INTELLIGENT GEARING SYSTEM 51

IntroductionHorizontal rotating mills are used all over the world, indifferent mineral and power generation industries. DavidBrown South Africa, with over 140 years of experience ingear manufacture and design, has been supplying theseindustries with innovative designs at exceptional quality.

The gearing systems associated with these industries are

challenged daily with operating conditions that are notalways fully understood. Failures are therefore experienced,in the industry over time, which cannot always be fullyexplained.

In this article the author demonstrates, throughexperimental work done on a ball mill in service, that thecurrent methods used in industry in general, are notadequate to prevent fatigue failures associated with girthgear alignment running conditions. SixSigma designphilosophies, Design For Six Sigma (DFSS), is used tovalidate the IntelGear(T) system through Design ofExperiments (DOE), and other DFSS tools, which aredeveloped specifically to overcome the problem ofoperational gear mesh misalignment. Refer to Figure 1.

BackgroundDifferent mills are used in the mineral processing andpower generation industry. The work done in this articleconcentrates on horizontal rotating mills, i.e. ball mills, butthe same would apply for other types of horizontal rotatingequipment. The work discussed in this article was done on aball mill used in the power generation industry in SouthAfrica.

The prime purpose of the mill is to pulverize the coal that

VAN DYK, D. Intelligent gearing system—solution to understand and correct operational conditions that reduce the fatigue life of a girth gear. InternationalPlatinum Conference ‘Platinum Surges Ahead’, The Southern African Institute of Mining and Metallurgy, 2006.

Intelligent gearing system—solution to understand andcorrect operational conditions that reduce the fatigue life of a

girth gear

D. VAN DYKDavid Brown Gear Industries (Pty) Ltd., South Africa

Horizontal rotating mills are being used all over the world in different mineral and powergeneration industries. David Brown South Africa, with over 140 years of experience in gearmanufacture and design, has been supplying these industries with innovative designs atexceptional quality.

The gearing systems associated with these industries are challenged daily with operatingconditions that are not always fully understood. Failures are therefore experienced, over time inthe industry, which cannot always be fully explained.

David Brown South Africa has developed a gear monitoring system, the Intelligent GearingSystem, in association with Transmission Dynamics (UK), in order to monitor and analyse theseoperating conditions in real time. The system has been designed on the principles of Six Sigma,incorporating Design for Six Sigma.

The purpose with this system design is to monitor the operating conditions on the pinion, recordthe information and analyse the data in relation to the rate of fatigue damage to the girth gear andpinion. This is done in real time and unattended. The output from the Intelligent Gearing Systemcan be fed back into the operating system of the mill user, in order to display an alarm foroperating conditions exceeding the design criteria as well as information on the rate of fatiguedamage due to these operating conditions.

When the mill operating and the effect on the fatigue life of the mill gearing components,conditions are better understood, mill users can forecast critical spare holding levels with anincreased accuracy. The Intelligent Gearing System also allows early actions to remove reasonsfor system overloads.

Figure 1. Typical misalignment damage on a girth gear

PLATINUM SURGES AHEAD52

is used for fuel for the boilers of the coal fired powergeneration plant. Refer to Figure 2 for a schematicdescription of the mill process flow.

The coal is fed to the mill from both sides of the mill,mixed with air. The milling process of the coal happensthrough the ball charge inside the mill where the coal iscrushed through the rolling action of the balls on each otheras well as the side of the mill. This continuous milling takesplace until the coal is pulverized enough to be taken up bythe air passing through the mill and then fed to the classifierand then to the boiler. The purpose of the classifier is toseparate the coal that is not suitable for the combustionprocess yet and is therefore fed back to the mill via thereject feed pipes.

Adding more coal to the process changes the load of themill but the ball charge stays constant. The amount of ballcharge in the mill is a function of the condition of the millliners.

The mill drive system consists of the main mill motor, themain reduction gear box, mill pinion and girth gear. Themill is also equipped with a barring drive, which is eitherconnected to the main drive reduction unit or, alternativelymounted at the back of the main motor. Refer to Figure 3

for a schematic of the mill drive system. The girth gear is considered the most critical component

of the mill drive system due to the replacement cost of sucha gear as well as the leadtime for a replacement gear. Themaintenance of these drive components is therefore criticalfor the economical operation of a mill over an extendedperiod. Common maintenance techniques used in theindustry include (a) vibration analysis on the mill pinionbearings, main reduction gear box and main motor, (b) oilanalysis of the main reduction gear box, (c) spray patternanalysis on the girth gear, (d) stroboscope inspection of thegirth gear teeth during operation and (e) temperaturemeasurement across the face width of the girth gear.Annual shutdowns are also planned where NDT techniquessuch as MPI are done on the girth gear teeth to look forcracks. The gear teeth are then also inspected for abnormalwear and distinct wear patterns.

Over the years of girth gear inspections on site, DavidBrown has found that the most predominant failure mode issurface distress of the girth gear teeth (pitting), where thepitting is biased to the one side of the girth gear. Refer toFigure 1 of typical gear teeth with pitting. This is always anindication of misalignment between the gear teeth of themill pinion and girth gear. In most of the instances, theabove maintenance techniques have been adhered to andthe failure mode can therefore not be explained. Commonpractice is then to turn the girth gear around on the mill andrun it on the back flank.

In order to maintain alignment of the girth gear and millpinion, standard practice in the industry is to measure thetemperature difference across the face width of the girthgear. The David Brown standard is a maximum temperaturedifference (DeltaT) of 6 degrees Celsius across the facewidth of the girth gear. In the absence of any better methodto tell the misalignment, most mill users in the industryhave employed this standard.

The work that has been done and therefore reported bythis article is to prove an alternative method to detectmisalignment that is far more accurate and sensitive tomisalignment than a DeltaT across the face width of thegirth gear. The purpose of this study is therefore to provethe hypothesis that a temperature difference, DeltaT, is not

Figure 2. Schematic diagram of the milling process in the ball mill 1

Figure 3. Schematic diagram of the mill drive system

INTELLIGENT GEARING SYSTEM 53

sensitive and therefore not accurate enough to align thegirth gear and pinion to its optimum alignment forcontinuous operating conditions under load.

The temperature difference, DeltaT, has a fundamentalerror due to the fact that the one end of the mill pinion is afree end and therefore exposed to cooling due toconvection, while the drive end is connected to the maingear box and therefore exposed to heat due to conductionand radiation from the main drive. For a typical millapplication, due to the weight of the pinion and girth gear,the soaking time of the mill system takes a substantial timeand could therefore lead to ‘false’ temperature gradientsacross the face width of the gear.

For a typical installation of 1800 kW, the losses in themain reducer gear box due to gear mesh and bearings couldamount to 24 kW where the loss at the mill mesh could be14 kW. The mechanical losses inside the mill, due to themilling process, are another source of heat generation. Withthe unbalanced heat input into the mill pinion and the restof the thermodynamic forces due to cooling of the free endinto the air, cooling by the spray system, etc., thetemperature gradient across the face width of the girth gearand pinion may be significantly influenced by other factors,which are not related to gear misalignment.

It is therefore probable that the gear is set to run with amisalignment to compensate for the temperature gradientdue to the thermodynamics of the total system. It is also alengthy process due to the heat inertia of the girth gear andpinion in order to detect a DeltaT after an adjustment hasbeen made.

Design principlesThere are several standards used in industry today to designthe girth gears and pinions for mills of which the mostcommon standards are AGMA 321.05, AGMA 6004 F88and ISO 6336. The gears are designed for surface durability(pitting) and tooth bending strength. For the purpose of thisstudy, only design for surface durability will be consideredbecause the failure mode, misalignment, under invest-igation in this study is associated with surface durability.

The load distribution factor for AGMA 321.05 is readfrom a graph for gears with a face width of up to 1016 mm.AGMA 6004 F88 is a revision of AGMA 321.05 where theload distribution factor is limited to a maximum of 2.

ISO 6336-1 method A, recommends that the misalign-ment be measured, but method B to D does show how tocalculate the face load distribution factor. The face loaddistribution factor is a function of gear tooth manufacturingaccuracy, alignment of the axes of rotation, elasticdeflection of gear unit elements, bearing clearances,Hertzian contact deformations at the tooth surface, thermaldeformations due to operating temperature, total tangentialtooth load, which includes the dynamic and applicationfactor, to name a few. The advantage of method A is thatthe actual face load distribution factor is measured inoperation and therefore already accounting for all theabove-mentioned influences.

According to ISO 6336-2 the contact stress is calculatedas follows:

[1]

where:�HO = nominal contact stress at the pitch point

KA = application factorKV = synamic factorKH� = face load distribution factor for contact stressKH� = transverse load distribution factor for contact

stress�HP = permissible contact stress

From Equation [1] it is therefore clear that the contactstress of a gear pair, and hence its life, is influenced by theface load distribution factor, which is strongly influencedby gear misalignment.

This study will now further focus on the face loaddistribution factor (KH�).

Experimental workDesign of Experiments, DOE, has been used to proof theIntelGear(T) pilot system and hence proved the hypothesisthat a temperature difference across the face width of thegirth gear is not sensitive enough to set the alignment foroptimum aligned prolonged running conditions. Theexperimental work has been done on a ball mill at a coalfired power station in South Africa.

Experimental set-upThe experimental set-up took 3 working days to install theIntelGear system on the mill pinion of the ball mill (refer toFigure 4). The experimental system consists of two majorcomponents: (a) the torque measurement module and (b)the gear alignment module, which are both mounted insidea tufnol disk that is mounted next to the pinion gear teeth(Refer to Figure 5). The torque measurement module isused to measure the application factor, KA, while the gearalignment module is used to measure the load distributionfactor, KH�, for the mill pinion.

The temperature gradient, DeltaT, is measured with ahand-held laser temperature measurement device that iscommonly used in the industry today. After each alignmentadjustment was made, the system was left to run for 12hours in order for the temperature to stabilize, beforetemperature measurements were taken across the gear facewidth. In order to validate the experimental set-up ameasurement system analysis, MSA, was done on the

Figure 4. Typical installation on a 1800 kW ball mill (courtesy ofKendal Power Station, South Africa)

temperature measurement system as well as on theIntelGear system. The purpose of the MSA is to determineif the variance measured is due to the variance in themeasurement system, repeatability and reproducibility, or ifthe variance measured is a true reflection of the response ofthe system being measured.

The alignment adjustments were made by installing pre-determined stainless steel shims under the mill pinionbearing housings. The DOE simulated the effect ofmisalignment from one end of the mill pinion through themesh to the other end of the mill pinion. The alignmentconvention used was that, anti clockwise relative movementof the pinion (shim the drive end bearing housing), denotesa negative specific alignment and if the movement ispositive (shim the non drive end bearing housing), denotesa positive specific alignment.

The order in which these alignment adjustments weremade was done according to the run order from the DOE.The standard order was randomized to prevent any specialcauses in the recorded data during the experiment that couldlead to misinterpretation of the experimental data. Onecentre point was added in order to investigate if there iscurvature present in the output data. Refer to Table 1.

The DOE is designed as a 2k factorial with two factors:

(a) load and (b) alignment. The purpose of the DOE is totest the sensitivity of the IntelGear towards misalignmentand then also to find a prediction equation that describes theload distribution factor KH� as a function of the load andmisalignment as described in Equation [2].

y=f(x1,x2) [2]

where: y = KH�

x1 = specific alignment [�m]x2 = Load [%]

The MSA was done by three people by taking fourmeasurements with two replicates each. An R&R gaugestudy (crossed) was performed on the data to test if thevariance of the data is in the data itself or in therepeatability and reproducibility of the measurementsystem.

Experimental results and discussion The results from the DOE are tabled in Table I with acentre point at 0.0 �m specific alignment and 60% load.The results from the DOE demonstrated that the loadchange in the mill is not a significant factor to beconsidered at a confidence interval of 95% (refer to Figure7).

The results further demonstrate that curvature exists inthe data. Refer to Figure 8 for a main effects plot for thealignment. The centre point is offset to the datademonstrated by the line between the corner points. Thecentre point suggests that the value of KH� decreases to zeroand then increases again as the alignment decreases to zero,(perfect alignment), and increases again on the opposite end

PLATINUM SURGES AHEAD54

Figure 5. Tufnol disk mounted on the mill pinion next to the gearteeth

Figure 6. Torque measurement module and gear alignmentmodule inside Tufnol disk before installation

Table IDOE run order and specific alignment data per gear face width

StdOrder RunOrder CentrePt Blocks Alignment Load KH�

2 1 1 1 102.2 40 1.451 2 1 1 -102.2 40 1.635 3 0 1 0.0 60 1.173 4 1 1 -102.2 80 1.634 5 1 1 102.2 80 1.45

Figure 7. The load is not a significant factor with a confidence of95%

INTELLIGENT GEARING SYSTEM 55

of the pinion.An extra set of data points was taken during the DOE for

alignment conditions as displayed in Table II. This datahave been used to find the prediction equation by using afitted line plot with a confidence interval of 95% andprediction interval of 95%. Analysis of the residuals revealsa normal distribution with no distinct patterns (refer toFigure 9).

Figure 10 displays the prediction equation that isquadratic. Figure 10 also displays the confidence interval aswell as the prediction interval, both at 95%. This equationcan therefore be used to predict K�� for a known specificalignment value.

The prediction equation for K�� is therefore calculated asfollows:

[3]

where: y = K��

x = alignment [�m]

Based on recommendations from ISO 6336-1 (methodC)2 mesh stiffness is

C� = 20 N/mm/�m [4]

From the experimental torque measurements, a specificloading for the girth gear at a face width of 650 mm iscalculated at

[5]

The mean mesh deflection is therefore:

f = 27.5 �m [6]

When gear misalignment errors are of the same order asthe mean mesh deflection, the load distribution along theface width of the gear teeth will become non uniform acrossthe gear face width, which could significantly increase thelocalized stress at the mesh, which in turn could lead tofatigue of the gear teeth surface. In the industry today, withthe methods employed, it is therefore extremely difficult toalign the girth gear and pinion to 30 �m.

By substituting x in equation 3 with a value of +30 �m, aK�� value of 1.25 is predicted or -30 �m a K�� value of1.29 is predicted. With this method explained by this study,it is therefore possible to align girth gear and pinionsystems to 30 �m which, for this type of application willgive a K�� value of less than 1.3.

The current method, widely used in the industry, was alsoinvestigated. Temperature readings were recorded (refer toTable III), but the measurement system used failed theMSA and no correlation could therefore be found. Thesystem tolerance is set at 6 degrees Celsius.

From the analysis of the MSA the total % contribution

Figure 8. Centre point included to test for curvature

Table IIAdditional data to find prediction equation

Alignment KHb-102.201 1.63-61.3208 1.52-40.8805 1.17-20.4403 1.2920.44025 1.2540.8805 1.361.32075 1.35

102.2013 1.45

Figure 10. Prediction equation for K��

Figure 9. Residual plots for the fitted line K��

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(92.85%) to variance is in the Gage R&R, where most ofthe variance is in the repeatability (58.82%) but also inreproducibility and operator at 35% each. For an acceptablemeasurement system, the total % contribution to varianceshould preferably not be more than 1% but up to 10% canbe tolerated pending the application. The number of distinctcategories is only 1 where it should be 5 or more for anacceptable measurement system.

The variance part to part is very small at 7.15%, whichtherefore indicates that the DeltaT measured in Table III isof no significance and can therefore not be used to checkfor correlation. The analysis further indicated that themeasurements taken by two operators were outside thecontrol limits for the measurement system. Refer to Figure11.

ConclusionThis study successfully demonstrated that the face loaddistribution factor, K��, can successfully be measured ontypical mill applications by the IntelGear system. Bymeasuring the K��, the alignment between the mill pinionand girth gear can therefore be adjusted much moreaccurately than the current systems used in the industry

today. Being able to adjust the alignment accurately, thefailure mode pitting, due to misalignment can therefore beeliminated. Misalignment, being one of the most commongear failure modes, would therefore be eliminated.

References1. Process flow as supplied by Mathew Miller, Plant

Engineer, Kendal Power Station2. Calculation of load capacity of spur and helical gears –

Part 1. Basic principles, introduction and generalinfluence factors

Table III Temperature recordings after alignment adjustments

Alignment Temp � Bias2 NDE

20.4 2 NDE-20.4 2 DE

Figure 11. MSA results for R&R gauge study (crossed)