CNC machine tool monitoring by AE sensors

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A machine tool monitoring system is a flow of information and system processing in which the information selection, obtaining data, processing of information and decision making on the refined information are integrated. The aim of tool condition monitoring is to detect early the disturbances in the machining process and wear of machine tool components. [1]

Contents

The condition of tool has been researched extensively in the past and have focused on detection of tool wear, tool breakage and the estimation of remaining tool life. It is very important for on-line identification of tool condition in machining process for enhanced productivity, better quality of parts and lower costs for unmanned, automated manufacturing systems. [2]

Techniques of machine tool monitoring

Machine tool monitoring can be done with or without additional sensors. Using additional sensors, monitoring can be done by measuring:

Sensor-less machine tool monitoring is done by measuring internal drive signals such as:

Combined measuring of multiple quantities is also possible. [6]

Acoustic emission sensor

Machine tool monitoring is explained with Acoustic Emission (AE) sensors. [7] An AE sensor is commonly defined as the sound emitted as an elastic wave by a solid when it is deformed or struck, caused by the rapid release of localized stress energy. Therefore, it is an occurrence phenomenon which releases elastic energy into the material, which then propagates as an elastic wave. The detection frequency range of acoustic emission is from 1 kHz to 1 MHz.

Rapid stress-releasing events generate a spectrum of stress waves starting at 0 Hz and typically falling off at several MHz. AE can be related to an irreversible release of energy. It can also be generated from sources not involving material failure including friction, cavitation and impact. [8] The three major applications of AE sensors phenomena are: a) Source location - determine the locations of occurrence of an event b) Material mechanical performance - evaluate and characterize materials/structures; and c Health monitoring – monitors the safety operation. [8]

How an AE sensor monitors machine tool

An AE sensor works on the principle of measuring the high-frequency energy signals produced during cutting process. It also measures the AE energy resulting from the fracture when a tool breaks. It is best suited to applications where the level of background AE signal is low compared to the sound of tool breakage. This makes the AE sensor ideal for breakage detection of small drills and taps. It is easy to install on both new and existing machines.

An AE sensor detects force proportional monitoring signals even in machining operations, which generate very small cutting forces. In combination with true power, it increases the reliability of breakage monitoring. [9] It is used especially with solid carbide tools, or very small tools on large machines and multi spindles. Most of the sensors have to be attached to the machine tool surface. [10] However, there are alternative methods of AE wave transmitting. A rotating, wireless AE sensor consists of a rotating sensor and a fixed receiver. [11] An AE sensor can also receive the acoustic waves via a jet of cooling lubricant, which can be connected directly to the tool or workpiece. [12] [13]

The machine tool monitoring systems commonly use sensors for measuring cutting force components or quantities related to cutting force (power, torque, distance/displacement and strain). AE sensors are relatively easy to install in existing or new machines, and do not influence machine integrity and stiffness. All systems suppliers also use acoustic emission sensors, especially for monitoring small tools [14] and for grinding.

All sensors used in machine tool monitoring systems are well adjusted to harsh machine tool environments. The difficulties in designing reliable machine tool monitoring can be related to the complexity of the machining process itself, which may have one or more of the following characteristics, apart from the changes of the machine tool itself. [15]

Related Research Articles

<span class="mw-page-title-main">Ultrasound</span> Sound waves with frequencies above the human hearing range

Ultrasound is sound with frequencies greater than 20 kilohertz. This frequency is the approximate upper audible limit of human hearing in healthy young adults. The physical principles of acoustic waves apply to any frequency range, including ultrasound. Ultrasonic devices operate with frequencies from 20 kHz up to several gigahertz.

<span class="mw-page-title-main">Electrical discharge machining</span> Metal fabrication process

Electrical discharge machining (EDM), also known as spark machining, spark eroding, die sinking, wire burning or wire erosion, is a metal fabrication process whereby a desired shape is obtained by using electrical discharges (sparks). Material is removed from the work piece by a series of rapidly recurring current discharges between two electrodes, separated by a dielectric liquid and subject to an electric voltage. One of the electrodes is called the tool-electrode, or simply the tool or electrode, while the other is called the workpiece-electrode, or work piece. The process depends upon the tool and work piece not making physical contact. Extremely hard materials like carbides, ceramics, titanium alloys and heat treated tool steels that are very difficult to machine using conventional machining can be precisely machined by EDM.

<span class="mw-page-title-main">Photonics</span> Technical applications of optics

Photonics is a branch of optics that involves the application of generation, detection, and manipulation of light in form of photons through emission, transmission, modulation, signal processing, switching, amplification, and sensing. Photonics is closely related to quantum electronics, where quantum electronics deals with the theoretical part of it while photonics deal with its engineering applications. Though covering all light's technical applications over the whole spectrum, most photonic applications are in the range of visible and near-infrared light. The term photonics developed as an outgrowth of the first practical semiconductor light emitters invented in the early 1960s and optical fibers developed in the 1970s.

<span class="mw-page-title-main">Thermography</span> Infrared imaging used to reveal temperature

Infrared thermography (IRT), thermal video and/or thermal imaging, is a process where a thermal camera captures and creates an image of an object by using infrared radiation emitted from the object in a process, which are examples of infrared imaging science. Thermographic cameras usually detect radiation in the long-infrared range of the electromagnetic spectrum and produce images of that radiation, called thermograms. Since infrared radiation is emitted by all objects with a temperature above absolute zero according to the black body radiation law, thermography makes it possible to see one's environment with or without visible illumination. The amount of radiation emitted by an object increases with temperature; therefore, thermography allows one to see variations in temperature. When viewed through a thermal imaging camera, warm objects stand out well against cooler backgrounds; humans and other warm-blooded animals become easily visible against the environment, day or night. As a result, thermography is particularly useful to the military and other users of surveillance cameras.

In electrical engineering, partial discharge (PD) is a localized dielectric breakdown (DB) of a small portion of a solid or fluid electrical insulation (EI) system under high voltage (HV) stress. While a corona discharge (CD) is usually revealed by a relatively steady glow or brush discharge (BD) in air, partial discharges within solid insulation system are not visible.

<span class="mw-page-title-main">Numerical control</span> Computer control of machine tools

In machining, numerical control, also called computer numerical control (CNC), is the automated control of tools by means of a computer. It is used to operate tools such as drills, lathes, mills, grinders, routers and 3D printers. CNC transforms a piece of material into a specified shape by following coded programmed instructions and without a manual operator directly controlling the machining operation.

<span class="mw-page-title-main">Security alarm</span> System that detects unauthorised entry

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Photoacoustic spectroscopy is the measurement of the effect of absorbed electromagnetic energy on matter by means of acoustic detection. The discovery of the photoacoustic effect dates to 1880 when Alexander Graham Bell showed that thin discs emitted sound when exposed to a beam of sunlight that was rapidly interrupted with a rotating slotted disk. The absorbed energy from the light causes local heating, generating a thermal expansion which creates a pressure wave or sound. Later Bell showed that materials exposed to the non-visible portions of the solar spectrum can also produce sounds.

<span class="mw-page-title-main">Acoustic emission</span>

Acoustic emission (AE) is the phenomenon of radiation of acoustic (elastic) waves in solids that occurs when a material undergoes irreversible changes in its internal structure, for example as a result of crack formation or plastic deformation due to aging, temperature gradients, or external mechanical forces.

Condition monitoring is the process of monitoring a parameter of condition in machinery, in order to identify a significant change which is indicative of a developing fault. It is a major component of predictive maintenance. The use of condition monitoring allows maintenance to be scheduled, or other actions to be taken to prevent consequential damages and avoid its consequences. Condition monitoring has a unique benefit in that conditions that would shorten normal lifespan can be addressed before they develop into a major failure. Condition monitoring techniques are normally used on rotating equipment, auxiliary systems and other machinery like belt-driven equipment,, while periodic inspection using non-destructive testing (NDT) techniques and fit for service (FFS) evaluation are used for static plant equipment such as steam boilers, piping and heat exchangers.

<span class="mw-page-title-main">Predictive maintenance</span> Method to predict when equipment should be maintained

Predictive maintenance techniques are designed to help determine the condition of in-service equipment in order to estimate when maintenance should be performed. This approach promises cost savings over routine or time-based preventive maintenance, because tasks are performed only when warranted. Thus, it is regarded as condition-based maintenance carried out as suggested by estimations of the degradation state of an item.

Level sensors detect the level of liquids and other fluids and fluidized solids, including slurries, granular materials, and powders that exhibit an upper free surface. Substances that flow become essentially horizontal in their containers because of gravity whereas most bulk solids pile at an angle of repose to a peak. The substance to be measured can be inside a container or can be in its natural form. The level measurement can be either continuous or point values. Continuous level sensors measure level within a specified range and determine the exact amount of substance in a certain place, while point-level sensors only indicate whether the substance is above or below the sensing point. Generally the latter detect levels that are excessively high or low.

<span class="mw-page-title-main">Tool wear</span> Gradual failure of cutting tools due to regular use

In machining, tool wear is the gradual failure of cutting tools due to regular operation. Tools affected include tipped tools, tool bits, and drill bits that are used with machine tools.

<span class="mw-page-title-main">Electronic nose</span> Electronic sensor for odor detection

An electronic nose is an electronic sensing device intended to detect odors or flavors. The expression "electronic sensing" refers to the capability of reproducing human senses using sensor arrays and pattern recognition systems.

<span class="mw-page-title-main">Ultrasonic transducer</span> Acoustic sensor

Ultrasonic transducers and ultrasonic sensors are devices that generate or sense ultrasound energy. They can be divided into three broad categories: transmitters, receivers and transceivers. Transmitters convert electrical signals into ultrasound, receivers convert ultrasound into electrical signals, and transceivers can both transmit and receive ultrasound.

In machining, vibrations, also called chatter, are the relative movements between the workpiece and the cutting tool. The vibrations result in waves on the machined surface. This affects typical machining processes, such as turning, milling and drilling, and atypical machining processes, such as grinding.

A drawbar force gauge is a gauge designed to measure forces on a machine tool's drawbar. These types of machines are found in metalworking, woodworking, stone cutting, and carbon fiber fabricating shops. Many modern machines generate well in excess of 50,000 N (12,000 lbf). Measuring and maintaining this force is an important and necessary part of a machine shop preventative maintenance plan.

The photoacoustic effect or optoacoustic effect is the formation of sound waves following light absorption in a material sample. In order to obtain this effect the light intensity must vary, either periodically or as a single flash. The photoacoustic effect is quantified by measuring the formed sound with appropriate detectors, such as microphones or piezoelectric sensors. The time variation of the electric output from these detectors is the photoacoustic signal. These measurements are useful to determine certain properties of the studied sample. For example, in photoacoustic spectroscopy, the photoacoustic signal is used to obtain the actual absorption of light in either opaque or transparent objects. It is useful for substances in extremely low concentrations, because very strong pulses of light from a laser can be used to increase sensitivity and very narrow wavelengths can be used for specificity. Furthermore, photoacoustic measurements serve as a valuable research tool in the study of the heat evolved in photochemical reactions, particularly in the study of photosynthesis.

Virtual machining is the practice of using computers to simulate and model the use of machine tools for part manufacturing. Such activity replicates the behavior and errors of a real environment in virtual reality systems. This can provide useful ways to manufacture products without physical testing on the shop floor. As a result, time and cost of part production can be decreased.

<span class="mw-page-title-main">High-frequency impulse-measurement</span> Measurement technique

HFIM, acronym for high-frequency-impulse-measurement, is a type of measurement technique in acoustics, where structure-borne sound signals are detected and processed with certain emphasis on short-lived signals as they are indicative for crack formation in a solid body, mostly steel. The basic idea is to use mathematical signal processing methods such as Fourier analysis in combination with suitable computer hardware to allow for real-time measurements of acoustic signal amplitudes as well as their distribution in frequency space. The main benefit of this technique is the enhanced signal-to-noise ratio when it comes to the separation of acoustic emission from a certain source and other, unwanted contamination by any kinds of noise. The technique is therefore mostly applied in industrial production processes, e.g. cold forming or machining, where a 100 percent quality control is required or in condition monitoring for e.g. quantifying tool wear.

References

  1. ↑ Preparing and Proving CNC Machine Tool Programs. Benchmark Media Limited.
  2. ↑ www.eng.nus.edu.sg http://www.eng.nus.edu.sg/EResnews/0310/rd/rd_7.html.{{cite web}}: Missing or empty |title= (help)
  3. ↑ Jemielniak, K.; Arrazola, P.J. (January 2008). "Application of AE and cutting force signals in tool condition monitoring in micro-milling". CIRP Journal of Manufacturing Science and Technology. 1 (2): 97–102. doi:10.1016/j.cirpj.2008.09.007.
  4. ↑ Haber, R.E.; Jiménez, J. E.; Peres, C.Ronei; Alique, J. R. (2004). "An investigation of tool-wear monitoring in a high-speed machining process". Sensors and Actuators A: Physical. 116 (3): 539–545. doi:10.1016/j.sna.2004.05.017.
  5. ↑ Li, Xiaoli (January 2002). "A brief review: acoustic emission method for tool wear monitoring during turning". International Journal of Machine Tools and Manufacture. 42 (2): 157–165. doi:10.1016/S0890-6955(01)00108-0.
  6. ↑ REPO, JARI (2010). Thesis on Condition Monitoring of Machine Tools and Machining Processes using Internal Sensor Signals. Stockholm, Sweden.{{cite book}}: CS1 maint: location missing publisher (link)
  7. ↑ Liang, S. Y.; Dornfeld, D. A. (1989-08-01). "Tool Wear Detection Using Time Series Analysis of Acoustic Emission". Journal of Engineering for Industry. 111 (3): 199–205. doi:10.1115/1.3188750. ISSN   0022-0817.
  8. 1 2 "The Minerals, Metals & Materials Society (TMS)".
  9. ↑ arbor, ann (1997). MTC tool and process monitoring. USA: Artiscompany.
  10. ↑ hur, Winter (1997). Piezo-instrumentation. Switzerland: Kistler company.
  11. ↑ Aachen. Wireless AE sensor AEL 200. Germany: Prometec company.
  12. ↑ Nordmann sensor technology. Germany: Nordmann company. 1997.
  13. ↑ Fluid sound sensor WAE 100 (Aachen, Germany: Prometec company ed.). Aachen, Germany: Prometec company.
  14. ↑ Beruvides, G.; Quiza, R.; del Toro, R.; Haber-Guerra, R.E. (2013). "Sensoring systems and signal analysis to monitor tool wear in microdrilling operations on a sintered tungsten–copper composite material". Sensors and Actuators A: Physical. 199: 165–175. doi:10.1016/j.sna.2013.05.021.
  15. ↑ Dimla, Dimla E (2000). "Sensor signals for tool-wear monitoring in metal cutting operations–a review of methods". International Journal of Machine Tools and Manufacture. 8 (40): 1073. doi:10.1016/S0890-6955(99)00122-4.
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