A tmb cutterhead main drive intelligent decision method and system

Abstract

The application discloses a TBM cutter head main drive intelligent decision method and system, and belongs to the technical field of cutter head drive control. By constructing a master-slave type multi-drive unit collaborative architecture, unified regulation and control and target torque distribution of the drive system are realized; by monitoring current signals to identify faults, voltage vectors are reconstructed according to fault types, and continuous and stable output under faults is ensured; a disturbance observation method based on integral sliding mode is proposed, control deviation caused by system disturbance and parameter change is dynamically estimated and compensated; an MPTA control strategy of high-frequency virtual signal injection is designed, utilization of reluctance torque and stable tracking of the MTPA operating point are realized; the torque output capacity of the fault unit and the torque margin of the healthy unit are considered as a whole, a load distribution strategy is planned, and the overall load carrying capacity and operating life of the drive system are improved.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of tunnel boring machine (TBM) cutterhead driving control, and particularly relates to a TBM cutterhead main driving intelligent decision method and system. BACKGROUND

[0002] The cutterhead system of a tunnel boring machine (TBM) is a core working component of the whole machine, and directly undertakes the tasks of rock breaking, cutting and advancing, which has a crucial influence on the tunneling efficiency and construction safety of the whole machine. The driving forms of the TBM cutterhead mainly include hydraulic driving and electric driving. The electric driving mode has the advantages of compact structure, high operation efficiency, high control precision and simple maintenance, and gradually becomes the mainstream scheme of the TBM cutterhead driving system. The electric driving system of the TBM cutterhead usually adopts a parallel driving architecture formed by multiple electric driving units (9~1 four units), and through the cooperative action of the multiple electric driving units, the required high torque output is provided for the cutterhead, so as to ensure the continuity and efficiency of the tunneling operation.

[0003] Under complex tunneling conditions, the TBM cutterhead driving system needs to run in harsh environments such as high load, high disturbance and even power grid fluctuation for a long time, and the electric driving unit is prone to open circuit, short circuit and other faults. Once a fault occurs in one electric driving unit, the system may face the risks of uneven load, interruption of tunneling, and even the stability and efficiency of the whole system may be affected. Fault-tolerant control technology, as a kind of high-reliability intelligent decision method, is an important means to ensure the continuous tunneling of the TBM under fault conditions. When one or more electric driving units fail, the system can still maintain a certain output capacity to realize "sick running".

[0004] In the existing fault-tolerant control technology for the TBM cutterhead electric driving system, the fault isolation method is generally adopted, which can maintain the system operation to a certain extent and ensure the continuity of equipment operation to prevent fault propagation. However, the existing fault-tolerant control scheme for the TBM cutterhead electric driving system usually only removes the faulty unit, which seriously reduces the load capacity of the electric driving system under fault and the utilization rate of the system, leading to insufficient power output of the TBM during long-distance and complex geological conditions, reduced tunneling efficiency, and even secondary fault risks. Therefore, a fault-tolerant control strategy based on the principle of constant magnetic motive force is further proposed, which can maintain the basic operating state of the cutterhead electric driving unit by reconstructing the remaining phase current distribution and orthogonal downshift transformation matrix. However, the existing fault-tolerant control strategy does not fully exploit the available torque potential of the electric driving unit under fault conditions, and if it is directly introduced into the TBM cutterhead electric driving system, it may cause uneven torque distribution of the cutterhead, and further cause instability factors such as vibration and impact, ultimately affecting the reliability, service life and overall tunneling efficiency of the system. SUMMARY

[0005] The application provides a TBM cutter head main drive intelligent decision method and system, which can timely switch to a fault-tolerant mode and improve torque output and reduce load pressure of the remaining units when a fault occurs in a certain electric drive unit, thereby prolonging the continuous operation time of the whole machine and improving the stability and robustness of the equipment under complex tunneling working conditions.

[0006] The application adopts the following technical scheme: a TBM cutter head main drive intelligent decision method, comprising the following steps:

[0007] In the TBM cutter head drive system, a plurality of electric drive units are rigidly connected to the main shaft of the cutter head to establish a master-slave cooperative control mode; the total torque required by the cutter head is calculated through a kinematics model The total torque is divided into a plurality of torque components according to the master-slave cooperative control mode The total torque is divided into a plurality of torque components according to the master-slave cooperative control mode

[0008] The phase current waveform characteristics of each electric drive unit are monitored, and the faulty electric drive unit and the healthy electric drive unit are identified; the fault type of the faulty electric drive unit is judged, the phase current is reconstructed according to the fault type to obtain the reconstructed phase current, and the reconstructed phase current is converted through an inverse matrix to obtain the shaft current instruction under the fault-tolerant mode d-q

[0009] An integral sliding surface is constructed with the shaft current tracking error d as input , and a disturbance estimation amount is generated based on the integral sliding surface to dynamically compensate the current disturbance through the disturbance estimation amount

[0010] A virtual compensation factor and a disturbance estimation amount are introduced, and a virtual high-frequency signal is injected into the current angle to estimate the electromagnetic torque , so as to extract the sensitivity of the electromagnetic torque to the current angle, obtain the optimal current angle according to the sensitivity, and generate the optimal shaft current instruction d-q

[0011] When the output torque of the faulty electric drive unit is adjusted, the dynamic load distribution is performed according to the maximum output capacity of each healthy electric drive unit.

[0012] In a further embodiment, the establishment process of the master-slave cooperative control mode is as follows:

[0013] One of the electric drive units is set as a master control unit, and the others are slave control units; the master control unit receives the total torque , and divides the total torque into a plurality of torque components ​​​The dynamic allocation is performed to all working electric drive units including the master unit and the slave units to realize the cooperative driving.

[0014] In a further embodiment, the total torque required by the cutter head is calculated as follows:

[0015] The kinematic model is created as follows:

[0016] wherein, I is the equivalent moment of inertia of the cutter head, F is the load on the cutter head, C is the motion damping coefficient of the cutter head, is the first-order derivative of the motion rotation angle of the cutter head, is the second-order derivative of the motion rotation angle of the cutter head, N is the number of motors, , T is the electromagnetic torque of the reducer, is the meshing transmission ratio of each pair of pinions;

[0017] The total torque is calculated using the following formula:

[0018] .

[0019] In a further embodiment, when the fault type is an open circuit fault, the phase current is reconstructed using a reduced-order transformation matrix, and the reconstruction formula is as follows:

[0020] ;

[0021] wherein, and represent the reconstructed phase current of the remaining phase, and are the actual currents of the d axis and the q axis respectively, is the reduced-order transformation matrix.

[0022] In a further embodiment, when the fault type is a short circuit fault, the phase current is reconstructed in the form of injecting a compensation current, and the reconstruction method is as follows:

[0023] , ; wherein, and are the compensation currents of the remaining phase, is the short circuit current of the short circuit phase.

[0024] In a further embodiment, the creation process of the adaptive control law comprises:​​

[0025] Constructing integral sliding mode surface , whose expression form is as follows:

[0026] ; in the formula, , is a constant, is the d axis reference current, is the d axis actual current, is an integral variable;

[0027] Based on integral sliding mode surface Establishing control input function and sliding mode gain control rate :

[0028] ;

[0029] ; in the formula, and are respectively a constant rate reaching coefficient and an exponential reaching coefficient, and are both adjustment factors, is an ideal gain, represents the integral sliding mode surface ;

[0030] Constructing a disturbance update model to generate a disturbance estimation quantity by using a disturbance change trend ; the expression form of the disturbance update model is as follows:

[0031] ;

[0032] wherein, denotes a forgetting factor, and are respectively a disturbance estimation quantity at a current time and a disturbance estimation quantity at a next time, and respectively denote a current time current tracking error and a next time current tracking error, denotes a time point.

[0033] In a further embodiment, the virtual compensation factor is calculated according to an electric drive parameter:

[0034] wherein, is a virtual compensation factor, denotes an inductance of an electric drive unit d axis, denotes a number of pole pairs of the electric drive unit

[0035] the electromagnetic torque is estimated by the following formula:

[0036] ;

[0037] wherein, and are the d axis voltage and q axis voltage, is the stator resistance, and are the d axis actual current and q axis actual current, is the mechanical angular velocity, and are the d axis current component and q axis current component after disturbance compensation.

[0038] In further embodiments, the sensitivity of the electromagnetic torque to the current angle is expressed as ;

[0039] the optimal current angle is obtained by integrating the sensitivity , i.e.: ;

[0040] When the sensitivity satisfies , the optimal current angle corresponds to the MTPA point generating the optimal d-q axis current command:

[0041] , ; wherein, is the d axis optimal reference current, is the q axis optimal reference current, is the phase current amplitude.

[0042] In further embodiments, the dynamic load distribution is distributed by the following method:

[0043] wherein, is the output torque of the th healthy electric drive unit, is the number of healthy electric drive units, is the estimated electromagnetic torque.

[0044] A TBM cutter head main drive intelligent decision system for implementing the intelligent decision method as described above, comprising:

[0045] A first module is configured to rigidly connect a plurality of electric drive units to the main shaft of the cutter head in the TBM cutter head drive system to establish a master-slave collaborative control mode, and calculate the total torque required by the cutter head through a kinematic model The total torque is dynamically allocated according to the master-slave collaborative control mode.

[0046] A second module is configured to monitor the phase current waveform characteristics of each electric drive unit and identify the faulty electric drive unit and the healthy electric drive unit, judge the fault type of the faulty electric drive unit, reconstruct the phase current according to the fault type to obtain the reconstructed phase current, and obtain the shaft current instruction in the fault-tolerant mode through matrix transformation. d-q

[0047] A third module is configured to construct an integral sliding mode surface with the shaft current tracking error d as input. An adaptive control law is created based on the integral sliding mode surface to generate a disturbance estimation, and the shaft current disturbance is dynamically compensated through the disturbance estimation. d

[0048] A fourth module is configured to introduce a virtual compensation factor and a disturbance estimation to the current angle and inject a virtual high-frequency signal to estimate the electromagnetic torque to extract the sensitivity of the electromagnetic torque to the current angle, obtain the optimal current angle according to the sensitivity, and generate the optimal d-q shaft current instruction.

[0049] A fifth module is configured to dynamically load distribute according to the maximum output capacity of each healthy electric drive unit after adjusting the output torque of the faulty electric drive unit.

[0050] The present application has the following advantages: the present application constructs an MTPA control fault-tolerant strategy for the TBM cutter head main drive system, considers the operating characteristics and torque output capacity of the electric drive unit in normal and fault states, takes into account the torque bearing margin of the healthy unit and the load balancing demand of the system as a whole, reconstructs the current vector and optimizes the reluctance torque in the electromagnetic torque, realizes high torque output and stable tracking of the MTPA operating point in the fault-tolerant mode, and is particularly suitable for high load operation requirements in the long distance and long time continuous tunneling process of TBM, effectively ensures that the system still has stable tunneling capacity under fault conditions.

[0051] ​​​​This invention proposes an MTPA method based on virtual high-frequency signal injection, which achieves high-precision MTPA point tracking without relying on a precise parameter model. It adapts to the complex operating environment of TBM cutterhead drive under different rock strata and different tunneling speeds, and effectively enhances the robustness and response speed of the intelligent decision-making system to geological and load changes.

[0052] This invention designs an integral sliding mode disturbance observation model based on the MTPA control structure. By constructing an integral sliding mode surface and a nonlinear reaching law, the system's adaptability to common mechanical shocks, power grid disturbances, and load changes during TBM tunneling is enhanced, significantly improving the high reliability and anti-disturbance capability of the main drive system.

[0053] This invention can adjust the observation gain in real time according to the disturbance characteristics, thereby achieving real-time compensation for torque disturbance and current error. It is especially suitable for the working conditions where the cutterhead drive operation fluctuates drastically when the TBM traverses complex strata such as soft and hard alternation and fractured zones, effectively improving the overall stability and intelligent control accuracy of the system.

[0054] This invention proposes to model the current error as an equivalent disturbance and introduce a feedforward compensation mechanism, which significantly reduces torque pulsation, improves the tracking accuracy of the MTPA point, ensures that the TBM cutterhead main drive can achieve smooth tunneling in key stages such as tunnel correction, and improves the execution effect of intelligent decision-making.

[0055] In this invention, a compensation factor is designed. And reconstruct the virtual torque expression to keep the electric drive unit in d The reluctance torque output when the shaft back electromotive force approaches zero effectively improves the torque output capability of the TBM cutterhead drive system. This meets the high-reliability continuous propulsion requirements of the TBM under complex and variable working conditions, reducing the risk of machine jamming. Attached Figure Description

[0056] Figure 1 This is a schematic diagram of the highly reliable intelligent decision-making structure of the TBM cutterhead drive system. Detailed Implementation

[0057] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the invention.

[0058] Example 1

[0059] This embodiment takes four three-phase electric drive units driven by a TBM cutterhead as an example, including four electric drive units, namely electric drive unit D1, electric drive unit D2, electric drive unit D3 and electric drive unit D4.

[0060] like Figure 1As shown, the embodiment discloses a TBM cutterhead main drive intelligent decision method, comprising the following steps:

[0061] In the TBM cutterhead drive system, a plurality of electric drive units are rigidly connected to the main shaft of the cutterhead to establish a master-slave cooperative control mode; the total torque required by the cutterhead is calculated through a kinematic model , and the total torque is dynamically allocated according to the master-slave cooperative control mode.

[0062] The phase current waveform characteristics of each electric drive unit, such as the harmonic distortion rate and amplitude anomaly, are monitored, and the faulty electric drive unit and the healthy electric drive unit are identified; the fault type of the faulty electric drive unit is judged, the phase current is reconstructed according to the fault type to obtain the reconstructed phase current, and the shaft current instruction under the fault-tolerant mode is obtained through matrix transformation. d-q

[0063] Based on the shaft current instruction under the fault-tolerant mode, an integral sliding mode surface is constructed with the shaft current tracking error d-q as the input. d Based on the integral sliding mode surface , an adaptive control law is created to generate a disturbance estimation, and the current disturbance such as the shaft current disturbance is dynamically compensated through the disturbance estimation. d A virtual compensation factor and a disturbance estimation are introduced to ensure that the reluctance torque can still be effectively extracted and utilized when tends to 0, thereby improving the maximum torque output capability under the fault-tolerant mode. A virtual high-frequency signal is injected into the current angle

[0064] to estimate the electromagnetic torque , so as to extract the sensitivity of the electromagnetic torque to the current angle, obtain the optimal current angle according to the sensitivity, and generate the optimal shaft current instruction. d-q

[0065] When the output torque of the faulty electric drive unit is adjusted, the maximum output capability of each healthy electric drive unit is used for dynamic load distribution.

[0066] In further embodiments, the establishment process of the master-slave cooperative control mode is as follows:

[0067] One of the electric drive units is set as the master control unit, and the others are set as the slave control units; the master control unit receives the total torque , and dynamically allocates the total torque to all working electric drive units including the master control unit and the slave control units to realize cooperative driving.

[0068] ​​​​​​In combination with the above example, the output shafts of the electric drive units D1, D2, D3 and D4 are rigidly connected to the main shaft of the cutter head through a planetary gear box, and the electric drive unit D1 is set as the master control unit, and the electric drive units D2, D3 and D4 are slave control units. The central controller periodically collects the states of each electric drive unit through a bus, and correspondingly, the electric drive unit D1 is used to receive the instructions of the central controller, and the electric drive units D2, D3 and D4 realize closed-loop adjustment through the rear speed feedback.

[0069] In order to realize real-time distribution of the load torque of the TBM cutter head, the central controller calculates the total torque required by the cutter head according to the inertia load characteristics and rotation damping characteristics of the cutter head mechanism, and the calculation process is as follows:

[0070] The kinematic model in the following form is created:

[0071] In the formula, is the equivalent rotational inertia of the cutter head, is the load on the cutter head, is the cutter head motion damping coefficient, is the first derivative of the cutter head motion angle, is the second derivative of the cutter head motion angle, is the number of motors, , is the reducer electromagnetic torque, is the meshing transmission ratio of each pair of gear,

[0072] Therefore, the total torque required by the cutter head is calculated using the following formula:

[0073] In combination with the above example, the value of n in the present embodiment is 4.

[0074] When no fault occurs, the central controller evenly distributes the estimated total torque required by the cutter head to each electric drive unit, and for four electric drive units, it is expressed as:

[0075] In further embodiments, the current sensor is used to sample the phase currents of the electric drive unit i A , i B , i C ​​​​The fault type is determined based on the sampled phase currents. If the amplitude of a phase current approaches 0, and the amplitudes of the remaining two phase currents increase and maintain a symmetrical trend, it is an open circuit fault. If the amplitude of a phase current suddenly increases and far exceeds the rated value, and the waveforms of the remaining two phase currents are distorted and the phases are unbalanced, it is a short circuit fault.

[0076] When the fault type is an open circuit fault, the phase current is reconstructed using a reduced-order transformation matrix, and the reconstruction formula is as follows: ;

[0077] In the formula, and This represents the reconstructed phase current of the remaining phase. and They are respectively d Actual shaft current and q Actual shaft current, This is the reduced-order transformation matrix. If phase A is open-circuited, the remaining phases are phases B and C, respectively. and These are the reconstructed phase currents of phases B and C, respectively.

[0078] In this embodiment, , This refers to the rotation angle of the cutter head.

[0079] Therefore, in fault-tolerant mode d-q The shaft current command is obtained as follows:

[0080] In the formula, For fault-tolerant mode d Shaft reference current, For fault-tolerant mode q Shaft reference current.

[0081] Furthermore, when the fault type is a short-circuit fault, the phase current is reconstructed by injecting compensation current. The reconstruction method is as follows:

[0082] , ;in, and This is the compensation current for the remaining phase. This represents the short-circuit current of the short-circuited phase. Furthermore, if phase C is currently short-circuited, the remaining phases are phases A and B, respectively. and These are the reconstructed phase currents of phases A and B, respectively.

[0083] Correspondingly, fault-tolerant mode d-q The process of obtaining the shaft current command is as follows: in fault-tolerant mode d-qThe acquisition of the shaft current instruction is as follows:

[0084] .

[0085] In another embodiment, the creation process of the adaptive control law comprises:

[0086] Building an integral sliding mode surface , which is expressed as follows:

[0087] ; in the formula, , is a constant, is the shaft reference current in the fault-tolerant mode d , is the shaft actual current; d Based on the integral sliding mode surface

[0088] , the control input function and the sliding mode gain control rate are established:

[0089] ;

[0090] ; in the formula, and are the constant approach coefficient and the exponential approach coefficient respectively, and are both adjustment factors, is the ideal gain, and S represents the integral sliding mode surface ;

[0091] Building a disturbance update model to generate a disturbance estimator using the disturbance change trend ; the expression of the disturbance update model is as follows:

[0092] ; wherein, represents a forgetting factor, and are the disturbance estimator at the current time and the disturbance estimator at the next time respectively, and represent the current time current tracking error and the next time current tracking error respectively, represents the time point.

[0093] In a further embodiment, the virtual compensation factor is calculated according to the electric drive parameters:

[0094] , wherein, is the virtual compensation factor,​ representing the electric drive unit d inductance of the shaft, representing the number of pole pairs of the electric drive unit;

[0095] then, the electromagnetic torque is estimated by the following formula:

[0096] ;

[0097] wherein, and are respectively d shaft voltage and q shaft voltage, is the stator resistance, and are respectively d shaft actual current and q shaft actual current, is the mechanical angular velocity, and are respectively the disturbance-compensated d shaft current component and q shaft current component. It should be noted that the disturbance-compensated d shaft current component and the disturbance-compensated q shaft current component of the present embodiment are obtained by the disturbance update module mentioned above, and are corrected.

[0098] The sensitivity of the electromagnetic torque to the current angle is represented by ;

[0099] The optimal current angle is obtained by integral operation of the sensitivity , i.e.: ;

[0100] When the sensitivity satisfies , the optimal current angle corresponds to the MTPA point to generate the optimal d-q shaft current instruction:

[0101] , ; wherein, is the optimal reference current of the d shaft, is the optimal reference current of the q shaft, is the phase current amplitude. Finally, the distribution method of the dynamic load distribution is as follows:

[0102] wherein, is the number of healthy electric drive units, is the output torque of the electric drive unit, is the number of healthy electric drive units, is the estimated electromagnetic torque.

[0103] In summary, the present application proposes a high-reliability intelligent decision-making method for multi-electric drive architecture around the high-reliability operation demand of TBM cutterhead main drive system under long-distance, high-load continuous excavation conditions. First, a master-slave control structure is constructed and combined with a kinematic model to realize the estimation of the total torque of the cutterhead and the coordinated distribution among the multi-electric drive units, improving the system collaborative consistency. Second, based on the identification of fault types from phase current waveforms, combined with voltage vector reconstruction and current reconstruction compensation strategies, fault tolerance for open-circuit and short-circuit faults is realized. Further, an integral sliding mode disturbance observer is designed, and an adaptive gain adjustment mechanism is proposed to enhance the perception ability and robust suppression effect of the TBM system to complex disturbances. Subsequently, by injecting high-frequency virtual signals and designing compensation factors, stable tracking of the MTPA operating point under fault conditions is realized, thereby significantly improving the utilization rate of reluctance torque. Finally, a dynamic load reconstruction mechanism based on electric drive unit state identification is designed, which can adaptively redistribute the drive torque after the main drive system fails, effectively relieving the load pressure of healthy units. It provides a solid guarantee for the stable propulsion of TBM in complex geological environments.

[0104] Embodiment 2

[0105] The present embodiment discloses a TBM cutterhead main drive intelligent decision-making system for implementing the intelligent decision-making method described in Embodiment 1, comprising:

[0106] The first module is configured to rigidly connect a plurality of electric drive units to the main shaft of the cutterhead in the TBM cutterhead drive system, establishing a master-slave collaborative control mode; the total torque required by the cutterhead is calculated through a kinematic model The total torque is dynamically allocated according to the master-slave collaborative control mode;

[0107] The second module is configured to monitor the phase current waveform characteristics of each electric drive unit and identify the faulty electric drive unit and the healthy electric drive unit; the fault type of the faulty electric drive unit is determined, the phase current is reconstructed according to the fault type to obtain the reconstructed phase current, and the d-q shaft current instruction under the fault tolerance mode is obtained through matrix transformation;

[0108] The third module is configured to construct an integral sliding surface with d the shaft current tracking error as the input , based on the integral sliding surface ​An adaptive control law is created to generate a disturbance estimator, which dynamically compensates for d Shaft current disturbance;

[0109] A fourth module is configured to introduce a virtual compensation factor and a disturbance estimator to the current angle A virtual high-frequency signal is injected to estimate the electromagnetic torque to extract the sensitivity of the electromagnetic torque to the current angle, and to obtain an optimal current angle according to the sensitivity and to generate an optimal d-q d-q shaft current command;

[0110] A fifth module is configured to dynamically distribute the load according to the maximum output capacity of each healthy electric drive unit after the output torque of the faulty electric drive unit is adjusted.

[0111] The above embodiments are only used to illustrate the design ideas and characteristics of the present application, and the purpose is to enable those skilled in the art to understand the content of the present application and to implement it, and the protection scope of the present application is not limited to the above embodiments. Therefore, any equivalent changes or modifications made according to the principles and design ideas disclosed by the present application are within the scope of protection of the present application.

Claims

1. A TBM cutterhead main drive intelligent decision-making method, characterized in that, The method comprises the following steps: In the TBM cutterhead driving system, several electric driving units are rigidly connected to the main shaft of the cutterhead to establish a master-slave cooperative control mode; the total torque required by the cutterhead is calculated through a kinematic model The total torque is dynamically allocated according to the master-slave cooperative control mode The total torque is dynamically allocated according to the master-slave cooperative control mode The phase current waveform characteristics of each electric drive unit are monitored, and a faulty electric drive unit and a healthy electric drive unit are identified; the fault type of the faulty electric drive unit is judged, the phase current is reconstructed according to the fault type to obtain reconstructed phase current, and the reconstructed phase current is transformed to obtain the shaft current instruction in the fault-tolerant mode through an inverse matrix d-q transformed to obtain the shaft current instruction in the fault-tolerant mode.​ Construction of a d Axis current tracking error Integral sliding mode surface for input Integral sliding mode surface An adaptive control law is created to generate a disturbance estimator by which current disturbances are dynamically compensated. Introducing a virtual compensation factor and a disturbance estimator, to the current angle Injecting a virtual high-frequency signal to estimate the electromagnetic torque to extract the sensitivity of the electromagnetic torque to the current angle, and obtaining an optimal current angle from the sensitivity and generating an optimal d-q shaft current command; When the output torque of the fault electric drive unit is adjusted, dynamic load distribution is performed according to the maximum output capacity of each healthy electric drive unit.

2. The TBM cutterhead main drive intelligent decision-making method according to claim 1, characterized in that, The establishment process of the master-slave cooperative control mode is as follows: One of the electric drive units is set as a master control unit, and the others are slave control units; the master control unit receives total torque and dynamically allocates the total torque to all working electric drive units including the master control unit and the slave control units, to achieve cooperative driving.

3. The TBM cutterhead main drive intelligent decision-making method according to claim 1, characterized in that, the total torque required by the cutterhead The calculation process is as follows: A kinematic model in the following form is created: ; where, is the equivalent moment of inertia of the cutterhead, is the load on the cutterhead, is the motion damping coefficient of the cutterhead, is the first derivative of the motion angle of the cutterhead, is the second derivative of the motion angle of the cutterhead, is the number of motors, , is the electromagnetic torque of the reducer, is the transmission ratio of each pair of pinions. Then, the total torque is calculated using the following equation : 。 4. The TBM cutterhead main drive intelligent decision-making method of claim 1, wherein, When the fault type is an open circuit fault, a reduced transformation matrix is used to reconstruct the phase current, and the reconstruction formula is as follows: ； wherein and denotes the reconstructed phase current of the remaining phase, and are d the actual current of the axis and q the actual current of the axis, is a reduced transformation matrix.

5. The TBM cutterhead main drive intelligent decision-making method of claim 1, wherein, When the fault type is a short circuit fault, a compensation current injection form is used to reconstruct the phase current, and the reconstruction method is as follows: , ; wherein, and is the compensation current of the remaining phases, is the short circuit current of the short circuited phase.

6. The TBM cutterhead main drive intelligent decision-making method of claim 1, wherein, The creation process of the adaptive control law comprises: Constructing an integral sliding surface in the form of an expression ; where , is a constant, is the d axis reference current, is the d axis actual current, is the integral variable; Integral-type sliding surface Establishing control input function And sliding mode gain control rate : ； ; where, and are the constant and exponential reaching coefficients, respectively, and are the tuning factors, is the ideal gain, represents the integral sliding surface ; A disturbance updating model is constructed, and a disturbance estimator is generated by using a disturbance change trend The disturbance updating model is expressed as follows: ； wherein denotes a forgetting factor, and denotes a disturbance estimate at the current time instant and a disturbance estimate at the next time instant, respectively, and denotes a current time instant current tracking error and a next time instant current tracking error, respectively, denotes a time point.

7. The TBM cutterhead main drive intelligent decision-making method of claim 1, wherein, The virtual compensation factor is calculated according to the electric drive parameters: wherein, is a virtual compensation factor, represents the electric drive unit d inductance of the shaft, represents the electric drive unit pole pair number; The electromagnetic torque The estimation formula is as follows: ； wherein and are respectively d shaft voltage and q shaft voltage, is the stator resistance, and are respectively d shaft actual current and q shaft actual current, is the mechanical angular velocity, and are respectively the disturbance compensated d shaft current component and q shaft current component.

8. The TBM cutterhead main drive intelligent decision-making method of claim 1, wherein, The sensitivity of the electromagnetic torque to the current angle is expressed as ; Optimal current angle By integrating the sensitivity , i.e. ; When the sensitivity meets the optimal current angle The corresponding operating point is the MTPA point to generate the optimal d-q axis current command: , ; wherein, is d optimal reference current for the q-axis, is q optimal reference current for the q-axis, is the phase current amplitude.

9. The TBM cutterhead main drive intelligent decision-making method of claim 1, wherein, The dynamic load distribution method is as follows: wherein, is the number of healthy electric drive units, is the output torque of the healthy electric drive unit, is the number of healthy electric drive units, is the estimated electromagnetic torque.

10. A TBM cutterhead main drive intelligent decision system for implementing the intelligent decision method of any one of claims 1 to 9, characterized in that, It comprises: The first module is configured to rigidly connect a plurality of electric drive units to the main shaft of the cutter head in the TBM cutter head drive system, and establish a master-slave cooperative control mode; calculating the total torque required for the cutter head by a kinematic model calculating the total torque required for the cutter head by a kinematic model dynamically allocating in a master-slave cooperative control mode The second module is configured to monitor the phase current waveform characteristics of each electric drive unit, and identify the fault electric drive unit and the healthy electric drive unit; determining the fault type of the faulty electric drive unit, reconstructing the phase current according to the fault type to obtain a reconstructed phase current, and obtaining the shaft current instruction in the fault-tolerant mode through matrix transformation d-q shaft current instruction a third module configured to construct a d axis current tracking error for the input integral sliding surface based on the integral sliding surface create an adaptive control law generating a disturbance estimate by which to dynamically compensate d axis current disturbance; a fourth module configured to introduce a virtual compensation factor and a disturbance estimate into the current angle injecting a virtual high frequency signal to estimate electromagnetic torque to extract the sensitivity of electromagnetic torque to the current angle, and to derive an optimal current angle from the sensitivity and to generate an optimal d-q shaft current command The fifth module is configured to perform dynamic load distribution according to the maximum output capacity of each healthy electric drive unit when the output torque of the fault electric drive unit is adjusted.

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