Optimistic data retrieval in a process control environment

Abstract

Processing raw data stored in an historian device for determining an amount of products passed through a process element in a process control environment is described. A count value is incremented by a counter at a rate at which products pass through the process element. The count value rolls over to zero when the count value reaches a rollover value R. An historian device periodically receives count value data points from the counter. A deadband value D is set in the historian device for distinguishing between rollovers, resets, and reversals. A client device queries the historian device for an amount of products passed through the process element for a timeframe. The historian device selects a set of count value data points from within the queried timeframe. The historian device determines, based on the selected data points and their quality, an amount of products passed through the process element.

What is claimed is: 
     
         1 . A method for determining an amount of products passed through a process element in a process control environment comprising:
 incrementing, by a counter, a count value at a rate at which products pass through the process element;   rolling over the count value to zero by the counter when the count value reaches a rollover value R after which the counter rolls the count value over to 0 and continues incrementing;   receiving by a historian device connected to the counter, count value data points periodically;   setting in the historian device, a deadband value D for distinguishing among rollovers, resets, and/or reversals;   querying by a client device to the historian device, an amount of products passed through the process element for a timeframe;   selecting by the historian device, a set of count value data points received within the queried timeframe; and   determining by the historian device, based on the selected data points, an amount of products passed through the process element.   
     
     
         2 . The method of  claim 1  wherein the determining comprises:
 determining a reset has occurred if a first data point is greater than a following data point and the first data point is less than R*(1−D/100) and the following data point is less than R*D/100, and determining the amount of products passed through the process element based on the determined reset; 
 determining a reversal has occurred if the first data point is greater than the following data point and the difference between the first data point and the following data point is less than R*D/100, and determining the amount of products passed through the process element based on the determined reversal; and 
 determining a rollover has occurred if the first data point is greater than the following data point and it has not been determined that reset has occurred between the first and following data points and it has not been determined that a reversal has occurred between the first and following data points, and determining the amount of products passed through the process element based on the determined rollover. 
 
     
     
         3 . The method of  claim 2  wherein at least one of the following:
 if it has been determined that a rollover has occurred, the amount of products is increased by the rollover value R; 
 if it has been determined that a reset has occurred, the amount of products is increased by the value of the first data point; 
 if it has been determined that a reversal has occurred, the amount of products is decreased by the difference between the first data point and the following data point. 
 
     
     
         4 . The method of  claim 2  further comprising returning the calculated value of the amount of products passed through the process element to the client device. 
     
     
         5 . The method of  claim 2  wherein the deadband value D is set as a percentage of a rollover value of the counter. 
     
     
         6 . The method of  claim 1  wherein the historian device receives a query for a result over a timeframe from the client device connected to the historian device, and wherein the historian device selects data points within the timeframe; and further comprising:
 identifying in the historian device, data points as having a ‘GOOD’ quality, a ‘BAD’ quality, or a ‘DOUBTFUL’ quality; 
 setting in the historian device, one of the following quality rule modes:
 a ‘GOOD’ quality rule mode wherein the historian device includes in the retrieval calculations data points with a ‘GOOD’ quality and a ‘BAD’ quality, wherein data points with a ‘DOUBTFUL’ quality will not be included in a calculation; 
 an ‘EXTENDED’ quality rule mode wherein the historian device includes in the retrieval calculations data points with both a ‘GOOD’ quality, a ‘BAD’ quality, and a ‘DOUBTFUL’ quality; and 
 an ‘OPTIMISTIC’ quality rule mode wherein the historian device includes in the retrieval calculations data points with both a ‘GOOD’ quality and a ‘DOUBTFUL’ quality except that data points with a ‘BAD’ quality will not be included in a calculation; and 
 
 wherein the determined amount of products by the historian device is based on the included data points; and 
 wherein the historian device returns the determined amount of products to the client device. 
 
     
     
         7 . The method of  claim 6  wherein the historian device sets an ‘OPTIMISTIC’ quality rule mode wherein the historian device includes in its retrieval calculations data points except a “BAD” quality data point and at least one of the following:
 if a “BAD” quality data point is encountered, then a last known ‘GOOD’ quality data point or a last known ‘DOUBTFUL’ quality data point is used as if the “BAD” quality data point never occurred; 
 if a “BAD” quality data point is encountered, then a last known ‘GOOD’ quality data point or a last known ‘DOUBTFUL’ quality data point is used as if the “BAD” quality data point never occurred; wherein if a particular data point is a “BAD” quality data point and if there are no points prior to the start of the query, then 0.0 will be used as a starting base value for the particular “BAD” quality data point; 
 if a “BAD” quality data point is encountered, then a last known ‘GOOD’ quality data point or a last known ‘DOUBTFUL’ quality data point is used as if the “BAD” quality data point never occurred; wherein if a particular data point is a “BAD” quality data point and if there are no points prior to the start of the query, then 0.0 will be used as a starting base value for the particular “BAD” quality data point, and then the value change for the cycle is calculated from the first actual data point in the cycle, rather than 0.0. 
 
     
     
         8 . A method of retrieving data from an historian device in a process control environment comprising:
 receiving in the historian device, a query for a result over a timeframe by an historian device from a client device connected to the historian device;   selecting by the historian device, data points within the timeframe;   identifying in the historian device, data points as having a ‘GOOD’ quality, a ‘BAD’ quality, or a ‘DOUBTFUL’ quality;   setting in the historian device, an ‘OPTIMISTIC’ quality rule mode wherein the historian device includes in the retrieval calculations data points with both a ‘GOOD’ quality and a ‘DOUBTFUL’ quality except that that ‘BAD” quality data points will not be included in a calculation;   wherein the determined amount of products by the historian device is based on the included data points; and   wherein the historian device returns the determined amount of products to the client device.   
     
     
         9 . The method of  claim 8  wherein at least one of the following:
 if a “BAD” quality data point is encountered, then a last known ‘GOOD’ quality data point or a last known ‘DOUBTFUL’ quality data point is used as if the “BAD” quality data point never occurred; 
 if a “BAD” quality data point is encountered, then a last known ‘GOOD’ quality data point or a last known ‘DOUBTFUL’ quality data point is used as if the “BAD” quality data point never occurred; wherein if a particular data point is a “BAD” quality data point and if there are no points prior to the start of the query, then 0.0 will be used as a starting base value for the particular “BAD” quality data point; 
 if a “BAD” quality data point is encountered, then a last known ‘GOOD’ quality data point or a last known ‘DOUBTFUL’ quality data point is used as if the “BAD” quality data point never occurred; wherein if a particular data point is a “BAD” quality data point and if there are no points prior to the start of the query, then 0.0 will be used as a starting base value for the particular “BAD” quality data point, and then the value change for the cycle is calculated from the first actual data point in the cycle, rather than 0.0. 
 
     
     
         10 . The method of  claim 9  further comprising:
 incrementing by a counter, a count value at a rate at which products pass through the process element; 
 rolling over the count value to zero by the counter when the count value reaches a rollover value R after which the counter rolls the count value over to 0 and continues incrementing; 
 receiving by the historian device connected to the counter, count value data points periodically; 
 setting, in the historian device, a deadband value D for distinguishing among rollovers, resets, and/or reversals; 
 querying by the client device from the historian device, an amount of products passed through the process element for a timeframe; 
 selecting by the historian device, a set of count value data points received within the queried timeframe; and 
 determining by the historian device, based on the selected data points, an amount of products passed through the process element. 
 
     
     
         11 . The method of  claim 10  wherein the determining comprises:
 determining a reset has occurred if a first data point is greater than a following data point and the first data point is less than R*(1−D/100) and the following data point is less than R*D/100, and determining the amount of products passed through the process element based on the determined reset; 
 determining a reversal has occurred if the first data point is greater than the following data point and the difference between the first data point and the following data point is less than R*D/100, and determining the amount of products passed through the process element based on the determined reversal; and 
 determining a rollover has occurred if the first data point is greater than the following data point and it has not been determined that reset has occurred between the first and following data points and it has not been determined that a reversal has occurred between the first and following data points, and determining the amount of products passed through the process element based on the determined rollover. 
 
     
     
         12 . A historian device for use with a client device for displaying statistical data in a process control environment, the historian device comprising:
 a historian memory storage device and a historian processor including a counter, said historian memory storage device storing statistical data and storing processor-executable instructions for execution by the historian processor for implementing a historian connection module and a historian server module, said processor-executable instructions configured for, when executed by the historian processor:   incrementing by the counter, a count value at a rate at which products pass through the process element;   rolling over the count value to zero by the counter when the count value reaches a rollover value R after which the counter rolls the count value over to 0 and continues incrementing;   receiving by an historian device connected to the counter, count value data points periodically;   setting, in the historian device, a deadband value D for distinguishing among rollovers, resets, and/or reversals;   querying by a client device from the historian device, an amount of products passed through the process element for a timeframe;   selecting by the historian device, a set of count value data points received within the queried timeframe; and   determining by the historian device, based on the selected data points, an amount of products passed through the process element;   wherein the historian processor returns at the calculated value of the amount of products passed through the process element to the client device.   
     
     
         13 . The device of  claim 12  wherein the determining processor-executable instructions are configured for:
 determining a reset has occurred if a first data point is greater than a following data point and the first data point is less than R*(1−D/100) and the following data point is less than R*D/100, and determining the amount of products passed through the process element based on the determined reset; 
 determining a reversal has occurred if the first data point is greater than the following data point and the difference between the first data point and the following data point is less than R*D/100, and determining the amount of products passed through the process element based on the determined reversal; and 
 determining a rollover has occurred if the first data point is greater than the following data point and it has not been determined that reset has occurred between the first and following data points and it has not been determined that a reversal has occurred between the first and following data points, and determining the amount of products passed through the process element based on the determined rollover. 
 
     
     
         14 . The device of  claim 13  wherein the determining processor-executable instructions are configured for at least one of the following:
 if it has been determined that a rollover has occurred, the amount of products is increased by the rollover value R; 
 if it has been determined that a reset has occurred, the amount of products is increased by the value of the first data point; 
 if it has been determined that a reversal has occurred, the amount of products is decreased by the difference between the first data point and the following data point. 
 
     
     
         15 . The device of  claim 13  wherein the determining processor-executable instructions are configured for returning the calculated value of the amount of products passed through the process element to the client device. 
     
     
         16 . The device of  claim 13  wherein the determining processor-executable instructions are configured for the deadband value D is set as a percentage of a rollover value of the counter. 
     
     
         17 . The device of  claim 12  wherein the historian device receives a query for a result over a timeframe from the client device connected to the historian device, and wherein the historian device selects data points within the timeframe; and wherein the determining processor-executable instructions are configured for:
 identifying in the historian device, data points as having a ‘GOOD’ quality, a ‘BAD’ quality, or a ‘DOUBTFUL’ quality; 
 setting in the historian device, one of the following quality rule modes:
 a ‘GOOD’ quality rule mode wherein the historian device includes in the retrieval calculations data points with a ‘GOOD’ quality and a ‘BAD’ quality, wherein data points with a ‘DOUBTFUL’ quality will not be included in a calculation; 
 an ‘EXTENDED’ quality rule mode wherein the historian device includes in the retrieval calculations data points with both a ‘GOOD’ quality, a ‘BAD’ quality, and a ‘DOUBTFUL’ quality; and 
 an ‘OPTIMISTIC’ quality rule mode wherein the historian device includes in the retrieval calculations data points with both a ‘GOOD’ quality and a ‘DOUBTFUL’ quality except that data points with a ‘BAD’ quality will not be included in a calculation; and 
 
 wherein the determined amount of products by the historian device is based on the included data points; and 
 wherein the historian device returns the determined amount of products to the client device. 
 
     
     
         18 . The device of  claim 17  wherein the historian device sets at an ‘OPTIMISTIC’ quality rule mode wherein the historian device includes in its retrieval calculations data points except a “BAD” quality data point and wherein the determining processor-executable instructions are configured for at least one of the following:
 if a “BAD” quality data point is encountered, then a last known ‘GOOD’ quality data point or a last known ‘DOUBTFUL’ quality data point is used as if the “BAD” quality data point never occurred; 
 if a “BAD” quality data point is encountered, then a last known ‘GOOD’ quality data point or a last known ‘DOUBTFUL’ quality data point is used as if the “BAD” quality data point never occurred; wherein if a particular data point is a “BAD” quality data point and if there are no points prior to the start of the query, then 0.0 will be used as a starting base value for the particular “BAD” quality data point; 
 if a “BAD” quality data point is encountered, then a last known ‘GOOD’ quality data point or a last known ‘DOUBTFUL’ quality data point is used as if the “BAD” quality data point never occurred; wherein if a particular data point is a “BAD” quality data point and if there are no points prior to the start of the query, then 0.0 will be used as a starting base value for the particular “BAD” quality data point, and then the value change for the cycle is calculated from the first actual data point in the cycle, rather than 0.0. 
 
     
     
         19 . A historian memory storage device and a historian processor including a counter, said historian memory storage device storing statistical data and storing processor-executable instructions for execution by the historian processor for implementing a historian connection module and a historian server module, said processor-executable instructions configured for, when executed by the historian processor:
 receiving in the historian device, a query for a result over a timeframe by an historian device from a client device connected to the historian device;   selecting by the historian device, data points within the timeframe;   identifying in the historian device, data points as having a ‘GOOD’ quality, a ‘BAD’ quality, or a ‘DOUBTFUL’ quality;   setting, in the historian device, an ‘OPTIMISTIC’ quality rule mode wherein the historian device includes in the retrieval calculations data points with both a ‘GOOD’ quality and a ‘DOUBTFUL’ quality except that that ‘BAD’ quality data points will not be included in a calculation;   wherein the determined amount of products by the historian device is based on the included data points; and   wherein the historian device returns the determined amount of products to the client device.   
     
     
         20 . The device of  claim 19  wherein the determining processor-executable instructions are configured for at least one of the following:
 if a “BAD” quality data point is encountered, then a last known ‘GOOD’ quality data point or a last known ‘DOUBTFUL’ quality data point is used as if the “BAD” quality data point never occurred; 
 if a “BAD” quality data point is encountered, then a last known ‘GOOD’ quality data point or a last known ‘DOUBTFUL’ quality data point is used as if the “BAD” quality data point never occurred; wherein if a particular data point is a “BAD” quality data point and if there are no points prior to the start of the query, then 0.0 will be used as a starting base value for the particular “BAD” quality data point; 
 if a “BAD” quality data point is encountered, then a last known ‘GOOD’ quality data point or a last known ‘DOUBTFUL’ quality data point is used as if the “BAD” quality data point never occurred; wherein if a particular data point is a “BAD” quality data point and if there are no points prior to the start of the query, then 0.0 will be used as a starting base value for the particular “BAD” quality data point, and then the value change for the cycle is calculated from the first actual data point in the cycle, rather than 0.0. 
 
     
     
         21 . The device of  claim 20  wherein the determining processor-executable instructions are configured for:
 incrementing by a counter, a count value at a rate at which products pass through the process element; 
 rolling over the count value to zero by the counter when the count value reaches a rollover value R after which the counter rolls the count value over to 0 and continues incrementing; 
 receiving by the historian device connected to the counter, count value data points periodically; 
 setting, in the historian device, a deadband value D for distinguishing among rollovers, resets, and/or reversals; 
 querying by the client device from the historian device, an amount of products passed through the process element for a timeframe; 
 selecting by the historian device, a set of count value data points received within the queried timeframe; and 
 determining by the historian device, based on the selected data points, an amount of products passed through the process element. 
 
     
     
         22 . The device of  claim 21  wherein the determining processor-executable instructions are configured for:
 determining a reset has occurred if a first data point is greater than a following data point and the first data point is less than R*(1−D/100) and the following data point is less than R*D/100, and determining the amount of products passed through the process element based on the determined reset; 
 determining a reversal has occurred if the first data point is greater than the following data point and the difference between the first data point and the following data point is less than R*D/100, and determining the amount of products passed through the process element based on the determined reversal; and 
 determining a rollover has occurred if the first data point is greater than the following data point and it has not been determined that reset has occurred between the first and following data points and it has not been determined that a reversal has occurred between the first and following data points, and determining the amount of products passed through the process element based on the determined rollover.