DE112018003914T5 - A real-time perception system and method for the TBM drilling rock state - Google Patents

Abstract

The invention provides a real-time perception system and method for the TBM drilling rock condition to solve the problem that existing resources cannot effectively reflect the rock condition of the TBM drilling tunnel in real time to facilitate the selection of an appropriate drilling plan. TBM drilling parameters for hard rock tunnels and corresponding rock mass condition parameter data are collected, a data storage module is set up, a perception model for the rock machine relationship of TBM and a clustering algorithm are created via step-by-step regression to implement the classification of the rock mass quality. A calculation module core is formed. Rock mass information is inversely calculated in a model calculation module by reading current TBM drilling parameters during drilling, and rock mass information is displayed in real time on a visualization interface of a TBM host computer via a real time output display module. The present invention overcomes disadvantages such as difficult to obtain rock mass parameters, lagging traditional means and unknown rock conditions in front of tunnel areas, etc. The present invention reduces the energy consumption of TBM, ensures the safety of equipment and personnel, increases the efficiency of TBM drilling and improves safety and efficiency of TBM drilling significantly.

Description

Technical part

The invention relates to the technical field of TBM tunneling, particularly a real time perception system and method for the TBM drilling rock condition.

Background technology

TBM is an important technical equipment for tunnel construction, which integrates mechanical engineering, electronics and hydraulics. It can achieve one-time drilling and tunneling, loading of rock slag, tunnel wall support, etc. It has a high level of mechanization and automation, fast excavation speed, construction safety, and environmental friendliness and other significant advantages. In many countries around the world, it is widely used in hydropower, railways, coal mines, urban subways and other underground engineering structures.

Due to the limitation of time, cost, technical level and many other factors, the geological survey before the TBM tunnel construction cannot be very detailed and precise. During the construction process, people often encounter poor geological conditions that are not specified in the geological data. At the same time, information about the TBM rock mass condition such as compressive strength, connection conditions and other parameters is still obtained through a manual sketch on site, sampling and internal testing. This type of parameter perception method is relatively backward, and it is impossible to get the rock mass information in advance and in real time, making it difficult for TBM to adjust the drilling plan and control parameters in time in the event of a shift change or complex geological conditions. This leads to breakdowns, damage, scrap and even serious accidents like death. During TBM drilling, a large amount of data on device operating parameters such as thrust, torque, penetration, speed of the cutter head etc. is generated in real time. These data directly reflect the current quarry condition of the TBM drilling.

Summary of the invention

Given the technical problem that the existing information perception process for the TBM drill rock condition is relatively backward and cannot effectively reflect the TBM drill hole condition in real time to select the appropriate drill plan, the present invention provides a real time sensing system and method for the TBM - Drill bulk condition ready. It is based on the quantitative relationship of the interaction between rock machines in TBM tunneling and the real-time perception of the TBM drilling rock condition parameters according to the TBM drilling parameters to overcome the lack that existing technology cannot effectively reflect the rock condition in TBM tunneling in real time, to select the appropriate drilling plan.

• Ein Echtzeit-Wahrnehmungssystem für den TBM-Bohrgesteinsmassenzustand umfasst ein Datenspeicher-Lagermodul, ein Modellberechnungsmodul, ein Gesteinsmaschinen-Beziehungsmodell und ein Echtzeit-Ausgangsanzeigemodul. Das Datenspeicher-Lagermodul ist mit der Gesteinsmaschinendatenbank verbunden, das Datenspeicher-Lagermodul ist mit dem Gesteinsmaschinen-Beziehungsmodell verbunden, das Datenspeicher-Lagermodul und das Gesteinsmaschinen-Beziehungsmodell sind mit dem Modellberechnungsmodul verbunden. Das Modellberechnungsmodul ist mit dem aktuellen Bohrparameterspeicher der TBM verbunden, und das Modellberechnungsmodul ist mit dem Echtzeit-Ausgangsanzeigemodul verbunden.

To achieve the above purpose, the technical solution of the present invention is implemented as follows:

• A real-time perception system for the TBM drilling rock condition includes a data storage module, a model calculation module, a rock machine relationship model, and a real-time output display module. The data storage module is connected to the rock machine database, the data storage module is connected to the rock machine relationship model, the data storage module and the rock machine relationship model are connected to the model calculation module. The model calculation module is connected to the TBM's current drilling parameter memory and the model calculation module is connected to the real time output display module.

The rock machine database is used to store TBM drilling parameters and corresponding rock mass condition parameters. The rock machine database includes the rock mass parameter database, the rock machine database, and other TBM engineering databases. The rock mass parameter database, the rock machine database and other TBM engineering databases are all connected to the data storage storage module. The current drilling parameter memory transfers the current drilling parameters to the model calculation module in real time on TBM.

• Schritt 1: Erfassen Sie die TBM-Bohrparameter und Gesteinsmassenzustandsparameterdaten im TBM-Konstruktionsfall oder die TBM-Bohrparameter und Gesteinsmassenzustandsparameter des aktuell im Bau befindlichen TBM-Bautunnels. Bitte geben Sie TBM-Bohrparameter und Gesteinsmassenzustandsparameter in die Gesteinsmaschinendatenbank ein und erstellen Sie ein Datenspeicher-Lagermodul mit Gesteinsmaschinenzustandsparametern.
• Schritt 2: Entsprechend den im Datenspeicher-Lagermodul gespeicherten TBM-Bohrparametern und den entsprechenden Gesteinsmassenzustandsparametern werden ein schrittweiser Regressionsalgorithmus und ein Clustering-Algorithmus verwendet, um das Gesteinsmaschinen-Beziehungsmodell zu erstellen, das den Kern des Modellberechnungsmoduls bildet;
• Schritt 3: Das Modellberechnungsmodul kombiniert die aktuellen Bohrparameter auf der TBM und berechnet anhand des Gesteinsmaschine-Beziehungsmodells die Informationen zum Gesteinsmassenzustand der aktuellen Tunnelfläche der TBM in Echtzeit.
• Schritt 4: Das Modellberechnungsmodul überträgt die Druckfestigkeit der Gesteinsmasse (UCS), die Gelenkezahl pro Volumeneinheit (Jv) und den umgebenden Gesteinsgrad an das Echtzeit-Ausgangsanzeigemodul. Das Echtzeit-Ausgangsanzeigemodul zeigt die Druckfestigkeit der Gesteinsmasse (UCS), die Gelenkezahl pro Volumeneinheit (Jv) und den umgebenden Gesteinsgrad auf einer Visualisierungsschnittstelle des Hostcomputers von TBM an.

A real-time perception process for the TBM drilling rock state includes the following steps:

• Step 1: Collect the TBM drilling parameters and rock mass parameter data in the TBM design case or the TBM drilling parameters and rock mass parameters of the TBM construction tunnel currently under construction. Please enter TBM drilling parameters and rock mass condition parameters in the rock machine database and create a data storage module with rock machine condition parameters.
• Step 2: In accordance with the TBM drilling parameters stored in the data storage storage module and the corresponding rock mass condition parameters, a stepwise regression algorithm and a clustering algorithm are used to create the rock machine relationship model that forms the core of the model calculation module;
• Step 3: The model calculation module combines the current drilling parameters on the TBM and uses the rock machine relationship model to calculate the information about the rock mass status of the current tunnel area of the TBM in real time.
• Step 4: The model calculation module transfers the compressive strength of the rock mass (UCS), the number of joints per unit volume (Jv) and the surrounding rock grade to the real-time output display module. The real-time output display module shows the compressive strength of the rock mass (UCS), the number of joints per unit volume (Jv) and the surrounding rock grade on a visualization interface of the host computer from TBM.

The TBM drilling parameters include the operating parameters of the TBM, such as thrust, torque, and the control parameters, such as penetration and speed. The rock mass condition parameters include the compressive strength of the rock mass (UCS), the number of joints per unit volume (Jv) and the surrounding rock grade. The number of joints per unit volume (Jv) refers to the number of joints in the unit volume rock mass. The calculation formula is: J _v = Σ (1 / d _k ) + S _k / 5, where d _{k is} the distance between the joints of the kth group and S _{K is} the number of non-group-related joints per cubic rock mass of the kth group .

• Schritt 1: Bestimmen Sie den entsprechenden Gesteinsmassenintegritätskoeffizienten Kv unter Verwendung der Gelenkezahl pro Volumeneinheit (Jv). Die Korrelation zwischen der Gelenkezahl pro Volumeneinheit (Jv) und dem Gesteinsmassenintegritätskoeffizienten Kv ist in der folgenden Tabelle gezeigt.

Jv (Stücke/m3) <3 3~10 10~20 20∼35 >35 Kv >0,75 0,75 ~ 0,55 0,55 ~ 0,35 0,35 ~ 0,15 <0,15

• Schritt 2: Bitte berechnen Sie den Grundqualitätsindex BQ der Gesteinsmasse gemäß der Druckfestigkeit der Gesteinsmasse (UCS) und dem Gesteinsmassenintegritätskoeffizienten k_V des quantitativen Index des umgebenden Gesteinsklassifizierungsfaktors. Die Berechnungsformel lautet: BQ = 90 + 3UCS + 250 K_V. Beachten Sie außerdem die folgenden Einschränkungen: ① Wenn UCS> 90 K_V + 30 ist, benutzen Sie die Berechnungsformel UCS = 90 K_V + 30, um den Grundqualitätsindex (BQ-Wert) des umgebenden Gesteins zu berechnen. ② Wenn K_V> 0,04UCS + 0,4 ist, wird der Grundqualitätsindex BQ-Wert des umgebenden Gesteins mit K_V = 0,04 UCS + 0,4 berechnet;
• Schritt ③: Bestimmen Sie gemäß dem Umfang des Grundqualitätsindex BQ der Gesteinsmasse den umgebenden Gesteinsgrad wie folgt:

Grad des umgebenden Gesteins I II III IV V Grundqualitätsindex der Gesteinsmasse (BQ-Wert) >550 550 ~ 451 450 ~ 351 350 ~ 251 <250 The surrounding rock grade consists of using the compressive strength of the rock mass (UCS) and the number of joints per unit volume (Jv) to calculate the basic quality index (BQ value) of the surrounding rock to classify the surrounding rock. The steps are as follows:

• Step 1: Determine the corresponding rock mass integrity coefficient Kv using the number of joints per unit volume (Jv). The correlation between the number of joints per unit volume (Jv) and the rock mass integrity coefficient Kv is shown in the following table.

Jv (pieces / m3) <3 3 ~ 10 10 ~ 20 20∼35 > 35 Kv > 0.75 0.75 ~ 0.55 0.55 ~ 0.35 0.35 ~ 0.15 <0.15

• Step 2: Please calculate the basic quality index BQ of the rock mass according to the compressive strength of the rock mass (UCS) and the rock mass integrity coefficient k _{V of} the quantitative index of the surrounding rock classification factor. The calculation formula is: BQ = 90 + 3UCS + 250 K _V. Also note the following restrictions: ① If UCS> 90 K _V + 30, use the calculation formula UCS = 90 K _V + 30 to calculate the basic quality index (BQ value) of the surrounding rock. ② If K _V > 0.04UCS + 0.4, the basic quality index BQ value of the surrounding rock is calculated with K _V = 0.04 UCS + 0.4;
• Step ③: Determine the surrounding rock grade according to the scope of the basic quality index BQ of the rock mass as follows:

Degree of the surrounding rock I. II III IV V Basic quality index of the rock mass (BQ value) > 550 550 ~ 451 450 ~ 351 350 ~ 251 <250

• ① Erstellen des Geräteparametermodells: Erstellen Sie das Beziehungsmodell zwischen dem Gerätebetriebsparameter, wie Schubkraft und dem Steuerparameter, wie Durchdringung im ansteigenden Abschnitt der TBM-Bohrparameter unter verschiedenen Gesteinsmassenbedingungen. Die Regressionsanpassungsformel der Schubkraft eines einzelnen Fräsers lautet: F = a x P + b, a ist der Einflusskoeffizient der Durchdringung auf die Schubkraft eines einzelnen Fräsers, b ist der Schwellenwert für das Gesteinbrechen mit Schneidwerkzeugen, P ist die Durchdringung;
• ② Erstellen Sie das Beziehungsmodell zwischen dem Einflusskoeffizient (a) der Durchdringung auf die Schubkraft eines einzelnen Fräsers, dem Schwellenwert für das Gesteinbrechen mit Schneidwerkzeugen (b) und der Druckfestigkeit der Gesteinsmasse (UCS) und der Gelenkezahl pro Volumeneinheit (Jv) im Gesteinsmassenzustandsparameter: Die Regressionsanpassungsformel für die Funktion zwischen dem Einflusskoeffizient (a) der Durchdringung auf die Schubkraft eines einzelnen Fräsers und der Gelenkezahl pro Volumeneinheit (Jv) lautet: a=f (Jv) =po X Jv²+p1 X Jv+p2, wobei p0, p1, p2 in der Formel die Anpassungskonstanten sind und f die Funktion ist. Der Schwellenwert für das Gesteinbrechen mit Schneidwerkzeugen (b) ist der minimale Schwellwert des Fräsers, das in die Gesteinsmasse eindringt und die Vertiefung erzeugt. Wenn p = 1 ist, ist die Schubkraft eines einzelnen Fräsers F= a + b, der verwendet wird, um die Tunnellierbarkeitseigenschaften der Gesteinsmasse zu messen. Die Regressionsanpassungsformel lautet: a+b=g(UCS, Jv)=p3 X UCS+p4 X Jv+p5, wobei p3, p4, p5 in der Formel Anpassungskonstanten sind und g Funktion ist.

The procedure for creating a rock machine relationship model through a stepwise regression algorithm is as follows:

• ① Creating the device parameter model: Create the relationship model between the device operating parameter, such as thrust and the control parameter, such as penetration in the rising section of the TBM drilling parameters under different rock mass conditions. The regression adjustment formula of the shear force of a single milling cutter is: F = ax P + b, a is the coefficient of influence of the penetration on the shear force of a single milling cutter, b is the threshold value for rock breaking with cutting tools, P is the penetration;
• ② Create the relationship model between the coefficient of influence (a) of penetration on the thrust of an individual milling cutter, the threshold value for rock breaking with cutting tools (b) and the compressive strength of the rock mass (UCS) and the number of joints per unit volume (Jv) in the rock mass condition parameter: The Regression adaptation formula for the function between the influence coefficient (a) of the penetration on the thrust force of an individual milling cutter and the number of joints per unit volume (Jv) is: a = f (Jv) = po X Jv ² + p1 X Jv + p2, where p0, p1 , p2 in the formula are the adjustment constants and f is the function. The threshold value for rock breaking with cutting tools (b) is the minimum threshold value of the milling cutter, which penetrates the rock mass and creates the depression. If p = 1, the thrust of a single cutter is F = a + b, which is used to measure the tunnelability properties of the rock mass. The regression fit formula is: a + b = g (UCS, Jv) = p3 X UCS + p4 X Jv + p5, where p3, p4, p5 in the formula are fit constants and g is a function.

• ① Verwenden Sie die Geräteparameter in der Gesteinsmaschinendatenbank, um das Verhältnis (FPI) von Schubkraft eines einzelnen Fräsers zur Durchdringung und das Verhältnis (TPI) des Schneidkopfdrehmoments zur Durchdringung zu berechnen. Bitte verwenden Sie das Verhältnis (FPI) von Schubkraft eines einzelnen Fräsers zur Durchdringung und das Verhältnis (TPI) des Schneidkopfdrehmoments zur Durchdringung als Probendatenbank.
• ② Das Verhältnis (FPI) von Schubkraft eines einzelnen Fräsers zur Durchdringung und das Verhältnis (TPI) des Schneidkopfdrehmoments zur Durchdringung werden zufällig aus der Gesteinsmaschinendatenbank als Proben-Massenschwerpunkt jedes umgebenden Gesteinsgrades ausgewählt, um ein zweidimensionales Koordinatensystem (FPI_(n), TPI_(n)) zu bilden. n ist der umgebende Gesteinsgrad I, II, III, IV, V, und FPI_(n) und TPI_(n) stellen jeweils die Werte von FPI und TPI der TBM-Bohrparameter unter der Bedingung eines zufällig ausgewählten umgebenden Gesteins des umgebenden Gesteinsgrades I bis V aus der Gesteinsmaschinendatenbank dar;
• ③ Berechnen Sie die umgebende Gesteinskategorie der aktuellen Probe (TPI(i), TPI(ix) in der Probendatenbank: $c^{\left(i\right)}=\text{arg }\underset{J}{{\displaystyle \text{min}}}{\Vert x^{\left(i\right)}-{\mu }_j\Vert }^2,c^{\left(i\right)}.$
  
  c⁽ⁱ⁾ repräsentiert den umgebenden Gesteinsgrad des Massenschwerpunkts, der der aktuellen Probe (FPI_(n), TPI_(n)) am nächsten liegt. x⁽ⁱ⁾ repräsentiert den aktuellen Koordinatenpunkt (FPI_(n), TPI_(n)). µ_j ist der Proben-Massenschwerpunkt jedes umgebenden Gesteinsgrades. FPI_(n) und TPI_(n) stellen die FPI- und TPI-Werte der TBM-Bohrparameter dar, die in der aktuellen Berechnungsprobe i enthalten sind;
• ④ Berechnen Sie mit zunehmender Probengröße den Proben-Massenschwerpunkt des Verhältnisses (FPI) von Schubkraft eines einzelnen Fräsers zur Durchdringung jedes umgebenden Gesteinsgrades und des Verhältnisses (TPI) des Schneidkopfdrehmoments zur Durchdringung neu: ${\mu }_j=\frac{{\displaystyle {\sum }_{i=1}^{m}1\left\{c^{\left(i\right)}=j\right\}{x}^{\left(i\right)}}}{{\displaystyle {\sum }_{i=1}^{m}1\left\{c^{\left(i\right)}=j\right\}}},$
  
  m ist die Anzahl der Proben von FPI und TPI unter der Bedingung des gleichen umgebenden Gesteinsgrades. 1 im Zähler-Nenner repräsentiert die Probenpunkte der TBM-Bohrparameter FPI und TPI unter den Bedingungen des gleichen umgebenden Gesteinsgrades. ${\displaystyle {\sum }_{i=1}^{m}1\left\{c^{\left(i\right)}=j\right\}}$
  
  repräsentiert die Anzahl der Probenpunkte der TBM-Bohrparameter FPI und TPI unter den Bedingungen des gleichen umgebenden Gesteinsgrades. ${\displaystyle {\sum }_{i=1}^{m}1\left\{c^{\left(i\right)}=j\right\}}{x}^{\left(i\right)}$
  
  ist die Summe aller Probenpunkte unter den Bedingungen dieses umgebenden Gesteinsgrades;
• ⑤ Wiederholen Sie die obigen Schritte ③ ∼ ④, bis sich die Position des Massenschwerpunkts nicht mehr ändert oder die Änderung sehr klein ist und der Verteilungsbereich des Verhältnisses (FPI) von Schubkraft eines einzelnen Fräsers zur Durchdringung jedes umgebenden Gesteinsgrades und des Verhältnisses (TPI) des Schneidkopfdrehmoments zur Durchdringung und die Position des Massenschwerpunkts µj unter den Bedingungen des jeweiligen umgebenden Gesteinsgrades in der Datenbank können ermittelt werden.

The clustering algorithm is used to establish the relationship between the surrounding rock grade and the TBM drilling parameters by calculating the distribution range of the TBM drilling parameters under different conditions of the surrounding rock grade. The steps are as follows:

• ① Use the device parameters in the rock machine database to calculate the ratio (FPI) of thrust of a single cutter to penetration and the ratio (TPI) of cutting head torque to penetration. Please use the ratio (FPI) of the thrust of a single milling cutter to the penetration and the ratio (TPI) of the cutting head torque to the penetration as a sample database.
• ② The ratio (FPI) of thrust force of a single milling cutter to penetration and the ratio (TPI) of the cutting head torque to penetration are randomly selected from the rock machine database as the sample mass center of gravity of each surrounding rock grade to create a two-dimensional coordinate system (FPI _(n) , TPI _{(n )} ) to form. n is the surrounding rock grade I, II, III, IV, V, and FPI _(n) and TPI _(n) each represent the values of FPI and TPI of the TBM drilling parameters under the condition of a randomly selected surrounding rock of the surrounding rock grade I bis V from the rock machine database;
• ③ Calculate the surrounding rock category of the current sample (TPI (i), TPI (ix) in the sample database: $c^{\left(i\right)}=\text{bad}\underset{J}{{\displaystyle \text{min}}}{\Vert x^{\left(i\right)}-{\mu }_j\Vert }^{\mathrm{2nd}},c^{\left(i\right)}.$
  
  c ⁽ⁱ⁾ represents the surrounding rock level of the center of gravity that is closest to the current sample (FPI _(n) , TPI _(n) ). x ⁽ⁱ⁾ represents the current coordinate point (FPI _(n) , TPI _(n) ). µ _j is the sample mass center of gravity of each surrounding rock grade. FPI _(n) and TPI _(n) represent the FPI and TPI values of the TBM drilling parameters contained in the current sample i;
• ④ With increasing sample size, recalculate the sample mass center of gravity of the ratio (FPI) of the thrust force of a single milling cutter to penetrate every surrounding rock grade and the ratio (TPI) of the cutting head torque to the penetration: ${\mu }_j=\frac{{\displaystyle {\sum }_{i=1}^{m}1\left\{c^{\left(i\right)}=j\right\}{x}^{\left(i\right)}}}{{\displaystyle {\sum }_{i=1}^{m}1\left\{c^{\left(i\right)}=j\right\}}},$
  
  m is the number of samples of FPI and TPI under the condition of the same surrounding rock grade. 1 in the numerator denominator represents the sample points of the TBM drilling parameters FPI and TPI under the conditions of the same surrounding rock grade. ${\displaystyle {\sum }_{i=1}^{m}1\left\{c^{\left(i\right)}=j\right\}}$
  
  represents the number of sample points of the TBM drilling parameters FPI and TPI under the conditions of the same surrounding rock grade. ${\displaystyle {\sum }_{i=1}^{m}1\left\{c^{\left(i\right)}=j\right\}}{x}^{\left(i\right)}$
  
  is the sum of all sample points under the conditions of this surrounding rock grade;
• ⑤ Repeat the above steps ③ ∼ ④ until the position of the center of gravity no longer changes or the change is very small and the range of distribution of the ratio (FPI) of thrust of a single cutter to penetrate each surrounding rock grade and the ratio (TPI) of Cutting head torque for penetration and the position of the center of gravity µj under the conditions of the respective surrounding rock grade can be determined in the database.

• Schritt 1: Das Modellberechnungsmodul liest die Schubkraft (F) eines einzelnen Fräsers und die Durchdringung (P) des Zirkulationsanstiegsabschnitts des normalen TBM-Bohrens. Bitte nehmen Sie eine lineare Anpassung gemäß der Form des Geräteparametermodells F=aXP+b vor, um den Einflusskoeffizienten (a) der Durchdringung auf die Schubkraft eines einzelnen Fräsers und den Schwellenwert (b) für das Gesteinbrechen mit Schneidwerkzeugen zu erhalten.
• Schritt 2: Bitte setzen Sie den in Schritt 1 erhaltenen Einflusskoeffizienten (a) der Durchdringung auf die Schubkraft eines einzelnen Fräsers und den Schwellenwert (b) für das Gesteinbrechen mit Schneidwerkzeugen in die Formel a=po X Jv²+p1 X Jv+p2, a+b=p3 X UCS-p4 X Jv+p5 ein, um die Druckfestigkeit der Gesteinsmasse (UCS) und die Gelenkezahl pro Volumeneinheit (Jv) zu berechnen;
• Schritt 3: Verwenden Sie den in Schritt 2 erhaltenen Wert für die Gelenkezahl pro Volumeneinheit (Jv) und berechnen Sie den entsprechenden Gesteinsmassenintegritätskoeffizienten Kv durch Interpolationsverfahren gemäß der Korrelation zwischen der Gelenkezahl pro Volumeneinheit (Jv) und dem Gesteinsmassenintegritätskoeffizienten (Kv).
• Schritt 4: Verwenden Sie die in Schritt 2 erhaltene Druckfestigkeit der Gesteinsmasse (UCS) und den in Schritt 3 erhaltenen Kv-Wert des Gesteinsmassenintegritätskoeffizienten in der Berechnungsformel des Grundqualitätsindex (BQ) der Gesteinsmasse: BQ=90+3UCS+250Kv, und berechnen Sie den Grundqualitätsindex (BQ-Wert) der Gesteinsmasse. Wenn UCS> 90Kv + 30 ist, wird außerdem der Grundqualitätsindex (BQ-Wert) der Gesteinsmasse mit der Brechnungsformel UCS = 90Kv + 30 berechnet. Wenn Kv> 0,04UCS+0,4 ist, sollte der Grundqualitätsindex BQ der Gesteinsmasse mit der Brechnungsformel Kv=0,04UCS+0,4 berechnet werden;
• Schritt 5: Bestimmen Sie den umgebenden Gesteinsgrad gemäß dem in Schritt 4 berechneten Umfang des Grundqualitätsindex (des BQ-Wertes) der Gesteinsmasse gemäß der Beziehung zwischen dem Grundqualitätsindex (BQ-Wert) der Gesteinsmasse und dem umgebenden Gesteinsgrad.

The stepwise regression algorithm is used to calculate the rock mass information in the model calculation module as follows:

• Step 1: The model calculation module reads the thrust (F) of a single cutter and the penetration (P) of the circulation increase section of normal TBM drilling. Please make a linear adjustment in accordance with the form of the device parameter model F = aXP + b in order to obtain the influence coefficient (a) of the penetration on the thrust force of an individual milling cutter and the threshold value (b) for rock breaking with cutting tools.
• Step 2: Please set the coefficient of influence (a) of the penetration obtained in step 1 on the thrust of an individual milling cutter and the threshold value (b) for rock breaking with cutting tools in the formula a = po X Jv ² + p1 X Jv + p2, a + b = p3 X UCS-p4 X Jv + p5 to calculate the compressive strength of the rock mass (UCS) and the number of joints per unit volume (Jv);
• Step 3: Use the joint number per unit volume (Jv) value obtained in step 2 and calculate the corresponding rock mass integrity coefficient Kv by interpolation method according to the correlation between the joint number per unit volume (Jv) and the rock mass integrity coefficient (Kv).
• Step 4: Use the rock mass compressive strength (UCS) obtained in step 2 and the Kv value of the rock mass integrity coefficient obtained in step 3 in the calculation formula of the basic quality index (BQ) of the rock mass: BQ = 90 + 3UCS + 250Kv, and calculate the Basic quality index (BQ value) of the rock mass. If UCS> 90Kv + 30, the basic quality index (BQ value) of the rock mass is also calculated using the calculation formula UCS = 90Kv + 30. If Kv> 0.04UCS + 0.4, the basic quality index BQ of the rock mass should be calculated using the formula Kv = 0.04UCS + 0.4;
• Step 5: Determine the surrounding rock grade according to the extent of the basic quality index (BQ value) of the rock mass calculated in step 4 according to the relationship between the basic quality index (BQ value) of the rock mass and the surrounding rock grade.

• Schritt 1: Das Modellberechnungsmodul liest die aktuellen TBM-Bohrparameter im aktuellen Bohrparameterspeicher, einschließlich Schubkraft, Drehmoment und Durchdringung.
• Schritt 2: Das Modellberechnungsmodul berechnet das Verhältnis FPI (neu) von Schubkraft (F) eines einzelnen Fräsers zur Durchdringung und des Verhältnisses TPI (neu) des Schneidkopfdrehmoments (T) zur Durchdringung (P) der aktuellen TBM-Bohrparameter.
• Schritt 3: Berechnen Sie im zweidimensionalen Koordinatensystem (FPI_(n), TPI_(n) ) den Abstand zwischen dem Strom (FPI (neu), TPI (neu)) und dem Massenschwerpunkt µj der umgebenden Gesteinsproben aller Klassen, und der umgebende Gesteinsgrad, der dem Massenschwerpunkt in der Mindestentfernung entspricht, ist der aktuelle Zustand der TBM-Bohrgesteinsmasse.

A clustering algorithm is used in the model calculation module to calculate the classification of the rock mass quality. The steps are as follows:

• Step 1: The model calculation module reads the current TBM drilling parameters in the current drilling parameter memory, including thrust, torque and penetration.
• Step 2: The model calculation module calculates the ratio FPI (new) of the thrust (F) of a single milling cutter to the penetration and the ratio TPI (new) of the cutting head torque (T) to the penetration (P) of the current TBM drilling parameters.
• Step 3: Use the two-dimensional coordinate system (FPI _(n) , TPI _(n) ) to calculate the distance between the current (FPI (new), TPI (new)) and the center of gravity µj of the surrounding rock samples of all classes, and the surrounding rock grade, which corresponds to the center of gravity in the minimum distance, is the current state of the TBM drilling rock mass.

The invention provides a real time perception method for the rock mass condition. In accordance with the accumulated equipment drilling parameters and the rock machine database for the corresponding rock mass status in the TBM construction, the perception model for the rock machine relationship of TBM is created by a step-by-step regression method and the quality classification of TBM rock mass is realized using a clustering algorithm. The above two methods complement each other. It can simultaneously sense and predict the current TBM drilling rock condition parameters according to the drilling parameters of the equipment, including rock mass strength, number of joints per unit volume, and the surrounding rock grade. This compensates for the difficulties in determining parameters, the backwardness in determining parameters and the shortcomings of unknown rock mass conditions in front of the tunnel area under the conditions of the traditional rock mass. The invention provides a rock mass sensing system. It gets the Rock mass condition parameters by writing the current TBM drilling parameters and displaying them on a TBM host computer visualization interface that can be used by TBM main drivers to adjust the current drilling plan, select an appropriate drilling plan and optimize the drilling parameters, TBM energy consumption lower, ensure the safety of equipment and personnel, improve the efficiency of TBM drilling and significantly improve the safe and efficient drilling ability of TBM.

The invention solves the problem of quantitative real-time perception of the rock mass condition in TBM tunnel construction and solves the problems of "inaccurate, slow and incomplete measurement" in the dynamic examination of the condition parameters of the drilled rock mass and provides the basis for ensuring safe and efficient tunneling of TBM .

Figure list

• 1 zeigt die Änderungskurve der TBM-Bohrparameter (Schubkraft, Drehmoment, Durchdringung usw.) mit der Zeit während des normalen TBM-Bohrens.
• 2 zeigt die Klassifizierung der Gesteinsmassenqualität durch einen Clustering-Algorithmus gemäß der vorliegenden Erfindung.
• 3 ist ein Arbeitsablaufdiagramm der vorliegenden Erfindung.

In order to explain the embodiments of the present invention or the technical solutions in the prior art more clearly, a brief introduction is given below to the figures which are required in the embodiments or in the description of the prior art. Obviously, the figures in the following description are only a few embodiments of the present invention. For the ordinary technicians in the field, other figures according to these figures can be obtained without creative work.

• 1 shows the change curve of TBM drilling parameters (thrust, torque, penetration, etc.) over time during normal TBM drilling.
• 2nd shows the classification of the rock mass quality by a clustering algorithm according to the present invention.
• 3rd Figure 11 is a work flow diagram of the present invention.

Specific embodiment

The technical solution of the present utility model is clearly and completely described with the aid of the attached figures. Obviously, the described embodiment is only part of the embodiments of the utility model, not all of them. Based on the embodiment of the utility model, all other embodiments obtained by ordinary technicians in the field without creative work belong to the scope of the present utility model.

As in 3rd shown, a real-time rock mass sensing system for TBM drilling is installed in the TBM host computer, which includes a data storage module, a model calculation module, a rock machine relationship model, and a real-time output display module. The data storage module is connected to the rock machine database, the data storage module is connected to the rock machine relationship model, the data storage module and the rock machine relationship model are connected to the model calculation module. The model calculation module is connected to the TBM's current drilling parameter memory and the model calculation module is connected to the real time output display module.

The rock machine database is used to store TBM drilling parameters and corresponding rock mass condition parameters. The rock machine database includes the rock mass parameter database, the rock machine database, and other TBM engineering databases. The rock mass parameter database, the rock machine database and other TBM engineering databases are all connected to the data storage storage module. The rock machine database uses TBM's host computer to regularly collect and store the design database of several TBM construction projects, including TBM drilling parameters and corresponding rock mass parameters. It includes, but is not limited to, TBMs of the same type or similar geological excavations. The current drilling parameter memory receives technical data from the current TBM host computer at a certain interval. The current drilling parameter memory transfers the current drilling parameters to the model calculation module in real time on TBM.

The model calculation module transmits the rock mass condition parameter data and the TBM drilling parameter data from the data storage module. It uses a stepwise regression algorithm and a clustering algorithm to create the rock machine relationship model. By reading the current TBM drilling parameters in the current drilling parameter memory in real time, the Rock mass condition parameters such as compressive strength, number of joints per unit volume and the surrounding rock grade etc. are calculated in real time. The real-time output display module outputs the current rock mass condition parameters obtained by the step regression algorithm and the clustering algorithm in the model calculation module, evaluates the current surrounding rock grade comprehensively and outputs the results to the visualization interface.

• Schritt 1: Bitte erfassen Sie die TBM-Bohrparameter und Gesteinsmassenzustandsparameter im TBM-Konstruktionsfall oder die TBM-Bohrparameter und Gesteinsmassenzustandsparameter des aktuell im Bau befindlichen TBM-Bautunnels. Bitte geben Sie TBM-Bohrparameter und Gesteinsmassenzustandsparameter in die Gesteinsmaschinendatenbank ein und erstellen Sie das Datenspeicher-Lagermodul der Gesteinsmaschinenzustandsparameter.

As in 3rd shown, a real-time perception method for the TBM drilling rock state is characterized by comprising the following steps:

• Step 1: Please record the TBM drilling parameters and rock mass status parameters in the TBM construction case or the TBM drilling parameters and rock mass status parameters of the TBM construction tunnel currently under construction. Please enter TBM drilling parameters and rock mass condition parameters in the rock machine database and create the data storage module of the rock machine condition parameters.

The more data that comes from the rock machine database, the better the postprocessing of the current rock mass. Therefore, we should collect the data from the TBM drilling parameters and the rock mass parameters as much as possible, but this increases the calculation amount.

TBM drilling parameters include operating parameters such as thrust, torque, and control parameters such as penetration and speed of TBM. These parameters can be obtained directly from the TBM host computer. The rock mass condition parameters include the compressive strength of the rock mass (UCS), the number of joints per unit volume (Jv) and the surrounding rock grade. The compressive strength of the rock mass (UCS) is determined by coring on site and by carrying out a laboratory test of the rock compressive strength or by a detailed geological exploration report. Number of joints per unit volume (Jv) refers to the number of joints in a unit volume of the rock mass, which is determined by counting the distance between the joints and the number of joints in the sketch of the tunnel area and according to the calculation formula J _v = Σ (1 / d _k ) + S _k / 5 of the number of joints per unit volume (Jv) of the rock mass can be obtained. Among these, d _{k is} the distance of the kth group from joints and s _k is the number of non-group-related joints per cubic rock mass of the kth group. The surrounding rock grade is determined by a detailed geological exploration report, or the basic quality index (BQ value) of the surrounding rock is calculated by the compressive strength of the rock mass (UCS) and the number of joints per unit volume (Jv) to classify the surrounding rock.

• Schritt 1: Bestimmen Sie den entsprechenden Gesteinsmassenintegritätskoeffizienten Kv unter Verwendung der Gelenkezahl pro Volumeneinheit (Jv). Die Korrelation zwischen der Gelenkezahl pro Volumeneinheit (Jv) und dem Gesteinsmassenintegritätskoeffizienten Kv ist in Tabelle 1 gezeigt.

Tabelle 1 Vergleichstabelle des Gesteinsmassenintegritätskoeffizienten Kv, bestimmt durch die Gelenkezahl pro Volumeneinheit (Jv) Jv (Stücke/m³) <3 3-10 10 -20 20-35 >35 Kv >0,75 0,75 ~ 0.55 0,55 ~ 0,35 0,35 ~ 0,15 <0,15

• Schritt 2: Berechnen Sie den Grundqualitätsindex (BQ-Wert) der Gesteinsmasse gemäß quantitativem Index der umgebenden Gesteinsklassifizierungsfaktoren wie die Druckfestigkeit der Gesteinsmasse (UCS) (Einheit: MPa) und die Gesteinsmassenintegritätskoeffizienten Kv. Die Berechnungsformel lautet: BQ=90+3UCS+250Kv. Folgende einschränkende Bedingungen sind zu beachten: Wenn UCS>90Kv+30 beträgt, wird der Grundqualitätsindex BQ des umgebenden Gesteins mit UCS=90Kv+30 berechnet. ② Wenn Kv>0,04UCS+0,4 ist, wird der Grundqualitätsindex (BQ-Wert) des umgebenden Gesteins mit Kv=0,04UCS+0,4 berechnet.
• Schritt 3: Bestimmen Sie anhand des Grundqualitätsindex-BQ-Bereichs der Gesteinsmasse den umgebenden Gesteinsgrad gemäß Tabelle 2.

Tabelle 2 Beziehung zwischen dem umgebenden Gesteinsgrad und dem Grundqualitätsindex der Gesteinsmasse Umgebender Gesteinsgrad I II III IV V Grundqualitätsindex der Gesteinsmasse (BQ-Wert) >550 550 ∼ 451 450 ∼ 351 350 ~ 251 <250

• Schritt 2: Entsprechend den im Datenspeicher-Lagermodul gespeicherten TBM-Bohrparametern und den entsprechenden Gesteinsmassenzustandsparametern werden ein schrittweiser Regressionsalgorithmus und ein Clustering-Algorithmus verwendet, um das Gesteinsmaschinen-Beziehungsmodell zu erstellen, das den Kern des Modellberechnungsmoduls bildet.

This invention classifies the surrounding rock according to the basic quality index (BQ value) of the rock mass in the national standard. The surrounding rock straight line is used to calculate the basic quality index (BQ value) of the surrounding rock using the compressive strength of the rock mass (UCS) and the number of joints per unit volume (Jv) in order to classify the surrounding rock. The steps are as follows:

• Step 1: Determine the corresponding rock mass integrity coefficient Kv using the number of joints per unit volume (Jv). The correlation between the number of joints per unit volume (Jv) and the rock mass integrity coefficient Kv is shown in Table 1.

Table 1 Comparison table of the rock mass integrity coefficient Kv, determined by the number of joints per unit volume (Jv) Jv (pieces / m ³ ) <3 3-10 10 -20 20-35 > 35 Kv > 0.75 0.75 ~ 0.55 0.55 ~ 0.35 0.35 ~ 0.15 <0.15

• Step 2: Calculate the basic quality index (BQ value) of the rock mass according to the quantitative index of the surrounding rock classification factors such as the compressive strength of the rock mass (UCS) (unit: MPa) and the rock mass integrity coefficient Kv. The calculation formula is: BQ = 90 + 3UCS + 250Kv. The following restrictive conditions must be observed: If UCS> 90Kv + 30, the basic quality index BQ of the surrounding rock is calculated with UCS = 90Kv + 30. ② If Kv> 0.04UCS + 0.4, the basic quality index (BQ value) of the surrounding rock is calculated with Kv = 0.04UCS + 0.4.
• Step 3: Use the basic quality index BQ range of the rock mass to determine the surrounding rock grade according to Table 2.

Table 2 Relationship between the surrounding rock grade and the basic quality index of the rock mass Surrounding rock grade I. II III IV V Basic quality index of the rock mass (BQ value) > 550 550 ∼ 451 450 ∼ 351 350 ~ 251 <250

• Step 2: In accordance with the TBM drilling parameters stored in the data storage storage module and the corresponding rock mass condition parameters, a step-by-step regression algorithm and a clustering algorithm are used to create the rock machine relationship model that forms the core of the model calculation module.

The model calculation module realizes the real-time reading of TBM drilling parameters in the data storage module and in the current drilling parameter memory, the creation of a rock machine relationship model, the real-time calculation of rock parameters as well as the correction and optimization of rock machine state relationship model. The model calculation module can implement the real-time calculation of rock mass condition parameters for a TBM tunnel area.

During normal TBM drilling, thrust, torque, and penetration of the TBM can be divided into a rising section and a stable section, as in 1 shown. The TBM drilling parameters and the corresponding rock mass condition parameters in the ascending section are retrieved from the data storage module. The stepwise regression algorithm and the clustering algorithm are each used to create the correlation model between the state parameters of the rock mass and the state parameters of the TBM drilling.

• ① Erstellen des Geräteparametermodells: Erstellen Sie das Beziehungsmodell zwischen dem Gerätebetriebsparameter, wie Schubkraft und dem Steuerparameter, wie Durchdringung im ansteigenden Abschnitt der TBM-Bohrparameter unter verschiedenen Gesteinsmassenbedingungen. Die Regressionsanpassungsformel der Schubkraft eines einzelnen Fräsers lautet: F = a x P + b. Die Schubkraft des einzelnen Fräsers F wird erhalten, indem die Gesamtschubkraft der TBM durch die Anzahl der Werkzeuge dividiert wird, und a ist der Einflusskoeffizient der Durchdringung auf die Schubkraft eines einzelnen Fräsers, b ist der Schwellenwert für das Gesteinbrechen mit Schneidwerkzeugen, P ist die Durchdringung;
• ② Erstellen Sie das Beziehungsmodell zwischen dem Einflusskoeffizient (a) der Durchdringung auf die Schubkraft eines einzelnen Fräsers, dem Schwellenwert für das Gesteinbrechen mit Schneidwerkzeugen (b) und der Druckfestigkeit der Gesteinsmasse (UCS) und der Gelenkezahl pro Volumeneinheit (Jv) im Gesteinsmassenzustandsparameter. Der Einflusskoeffizient (a) der Durchdringung auf die Schubkraft eines einzelnen Fräsers repräsentiert das Inkrement der Schubkraft eines einzelnen Fräsers, das erforderlich ist, um die Durchdringung pro Einheit zu erhöhen. Je stärker die Gesteinsmasse gebrochen ist, desto geringer ist das zur Erhöhung der Durchdringung pro Einheit erforderliche Inkrement der Schubkraft, so dass der Einflusskoeffizient (a) der Durchdringung auf die Schubkraft eines einzelnen Fräsers eine Funktion der Anzahl der Gelenkezahl der Gesteinsmasse ist. Die Regressionsanpassungsformel für die Funktion zwischen dem Einflusskoeffizienten (a) der Durchdringung auf die Schubkraft eines einzelnen Fräsers und der Gelenkezahl pro Volumeneinheit (Jv) lautet: a=f (Jv) =po X Jv ²+p1 X Jv+p2, wobei Po, P1 und P2 Anpassungskonstanten sind. Der Schwellenwert für das Gesteinbrechen mit Schneidwerkzeugen (b) ist der minimale Schwellwert des Fräsers, das in die Gesteinsmasse eindringt und die Vertiefung erzeugt. Wenn p = 1 ist, ist die Schubkraft eines einzelnen Fräsers F= a + b. Es zeigt den Schubkraft, den das Fräser benötigt, wenn es eine effektive Durchdringung von 1 mm hat. Daher kann a + b verwendet werden, um die Tunnellierbarkeitseigenschaften der Gesteinsmasse zu messen, und seine Regressionsanpassungsformel lautet: a+b=g(UCS,Jv)=p3 X UCS+p4 X Jv+p5, wobei p3, p4, p5 Anpassungskonstanten sind. Sowohl f als auch g repräsentieren Funktionen. a=f(Jv) zeigt an, dass a eine Funktion von Jv ist, und a+b=g(UCS,Jv) zeigt an, dass a + b eine Funktion von der Druckfestigkeit der Gesteinsmasse (UCS) und der Gelenkezahl pro Volumeneinheit (Jv) ist.

The procedure for creating a rock machine relationship model through a stepwise regression algorithm is as follows:

• ① Creating the device parameter model: Create the relationship model between the device operating parameter, such as thrust and the control parameter, such as penetration in the rising section of the TBM drilling parameters under different rock mass conditions. The regression adjustment formula for the thrust of a single milling cutter is: F = ax P + b. The shear force of the individual milling cutter F is obtained by dividing the total thrust force of the TBM by the number of tools, and a is the coefficient of influence of the penetration on the shear force of a single milling cutter, b is the threshold value for rock breaking with cutting tools, P is the penetration ;
• ② Create the relationship model between the coefficient of influence (a) of penetration on the thrust of a single milling cutter, the threshold value for rock breaking with cutting tools (b) and the compressive strength of the rock mass (UCS) and the number of joints per unit volume (Jv) in the rock mass parameter. The coefficient of influence (a) of penetration on the thrust of a single cutter represents the increment of the thrust of a single cutter that is required to increase the penetration per unit. The more the rock mass is broken, the smaller the increment of the shear force required to increase the penetration per unit, so that the coefficient of influence (a) of the penetration on the shear force of an individual milling cutter is a function of the number of joints in the rock mass. The regression adjustment formula for the function between the influence coefficient (a) of the penetration on the thrust force of a single milling cutter and the number of joints per unit volume (Jv) is: a = f (Jv) = po X Jv ² + p1 X Jv + p2, where Po, P1 and P2 are adjustment constants. The threshold value for rock breaking with cutting tools (b) is the minimum threshold value of the milling cutter, which penetrates the rock mass and creates the depression. If p = 1, the thrust of a single cutter is F = a + b. It shows the thrust that the milling cutter needs when it has an effective penetration of 1 mm. Therefore, a + b can be used to measure the tunnelability properties of the rock mass, and its regression fit formula is: a + b = g (UCS, Jv) = p3 X UCS + p4 X Jv + p5, where p3, p4, p5 are fit constants . Both f and g represent functions. a = f (Jv) indicates that a is a function of Jv, and a + b = g (UCS, Jv) indicates that a + b is a function of the compressive strength of the rock mass (UCS) and the number of joints per unit volume (Jv) is.

The model created in the above two steps forms the rock machine relationship model.

• ① Verwenden Sie die Geräteparameter in der Gesteinsmaschinendatenbank, um das Verhältnis (FPI) von Schubkraft eines einzelnen Fräsers zur Durchdringung und das Verhältnis (TPI) des Schneidkopfdrehmoments zur Durchdringung zu berechnen. Bitte verwenden Sie das Verhältnis (FPI) von Schubkraft eines einzelnen Fräsers zur Durchdringung und das Verhältnis (TPI) des Schneidkopfdrehmoments zur Durchdringung als Probendatenbank.
• ② Das Verhältnis (FPI) von Schubkraft eines einzelnen Fräsers zur Durchdringung und das Verhältnis (TPI) des Schneidkopfdrehmoments zur Durchdringung werden zufällig aus der Gesteinsmaschinendatenbank als Proben-Massenschwerpunkt jedes umgebenden Gesteinsgrades ausgewählt, um ein zweidimensionales Koordinatensystem (FPI_(n), TPI_(n)) zu bilden. n ist der umgebende Gesteinsgrad I, II, III, IV, V, und FPI_(n) und TPI_(n) stellen jeweils die Werte von FPI und TPI der TBM-Bohrparameter unter der Bedingung eines zufällig ausgewählten umgebenden Gesteins des umgebenden Gesteinsgrades I bis V aus der Gesteinsmaschinendatenbank dar;
• ③Berechnen Sie die umgebende Gesteinskategorie der aktuellen Probe (FPI_(i), TPI_(i) in der Probendatenbank: $c^{\left(i\right)}=\text{arg }\underset{J}{{\displaystyle \text{min}}}{\Vert x^{\left(i\right)}-{\mu }_j\Vert }^2,c^{\left(i\right)}$
  
  . c⁽ⁱ⁾ repräsentiert den umgebenden Gesteinsgrad des Massenschwerpunkts, der der aktuellen Probe (FPI_(i), TPI_(i)) am nächsten liegt. x⁽ⁱ⁾ repräsentiert den aktuellen Koordinatenpunkt (FPI_(i), TPI_(i)). µ_j ist der Proben-Massenschwerpunkt jedes umgebenden Gesteinsgrades. FPI_(i) und TPI_(i) stellen die FPI- und TPI-Werte der TBM-Bohrparameter dar, die in der aktuellen Berechnungsprobe i enthalten sind;
• ④ Berechnen Sie mit zunehmender Probengröße den Proben-Massenschwerpunkt des Verhältnisses (FPI) von Schubkraft eines einzelnen Fräsers zur Durchdringung jedes umgebenden Gesteinsgrades und des Verhältnisses (TPI) des Schneidkopfdrehmoments zur Durchdringung neu: ${\mu }_J=\frac{{\displaystyle {\sum }_{i=1}^{m}1\left\{c^{\left(i\right)}=j\right\}{x}^{\left(i\right)}}}{{\displaystyle {\sum }_{i=1}^{m}1}\left\{c^{\left(i\right)}=j\right\}},$
  
  m ist die Anzahl der Proben von FPI und TPI unter der Bedingung des gleichen umgebenden Gesteinsgrades. 1 im Zähler-Nenner repräsentiert die Probenpunkte der TBM-Bohrparameter FPI und TPI unter den Bedingungen des gleichen umgebenden Gesteinsgrades. Der Nenner repräsentiert die Anzahl der Probenpunkte der TBM-Bohrparameter FPI und TPI unter den Bedingungen des gleichen umgebenden Gesteinsgrades. Der Zähler repräsentiert die Summe aller Probenpunkte unter den Bedingungen dieses umgebenden Gesteinsgrades;
• ⑤ Wiederholen Sie die obigen Schritte ③ ~ ④, bis sich die Position des Massenschwerpunkts nicht mehr ändert oder die Änderung sehr klein ist und der Verteilungsbereich des Verhältnisses (FPI) von Schubkraft eines einzelnen Fräsers zur Durchdringung jedes umgebenden Gesteinsgrades und des Verhältnisses (TPI) des Schneidkopfdrehmoments zur Durchdringung und die Position des Massenschwerpunkts µj unter den Bedingungen des jeweiligen umgebenden Gesteinsgrades in der Datenbank können ermittelt werden, wie in 2 gezeigt. Aus der 2 ist ersichtlich, dass die Verteilungsbereiche von FPI und TPI unterschiedlicher Grade des umgebenden Gesteins unterschiedlich sind. Die Beziehung zwischen dem umgebenden Gesteinsgrad und FPI und TPI besteht darin, dass der umgebende Gesteinsgrad des nächstgelegenen Massenschwerpunkts aus den aktuellen Bohrparametern (FPI, TPI) der umgebende Gesteinsgrad der aktuellen Bohrgesteinsmasse ist.
• Schritt 3: Das Modellberechnungsmodul kombiniert die aktuellen Bohrparameter auf der TBM und berechnet anhand des Gesteinsmaschine-Beziehungsmodells die Informationen zum Gesteinsmassenzustand der aktuellen Tunnelfläche der TBM in Echtzeit.

The clustering algorithm is used to establish the relationship between the surrounding rock grade and the TBM drilling parameters by calculating the distribution range of the TBM drilling parameters under different conditions of the surrounding rock grade. The steps are as follows:

• ① Use the device parameters in the rock machine database to calculate the ratio (FPI) of thrust of a single cutter to penetration and the ratio (TPI) of cutting head torque to penetration. Please use the ratio (FPI) of thrust of a single milling cutter to penetration and the ratio (TPI) of the cutting head torque to penetration as a sample database.
• ② The ratio (FPI) of thrust force of a single milling cutter to penetration and the ratio (TPI) of the cutting head torque to penetration are randomly selected from the rock machine database as the sample mass center of gravity of each surrounding rock grade to create a two-dimensional coordinate system (FPI _(n) , TPI _{(n )} ) to form. n is the surrounding rock grade I, II, III, IV, V, and FPI _(n) and TPI _(n) each represent the values of FPI and TPI of the TBM drilling parameters under the condition of a randomly selected surrounding rock of the surrounding rock grade I bis V from the rock machine database;
• ③Calculate the surrounding rock category of the current sample (FPI _(i) , TPI _(i) in the sample database: $c^{\left(i\right)}=\text{bad}\underset{J}{{\displaystyle \text{min}}}{\Vert x^{\left(i\right)}-{\mu }_j\Vert }^{\mathrm{2nd}},c^{\left(i\right)}$
  
  . c ⁽ⁱ⁾ represents the surrounding rock level of the center of gravity that is closest to the current sample (FPI _(i) , TPI _(i) ). x ⁽ⁱ⁾ represents the current coordinate point (FPI _(i) , TPI _(i) ). µ _j is the sample mass center of gravity of each surrounding rock grade. FPI _(i) and TPI _(i) represent the FPI and TPI values of the TBM drilling parameters included in current calculation sample i;
• ④ With increasing sample size, recalculate the sample mass center of gravity of the ratio (FPI) of the thrust force of a single milling cutter to penetrate every surrounding rock grade and the ratio (TPI) of the cutting head torque to the penetration: ${\mu }_J=\frac{{\displaystyle {\sum }_{i=1}^{m}1\left\{c^{\left(i\right)}=j\right\}{x}^{\left(i\right)}}}{{\displaystyle {\sum }_{i=1}^{m}1}\left\{c^{\left(i\right)}=j\right\}},$
  
  m is the number of samples of FPI and TPI under the condition of the same surrounding rock grade. 1 in the numerator denominator represents the sample points of the TBM drilling parameters FPI and TPI under the conditions of the same surrounding rock grade. The denominator represents the number of sample points of the TBM drilling parameters FPI and TPI under the conditions of the same surrounding rock grade. The counter represents the sum of all sample points under the conditions of this surrounding rock grade;
• ⑤ Repeat steps ③ ~ ④ above until the position of the center of gravity no longer changes or the change is very small and the range of distribution of the ratio (FPI) of thrust of a single milling cutter to penetrate each surrounding rock grade and the ratio (TPI) of Cutting head torque for penetration and the position of the center of mass µj under the conditions of the respective surrounding rock grade in the database can be determined, as in 2nd shown. From the 2nd it can be seen that the distribution ranges of FPI and TPI are different with different degrees of surrounding rock. The relationship between the surrounding rock grade and FPI and TPI is that the surrounding rock grade of the nearest center of gravity from the current drilling parameters (FPI, TPI) is the surrounding rock grade of the current drilling rock mass.
• Step 3: The model calculation module combines the current drilling parameters on the TBM and uses the rock machine relationship model to calculate the information about the rock mass status of the current tunnel area of the TBM in real time.

The model calculation module combines the current drilling parameters of the TBM construction and uses the rock machine relationship model created by the step regression algorithm and the clustering algorithm to calculate the rock mass condition parameters, including the compressive strength of the rock mass (UCS), the number of joints per unit volume (Jv) and the surrounding rock grade. With the continuous increase of the rock mass condition parameters and TBM drilling parameters in the data storage module, the rock machine relationship model in the calculation module is revised or optimized.

• Schritt 1: Das Modellberechnungsmodul liest die Daten (ungefähr 30 Datengruppen) wie Schubkraft (F) eines einzelnen Fräsers und die Durchdringung (P) (ungefähr 30 Sekunden) des Zirkulationsanstiegsabschnitts des normalen TBM-Bohrens. Bitte nehmen Sie eine lineare Anpassung gemäß der Form des Geräteparametermodells F=aXP+b vor, um den Einflusskoeffizienten (a) der Durchdringung auf die Schubkraft eines einzelnen Fräsers und den Schwellenwert (b) für das Gesteinbrechen mit Schneidwerkzeugen zu erhalten.
• Schritt 2: Bitte setzen Sie den in Schritt 1 erhaltenen Einflusskoeffizienten (a) der Durchdringung auf die Schubkraft eines einzelnen Fräsers und den Schwellenwert (b) für das Gesteinbrechen mit Schneidwerkzeugen in die Formel a=po X Jv²+p1 X Jv+p2, a+b=p3 X UCS-p4 X Jv+p5 ein, um die Druckfestigkeit der Gesteinsmasse (UCS) und die Gelenkezahl pro Volumeneinheit (Jv) zu berechnen;

The stepwise regression algorithm is adopted in the model calculation module in order to calculate the information on the rock mass status as follows:

• Step 1: The model calculation module reads the data (approximately 30 data groups) such as pushing force (F) of a single cutter and penetration (P) (approximately 30 seconds) of the circulation increase section of normal TBM drilling. Please make a linear adjustment in accordance with the form of the device parameter model F = aXP + b in order to obtain the influence coefficient (a) of the penetration on the thrust force of an individual milling cutter and the threshold value (b) for rock breaking with cutting tools.
• Step 2: Please set the coefficient of influence (a) of the penetration obtained in step 1 on the thrust of an individual milling cutter and the threshold value (b) for rock breaking with cutting tools in the formula a = po X Jv ² + p1 X Jv + p2, a + b = p3 X UCS-p4 X Jv + p5 to calculate the compressive strength of the rock mass (UCS) and the number of joints per unit volume (Jv);

• Schritt 3: Verwenden Sie den in Schritt 2 erhaltenen Wert für die Gelenkezahl pro Volumeneinheit (Jv) und berechnen Sie den entsprechenden Gesteinsmassenintegritätskoeffizienten Kv durch Interpolationsverfahren gemäß der Korrelation zwischen der Gelenkezahl pro Volumeneinheit (Jv) und dem Gesteinsmassenintegritätskoeffizienten (Kv).

The TBM drilling parameters and the corresponding rock mass condition parameters in the ascending section are retrieved from the data storage module and the corresponding adjustment constants P0, P1, P2, P3, P4 and P5 are obtained according to the stepwise regression algorithm. Different types of rock such as granite and limestone have different adaptation constants. In the specific embodiment, the adjustment constants P0, P1, P2, P3, P4 and P5 can be obtained by adjusting the adjustment constants P0, P1, P2, P3, P4 and P5 with the stepwise regression algorithm of the present invention according to the TBM construction data of the same rock type in FIG other projects or the design data of the excavated section of the current project that can be used to calculate the parameters of the rock mass in the current project.

• Step 3: Use the joint number per unit volume (Jv) value obtained in step 2 and calculate the corresponding rock mass integrity coefficient Kv by interpolation method according to the correlation between the joint number per unit volume (Jv) and the rock mass integrity coefficient (Kv).

verwendet.

• Schritt 4: Verwenden Sie die in Schritt 2 erhaltene Druckfestigkeit der Gesteinsmasse (UCS) und den in Schritt 3 erhaltenen Kv-Wert des Gesteinsmassenintegritätskoeffizienten in der Berechnungsformel des Grundqualitätsindex (BQ) der Gesteinsmasse: BQ=90+3UCS+250Kv, und berechnen Sie den Grundqualitätsindex (BQ-Wert) der Gesteinsmasse. Wenn UCS> 90Kv + 30 ist, wird außerdem der Grundqualitätsindex (BQ-Wert) der Gesteinsmasse mit der Brechnungsformel UCS = 90Kv + 30 berechnet. Wenn Kv> 0,04UCS+0,4 ist, sollte der Grundqualitätsindex BQ der Gesteinsmasse mit der Brechnungsformel Kv=0,04UCS+0,4 berechnet werden;
• Schritt 5: Bestimmen Sie den umgebenden Gesteinsgrad gemäß dem in Schritt 4 berechneten Umfang des Grundqualitätsindex (des BQ-Wertes) der Gesteinsmasse gemäß der Beziehung zwischen dem Grundqualitätsindex (BQ-Wert) der Gesteinsmasse und dem umgebenden Gesteinsgrad.

The interpolation method is a common method for calculating the difference in the ratio of proportions in mathematical theory. For example, if Jv = 3 ~ 10 in Table 1, Kv = 0.75-0.55. If Jv = 5 is calculated in step 2, the formula becomes $K_v=0.75-\frac{0.75-0.55}{\mathrm{10th}-\mathrm{3rd}}\times \left(5-\mathrm{3rd}\right)=0.69$

used.

• Step 4: Use the rock mass compressive strength (UCS) obtained in step 2 and the Kv value of the rock mass integrity coefficient obtained in step 3 in the calculation formula of the basic quality index (BQ) of the rock mass: BQ = 90 + 3UCS + 250Kv, and calculate the Basic quality index (BQ value) of the rock mass. If UCS> 90Kv + 30, the basic quality index (BQ value) of the rock mass is also calculated using the calculation formula UCS = 90Kv + 30. If Kv> 0.04UCS + 0.4, the basic quality index BQ of the rock mass should be calculated using the formula Kv = 0.04UCS + 0.4;
• Step 5: Determine the surrounding rock grade according to the extent of the basic quality index (BQ value) of the rock mass calculated in step 4 according to the relationship between the basic quality index (BQ value) of the rock mass and the surrounding rock grade.

• Schritt 1: Das Modellberechnungsmodul liest die aktuellen TBM-Bohrparameter im aktuellen Bohrparameterspeicher, einschließlich Schubkraft, Drehmoment und Durchdringung.
• Schritt 2: Das Modellberechnungsmodul berechnet das Verhältnis FPI (neu) von Schubkraft (F) eines einzelnen Fräsers zur Durchdringung und des Verhältnisses TPI (neu) des Schneidkopfdrehmoments (T) zur Durchdringung (P) der aktuellen TBM-Bohrparameter.
• Schritt 3: Berechnen Sie im zweidimensionalen Koordinatensystem (FPI_(n), TPI_(n) ) und unter den Bedingungen des umgebenden Gesteinsgrads aller Klassen (FPI, TPI), die durch den Clustering-Algorithmus in den Schritten ① bis ⑤ erhalten wurden, den Abstand zwischen dem aktuellen (FPI (neu), TPI (neu)) und dem Massenschwerpunkt µj der umgebenden Gesteinsproben aller Klassen, und der umgebende Gesteinsgrad, der dem Massenschwerpunkt in der Mindestentfernung entspricht, ist der aktuelle Zustand der TBM-Bohrgesteinsmasse.

In the model calculation module, the cluster algorithm is used to calculate the surrounding rock grade as follows:

• Step 1: The model calculation module reads the current TBM drilling parameters in the current drilling parameter memory, including thrust, torque and penetration.
• Step 2: The model calculation module calculates the ratio FPI (new) of the thrust (F) of a single milling cutter to the penetration and the ratio TPI (new) of the cutting head torque (T) to the penetration (P) of the current TBM drilling parameters.
• Step 3: Calculate in the two-dimensional coordinate system (FPI _(n) , TPI _(n) ) and under the conditions of the surrounding rock grade of all classes (FPI, TPI), which were obtained by the clustering algorithm in steps ① to ⑤ The distance between the current (FPI (new), TPI (new)) and the center of mass µj of the surrounding rock samples of all classes, and the surrounding rock grade, which corresponds to the center of gravity at the minimum distance, is the current state of the TBM drilling rock mass.

• Schritt 4: Das Modellberechnungsmodul überträgt die Druckfestigkeit der Gesteinsmasse (UCS), die Gelenkezahl pro Volumeneinheit (Jv) und den umgebenden Gesteinsgrad an das Echtzeit-Ausgangsanzeigemodul. Das Echtzeit-Ausgangsanzeigemodul zeigt die Druckfestigkeit der Gesteinsmasse (UCS), die Gelenkezahl pro Volumeneinheit (Jv) und den umgebenden Gesteinsgrad auf einer Visualisierungsschnittstelle des Hostcomputers von TBM an.

The clustering algorithm and the stepwise regression algorithm have a parallel relationship. The gradual regression algorithm can be used to calculate the compressive strength of the rock mass (UCS), the number of joints per unit volume (Jv) and the surrounding rock grade. The surrounding rock grade can be calculated using a clustering algorithm. If the surrounding grade of rock, as calculated by a stepwise regression algorithm and a clustering algorithm, is the same, it indicates that the TBM rock mass has this surrounding grade of rock. If the degree of the surrounding rock calculated using the two algorithms is different, this shows that the TBM drilling rock mass is in the transition section of two degrees of the surrounding rock.

• Step 4: The model calculation module transfers the compressive strength of the rock mass (UCS), the number of joints per unit volume (Jv) and the surrounding rock grade to the real-time output display module. The real-time output display module shows the compressive strength of the rock mass (UCS), the number of joints per unit volume (Jv) and the surrounding rock grade on a visualization interface of the host computer from TBM.

The real-time output display module displays the information on the state of the rock mass, which was obtained by the stepwise regression algorithm and the clustering algorithm, such as compressive strength of the rock mass (UCS), the number of joints per unit volume (Jv) and the surrounding rock grade on a visualization interface as a reference for the construction staff. The parameters such as the compressive strength of the rock mass (UCS), the number of joints per unit volume (Jv) and the surrounding rock grade are calculated using the step-by-step regression algorithm. The surrounding rock grade is calculated using a clustering algorithm. If the surrounding grade of rock obtained by the two algorithms is the same, this indicates that the TBM rock mass has this surrounding grade of rock. If the degree of the surrounding rock calculated using the two algorithms is different, this shows that the TBM drilling rock mass is in the transition section of two degrees of the surrounding rock.

The invention collects TBM drilling parameters of the hard rock tunnel and corresponding rock mass condition parameter data, creates a data storage module, creates a perception model for the rock machine relationship using a step-by-step regression algorithm, realizes the classification of the rock mass quality using a clustering algorithm and forms the core of the calculation module. In the model calculation module, the rock mass information is retrieved and inversely calculated by reading the current TBM drilling parameters in the tunnel project. In the real-time output display module, the rock mass information is displayed in real time on a visualization interface of the TBM host computer.

• (1) Die Informationen zum Gesteinsmassenzustand können schnell erhalten werden, und die Gesteinsmassenzustandsparameter des TBM-Bohrtunnels können in Echtzeit erfasst werden.
• (2) Die Wahrnehmungsgenauigkeit von Informationen über den Zustand der Gesteinsmasse ist hoch. Mit den aktuellen TBM-Bohrparametern und den entsprechenden Gesteinsmassenzustandsparametern des aktuellen Projekts, die im Datenspeicher-Lagermodul gespeichert sind, wird das Gesteinsmassenbeziehungsmodell kontinuierlich optimiert oder modifiziert, um die Wahrnehmungsgenauigkeit des Gesteinsmassenzustands zu verbessern.
• (3) Es ist einfach zu bedienen. Das System kann auf dem Hostcomputer von TBM installiert werden. Der Hostcomputer kann die aktuellen Informationen zum Gesteinsmassenzustand in Echtzeit anzeigen, wenn die TBM normal bohrt, was als Referenz für das TBM-Baupersonal verwendet werden kann.
• (4) Das TBM-Baupersonal kann den Bohrplan an den aktuellen Bohrgesteinszustand anpassen, die Bohrparameter optimieren, die Bohreffizienz verbessern, den Bauenergieverbrauch senken und die Bausicherheit gewährleisten.

The invention uses the TBM drilling parameters to assess the current state of rock mass information and other problems and can solve the difficulty of obtaining the current rock mass state parameters of the existing TBM construction and has the following characteristics:

• (1) The rock mass information can be obtained quickly, and the rock mass parameters of the TBM drilling tunnel can be captured in real time.
• (2) The perceptual accuracy of information about the state of the rock mass is high. With the current TBM drilling parameters and the corresponding rock mass status parameters of the current project, which are stored in the data storage module, the rock mass relationship model is continuously optimized or modified in order to improve the perception accuracy of the rock mass status.
• (3) It is easy to use. The system can be installed on the TBM host computer. The host computer can display the current rock mass information in real time when the TBM is drilling normally, which can be used as a reference for TBM construction personnel.
• (4) TBM construction personnel can adapt the drilling plan to the current state of the drilling rock, optimize the drilling parameters, improve drilling efficiency, reduce construction energy consumption and ensure construction safety.

The above is only a preferred embodiment of the present invention and does not limit this invention. Any modification, equivalent replacement, improvement, etc. made in the spirit and principle of the present invention are included within the scope of the invention.

Claims (9)

A real-time perception system for the TBM drilling rock condition , characterized in that it comprises a data storage module, a model calculation module, a rock machine relationship model and a real-time output display module. The data storage module is connected to the rock machine database, the data storage module is connected to the rock machine relationship model, the data storage module and the rock machine relationship model are connected to the model calculation module. The model calculation module is connected to the TBM's current drilling parameter memory and the model calculation module is connected to the real time output display module. A real-time perception system for the TBM drilling rock state after Claim 1 , characterized in that the rock machine database is used to store TBM drilling parameters and corresponding rock mass condition parameters. The rock machine database includes the rock mass parameter database, the rock machine database, and other TBM engineering databases. The rock mass parameter database, the rock machine database and other TBM engineering databases are all connected to the data storage storage module. The current drilling parameter memory transfers the current drilling parameters to the model calculation module in real time on TBM. A real-time perception process for the TBM drilling rock state, characterized in that the steps are as follows: Step 1: Record the TBM drilling parameters and rock mass parameter data in the TBM construction case or the TBM drilling parameters and rock mass parameters of the TBM building tunnel currently under construction . Please enter TBM drilling parameters and rock mass condition parameters in the rock machine database and create a data storage module with rock machine condition parameters. Step 2: In accordance with the TBM drilling parameters stored in the data storage storage module and the corresponding rock mass condition parameters, a step-by-step regression algorithm and a clustering algorithm are used to create the rock machine relationship model that forms the core of the model calculation module. Step 3: The model calculation module combines the current drilling parameters on the TBM and uses the rock machine relationship model to calculate the information about the rock mass status of the current tunnel area of the TBM in real time. Step 4: The model calculation module transfers the compressive strength of the rock mass (UCS), the number of joints per unit volume (Jv) and the surrounding rock grade to the real-time output display module. The real-time output display module shows the compressive strength of the rock mass (UCS), the number of joints per unit volume (Jv) and the surrounding rock grade on a visualization interface of the host computer from TBM. A real-time perception process for the TBM drilling rock state after Claim 3 , characterized in that the TBM drilling parameters include the operating parameters of the TBM, such as thrust, torque, and the control parameters such as penetration and speed. The rock mass condition parameters include the compressive strength of the rock mass (UCS), the number of joints per unit volume (Jv) and the surrounding rock grade. The number of joints per unit volume (Jv) refers to the number of joints in the unit volume rock mass. The calculation formula is: J _v = Σ (1 / d _k ) + S _k / 5, where d _{k is} the distance between the joints of the kth group and S _{K is} the number of non-group-related joints per cubic rock mass of the kth group . A real-time perception process for the TBM drilling rock state after Claim 4 , characterized in that the surrounding rock grade consists of using the compressive strength of the rock mass (UCS) and the number of joints per unit volume (Jv) to calculate the basic quality index (BQ value) of the surrounding rock for the classification of the surrounding rock. The steps are as follows: Step 1: Determine the corresponding rock mass integrity coefficient Kv using the number of joints per unit volume (Jv). The correlation between the number of joints per unit volume (Jv) and the rock mass integrity coefficient Kv is shown in the following table. Jv <3 3 ~ 10 10 ~ 20 20∼35 > 35 (Pieces / m ³ ) Kv > 0.75 0.75 ~ 0.55 0.55 ~ 0.35 0.35 ~ 0.15 <0.15 Step 2: Please calculate the basic quality index BQ of the rock mass according to the compressive strength of the rock mass (UCS) and the rock mass integrity coefficient k _{V of} the quantitative index of the surrounding rock classification factor. The calculation formula is: BQ = 90 + 3UCS + 250 K _V. Also note the following restrictions: ① If UCS> 90 K _V + 30, use the calculation formula UCS = 90 K _V + 30 to calculate the basic quality index (BQ value) of the surrounding rock. ② If K _V > 0.04UCS + 0.4, the basic quality index BQ value of the surrounding rock is calculated with K _V = 0.04 UCS + 0.4; Step 3: According to the scope of the basic quality index BQ of the rock mass, determine the surrounding rock grade as follows: Surrounding rock grade I. II III IV V Basic quality index of the rock mass (BQ value) > 550 550-451 450-351 350 ~ 251 <250 A real-time perception process for the TBM drilling rock state after Claim 3 , characterized in that the method of creating a rock machine relationship model through a stepwise regression algorithm is as follows: ① Creating the device parameter model: Create the relationship model between the device operating parameter, such as thrust, and the control parameter, such as penetration, in the increasing section of the TBM drilling parameters below different rock mass conditions. The regression adjustment formula of the shear force of a single milling cutter is: F = ax P + b, a is the coefficient of influence of the penetration on the shear force of a single milling cutter, b is the threshold value for rock breaking with cutting tools, P is the penetration; ② Create the relationship model between the coefficient of influence (a) of penetration on the thrust of an individual milling cutter, the threshold value for rock breaking with cutting tools (b) and the compressive strength of the rock mass (UCS) and the number of joints per unit volume (Jv) in the rock mass condition parameter: The Regression adaptation formula for the function between the influence coefficient (a) of the penetration on the thrust force of an individual milling cutter and the number of joints per unit volume (Jv) is: a = f (Jv) = po X Jv ² + p1 X Jv + p2, where p0, p1 , p2 in the formula are the adjustment constants and f is the function. The threshold value for rock breaking with cutting tools (b) is the minimum threshold value of the milling cutter, which penetrates the rock mass and creates the depression. If p = 1, the thrust of a single cutter is F = a + b, which is used to measure the tunnelability properties of the rock mass. The regression fit formula is: a + b = g (UCS, Jv) = p3 X UCS + p4 X Jv + p5, where p3, p4, p5 in the formula are fit constants and g is a function. A real-time perception process for the TBM drilling rock state after Claim 3 , characterized in that the clustering algorithm is used to establish the relationship between the surrounding rock grade and the TBM drilling parameters by calculating the distribution range of the TBM drilling parameters under different conditions of the surrounding rock grade. The steps are as follows: ① Use the machine parameters in the rock machine database to calculate the ratio (FPI) of thrust of a single cutter to penetration and the ratio (TPI) of cutting head torque to penetration. Please use the ratio (FPI) of the thrust of a single milling cutter to the penetration and the ratio (TPI) of the cutting head torque to the penetration as a sample database. ② The ratio (FPI) of thrust force of a single milling cutter to penetration and the ratio (TPI) of the cutting head torque to penetration are randomly selected from the rock machine database as the sample mass center of gravity of each surrounding rock grade to create a two-dimensional coordinate system (FPI _(n) , TPI _{(n )} ) to form. n is the surrounding rock grade I, II, III, IV, V, and FPI _(n) and TPI _(n) each represent the values of FPI and TPI of the TBM drilling parameters under the condition of a randomly selected surrounding rock of the surrounding rock grade I bis V from the rock machine database; ③ Calculate the surrounding rock category of the current sample (FPI _(i) , TPI _(i) in the sample database: $c^{\left(i\right)}=\text{bad}\underset{J}{{\displaystyle \text{min}}}{\Vert x^{\left(i\right)}-{\mu }_j\Vert }^{\mathrm{2nd}},c^{\left(i\right)}.$

c ⁽ⁱ⁾ represents the surrounding rock level of the center of gravity that is closest to the current sample (FPI _(i) , TPI _(i) ). x ⁽ⁱ⁾ represents the current coordinate point (FPI _(i) , TPI _(i) ). µ _j is the sample mass center of gravity of each surrounding rock grade. FPI _(i) and TPI _(i) represent the FPI and TPI values of the TBM drilling parameters included in current calculation sample i; ④ With increasing sample size, recalculate the sample mass center of gravity of the ratio (FPI) of the thrust force of a single milling cutter to penetrate each surrounding rock grade and the ratio (TPI) of the cutting head torque to the penetration: ${\mu }_j=\frac{{\displaystyle {\sum }_{i=1}^{m}1\left\{c^{\left(i\right)}=j\right\}{x}^{\left(i\right)}}}{{\displaystyle {\sum }_{i=1}^{m}1\left\{c^{\left(i\right)}=j\right\}}},$

m is the number of samples of FPI and TPI under the condition of the same surrounding rock grade. 1 in the numerator denominator represents the sample points of the TBM drilling parameters FPI and TPI under the conditions of the same surrounding rock grade. ${\displaystyle {\sum }_{i=1}^{m}1}\left\{c^{\left(i\right)}=j\right\}$

represents the number of sample points of the TBM drilling parameters FPI and TPI under the conditions of the same surrounding rock grade. ${\displaystyle {\sum }_{i=1}^m\left\{c^{\left(i\right)}=j\right\}}{x}^{\left(i\right)}$

is the sum of all sample points under the conditions of this surrounding rock grade; ⑤ Repeat steps ③ ~ ④ above until the position of the center of gravity no longer changes or the change is very small and the range of distribution of the ratio (FPI) of thrust of a single cutter to penetrate each surrounding rock grade and the ratio (TPI) of Cutting head torque for penetration and the position of the center of gravity µj under the conditions of the respective surrounding rock grade can be determined in the database. A real-time perception process for the TBM drilling rock state after Claim 6 or 7 , characterized in that the stepwise regression algorithm is used to calculate the rock mass condition information in the model calculation module as follows: Step 1: The model calculation module reads the data such as thrust force (F) of a single cutter and the penetration (P) of the circulation increase section of the normal TBM -Drilling. Please make a linear adjustment in accordance with the form of the device parameter model F = aXP + b in order to obtain the influence coefficient (a) of the penetration on the thrust force of an individual milling cutter and the threshold value (b) for rock breaking with cutting tools. Step 2: Please set the coefficient of influence (a) of the penetration obtained in step 1 on the thrust of an individual milling cutter and the threshold value (b) for rock breaking with cutting tools in the formula a = po X Jv ² + p1 X Jv + p2, a + b = p3 X UCS-p4 X Jv + p5 to calculate the compressive strength of the rock mass (UCS) and the number of joints per unit volume (Jv); Step 3: Use the joint number per unit volume (Jv) value obtained in step 2 and calculate the corresponding rock mass integrity coefficient Kv by interpolation method according to the correlation between the joint number per unit volume (Jv) and the rock mass integrity coefficient (Kv). Step 4: Use the rock mass compressive strength (UCS) obtained in step 2 and the Kv value of the rock mass integrity coefficient obtained in step 3 in the calculation formula of the basic quality index (BQ) of the rock mass: BQ = 90 + 3UCS + 250Kv, and calculate the Basic quality index (BQ value) of the rock mass. If UCS> 90Kv + 30, the basic quality index (BQ value) of the rock mass is also calculated using the calculation formula UCS = 90Kv + 30. If Kv> 0.04UCS + 0.4, the basic quality index BQ of the rock mass should be calculated using the formula Kv = 0.04UCS + 0.4; Step 5: Determine the surrounding rock grade according to the extent of the basic quality index (BQ value) of the rock mass calculated in step 4 according to the relationship between the basic quality index (BQ value) of the rock mass and the surrounding rock grade. A real-time perception process for the TBM drilling rock state after Claim 6 or 7 , characterized in that a clustering algorithm is used in the model calculation module to calculate the classification of the rock mass quality. The steps are as follows: Step 1: The model calculation module reads the current TBM drilling parameters in the current drilling parameter memory, including thrust, torque and penetration. Step 2: The model calculation module calculates the ratio FPI (new) of the thrust (F) of a single milling cutter to the penetration and the ratio TPI (new) of the cutting head torque (T) to the penetration (P) of the current TBM drilling parameters. Step 3: Use the two-dimensional coordinate system (FPI _(n) , TPI _(n) ) to calculate the distance between the current (FPI (new), TPI (new)) and the center of gravity µj of the surrounding rock samples of all classes, and the surrounding rock grade, which corresponds to the center of gravity in the minimum distance, is the current state of the TBM drilling rock mass.

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