Temperature prediction in high speed bone grinding using motor PWM signal

Tai, Bruce L.; Zhang, Lihui; Wang, Anthony; Sullivan, Stephen E.; Wang, Guangjun; Shih, Albert J.

doi:10.1016/j.medengphy.2013.05.011

Cited by 25 publications

(18 citation statements)

References 13 publications

(13 reference statements)

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“…17 Shih et al 1 studied thermal changes of the bone grinding process, and developed a model to determine heat flux distribution through Inverse heat transfer method. Tai et al 18 investigated bone high-speed grinding process and presented a model to determine heat flux, enabling temperature prediction with an error of less than 20%. Zhang et al 4 also predicted that heat-induced damage can diffuse 3 mm along the tool motion and 3 mm deep in the bone.…”

Section: Introductionmentioning

confidence: 99%

Infrared thermography of high-speed grinding of bone in skull base neurosurgery

Shakouri

Mirfallah

2019

Proc Inst Mech Eng H

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For skull base tumor removal neurosurgery, skull bone grinding is required. During this process, temperature rise occurs, which may result in an irrecoverable thermal damage. In the present research, temperature variations during bone grinding have been studied. Experimental tests have been conducted in 27 states in terms of the parameters of rotational speed (three states), feed rate (three states), and cutting depth (three states) on bovine femur bone samples. Attempts have been made to determine optimal processing conditions for minimizing thermal damage during the surgery through infrared thermography and measuring thermal variations of the bone. The results indicated that the temperature rise of the bone has a direct relationship with the parameters of rotational speed, feed rate, and cutting depth. In other words, with elevation of each of these parameters, temperature rise was also intensified. Out of the cutting parameters, rotational speed had the maximum impact on temperature rise, followed by cutting depth and feed rate. Therefore, to reduce the extent of thermal damage incurred to the neural tissue, the minimum values for the cutting parameters are proposed as follows: rotational speed = 45000 r min−1, feed rate = 20–30 mm min−1 with depth of cut = 0.25 mm, and feed rate = 20 mm min−1 with cutting depth = 0.50 mm.

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Section: Introductionmentioning

confidence: 99%

Infrared thermography of high-speed grinding of bone in skull base neurosurgery

Shakouri

Mirfallah

2019

Proc Inst Mech Eng H

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“…Consistent and repeatable temperature fitting results validated this approach. Tai et al [4] explored the feasibility of using motor electrical feedback to estimate temperature rise during a surgical bone grinding procedure. Experimental data under a variety of grinding conditions were analyzed toestablish a PWM to heat generation conversion function.…”

Section: Introductionmentioning

confidence: 99%

Experimental research on microscale grinding temperature under different nanoparticle jet minimum quantity cooling

Yang

Zhang

et al. 2016

Materials and Manufacturing Processes

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To solve the limited cooling capacity of drip cooling technique in current clinical grinding orthopedic surgery, this paper carried out a nanoparticle jet minimum quantity cooling grinding experiment by using hydroxyapatite, SiO 2 , Fe 2 O 3 , carbon nanotubes nanofluids, which mass fraction were 2%, 4%, 6%, 8%, 10% respectively. Grinding temperature during the grinding process was measured, results show that temperature peak of bone micro-grinding isn't always proportional to mass fraction of nanofluids. The measured temperature peak shows an inversely proportional relationship with mass fraction of nanofluid within a certain mass fraction range, but a proportional relationship beyond this mass fraction range. Such critical mass fraction varies when using different types of nanoparticles. Combining with heat transfer enhancement of nanofluids, the influence law of nanofluids type and concentration on grinding temperature was disclosed from rheological properties of nanofluids and micromechanisms of nanoparticles in the grinding zone. The bigger mass fraction, the easier to show rheological properties. As for hydroxyapatite, which length-diameter ratio is high and Downloaded by [Australian National University] at 14:31 01 June 2016 2 SiO 2 , carbon nanotubes, which hardness are high, are easier to show shear thinning and shear thickening, the effect of rheological properties on temperature is obvious.

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“…6.2). Same group also investigated prediction of grinding temperatures by coupling the pulse width modulation (PWM) factor of high speed grinding motor and FEM [2]. The prediction was again very close to the experimental results with an error of less than 20 %.…”

Section: F T = Ka (64)mentioning

confidence: 71%

Computational Modeling in Bone Machining

Dahotre

Joshi

2016

Machining of Bone and Hard Tissues

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In general machining of materials is a complex process involving several process and material parameters. During machining, multiple physical phenomena are associated with combination of these process and material parameters. These physical phenomenon may occur simultaneously or in sequence rendering the process of machining very complex. The complexity of machining further depends upon the type of machining process and the nature of material being machined. Especially, in case of bone, as described in Chap. 1, which is a multicomponent, multi-composition, and hierarchical material that in turn makes its interaction with a machining tool (mechanical or heat based) very complicated. To understand such interaction and involved physical phenomena during bone machining is very important to control the machining process for desired outcome. However, inherently complex nature of bone machining renders it to inability for in-situ probing of the physical phenomena employing any experimental techniques. In view of this, either numerical or analytical computational modeling appears to be a suitable approach in designing a bone machining process for desired outcome. Nonetheless, due to the complex nature of bone machining, the search of open literature revealed paucity of efforts on computational modeling. Only limited efforts were focused on heat transfer and stress based computational modeling. Furthermore, some of the efforts have also tried to model micro scaled mechanics in bone. Hence, the current chapter is divided in to three sections; heat transfer model, stress based models, and micro scaled models. Key equations and process parameters in each case have been elaborated. Important studies concerning all these aspects have been discussed. Heat Transfer ModelsPrediction of heat transfer during bone machining process aids in optimization of the operation intended to minimize the damage by thermal necrosis. Basic equation governing the heat transfer (Eq. 6.1) within the bone forms the foundation of thermal finite element model (FEMs).

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Temperature prediction in high speed bone grinding using motor PWM signal

Cited by 25 publications

References 13 publications

Infrared thermography of high-speed grinding of bone in skull base neurosurgery

Infrared thermography of high-speed grinding of bone in skull base neurosurgery

Experimental research on microscale grinding temperature under different nanoparticle jet minimum quantity cooling

Computational Modeling in Bone Machining

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