Prediction Model of Tunnel Boring Machine Disc Cutter Replacement Using Kernel Support Vector Machine

2.1. Evaluation Function and Related Parameters

As mentioned in the introduction section, the major reason to replace low-efficacy disc cutters is because cutting with them is not efficient under manual judgement. Therefore, a disc cutter evaluation criterion is needed to estimate the ability of disc cutters during tunneling. The most common and intuitive health index is abrasion loss of cutter rings, which is difficult to measure. Several other health indices have been proposed to indirectly estimate the ability. Bruland [ 21 33 ] took the excavated tunnel length per disc cutter as the health index of disc cutter performance. Hassanpour [ 9 ] proved that disc cutter life, which is defined as the length of time a disc cutter has been working before replacement, is more suitable to estimate disc cutter life. Yu [ 12 ] took into account the different rolling distances of disc cutters at different positions based on excavated tunnel length, and calculated the rolling distance of each disc cutter as the health index based on an equidistant cylindrical spiral. All these studies focused on indirect measurements of abrasion loss. However, changes of disc cutter ability result in changes of TBM rock-breaking ability. In this paper, a qualitative evaluation criterion for cutting ability is proposed to estimate disc cutters’ ability.

The studied TBM is an open-type girder TBM, widely used in tunneling with good surrounding rock integrity. The main components of an open-type girder TBM are shown in Figure 1 . The tunneling procedures of an open-type girder TBM can generally be summarized as follows:

Step 1: Tunneling preparation. At this stage, the gripper (10) is pressed on the excavated tunnel wall by stretching out the gripper cylinders. Then the back support (11) is withdrawn and the cutterhead drive motors (5) are started to get the cutterhead (1) ready for tunneling.

Step 2: Rock breaking and advancing. The thrust cylinders (9) located on either side of the girder are stretched out. The cutterhead (1) is pushed against the rock before it and rotates with the spindle (3) driven by the motors (5). The rock surface is crushed by disc cutters (2) mounted on the cutterhead to form concentric circular grooves. With the increase in the depth of the grooves, the cracks on the surface become deepened and intersected. Then rocks between adjacent concentric circular grooves flake off to form rock fragments. At the same time, the rock fragments are collected by the scraper on the cutterhead. Then they slide through the cutterhead (1) to the inside of the TBM, and are finally carried out of the tunnel through the belt conveyor (8). If soft or broken strata are encountered during the excavation, it is often necessary to stop the extension of the thrust cylinders (9) and shut down the cutterhead.

Step 3: Regripping and position adjusting. At this stage, the back support (11) extends and the gripper (10) retracts. The thrust cylinders (9) also retract, thus pulling the gripper ahead.

The TBM is constantly switching and circulating between these three steps until the tunneling is completed. In tunnel construction, the process of the above three steps is called a “stroke” of TBM,

c a = f 1 ( r o c k   p r o p e r t i e s ) w 1 F + f 2 ( r o c k   p r o p e r t i e s ) w 2 T p

(1)

ca

is cutting ability evaluation, f 1 and f 2 are functions of rock properties, w 1 and w 2 are weight coefficients, F is thrust, T is cutterhead torque, and p is penetration rate. The cutting ability evaluation can be simplified as:

c a = α 1 F + α 2 T p

(2)

α

1 and α 2 are variable coefficients about geological conditions.

Disc cutters work in Step 2 above. Therefore, the field parameters in Step 2 are needed to estimate disc cutter conditions. A feasible calculation of disc cutters’ cutting ability evaluation under different geological conditions referring to the specific energy [ 20 26 ] is as follows:whereis cutting ability evaluation,andare functions of rock properties,andare weight coefficients,is thrust,is cutterhead torque, andis penetration rate. The cutting ability evaluation can be simplified as:whereandare variable coefficients about geological conditions.

α 1 and α 2 can be approximately treated as invariant. The cutting ability evaluation before and after a cutter replacement in one day was calculated and is shown in

For a short piece of continuous rock formation where rock properties usually do not change much,andcan be approximately treated as invariant. The cutting ability evaluation before and after a cutter replacement in one day was calculated and is shown in Figure 2 . To observe the changing trend of cutting ability evaluation, only the data of rock breaking and advancing procedure is shown. The ability of the cutters can be observed from the changing trend of the curve in the figure. For example, cutting ability evaluation begins to change drastically and eventually stabilizes at a lower value before disc cutter replacement. On the contrary, cutting ability evaluation gets a big boost after disc cutter replacement, and as the time goes on, it generally decreases until the next disc cutter replacement is performed. The oscillation in the figure occurs because the mechanical model of TBM rock breaking is periodically changing every second even under uniform geology. Furthermore, there are outliers that do not follow the trend mainly because the geological conditions have changed in these parts.

f 1 and f 2 , are complex nonlinear. However, previous research has proved that TBM operational parameters can be used to predict rock information because they reflect the rock–machine interactions [

  c a = f 1 ( f ( p r i o r   g e o l o g i c a l   i n f o r m a t i o n ,   o p e r a t i o n a l   p a r a m e t e r s ) ) w 1 F + f 2 ( f ( p r i o r   g e o l o g i c a l   i n f o r m a t i o n ,   o p e r a t i o n a l   p a r a m e t e r s ) ) w 2 T p

(3)

If Equation (1) is used for quantitative judgement of the cutting ability, there are two main problems: (1) the specific rock properties are difficult to obtain during tunneling; (2) the functions associated with rock properties,and, are complex nonlinear. However, previous research has proved that TBM operational parameters can be used to predict rock information because they reflect the rock–machine interactions [ 34 ]. Therefore, it is possible to approximate real-time geological conditions with prior geological information and operational parameters, such as advance rate, thrust, cutterhead torque, cutterhead rotational speed, advance mileage, penetration rate, etc. Thus, Equation (1) can be transformed as an expression of known data:

From Equation (3), one may see that the cutting ability evaluation is affected by both geological features and operational parameters. Therefore, Equation (3) is highly complex and nonlinear. However, a threshold is enough to determine whether the disc cutters should be replaced for making cutter maintenance plans. As shown in Figure 2 , the cutting ability evaluation when disc cutter replacement is needed and when TBM works normally are highly different. The question then becomes a classification problem of the results of Equation (3). Considering the complexity of the model deployment in projects, this paper provides a cost-sensitive Gaussian kernel support vector machine for predicting whether disc cutters need to be replaced. The performance of the proposed model and some other common algorithms are shown in Section 4