magnetic field varying between + 50 A/cm at 15 Hz. A surface pick-up coil having a 2 mm diameter ferrite core wound with 3500 turns of 220 micron wire has been used to receive the MBN signal and a Hall probe integrated into the pick-up sensor has been used to measure the applied magnetic field. Low noise pre-amplifier with band-pass filter has been employed for better signal-to-noise ratio. The MBN signals have been digitised and stored in a computer for the evaluation of maximum amplitude, Mmax.
RESULTS AND DISCUSSION
Typical SQUID output from a 20% cold worked specimen as a function of scanning distance along rolling plane after averaging is shown in shown in Fig. 3. The pick up coil scan speed is 30 cm/s. The SQUID output of the 40% cold worked specimen at different scanning speeds is shown in Fig.4. As expected, the SQUID output is found to increase linearly with scanning speed. In order to detect very small changes in magnetic field arising from martensite, the maximum possible speed of 40 cm/s speed has been chosen for all further investigations. The SQUID output as a function of cold work is shown in Fig.5. It can be seen from Fig.5 that there is a monotonic increase in the SQUID output with the cold work i.e. with increase in volume fraction of martensite of SQUID. When fitted logarithmically, a correlation coefficient of 0.994 has been observed. Typical MBN signals from different cold worked specimens are shown in Fig.6. The peak MBN signal amplitude is plotted as a function of cold work in Fig.7. As can be observed in Fig. 7, with increasing cold work, the peak amplitude of MBN signal is found to increase.
In order to compare the sensitivity of SQUID and MBN method, experiments have been carried out using other NDT methods, namely X-ray diffraction, d-ferrite, eddy current, and hysteresis methods. In the specimens with higher cold work i.e. large volume fraction of martensite, the SQUID and MBN measurements are found to be in good agreement with X-ray diffraction, d-ferrite, eddy current, and hysteresis methods. However, the detection sensitivities are different for smaller volume fraction of martensite. SQUIDs and MBN methods have been able to successfully detect martensite in even 10% cold work specimen. However, the detection sensitivity of d-ferrite, eddy current, and hysteresis methods has been found to be relatively poor. While the lower detection limit for d-ferrite and hysteresis methods has been found to 30%, the limit for eddy current testing and X-ray diffraction method has been noted to be 20%. The SQUID and MBN outputs in rolling and transverse planes have been investigated and they have been found to be different, but confirming to the earlier observation [1, 11]. The SQUID and MBN outputs have been found to relatively high along transverse plane as compared to rolling plane. This difference in behaviour is attributed to the orientation relationship between the easy magnetisation direction, [100] of the martensite and the direction of the applied magnetic field.
The above studies clearly demonstrate the superior detection performance of SQUID and MBN methods over X-ray diffraction, d-ferrite, eddy current, and hysteresis methods for the characterisation of martensite. Further, on a comparative note, SQUID method has been noted to score over MBN method for two reasons viz. depth of interrogation and lift-off. Unlike MBN, SQUID has capability to detect very-weak magnetic fields emerging from a deep or buried source and to readily tolerate lift-offs of a few centimetres, thus offers a great potential for diverse applications.
CONCLUSION
SQUID and MBN methods have been developed for characterisation of martensite in cold worked AISI type 304 stainless steel specimens. SQUID and MBN outputs have monotonically increased with cold work i.e. volume fraction of martensite. Martensite in specimens cold worked to 10% has been unambiguously detected by these methods. This detection sensitivity has been demonstrated to be superior to other NDE methods such as X-ray diffraction, equivalent d-ferrite, hysterisis, and eddy current test methods. These studies clearly bring out the potential for using SQUID and MBN methods for early detection of fatigue damage by way of non-destructive characterisation of strain induced martensite.
X-ray diffraction is used for quantification of martensite. Since marteniste is a magnetic phase in a non-magnetic austenite matrix, it is possible to exploit the magnetic methods of NDE for characterisation of martensite. A few such methods reported in the literature include eddy current test, hystetisis, and equivalent delta-ferrite based Ferritescope method [1, 2]. Superconducting QUantum Interference Device (SQUID) is an ultrasensitivie magnetic sensor, which typically has resolution of 10-14 T [3]. In recent years, SQUID sensors have formed the basis for several new magnetic non-destructive evaluation (NDE) methods and these methods have been applied to variety of applications [4-10]. Similarly, MBN methods are being increasingly applied for characterisation of microstructures in a variety of materials [2]. We have applied SQUID and MBN methods for characterisaiton of martensite in cold worked AISI type 304 stainless steel. This paper describes the details of the experimental set up developed and discusses the results of characterisation of marteniste. The sensitivity of the SQUID method is compared with MBN, delta ferrite, eddy current, and hysterisis methods. For the benefit of readers in NDE, detailed descriptions of operating principles of SQUIDs, different SQUID systems and interesting applications of SQUIDS to NDE are also given in the paper.
SUPER CONDUCTING QUANTUM INTERFERENCE DEVICE (SQUID)
Superconductivity
Superconductivity is a unique thermodynamic state characterised by the condensation of the conduction electrons into pairs featuring opposite momentum and spin (Copper spins) [3]. At absolute temperature (0K) all the conduction electrons of the superconducting material are condensed into these pairs. At elevated temperatures, an increasing number of excitations occur (pair breaking), leading to a number of phi-0;quasi-particles; (electrons with a missing counterpart) in addition to the pair condensate. At a critical temperature Tc, all pairs break and superconductivity ceases. Tc values of some important materials are given in Table-I.
Table-I Important superconducting materials
SQUID Principles
A SQUID essentially consists of a superconducting ring (in practice any shape, provided that the superconducting material completely surrounds a void) interrupted at one or two positions by a Josephson junction. The operation of SQUID sensor is based on two effects namely flux quantisation and Josephsen effects, observable only in the presence of superconductivity; Flux quantisation dictates that the flux inside the SQUID ring due to an external magnetic field can not change continuously, but only in multiples of , the flux quantum (phi-0= h/2e = 2.7 x 10-15 Tesla/m2). The Josephsoneffect states that a superconducting current can cross the Josephson junction, which consists of a weak link between two superconductors, up to a limit known as the critical current. These properties cause the SQUID impedance, measured after inductively coupling to arf current bias, to be a periodic function of the magnetic flux threading the SQUID. The net result is that the SQUID works as a flux-to-voltage converter with unparalleled sensitivity [4]. SQUID is the most sensitive magnetic sensor to date. It can detect changes in magnetic field of several femtotesla (10-15T).
SQUIDs with one junction are called rfSQUIDs and those with two junctions are called DC SQUIDs, because of different types of electronic read-out commonly used. Generally to reduce the influence of magnetic signals from unwanted sources, the SQUID itself is placed inside a superconducting shield, while the signal of interest is transformer-coupled to the SQUID through a small opening in the shield. If the SQUID is unshielded or if there is only a simple pick-up coil for the section of the transformer outside the shield, then the SQUID gives a measure of the magnetic field, and functions as a magnetometer. If more complex external coil structures are used, such as two axial coils wound in opposite directions and separated by a distance relatively large compared to the distance of one of the coils to the signal source, then the system functions as a magnetic gradiometer. This gradiometer coil configuration effectively serves to nullify a uniform background without having much influence on the signal from the nearby source of interest [5]. The pickup coil configurations for magnetometer and gradiometer are shown in Fig.1(a). In order to compensate for the electromagnetic disturbances from surroundings, second order gradiometers are used. Figure 1(b) illustrates how the pickup coil loops are flux transformer coupled to the SQUID loops.
SQUIDs were first developed using low temperature superconductivity (LTS) materials in the 1960s and became available commercially in the early1970s as relatively crude Nd devices with single Josephson junctions formed by a mechanical point contact between a screw and bulk material. The reliability of this design was limited and in the early 1980s thin film devices fabricated with microelectronic film deposition and photolithographic patterning processes superseded it. The technology of superconducting devices was advanced in 1986 by the discovery of the high temperature superconductivity (HTS) materials, principally YBa2Cu3O7-x which superconductsupto 92K. Through this is still a low temperature in everyday terms, the ability to use liquid nitrogen for cooling led to the belief that many previously impractical applications, including NDE, would become practical. Significant progress has been made by many industrial and academic groups to realise simple, portable HTS SQUID systems for NDE research.
SQUID Configurations and Systems
Most commercial SQUID systems have high sensitivity from DC to 10 kHz. They have a linear response and a wide dynamic range. When used with gradiometer pick-up coils, they can easily reject distant magnetic noise sources or ambient background magnetic fields. Typical sensitivities for LTS commercial SQUIDs above 1 Hz are in the range of 1-10 fT, while HTS commercial SQUIDs are limited to the range of 30-300 fT. Nevertheless, even HTS SQUIDs are more sensitive than any other magnetic sensor technology. Relatively simple fluxgate magnetometers have sensitivities in the range of 1 nanotesla (10-9T) - 1 picotesla (110-12T). If the magnetic signal to be monitored is sufficiently large, high sensitivity systems are not required. Detection of a localised defect using a SQUID pick up coil is approximately limited by the a) diameter of the pick-up coil and b) lift-off between the coil and the signal source. Here, the lower HTS stand-offs as compared to those of LTS, compensate for the lower sensitivity of HTS SQUIDs. The most important drawback of SQUIDs is that they work only at low temperatures; -269 deg. C for LTS alloys and 197 deg. C for HTS ceramics.
SQUID Applications in NDE
For aircraft NDE, while ECT methods are among the better techniques available, they are not effective beyond a depth of a few millimeters. However, using multi-sensor LTS SQUIDs detection of simulated cracks and corrosion damage in hidden layers has been demonstrated [5, 6, 8]. By raster scan imaging of the SQUID gradiometer over the object surface, an electromagentic microscope has been realised and scans of aircraft fuselage and wheels have been produced to demonstrate the advantages of SQUID over conventional NDE techniques [5]. LTS SQUID systems are not well suited for practical use because of the sophisticated and expensive cryogenics involving liquid He. Further the SQUID systems have to be mobile and capable of operating without any magnetic shielding e.g. in aircraft maintenance hangers where the level of electromagnetic disturbances is very high (up to the micro-Tesla range).
With the availability of high temperature superconductivity (HTS) materials, new avenues have been opened up for SQUID sensors and they are being used in a variety of NDE applications [4-10]. Some of them include detection of defects in carbon steels [7] and aluminium alloys [5, 8], detection of buried steel pipelines, detection of gross flaws in sub-sea steels structures, and fatigue damage assessment in austenitic stainless steel [9]. Because steel provides its own ferromagnetic signal, or is easily magnetised, SQUIDs make excellent detectors of discontinuities in steels. Remote detection of defects in stainless steel pipe walls in chemical industry and in nuclear rectors is possible by using SQUIDs. Similarly, measurement of magnetic field at the surface of a stressed steel structure provides a very sensitive information of microscopic mechanical behaviour, which is generally not observed via traditional stress strain measurements [6]. SQUIDs are being explored for early detection of defects or microstructural degradations in civil and military aircraft. There are continuous attempts to find a niche for NDE SQUID applications.
MAGNETIC BARKHAUSEN NOISE (MBN) METHOD
Magnetic flux perturbation occurs when an induced magnetic field in ferromagnetic materials is swept in a hysteresis loop and as a result what are known as Barkhausen noise emissions are produced. These are due to the result of discrete changes in magnetisation caused mainly by the irreversible motion of the 180° domain walls during the sweeping of the magnetic field. NDE method that involves measurement of these perturbations for characterisation of materials is known as Magnetic Barkhausen Noise (MBN) method. The perturbations are measured by using a pick up coil and analysed as MBN signals. The nucleation and movement of magnetic domain walls directly depends on various microstructural features such as cavities, grain boundaries, precipitates, cracks etc. MBN parameters such as Mmax(the maximum value of MBN signal generated during a hysteresis cycle), Hcm(the magnetic field at which the maximum MBN occurs), number of signal counts, and rms voltage of MBN signal have been used to characterise these microstructural features. Typical successful applications of MBN method include microstructural characterisation, characterisation of post weld heat treatment in weld joints, assessment of creep and fatigue damage, and measurement of residual stresses. A more detailed description of the MBN method and its applications can be found elsewhere.
EXPERIMENTAL SET UP
Arf-HTS SQUID magnetometer system shown in Fig.2 has been used in the present study. The SQUID is made of YBa2Cu3O7-x or 1-2-3 compound. Liquid Nitrogen is used as coolant for maintaining temperature. This SQUID system has sensitivity better than 5 x 10-15 Tesla/ÖHz at 1 Hz. Because of very high sensitivity, SQUID is not used directly to measure the magnetic fields. Rather, it is encapsulated in a superconducting shield, with the magnetic signal coupled to it by a flux transformer [10]. The flux transformer consists of a primary (magnetometer) coil placed nearer to the measurement position and a secondary (input) coil coupled to the SQUID, inside the shield, as shown in Fig. 1 (b). Scanning is performed so that external magnetic field from the specimens induces voltage in the primary coil and the current in the primary coil generates a magnetic field in the SQUID through the input coil. The SQUID output in multiples of phi-0 is digitised and stored in the computer. Software written in Labview; is used for controlling the scanner as well as the data acquisition. This software also consists of provision for filtering to remove background noise and to process the acquired signals. During measurements using SQUIDs, proper magnetic shielding is ensured to avoid the background field pick-up, which many a times buries the magnetic field produced by the desired variables in specimens, e.g. martensite in austenitic stainless steel. Averaging has been performed on the SQUID data to enhance the signal-to-noise by approximately three times.
For MBN experimental studies 3MA system developed by IZFP has been used.MBN measurements have been made using sinusoidal magnetic field varying between + 50 A/cm at 15 Hz. A surface pick-up coil having a 2 mm diameter ferrite core wound with 3500 turns of 220 micron wire has been used to receive the MBN signal and a Hall probe integrated into the pick-up sensor has been used to measure the applied magnetic field. Low noise pre-amplifier with band-pass filter has been employed for better signal-to-noise ratio. The MBN signals have been digitised and stored in a computer for the evaluation of maximum amplitude, Mmax.
RESULTS AND DISCUSSION
Typical SQUID output from a 20% cold worked specimen as a function of scanning distance along rolling plane after averaging is shown in shown in Fig. 3. The pick up coil scan speed is 30 cm/s. The SQUID output of the 40% cold worked specimen at different scanning speeds is shown in Fig.4. As expected, the SQUID output is found to increase linearly with scanning speed. In order to detect very small changes in magnetic field arising from martensite, the maximum possible speed of 40 cm/s speed has been chosen for all further investigations. The SQUID output as a function of cold work is shown in Fig.5. It can be seen from Fig.5 that there is a monotonic increase in the SQUID output with the cold work i.e. with increase in volume fraction of martensite of SQUID. When fitted logarithmically, a correlation coefficient of 0.994 has been observed. Typical MBN signals from different cold worked specimens are shown in Fig.6. The peak MBN signal amplitude is plotted as a function of cold work in Fig.7. As can be observed in Fig. 7, with increasing cold work, the peak amplitude of MBN signal is found to increase.
In order to compare the sensitivity of SQUID and MBN method, experiments have been carried out using other NDT methods, namely X-ray diffraction, d-ferrite, eddy current, and hysteresis methods. In the specimens with higher cold work i.e. large volume fraction of martensite, the SQUID and MBN measurements are found to be in good agreement with X-ray diffraction, d-ferrite, eddy current, and hysteresis methods. However, the detection sensitivities are different for smaller volume fraction of martensite. SQUIDs and MBN methods have been able to successfully detect martensite in even 10% cold work specimen. However, the detection sensitivity of d-ferrite, eddy current, and hysteresis methods has been found to be relatively poor. While the lower detection limit for d-ferrite and hysteresis methods has been found to 30%, the limit for eddy current testing and X-ray diffraction method has been noted to be 20%. The SQUID and MBN outputs in rolling and transverse planes have been investigated and they have been found to be different, but confirming to the earlier observation [1, 11]. The SQUID and MBN outputs have been found to relatively high along transverse plane as compared to rolling plane. This difference in behaviour is attributed to the orientation relationship between the easy magnetisation direction, [100] of the martensite and the direction of the applied magnetic field.
The above studies clearly demonstrate the superior detection performance of SQUID and MBN methods over X-ray diffraction, d-ferrite, eddy current, and hysteresis methods for the characterisation of martensite. Further, on a comparative note, SQUID method has been noted to score over MBN method for two reasons viz. depth of interrogation and lift-off. Unlike MBN, SQUID has capability to detect very-weak magnetic fields emerging from a deep or buried source and to readily tolerate lift-offs of a few centimetres, thus offers a great potential for diverse applications.
CONCLUSION
SQUID and MBN methods have been developed for characterisation of martensite in cold worked AISI type 304 stainless steel specimens. SQUID and MBN outputs have monotonically increased with cold work i.e. volume fraction of martensite. Martensite in specimens cold worked to 10% has been unambiguously detected by these methods. This detection sensitivity has been demonstrated to be superior to other NDE methods such as X-ray diffraction, equivalent d-ferrite, hysterisis, and eddy current test methods. These studies clearly bring out the potential for using SQUID and MBN methods for early detection of fatigue damage by way of non-destructive characterisation of strain induced martensite.
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