Patent ID: 11919113
Assignee: CHANGZHOU ELECTROMECHANICAL VOCATIONAL AND TECHNICAL COLLEGE
Field: Machine tools (Mechanical engineering)
Classification: CPC B  G | IPC B  G

Claim 0:
1. A method for diagnosing health of a Computerized Numerical Control (CNC) machine tool, comprising the following steps:
step 1: using a cloud server to carry out Fast Fourier Transformation (FFT) processing on vibration data collected by a vibration sensor node, and obtaining spectrum averages of 800-1800 Hz, 1800-2800 Hz and 2800-3800 Hz;
obtaining a regression coefficient of relationship among the spectrum average of a relevant frequency band, temperature and operating state of equipment according to corresponding historical data of the spectrum average of the frequency band and temperature;
1.1 creating a data vector

x=(x(1),x(2),x(3),x(4))

wherein x(1) is the spectrum average of 800-1800 Hz, x(2) is the spectrum average of 1800-2800 Hz, x(3) is the spectrum average of 2800-3800 Hz, and x(4) is a temperature average of equipment;
1.2 creating a coefficient vector w=(w(1), w(2), w(3), w(4)), wherein w(1) is a coefficient of the spectrum average of 800-1800 Hz; w(2) is a coefficient of the spectrum average of 1800-2800 Hz; w(3) is a coefficient of the spectrum average of 2800-3800 Hz; and w(4) is a temperature coefficient;
1.3 xi is the ith trained data vector, and yi is a class marker of xi; when yi is −1, it means that the equipment fails; when yi is +1, it means that the equipment is normal; and N is a quantity of trained data;
finding a separating hyperplane with a maximum geometric margin, and a problem is expressed as the following constrained optimization problem:, min
        
          w
          ,
          b
          ,
          ξ
        
      
      ⁢
      
        
          1
          2
        
        ⁢
        
          
            
            W
            
          
          2
        
      
    
    +
    
      C
      ⁢
      
        
          ∑
          
            i
            =
            1
          
          N
        
        ⁢
        
          ξ
          i
        
      
    
  

  
    
      
        
          
            S
            .
            t
          
          ⁢
          
            
          
          ⁢
          
            
              y
              i
            
            ⁡
            
              (
              
                
                  w
                  .
                  
                    x
                    i
                  
                
                +
                b
              
              )
            
          
        
        ≥
        
          1
          -
          
            
              ξ
              i
            
            ⁢
            
              

            
            ⁢
            
              ξ
              i
            
          
        
        ≥
        
          0
          ⁢
          
            
          
          ⁢
          i
        
      
      =
      1
    
    ,
    2
    ,
    
      …
      ⁢
      
        
      
      ⁢
      N
    
  

C is a penalty coefficient, and is a slack variable;
assuming that the solutions of the constrained optimization problem are * and b*, transforming the original problem into a dual problem, and using Karush-Kuhn-Tucker (KKT) conditions to obtain an optimal solution of the dual problem, then:, w
      *
    
    =
    
      
        ∑
        
          i
          =
          1
        
        N
      
      ⁢
      
        
          α
          i
          *
        
        ⁢
        
          y
          i
        
        ⁢
        
          x
          i
        
      
    
  

  
    
      b
      *
    
    =
    
      -
      
        
          
            
              max
              
                i
                =
                
                  
                    y
                    i
                  
                  =
                  
                    -
                    1
                  
                
              
            
            ⁢
            
              w
              *
            
            ⁢
            
              x
              i
            
          
          +
          
            
              min
              
                i
                =
                
                  
                    y
                    i
                  
                  =
                  
                    -
                    1
                  
                
              
            
            ⁢
            
              
                w
                *
              
              ⁢
              
                x
                i
              
            
          
        
        2
      
    
  

wherein α* is a solution of the dual problem in a Lagrange multiplier vector;
step 2:
2.1 health degree of a CNC machine tool: health degree J of a CNC machine tool is a number between 0 and 1; the greater or the closer to 1 the value is, the more healthy the operating state is; the smaller or the closer to 0 the value is, the more unhealthy the operating state is and the greater the possibility of failure is; the health degree J of the CNC machine tool can be calculated by the following steps:, Lc
  =
  
    {
    
      
        
          
            
              
                
                  w
                  *
                
                ⁢
                
                  x
                  0
                
                +
                
                  b
                  *
                
              
              
                
                
                  w
                  *
                
                
              
            
          
          
            
              
                
                  w
                  *
                
                ⁢
                
                  x
                  c
                
              
              ≥
              
                
                  w
                  *
                
                ⁢
                
                  x
                  0
                
              
            
          
        
        
          
            
              
                
                  w
                  *
                
                ⁢
                
                  x
                  c
                
                +
                
                  b
                  *
                
              
              
                
                
                  w
                  *
                
                
              
            
          
          
            
              
                
                  w
                  *
                
                ⁢
                
                  x
                  c
                
              
              <
              
                
                  w
                  *
                
                ⁢
                
                  x
                  0
                
              
            
          
        
      
      ;
      
        

      
      ⁢
      
        
          L
          0
        
        =
        
          
            
              
                w
                *
              
              ⁢
              
                x
                0
              
            
            +
            
              b
              *
            
          
          
            0.95
            ⁢
            
              
              
                w
                *
              
              
            
          
        
      
      ;
      
        

      
      ⁢
      
        J
        =
        
          
            L
            ⁢
            c
          
          
            L
            0
          
        
      
    
  

wherein x0 is a data vector of a normally operating CNC machine tool calibrated by experts, and xc, is a data vector of a current CNC machine tool obtained by on-line monitoring;
Lo is an equivalent distance of the health degree of the calibrated CNC machine tool, and LC is an equivalent distance of the health degree of the current CNC machine tool;
2.2 determination of predictive maintenance alarm threshold
a failure possibility index p means the possibility of failure;, p
  =
  
    
      2
      ⁢
      
        e
        
          -
          J
        
      
    
    
      
        e
        J
      
      +
      
        e
        
          -
          J
        
      
    
  

when p>r, alarm is given to prompt that the CNC machine tool needs maintenance, wherein r is a predictive maintenance alarm threshold.