Diagnostic device and method for monitoring the operation of a control loop

Abstract

A diagnostic device and method for monitoring the operation of a slave or ratio control loop in a meshed control structure of an automation system. The diagnostic device includes an evaluation device and a data memory for storing sequences of setpoint data and actual value data. The evaluation device determines a first dimension for the scatter of the actual-value data and a second dimension for the scatter of the setpoint data. A characteristic number (CPI.sub.Var, CPI.sub.Kas) for evaluating control quality is determined and/or displayed as a function of the ratio of the first dimension to the second dimension to enable an operator to evaluate the control loop status, permitting automated control loop evaluation of a fluctuating setpoint.

Claims

1. A diagnostic device for monitoring operation of a control loop in a meshed control structure of an automation system, the diagnostic device comprising: a data memory for storing sequences of both setpoint data and actual-value data for the control loop; and an evaluation device for determining a stochastic feature with reference to at least one segment of the sequences of setpoint data and actual-value data; wherein the stochastic feature determined for the actual-value data is a first dimension for scatter of the actual-value data, the diagnostic device being configured such that, for monitoring operation of a ratio control loop in the meshed control structure, the evaluation device is operable to determine a second dimension for scatter of the setpoint data as a stochastic feature of the setpoint data and to determine a characteristic number for evaluating the control quality as a function of a ratio of the first dimension to the second dimension, a sensitivity factor being changed such that an alarm is generated based on the determined characteristic value falling below a pre-specified value to provide a notification when deterioration of the control loop in the meshed control structure of the automation system has occurred.

2. The diagnostic device of claim 1, wherein the evaluation device is operable for determining a first characteristic number and a second characteristic number, the first and second characteristic numbers are the variance (var(PV), var(SP)) of one of the data of the actual value and the data of the setpoint, and the first characteristic number is calculated in accordance with the following relationships: ${\mathrm{CPI}}_{\mathrm{Var}}=100\%*\left(e^{s*0.5*\left(1-\frac{\mathrm{var}\left(\mathrm{PV}\right)}{\mathrm{var}\left(\mathrm{SP}\right)}\right)}\right)$ $\mathrm{if}$ $\frac{\mathrm{var}\left(\mathrm{PV}\right)}{\mathrm{var}\left(\mathrm{SP}\right)}1,\mathrm{and}$ ${\mathrm{CPI}}_{\mathrm{Var}}=100\%$ $\mathrm{if}$ $\frac{\mathrm{var}\left(\mathrm{PV}\right)}{\mathrm{var}\left(\mathrm{SP}\right)}<1,$ wherein s is the sensitivity factor preset having a preset value of 1 and which is changeable by an operator of the diagnostic device, and CPI.sub.Var is the first characteristic value.

3. The diagnostic device of claim 2, wherein the first and second characteristic numbers comprise average changes to the actual-value data or to the setpoint data from one sampling step to a next sampling step, and wherein the second characteristic number is calculated in accordance with the following relationship: ${\mathrm{CPI}}_{\mathrm{Kas}}=100\%*\frac{\sqrt{\frac{1}{2\left(N-1\right)}\underset{i=0}{\overset{N-1}{.Math.}}{\left({\mathrm{SP}}_{i+1}-{\mathrm{SP}}_i\right)}^2}}{\sqrt{\frac{1}{2\left(N-1\right)}\underset{i=0}{\overset{N-1}{.Math.}}{\left({\mathrm{PV}}_{i+1}-{\mathrm{PV}}_i\right)}^2}},$ wherein N is the number of sampling steps included in the evaluation, and CPI.sub.Kas is the second characteristic value.

4. The diagnostic device of claim 1, wherein at least the data memory and the evaluation device are implemented in software on a remote service computer operable for remote diagnosis of the control loop.

5. A diagnostic method for monitoring operation of a control loop in a meshed control structure of an automation system, comprising: storing in a data memory sequences of setpoint data and of actual-value data of the control loop in the meshed control structure of the automation system; determining a stochastic feature with reference to at least one segment of the sequences of setpoint data and actual-value data by an evaluation device, the stochastic feature determined for the actual-value data being a first dimension for scatter of the actual-value data; determining a second dimension for scatter of the setpoint data as a stochastic feature of the setpoint data; determining and displaying a characteristic number for evaluating control quality as a function of a ratio of the first dimension to the second dimension; and changing a sensitivity factor such that an alarm is generated based on the determined characteristic number falling below a pre-specified value to provide a notification when deterioration of the control loop in the meshed control structure of the automation system has occurred.

6. A computer program stored in one of a storage device and a non-transitory computer-readable medium which, when executed on a processor of a computer apparatus, causes the processor to execute the method of claim 5.

7. A non-transitory computer readable medium encoded with a computer program executable by a computer apparatus to execute the method of claim 5.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

(1) In the drawings, wherein similar reference characters denote similar elements throughout the several embodiments and figures:

(2) FIG. 1 is a schematic block depiction of a cascade control system with a diagnostic device;

(3) FIG. 2 is a schematic block diagram of a ratio control system with a diagnostic device; and

(4) FIG. 3 is a timing diagram showing the courses of the setpoint and the actual value.

DETAILED DESCRIPTION OF THE CURRENTLY PREFERRED EMBODIMENTS

(5) FIGS. 1 and 2 depict, by way of example, control loops in meshed structure implemented in, respectively, a cascade control system and a ratio control system. A control loop to be monitored includes a controller R and a process P; the controller R is referred to as a slave controller in a cascade control system and as a ratio controller in a ratio control system. In a cascade control system such as that represented by FIG. 1, the controller R obtains its setpoint SP from a master controller R1, which is a component of an external control loop for controlling a controlled variable PV1 of a process P1. In the following description, the controlled variable PV of the process P is also referred to as the actual value. In a ratio control system such as that represented by FIG. 2, the setpoint SP is provided by a ratio module VB, which calculates the setpoint as the ratio of an actual value PV2 of another control loop and a ratio value V. The other control loop, the actual value PV2 of which is applied to the ratio module VB of FIG. 2, in turn includes a controller R2 and a process P2, and the other control loop is assigned a prespecified setpoint SP2. Hence, with the meshed structures depicted in FIGS. 1 and 2, the controller R as a slave controller or a ratio controller receives its setpoint SP from another control loop. Accordingly, in automatic mode the setpoint selection changes continuously and there are no time phases with a constant setpoint or clean setpoint step-changes so that the control quality of the subordinate control loop that includes the controller R and the process cannot be analyzed using conventional evaluation methodology.

(6) With continued reference to FIGS. 1 and 2, in addition to the actual value PV a diagnostic device D also includes in the evaluation the setpoint SP. To this end, sequences of setpoint and actual-value data are stored in a data memory DS. An evaluation device AE uses these sequences to calculate a first dimension for the scatter of the actual-value data and, in a similar manner, a second dimension for the scatter of the setpoint data. The ratio of these two characteristic numbers is then used to calculate a first characteristic number CPI.sub.Var and a second characteristic number CPI.sub.Kas which are displayed to enable evaluation of the control quality.

(7) The characteristic number CPI.sub.Var is calculated using the following formula:

(8) ${\mathrm{CPI}}_{\mathrm{Var}}=100\%*\left(e^{s*0.5*\left(1-\frac{\mathrm{var}\left(\mathrm{PV}\right)}{\mathrm{var}\left(\mathrm{SP}\right)}\right)}\right),$

(9) wherein the variance var(PV) of the actual-value data as the first dimension and the variance var(SP) of the setpoint data as the second dimension are used as characteristic numbers for the scatter of the respective data. If the controller R is working ideally and successfully and accurately tracks the actual value PV with respect to the setpoint SP, the two variances var(PV) and var(SP) are approximately the same. According to the calculation formula for CPI.sub.Var, this produces a value of about 100%. If, on the other hand, the variance var(PV) of the actual value PV is greater than the variance var(SP) of the setpoint SP, the controller R is evidently disrupting the control loop formed by the controller R and the process P. This is indicated by a value of the first characteristic number CPI.sub.Var, which evidences deterioration of the control loop response by displaying a value of less than 100%. Changing the sensitivity factor s, which is preset with the value 1, enables a user to make adaptations as desired if, with a specific deterioration of the control loop response, lesser or greater changes to the first characteristic number CPI.sub.Var are to be displayed.

(10) To calculate the second characteristic number CPI.sub.Kas, the average change from one sampling step to the next in each case is calculated as the dimension for the scatter of the setpoint or the actual-value data. Hence, the formula is as follows:

(11) ${\mathrm{CPI}}_{\mathrm{Kas}}=100\%*\frac{\sqrt{\frac{1}{2\left(N-1\right)}\underset{i=0}{\overset{N-1}{.Math.}}{\left({\mathrm{SP}}_{i+1}-{\mathrm{SP}}_i\right)}^2}}{\sqrt{\frac{1}{2\left(N-1\right)}\underset{i=0}{\overset{N-1}{.Math.}}{\left({\mathrm{PV}}_{i+1}-{\mathrm{PV}}_i\right)}^2}},$

(12) wherein the variance var(PV) of the actual-value data as the first dimension and the variance var(SP) of the setpoint data as the second dimension are used as characteristic numbers for the scatter of the respective data. If the controller R is working ideally and successfully and accurately tracks the actual value PV with respect to the setpoint SP, the two variances var(PV) and var(SP) are approximately the same. According to the calculation formula for CPI.sub.Var, this produces a value of about 100%. If, on the other hand, the variance var(PV) of the actual value PV is greater than the variance var(SP) of the setpoint SP, the controller R is evidently disrupting the control loop formed by the controller R and the process P. This is indicated by a value of the first characteristic number CPI.sub.Var, which evidences deterioration of the control loop response by displaying a value of less than 100%. Changing the sensitivity factor s, which is preset with the value 1, enables a user to make adaptations as desired if, with a specific deterioration of the control loop response, lesser or greater changes to the first characteristic number CPI.sub.Var are to be displayed.

(13) To calculate the second characteristic number CPI.sub.Kas, the average change from one sampling step to the next in each case is calculated as the dimension for the scatter of the setpoint or the actual-value data. Hence, the formula is as follows:

(14) ${\mathrm{CPI}}_{\mathrm{Kas}}=100\%*\frac{\sqrt{\frac{1}{2\left(N-1\right)}\underset{i=0}{\overset{N-1}{.Math.}}{\left({\mathrm{SP}}_{i+1}-{\mathrm{SP}}_i\right)}^2}}{\sqrt{\frac{1}{2\left(N-1\right)}\underset{i=0}{\overset{N-1}{.Math.}}{\left({\mathrm{PV}}_{i+1}-{\mathrm{PV}}_i\right)}^2}},$

(15) wherein the value N reflects the length of the respective data window. Hence, the second characteristic number CPI.sub.Kas takes account of changes in smaller time intervals. If the actual value PV fluctuates around the setpoint SP, but with a smaller amplitude compared to the value range of the setpoint SP, the faulty response is more clearly evident from changes to the second characteristic number CPI.sub.Kas than from changes to the first characteristic number CPI.sub.Var. Taking into account the two characteristic numbers CPI.sub.Var and CPI.sub.Kas advantageously assures that problems in subordinate control loops or the generation of erroneous messages due to faulty evaluations of such control loops will not remain unknown to an operator or monitor of the system.

(16) If the controller R is a controller with a dead zone, an operator is additionally or alternatively able to activate the calculation of a third characteristic number CPI.sub.Db by the diagnostic device D. The object of a dead zone is to allay the actuating signals generated by the controller R for as long as the controlled variable, i.e. the actual value PV, within the dead zone Db is at the setpoint SP. Therefore, in order to reduce wear on and energy consumption of, for example, mechanical actuators, the controller R does not adjust for smaller control deviations that are still within the dead zone. Accordingly, a particularly informative criterion for the evaluation of controllers with a dead zone is the time slice
t(|SPPV|<Db),
in which the controlled variable PV is within the dead zone Db based on a time slice t(AK) with a constant setpoint in automatic mode AK. The calculation formula for the third characteristic number CPI.sub.Db is:

(17) ${\mathrm{CPI}}_{\mathrm{Db}}=\frac{t\left(.Math.\mathrm{SP}-\mathrm{PV}.Math.<\mathrm{Db}\right)}{t\left(\mathrm{AK}\right)}*100\%.$

(18) If the time slice t(AK) is too short, this means that, for the combination of controller parameterization and dimensioning of the dead zone Db, the actual purpose of the dead zone Db, namely to allay the actuating signals, is only incompletely fulfilled because the control deviation leaves the dead zone Db too frequently. Therefore, either the dead zone Db is too narrow or the control response is too irregular. Following the display of a malfunction of this kind, the operator can make corresponding changes to the setting of the controller R to rectify the malfunction.

(19) FIG. 3 depicts courses 30 and 31 of the actual value PV or the setpoint SP for the controller R, which is not optimally set, in a cascade control system such as that shown in FIG. 1. The abscissa of the timing diagram in FIG. 3 shows the time t in seconds and the actual value PV and the setpoint SP are plotted without dimensions on the ordinate. The illustrated segment of a larger sequence of setpoint and actual-value data includes about 500 data pairs. It can be seen from the course 30 of the actual value PV that there is evidently a fluctuation that does not result from the setpoint SP, but must have other causes. This fluctuation is in particular identified by the second characteristic number CPI.sub.Kas with a value of 60%. If the first characteristic number CPI.sub.Var is calculated over the entire window width, a value of approximately 100% is obtained and hence there is no indication of the problem since the variances of the setpoint and of the actual value are virtually identical over the time range considered. This example shows that, preferably, the first and the second characteristic number should be displayed to an operator in conjunction. Preferably the calculation of a minimum should be used for an aggregation of the two characteristic numbers: if the controller produces a negative result with reference to one or the other characteristic number, i.e. the minimum is below a specific limit value, then the operator should thereby be alerted to a possible problem in this control loop.

(20) While there have been shown and described and pointed out fundamental novel features of the invention as applied to preferred embodiments thereof, it will be understood that various omissions and substitutions and changes in the form and details of the methods described and devices illustrated, and in their operation, may be made by those skilled in the art without departing from the spirit of the invention. It is the intention, therefore, to be limited only as indicated by the scope of the claims appended hereto