Abstract:
A system and method for detecting gas concentrations in a target environment uses an array of sensors. Each sensor generates a respective voltammogram in response to the environment, and the voltammograms are collectively transformed into bins that each have a distribution and a height.  Normalized bins are then matched with a training set to determine whether a selected gas is present. Also, an un-normalized bin is fitted with the training set to ascertain a concentration of the gas. For this operation, the training set includes normalized and un-normalized data references previously derived from empirically defined voltammograms.

Description:
[0001]    The U.S. Government has a paid-up license in this invention and the right in limited circumstances to require the patent owner to license others on reasonable terms as provided for by the terms of Contract No. N00014-03-C-0316 awarded by Office of Naval Research. 
     
    
     FIELD OF THE INVENTION 
       [0002]    The present invention pertains generally to gas sensors. More particularly, the present invention pertains to gas sensors that are capable of determining whether a particular gas (gases) is (are) present in an environment and, if present, the concentration of the gas (gases). The present invention is particularly, but not exclusively, useful as a gas sensor that employs transformed voltammograms to ascertain gas concentrations, to thereby improve the accuracy, reliability and response time of the gas sensor. 
       BACKGROUND OF THE INVENTION 
       [0003]    Many examples can be given wherein the detection of gas concentrations in a target environment may be either beneficial, or necessary, or both. In any event, the task of detecting a gas concentration may be quite challenging, and can be both problematic and time consuming. Obviously, these constraints are to be avoided. The solution is to use reliable gas sensors, and to use them in an efficient manner. 
         [0004]    Gas microsensors, such as cermet electrochemical cells, provide a well-known  means for detecting gas concentrations. Specifically, it is known that these microsensors will give a specific current response whenever a voltage is applied to them. When the voltage is varied, the result is a current-voltage envelope that is commonly referred to as a voltammogram. Importantly, this current-voltage envelope (i.e. voltammogram) will change, depending on the gaseous environment in which the voltage is applied to the sensors. This is due to the fact that the reaction of gases with the surface electrodes of these sensors causes them to change their current response. Importantly, in each case, the resultant voltammogram will be specific for the sensor (i.e. its electrode composition), as well as for the gas concentration in which the sensor is activated. 
         [0005]    As implied above, a voltammogram graphically presents current-voltage data in a manner that is characteristic of the gaseous environment in which the generating sensor is activated. Thus, as a practical matter, a voltammogram will typically include inputs from a variety of gases, and it will be influenced by the concentrations of the different gases. Stated differently, voltammograms will be of many different and varied sizes and shapes. Therefore, without more information, it can be an extremely difficult task to effectively and quickly analyze a voltammogram in real time, for a particular gas concentration in an operational setting. The situation is only further complicated when a plurality of voltammograms are involved. 
         [0006]    It happens that information from a voltammogram can be mathematically transformed into a more useable format by employing mathematical transforms. In this context, the so-called wavelet transformations can be particularly effective. Specifically, such a transformation will result in so-called “bins” of data (also referred to hereinafter, in some contexts, as “data references”). Importantly, in comparison to the underlying voltammogram, these “bins” more succinctly identify the salient characteristics of detected gas concentrations. In general, this is so because each resultant “bin” is in a format that is more manageably presented as a distribution and a height. Moreover, in addition to its simplified format, only about 5% of the “bins” in the transformation of a typical voltammogram are required to accurately identify a gas concentration. With this in mind, the selection of a reduced number of “bins” can be rather easily accomplished using statistical probabilities. 
         [0007]    It is axiomatic that the determination of a gas concentration requires the accomplishment of two, somewhat different tasks. First, it must be determined whether a particular gas is present in the target environment. Second, if the gas is present, its concentration must be ascertained. For the first task, the distribution and height format of the “bins” lend themselves to a matching procedure wherein the “bins” can be compared with empirically obtained data. For accomplishing the second task, this same format also facilitates the use of well-known “curve fitting” techniques. 
         [0008]    In light of the above, it is an object of the present invention to provide a system and method for determining gas concentrations in an environment, wherein wavelet transformations are employed to convert information from voltammograms into more manageable data. Further, it is an object of the present invention to reduce the amount of this more manageable data by statistical selection to improve the operational response of the system. Another object of the present invention is to provide a system and method for determining gas concentrations in an environment that effectively provides a real time response. Still another object of the present invention is to provide a system and method for determining gas concentrations in an environment that is easy to use, is relatively simple to manufacture, and is comparatively cost effective. 
       SUMMARY OF THE INVENTION 
       [0009]    In accordance with the present invention, a device for detecting gas concentrations in an environment includes a sensor array having a plurality of individual sensors (e.g. four sensors). Importantly, each sensor is different from every other sensor in the array, and each of the individual sensors in the array has a unique, predetermined gas sensitivity. Also, a baseline is established for each sensor so that the background influence on the sensor is removed, before the device is activated. 
         [0010]    When the sensors of the device are activated in a target environment, they generate a respective number of voltammograms. After they have been generated, the voltammograms are concatenated to create a collection of data points. The collection of data points is then compared with empirically obtained data to identify whether a particular gas is present. And, if so, its concentration is also ascertained. 
         [0011]    To create the collection of data points, the device of the present invention includes a converter. Specifically, the converter is used to transform the collection of data points into a like number of bins that are each characterized by having both a distribution and a height. For the present invention, this transformation is preferably accomplished using a wavelet transformation. Further, the number of bins corresponding to a particular voltammogram can be reduced for operational purposes by statistical selection. Once transformed and selected, the bins are normalized, and un-normalized, for analysis by an evaluator. Specifically, this analysis by the evaluator is accomplished by respectively comparing the normalized and un-normalized versions of the selected bins with a training set. 
         [0012]    As intended for the present invention, the training set (i.e. library) is empirically created. In particular, a sensor of each type that is to be incorporated into the operational device is used to generate a number of defined voltammograms for the training set. More particularly, each sensor is placed in a number of different, predetermined gaseous environments to generate a single defined voltammogram for each environment. Each defined voltammogram is then transformed to create data references (i.e. bins). Importantly, these transformations are accomplished using the same wavelet transformation that is to be subsequently used in the actual operation of the device. For the present invention, the transformed data references are then normalized, and un-normalized, to create the training set. Thus, the data references that are obtained from the defined voltammograms for the training set will correspond generally to the bins that are obtained from the voltammograms that are subsequently generated by sensors of the sensor array in the target environment. 
         [0013]    In this way, the training set is established to include a plurality of normalized data references, and a plurality of un-normalized data references, that can be collectively used by the evaluator for direct comparison with the bins. As disclosed above, both the normalized and un-normalized versions of the bins are created in the target environment that is to be evaluated. 
         [0014]    In operation, the device is activated in the target environment. Bins are then created as disclosed above. Normalized versions of the bins are then matched with normalized data references from the training set to identify the gas in the environment. Preferably, this matching is accomplished using a neural network. In a separate but coordinated operation, un-normalized versions of the bins are fitted with un-normalized data references from the training set to ascertain the concentration of the gas in the environment. Preferably, this fitting is accomplished using standard curve fitting techniques. The results are then displayed. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0015]    The novel features of this invention, as well as the invention itself, both as to its structure and its operation, will be best understood from the accompanying drawings, taken in conjunction with the accompanying description, in which similar reference characters refer to similar parts, and in which: 
           [0016]      FIG. 1  is a general schematic of a device for the present invention; 
           [0017]      FIG. 2  is a schematic of the components required to generate a training set for the present invention; and 
           [0018]      FIG. 3  is a schematic of the operational components used by the present invention for the detection of a gas concentration in a specified environment. 
       
    
    
     DESCRIPTION OF THE PREFERRED EMBODIMENTS 
       [0019]    Referring initially to  FIG. 1 , a device for determining gas concentrations in an environment, in accordance with the present invention, is schematically shown and is generally designated  10 . As shown, the device  10  includes a sensor unit  12  that is used for collecting data from a target environment (not shown) wherein the gas concentration is to be evaluated. The device  10  also includes a training set  14  that includes empirically obtained data for use in identifying a gas and its concentration in the target environment. Additionally, the device  10  includes an evaluator  16  that compares data obtained by the sensor unit  12  with empirical data in the training set  14 . The result of this comparison is an identification of a gas and its concentration in the target environment. This information is then presented on the display  18  for use by an operator. 
         [0020]    In detail, the creation of the training set  14  will be best appreciated with reference to  FIG. 2 . As indicated in  FIG. 2 , the training set  14  is created by collecting data from different cermet sensors  20 ,  22 ,  24  and  26 . Although only the sensors  20 ,  22 ,  24  and  26  are shown in  FIG. 2 , this is only exemplary. As can be appreciated by the skilled artisan, many more such sensors could be used for the creation of the training set  14 . Further, for purposes of this disclosure, the sensors  20 ,  22 ,  24  and  26  are preferably of the types disclosed in co-pending U.S. Patent Application entitled “Cermet Microsensor and Method of Making Same,” which is assigned to the same assignee as the present invention. With this in mind, the cermet sensor  20  is first considered individually, with the understanding that other such sensors are to be used in substantially the same way. Specifically, in order to create empirical data for the training set  14 , the cermet sensor  20  is placed in an environment wherein a specific gas (e.g. H 2 S), and its known concentration are predetermined. The sensor  20  is then activated by cyclically varying an applied voltage in an approximate range between ±1.5 volts. This will generate a voltammogram  28 . The voltammogram  28  is then transferred to a converter  30 . 
         [0021]    For the present invention, the converter  30 , shown in  FIG. 2 , is used for the present invention to transform voltammograms (e.g. voltammogram  28 ) into a plurality of data references  32 . As envisioned, the transformations accomplished by the converter  30  are preferably done using a wavelet transformation, such as Daubechie-8, which is a type of transformer that has been shown to be very effective in achieving significant data reduction. Further, the data references  32  that result from the transformation of the voltammogram  28  are subject to a selection process in which only statistically significant data references  32  are retained. Specifically, this is done in order to reduce the amount of data that is eventually contained in the training set  14 . As determined for the present invention, it happens that as few as about 5% of the transformed data references  32  are statistically significant. The result of this transformation and selection process in the converter  30  is exemplarily shown in  FIG. 2  as the data references   32 ,  32 ′ and  32 ″. In reality, however, there may be as many as several hundred statistically significant data references  32  for each voltammogram, such as the voltammogram  28 . In each case, the data references  32  will collectively include information that is pertinent to the salient characteristics of the gas environment where the cermet sensor  20  was activated. 
         [0022]    Still referring to  FIG. 2 , it will be seen that all of the statistically selected data references  32  are normalized (block  34 ), and un-normalized (block  36 ).  Both the normalized and un-normalized versions of the data references  32  are then stored in a sub-set  38  of the training set  14 , pertinent to the sensor  20 , for subsequent retrieval. Creation of the training set  14  is then continued by acquiring data from the sensor  20  in other different, predetermined gas environments. Each time, a different voltammogram  40  is generated that is characteristic of the particular environment in which it was generated. Again, for each voltammogram, the converter  30  transforms and selects data references  32  that are normalized and un-normalized for eventual inclusion in the sub-set  38  of training set  14 . This continues, with sequential activations of the cermet sensor  20 , for as many different predetermined gas environments, as desired. And, each time, the resultant voltammogram is transformed and normalized and un-normalized into data references  32  for inclusion in the sub-set  38 . 
         [0023]    After the sub-set  38  has been completed for the cermet sensor  20 , the same process is used for the cermet sensor  22 , the cermet sensor  24  and the cermet sensor  26 . For example, the cermet sensor  22  can be used to create the sub-set  42 , and the cermet sensor  26  can be used to create the sub-set  44 . The consequence of this is the creation of a training set  14  that includes transformed and statistically selected empirical data that is obtained from a plethora of voltammograms. As described above, each voltammogram is specific for a particular sensor (e.g. cermet sensor  20 ) and for a predetermined gas concentration. 
         [0024]    Returning now to  FIG. 1  it will be appreciated that the training set  14  that is created as described above is an integral component of the device  10 . Specifically, both the training set  14  and the sensor unit  12  are directly connected to the evaluator  16 . Turning now to  FIG. 3 , details of the sensor unit  12  are disclosed, and its interrelationship with the training set  14  is presented in greater detail. 
         [0025]    In  FIG. 3  it is seen that the cermet sensors  20 ,  22 ,  24 , and  26  are mounted as an array  46 , and that the array  46  is powered by a voltage source  48 . As envisioned for the device  10  of the present invention, each sensor  20 ,  22 ,  24  and  26  in the array  46  will generate its own voltammogram in response to a cycle of applied voltage from the voltage source  48 . For example, when the sensor  20  is cycled it will generate a voltammogram  50 . Similarly, the sensor  22  will generate a voltammogram  56  and, likewise, the sensors  24  and  26  will respectively generate voltammograms  54  and  52 . These voltammograms  50 ,  52 ,  54  and  56  are then passed to a converter  58  where they are concatenated and transformed by the wavelet transformation into bins  60 . Thus, mathematically, the bins  60  have similar characteristics to that of the data references  32  discussed above. As shown in  FIG. 3 , the bins  60  are sequentially normalized  62  and un-normalized  64  for access by the evaluator  16 . 
         [0026]    In the operation of the device  10  of the present invention, the array  46  of sensors  20 ,  22 ,  24  and  26  are first cleared. Specifically, this clearing is done by cycling all of the sensors in the array  46  to establish a baseline  66  for the device  10 . This baseline  66  effectively represents the background noise for the device  10 , and it will be subsequently mathematically subtracted from readings taken by the device  10 . In any event, when used, all of the sensors  20 ,  22 ,  24  and  26  in the array  46  are voltage cycled in the target environment. The voltammograms  50 ,  52 ,  54  and  56  that result from activation of the array  46  are then transformed by the converter  58  into bins  60 . And, normalized and un-normalized versions of the bins  60  are prepared. The evaluator  16  then compares the bins  60  with the data references  32  in the training set  14 . Specifically, normalized bins  60  are matched with normalized data references  32  to determine whether a particular gas is present in the target environment. If the gas is present, un-normalized bins  60  are curve fitted with un-normalized data references  32  to determine, by extrapolation, the concentration of the gas. 
         [0027]    While the particular System and Method for Evaluating a Gas Environment as herein shown and disclosed in detail is fully capable of obtaining the objects and providing the advantages herein before stated, it is to be understood that it is merely illustrative of the presently preferred embodiments of the invention and that no limitations are intended to the details of construction or design herein shown other than as described in the appended claims.