Abstract:
A system for controlling the quality of industrial processes including the steps of: having one or more reference signals relating to the industrial process, acquiring one or more real signals which are indicative of the quality of said industrial process, obtaining a transformed signal from the reference signal, obtaining a transformed signal from the real signal, calculating energies of the transformed reference and real signals, comparing the one or more reference signals to the one or more real signals to identify defects in the industrial process. Also, the comparing step includes: comparing the energies of the transformed reference and real signals to each other to extract corresponding time frequency distributions for selected frequency values, calculating energies of the time frequency distributions, and comparing the energies of the time frequency distributions with threshold values to identify energy values associated to defects.

Description:
This Application claims priority from European Patent Application No. 04425458.9 filed Jun. 24, 2004. 
   BACKGROUND OF THE INVENTION 
   The present invention relates to methods for controlling the quality of an industrial process, comprising the steps of: 
   making available one or more reference signals relating to the industrial process 
   acquiring one or more real signals indicating the quality of said industrial process, 
   comparing said one or more reference signals to said one or more real signals to identify defects of said industrial process 
   Monitoring defects in industrial processes is assuming a growing economic importance due to its impact in the analysis of the quality of industrial products. The ability to obtain an assessment of the quality of the industrial process in line and automatically has many advantages, both in economic terms and in terms of process velocity. Therefore, the desirable characteristics of the system are:
         on line and real time processing;   ability to recognise the main production defects with accuracy.       

   Currently, the problem of recognising the quality of an industrial process, and thus of identifying any defects, takes place through an off-line inspection by experts, or with automatic methods which, through sensors, identify only some of the aforementioned defects, in a manner that is not satisfactory and that is also sensitive to the different settings of the machine. 
   Methods and systems for controlling the quality of industrial processes are known, for instance applied to the on-line monitoring of the laser welding process, in particular in the case of metal sheet welding. The controlling system is able to assess the presence of porosities in the welded area or, in the case of butt-weeded thin metal sheets, the presence of defects due to the superposition or to the disjunction of the metal sheets. 
   Said used systems base quality control on a comparison between the signals obtained during the process and one or more predetermined reference signals, indicative of a high quality weld. Said reference signals, usually in a variable number between two and ten, are predetermined starting from multiple samples of high quality welds. Obviously, this way of proceeding implies the presence of an experienced operator able to certify the quality of the weld at the moment of the creation of the reference signals, entails time wastage and at times also material wastage (which is used to obtain the samples needed to obtain the reference signals). In some cases, reference signals indicating a defective weld are also arranged, and this entails additional problems and difficulties. 
   The European patent application EP-A-1275464 in the name of the present Applicant teaches to divide into blocks the signal acquired by means of a photodiode which collects the radiation emitted by a weld point, calculating the mean of the signal in each sampled block and taking in account the blocks whose value is lower than or equal to the offset of the photodiode to be indicative of the presence of a defect. Said method eliminates the need for the reference, but it allows for a very approximate detection of defects. 
   SUMMARY OF THE INVENTION 
   The object of the present invention is to overcome all the aforesaid drawbacks. 
   In view of achieving said object, the invention relates to a method for controlling the quality of industrial processes having the characteristics set out at the beginning and further characterised by the fact that it further comprises the operations of:
         obtaining a transformed signal from said reference signal;   obtaining a transformed signal from said real signal;   calculating energies of said transformed signals, respectively reference and real signal;       

   said comparison operation comprising:
         comparing said energies of said transformed signals, respectively reference and real, to each other to extract corresponding time frequency distributions for selected frequency values;   calculating energies of said time frequency distributions;       

   comparing the energies of said time frequency distributions with threshold values to identify energy values associated to defects. 
   In the preferred embodiment, said steps of obtaining a transformed signal from said reference signal and of obtaining a transformed signal from said real signal comprise a filtering operation by the application of a DWT (Discrete Wavelet Transform), whilst said operation of comparing said energies of said transformed signals, respectively reference and real, to obtain corresponding time frequency distributions comprises operating a calculation of the conjugate of the Fourier transform of the envelope of the real signal and of the envelope of the normalised signal, obtaining conjugate transformed signals, respectively real and reference, and comparing the energies of the reference signal and of the real signal, extracting the frequency values for which the energy of the real signal is greater than the reference signal. 
   Naturally, the invention also relates to the system for controlling the quality of industrial which implements the method described above, as well as the corresponding computer product directly loadable into the memory of a digital computer such as a processor and comprising software code portions to perform the method according to the invention when the product is executed on a computer. 

   
     BRIEF DESCRIPTION OF THE DRAWINGS 
     Additional characteristics and advantages of the present invention shall become readily apparent from the description that follows with reference to the accompanying drawings, provided purely by way of non limiting example, in which: 
       FIG. 1  is a block diagram showing a system that implements the method according to the invention; 
       FIG. 2  shows a detail of the system of  FIG. 1 ; 
       FIGS. 3 ,  4  and  5  are flowcharts representing operations of the method according to the invention; 
       FIG. 6  is a diagram of quantities computed by the method according to the invention. 
       FIG. 7  is a flowchart representing operations of the method according to an exemplary embodiment of the invention relating to evaluating defects. 
   

   DETAILED DESCRIPTION OF THE INVENTION 
   The method according to the invention shall now be exemplified with reference to a laser welding method. Said laser welding method, however, constitutes only a non limiting example of industrial process to which the method for controlling the quality of industrial processes according to the invention can be applied. 
   With reference to  FIG. 1 , the number  1  designates as a whole a system for controlling the quality of a laser welding process. The example refers to the case of two metal plates  2 ,  3  which are welded by means of a laser beam. The number  4  designates the focusing head as a whole, including a lens  5  whereat arrives the laser beam originated by a laser generator (not shown) and reflected by a semi-reflecting mirror  6 , after the passage through a lens L. The radiation E emitted by the weld area passes through the reflecting mirror  6  and is sensed by a sensor  7  constituted by a photodiode able to sent its output signal to an electronic control and processing unit  8  associated to a personal computer  9 . 
   In an actual embodiment, the semi-reflecting mirror  6  used is a ZnSe mirror, with a diameter of 2 inches, thickness 5 mm. The sensor  7  is a photodiode with spectral response between 190 and 1100 nm, an active area of 1.1×1.1 mm and a quartz mirror. 
     FIG. 2  shows in greater detail the control and processing electronic unit  8  associated to the personal computer  9 . Said processing unit  8  comprises an antialiasing filter  11  which operates on the signal sent by the sensor  7 , hence an acquisition board  12  is provided, equipped with an analog-digital converter, which samples the filtered signal and converts it into digital form. Said acquisition board  12  is preferably directly associated to the personal computer  9 . 
   Also in the case of an actual embodiment, the acquisition card  12  is a PC card NI 6110E data acquisition card, with maximum acquisition frequency of 5 Ms/sec. 
   The antialiasing filter  11  filters the signal by means of a low pass filter (e.g. a Butterworth IIR filter). 
   In the personal computer  9  according to the invention is implemented a method for controlling quality, based on a comparison between a real signal x real  acquired by means of the photodiode  7  and a reference signal x ref , representing a defective weld, stored in said personal computer  9 . 
   The reference signal, designated as x ref (t) is acquired at an acquisition frequency f s , and hence, according to Nyquist&#39;s theorem, has associated a frequency band of the signal with value f s /2, whilst the number of samples acquired for the reference signal x ref (t) is N. 
     FIG. 3  shows a flow chart which represents the operations conducted on the reference signal x ref (t). 
   In a first step  100  is executed a filtering operation of the reference signal x ref (t) by the application of a DWT (Discrete Wavelet Transform). At the output of the step  100 , therefore, one obtains a signal x ref     —     DWT  having N/2 samples in the band 0:f s /4. 
   Subsequently, in a step  101  to the x ref     —     DWT  signal is applied a Hilbert transform operation, obtaining a complex analytical signal x ref     —     HIL , having N/2 samples and with null negative frequencies. 
   To said analytical signal x ref     —     HIL  is applied, in a step  102 , a normalisation operation, which outputs a normalised signal x ref     —     norm . 
   On said normalised signal x ref     —     norm , in a step  103 , an operation of calculating an envelope of the normalised signal, designated as x ref     —     inv     —     norm , is performed, whilst in a step  104  to said envelope of the normalised signal x ref     —     inv     —     norm  is applied a Fourier transform operation (FFT), obtaining a transformed envelope X ref     —     inv     —     norm . 
   Lastly, in a step  105 , an operation of calculating the energy of the reference signal, designated E ref , is conducted, applying the following relationship:
 
∫| x   ref     —     inv     —     norm ( t )| 2   dt=∫|X   ref     —     inv     —     norm ( f )| 2    df   (1)
 
   In regard to the real signal x real  (t), it is also acquired at an acquisition frequency f s , and hence, according to Nyquist&#39;s theorem, has associated a frequency band of the signal with value f s /2, whilst the number of samples acquired for the real signal x real  (t) is N. 
     FIG. 4  shows a f low chart which represents the operations conducted on the real signal x real (t). 
   In particular,  FIG. 4  shows a first step  200  in which a filtering operation of the real signal x real (t) is executed by the application of a DWT transform. At the output of the step  200 , therefore, one obtains a signal x real     —     DWT  having N/2 samples in the band 0:f s /4. 
   On said signal x real     —     DWT , in a step  211 , is performed a Fourier transform operation, obtaining a transformed signal FFT   —     real , which, subsequently, in a step  212 , is normalised, obtaining a transformed normalised signal FFT   —     real     —     norm . 
   In a step  250 , on the transformed normalised signal FFT   —     real     —     norm  an operation of calculating a mean frequency f 0  is conducted, according to the relationship:
 
 f   0   =∫f*FFT     —     real     —     norm ( f )* FFT     —     real     —     norm ( f ) df   (2)
 
   In a step  251 , an operation of calculating a standard deviation B is conducted, according to the relationship:
 
 B =(∫ f   2   *FFT     —real       —     norm   *FFT     —     real     —     norm    df−f   0   2 ) 1/2   (3)
 
   In a step  252  are then calculated a lower band F_Sn=(f 0 −B/ 2 ) and an upper band F_Dx=(f 0 +B/2). 
   In parallel, in a step  201 , to the x real     —     DWT  signal is applied a Hilbert transform operation, obtaining a complex analytical signal x real     —     HIL , having N/2 samples and with null negative frequencies. 
   To said analytical signal x real     —     HIL  is applied, in a step  202 , a normalisation operation, which outputs a normalised signal x real     —     norm . 
   On said normalised signal x real     —     norm , in a step  203 , an operation of calculating the envelope, designated as x real     —     inv     —     norm , is conducted, whilst in a step  204  to said envelope of the normalised signal x real     —     inv     —     norm  is applied a Fourier transform operation (FFT), obtaining a transformed envelope X real     —     inv     —     norm . 
   Lastly, in a step  205 , an operation of calculating the energy of the real signal E real  is performed, applying the following relationship:
 
∫| x   real     —     inv     —     norm ( t )| 2   dt=∫|X   real     —     inv     —norm   ( f )| 2   df   (4)
 
   The operations of calculating the energies E real  and E ref  are conducted in a band delimited between the lower band F_Sn and the upper band F_Dx calculated at the step  252 . More in detail, the calculation is performed on the band so delimited, considering frequency steps, for example of one Hertz, i.e.: 
   In this way the operation of calculating the energies E ref  and E real  produces two respective vectors, respectively a vector of energies of the reference
 
∫ F     —     Sn   step   |X   real     —     inv     —     norm ( f )| 2   df∫   step   F     DX     |X   real     —     inv     —     norm ( f )| 2   df  
 
∫ F     —     Sn   step   |X   ref     —     inv     —     norm ( f )| 2   df∫   step   F     DX     |X   ref     —     inv     —     norm ( f )| 2   df  
 
   Energy_Ref_step (1, . . . k) and a vector of energies of the real signal Energy_Real_step (1, . . . k), both comprising k values in frequency. 
   Subsequently, a procedure of calculating the time-frequency quadratic distributions is performed, shown in the flowchart of  FIG. 5 , and comprising the following operations:
         in a step designated as  300 , calculating the conjugate of the Fourier transform (FFT) of the envelope of the real signal X real     —     inv     —     norm (f) and of the envelope of the reference signal X ref     —     inv     —     norm (f), obtaining conjugate transformed signals, respectively real X* real     —     inv     —     norm (f) and reference X* ref     —     inv     —     norm (f);   in a step  301 , taking in account the energies of the reference signal E ref  and of the real signal E real , represented by the respective energy vector of the reference Energy_Ref_step (1, . . . k) and the energy vector of the real signal Energy_Real_step (1, . . . k), and for each element k of said two vectors, evaluating whether the following criterion is met:
 
Energy_Real_step(1 , . . . k )&gt;Energy_Ref_step(1  . . . k )  (5)
       

   This operation can also be appreciated with reference to the chart of  FIG. 6 , which shows the amplitudes of the energies of the reference signal E ref  and of the real signal E real  (shown with thicker lines) as a function of frequency. 
   if the criterion ( 5 ) is met, then in a step  302  an operation of extracting the frequency value for which said criterion ( 5 ) is met is performed, said value being indicated as f_e. Depending on the number of times the condition is met, up to k values of frequency f_e are obtained.  FIG. 6  shows the regions corresponding to the values of frequency f_e for which the criterion ( 5 ) is met;
         in a step  303  a matrix M is constructed whose rows are constituted by extracted frequency values f_e, whilst the columns are constituted by N/2 time values t 1  . . . t N/2  of the output signal from the DWT transform operation  200 ;   in a step  304 , for each row of the matrix M is calculated a time-frequency quadratic distribution both for the reference signal, designated as Tfd ref , and for the real signal, designated Tfd real , using the Margenau_Hill relationship, i.e.:
 
 Tfd   real =Real( x   real     —     DWT ( t )• X   real     —     inv     —     norm *( f )• e   −j2πf )  (6)
 
 Tfd   ref =Real( x   ref     —     DWT ( t )• X   ref     —     inv     —     norm *( f )• e   −j2πf )  (7)
   in a step  305  for both reference and real signals are then calculated energies associated to the distributions for each time instant, respectively designated Et ref  and Et real ;   in a step  306  is then calculated a maximum value of energy max_Tfd ref  for the time frequency distribution of the reference Tfd ref .       

   To obtain an estimate of the defects S, lastly in a step  307  each time value of the energy Et real  of the time-frequency quadratic distribution of the real signal Tfd real  is compared with the maximum value of energy max_Tfd ref . If said value of the time-frequency quadratic distribution of the real signal Tfd real  exceeds the maximum value of the energy max_Tfd ref  then a defect is present at that time coordinate. 
   It is thereby possible to temporally locate defects. 
   To evaluate the defects, with reference to  FIG. 7 , the quantities taken into consideration are the energy of the real signal E real , originated at the step  205  of  FIG. 4 , as well as the lower band F_Sn=(f 0 −B/2) and the upper band F_Dx=(f 0 +B/2) of the defect calculated at the step  252 . Lastly, the extension and location of the defect in the frequency band is considered, as evaluated at the step  307  of  FIG. 5 . 
   Said parameters, i.e. the energy of the real signal E real , the lower band F_Sn and the upper band F_Dx, the extension and location of the defect, according to an aspect of the invention, are sent to a defect classifier  400  which, receiving at its input the identified characteristics (or a subset thereof) evaluates the quality of the weld as: “correct”/“not-correct”/“insufficient-penetration”/“discontinuous-laser-power”/“incorrect-mounting”/“porosity”. 
   In this way advantageously, the outputs of the steps  205 ,  252  and  307 , relating to the time/frequency analysis of defects are used to instruct the defect classifier  400  automatically, thereby avoiding steps of instructing the classifier  400  by an operator. Lastly, in a block  401  it is possible to cross check the results of the outputs of the steps  205 ,  252  and  307  and of the block  401  for a final evaluation of the defect. 
   Naturally, without altering the principle of the invention, the construction details and the embodiments may vary widely from what is described and illustrated purely by way of example herein, without thereby departing from the scope of the present invention.