Investigation of Acoustic Signals During W1 Tool Steel Quenching

Nikhare, Chetan P.; Ragai, Ihab; Loker, David; Sweeney, Shannon K.; Conklin, Chris; Roth, Joseph

doi:10.1115/msec2015-9412

Cited by 10 publications

(3 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As this is a non-contact measurement method, the contact of the sensor with the vibrating surface of the machine is eliminated. The research issues have included the investigation of acoustic signals in tool steel-hardening [14] and cold-drawn steel [15], cutting tool stability against impacts [16], tool wear and surface roughness in milling [17], tool wear in drilling by acoustic emission [18], detection of contact mechanism changes due to grinding tool wear by acoustic emission [19], and detection of suitable cutting operations [20]. The close relationship between the parasitic machine tool vibrations and the machined surface roughness is clearly shown in [21].…”

Section: Adaptive Control Methodsmentioning

confidence: 99%

Method of Using the Correlation between the Surface Roughness of Metallic Materials and the Sound Generated during the Controlled Machining Process

et al. 2022

View full text Add to dashboard Cite

The article aims to use the generated sound as operational information needed for adaptive control of the metalworking process and early monitoring and diagnosis of the condition of the machined materials using a newly introduced surface roughness quality index due to the sound-controlled machining process. The object of the measurement was correlation between the sound intensity generated during cutting and the material parameters of the machined surface, i.e., the roughness of the machined surface and the degree of wear of the cutting tool. The roughness was measured during longitudinal turning of a steel billet with a P25 insert made of 12X18H10T steel and a T15K6 cutting insert made of a titanium, cobalt, and tungsten group alloy. The correlation between the sound and roughness of the machined surface was 0.93, whereas between the sound and wear of the cutting tool was 0.93. The correlation between sound and tool wear in the experiment with P25 and T15K6 cutting inserts and the correlation between sound and roughness is positive.

show abstract

Section: Adaptive Control Methodsmentioning

confidence: 99%

Method of Using the Correlation between the Surface Roughness of Metallic Materials and the Sound Generated during the Controlled Machining Process

et al. 2022

View full text Add to dashboard Cite

show abstract

“…Erich et al [13] examined the relation between acoustic signals during quenching of steel and properties after quenching. Nikhare et al [14] evaluated the relation of the acoustic signal and specimen size or temperature for quenching of tool steel. Mojškerc et al [15,16] presented a method of monitoring steel quenching with non-destructive AE measurements.…”

Section: Introductionmentioning

confidence: 99%

Acoustic emission monitoring of immersion quenching bath attributes

Mojškerc¹,

Grum²,

Kek³

et al. 2023

eJNDT

View full text Add to dashboard Cite

This paper describes the use of acoustic emission (AE) testing for monitoring immersion quenching bath attributes. Immersion quenching is a heat treatment process used to change the mechanical properties of metallic workpieces. The quenching bath cooling attributes degrade with prolonged use, thus affecting the workpiece mechanical properties. A non-destructive monitoring method of the quenching bath is required. An AE measurement system is proposed for this purpose. Steel specimens are quenched in tap water, deionized water, 5 % NaCl-water solution and 5 % detergent-water solution. AE is measured with four piezoelectric sensors. The influence of quenching bath attributes on specimen cooling is described together with the measured AE signals. AE signal peak amplitude diagrams are evaluated. A reference AE peak amplitude signal is presented with the measurements. The quenching bath attribute assessment method is established by monitoring the amount of outlying AE signals in regard to the reference AE signal. The results confirm that AE monitoring provides a decent way of assessing quenching bath attributes and thus also the quenched specimen mechanical properties.

show abstract

“…The solution to this problem is achieved by eliminating the sensor contact with the machine tool vibrating surface that is implemented by a noncontact measurement method. In this case, it is of interest to control the sound accompanying the cutting process [21][22][23][24][25][26][27]. The close relationship between the parasitic vibrations of the machine tool and the roughness of the machined surface is clearly shown in [28].…”

Section: Introductionmentioning

confidence: 99%

Adaptive Control of the Metalworking Process With Using Sound Generated During Cutting

Nahornyi¹,

Panda²,

Valíček³

et al. 2021

Preprint

View full text Add to dashboard Cite

The presented paper proposes a method of adaptive control of the metal cutting process based on the analysis and interpretation of recorded sound for the identification of the cutting process. The presented research results clearly demonstrated the efficiency of using the sound generated during cutting by CNC lathe 16 K20T1 for the adaptive metalworking control. The sound makes it possible to control the accuracy of the workpiece part geometry and the surface quality in the online mode. The online mode also makes it possible to make an informed decision about a timely interruption of the cutting process or the continuation of the process in the altered modes for its successful completion. As the research results presented in the paper show, there is a close correlation between the sound generated by cutting and the roughness of the surface being machined or the degree of wear of the cutting tool. The correlation between the sound and roughness of the machined surface is 0.94, whereas between the sound and wear of the cutting tool is 0.93. The paper aims to use the generated sound as operational information needed for adaptive control of the metal processing process and timely monitoring and diagnostics of the condition of processed materials using the precision index, newly introduced as the machining quality index.

show abstract

Investigation of Acoustic Signals During W1 Tool Steel Quenching

Cited by 10 publications

References 0 publications

Method of Using the Correlation between the Surface Roughness of Metallic Materials and the Sound Generated during the Controlled Machining Process

Method of Using the Correlation between the Surface Roughness of Metallic Materials and the Sound Generated during the Controlled Machining Process

Acoustic emission monitoring of immersion quenching bath attributes

Adaptive Control of the Metalworking Process With Using Sound Generated During Cutting

Contact Info

Product

Resources

About