Heat flux-based process fluid temperature estimation system with improved heat time response

Abstract

The process fluid temperature estimation system (200) includes a mounting assembly (202) configured to mount the process fluid temperature estimation system (200) to an exterior surface of the process fluid conduit (100). A sensor capsule (206) has at least one temperature sensing element disposed therein and is configured to sense a temperature of at least the exterior surface of the process fluid conduit (100). A measurement circuit (228) is coupled to the sensor capsule (206) and configured to detect a characteristic of the at least one temperature sensing element that varies with temperature to provide sensor capsule temperature information. A controller (222) is coupled to the measurement circuit (228) and configured to obtain temperature measurements of the exterior surface of the process fluid conduit (100) and to obtain a reference temperature and generate an estimated process fluid temperature output using a heat transfer calculation using the reference temperature, the exterior surface temperature measurements, and a known thermal relationship between the exterior surface temperature sensor in the sensor capsule and the reference temperature. The controller (222) is also configured to mathematically improve a response time of the process fluid estimation system. In some examples, the controller (222) is configured to extract a system tau value from the measurement data.

Description

Technical Field

[0001] Background The process industry uses process variable transmitters to monitor process variables associated with substances such as solids, slurries, liquids, vapors, and gases in chemical, pulp, petroleum, pharmaceutical, food, and other fluid processing plants. Process variables include pressure, temperature, flow rate, level, turbidity, density, concentration, chemical composition, and properties.

[0002] A process fluid temperature transmitter provides an output related to the process fluid temperature. The temperature transmitter output can be sent to a control room via a process control loop or to another process device that can monitor and control the process.

[0003] Conventionally, process fluid temperature transmitters have been coupled to or used such thermowells, which provide a temperature sensor in thermal communication with the process fluid and, among other things, protect the temperature sensor from direct contact with the process fluid. The thermowell is placed within the process fluid to ensure substantial thermal contact between the process fluid and the temperature sensor disposed within the thermowell. Thermowells are typically designed using a relatively robust metal structure so that they can withstand numerous attacks provided by the process fluid. Such attacks include physical attacks, such as process fluids passing through the thermowell at relatively high speeds; thermal attacks, such as extremely high temperatures; pressure attacks, such as process fluids conveyed or stored at high pressures; and chemical attacks, such as those provided by caustic process fluids. Additionally, thermowells can sometimes be difficult to design into a process facility. Such thermowells require a process penetration to attach the thermowell and extend it into a process vessel such as a tank or pipe. This process penetration itself must be carefully designed and controlled so that the process fluid does not leak from the vessel at the penetration point.

[0004] There are several factors that can potentially compromise the structural integrity of a thermowell. In some cases, not all factors can be fully accounted for, and at times, the thermowell has bent or even broken, requiring the process facility to be shut down for a significant period. For some applications, a thermowell simply cannot be used without potential damage. In such applications, it may be beneficial or even required to use a non-invasive process fluid temperature calculation system. Without such a system, pipe clamp sensors are used to attach temperature sensors to process vessels such as pipes. Such non-invasive process fluid temperature calculations offer the advantage of not requiring process intrusion or directly exposing the thermowell to the process fluid, but there is a trade-off. Specifically, non-invasive process fluid temperature calculation systems are typically less accurate in detecting process fluid temperature than thermowells that extend into the process fluid and directly measure the temperature. Summary of the Invention Problems to be Solved by the Invention

[0005] The desire to use non-invasive temperature sensors located outside of pipes, as described above, is important, but users are generally accustomed to the response time of thermowell sensors. This creates similar expectations when using heat flux-based temperature estimation systems. Improving the response time of heat flux-based temperature estimation system sensors will help remove this barrier and facilitate adoption by users, and will likely increase the applicable fields currently enjoyed by thermowells. Means for Solving the Problems

[0006] The process fluid temperature estimation system includes a mounting assembly configured to mount the process fluid temperature estimation system to the outer surface of a process fluid conduit. A sensor capsule has at least one temperature sensing element disposed therein and is configured to sense at least the temperature of the outer surface of the process fluid conduit. A measurement circuit is coupled to the sensor capsule and is configured to detect the characteristics of at least one temperature sensing element that vary with temperature and provide sensor capsule temperature information. A control device is coupled to the measurement circuit and is configured to obtain a temperature measurement of the outer surface of the process fluid conduit, and obtain a reference temperature, and use a heat transfer calculation using the reference temperature, the outer surface temperature measurement, and a known thermal relationship between the outer surface temperature sensor in the sensor capsule and the reference temperature to generate an estimated process fluid temperature output. The control device is also configured to mathematically improve the response time of the process fluid estimation system.

Brief Description of the Drawings

[0007]

Figure 1A

Figure 1B

Figure 1C

Figure 2

Figure 3

Figure 4A-4B

Figure 4C

Figure 5A

Figure 5B

Figure 6A

Figure 6B

Figure 7

Figure 8A-8B

Figure 9

Figure 10

Figure 11A-11B

Figure 12A

Figure 12B

DETAILED DESCRIPTION OF THE INVENTION

[0008] Detailed Description of Exemplary Embodiments Figure 1A is a diagram of a process fluid temperature estimation system to which the embodiments described herein are particularly applicable. As shown, system 200 generally includes a pipe clamp portion 202 configured to clamp a conduit or pipe 100. The pipe clamp 202 can have one or more clamp ears 204 to enable placement of the clamp portion 202 on the pipe 100 and tightening. Although the clamp illustrated with respect to Figure 1A is particularly useful, in accordance with the embodiments described herein, a mechanical structure suitable for securely placing system 200 on the outer surface of the pipe can also be used.

[0009] System 200 includes a heat flux sensor 206 that is pressed against the outer diameter of the pipe by a spring 208. The term "capsule" is not intended to imply a specific structure or shape, and thus can be formed in a variety of shapes, sizes, and structures. Sensor capsule 206 generally includes one or more temperature sensing elements, such as a resistance temperature detector (RTD) or a thermocouple. The sensors within capsule 206 are electrically connected to a transmitter circuit within housing 260, which is configured to obtain one or more temperature measurements from sensor capsule 206 and calculate an estimated process fluid temperature based on the measurements from sensor capsule 206 and a reference temperature, such as a temperature measured within housing 260 or otherwise provided to the circuitry within housing 260.

[0010] In one example, the basic heat flux calculation can be simplified as follows. T corrected =T skin +(T skin -T reference )*(R pipe / R sensor )

[0011] In this equation, T skin is the measured temperature on the outer surface of pipe 100. T reference is a second temperature obtained from a temperature sensing element that measures T sensor with respect to a location having a known thermal impedance (R skin ). T reference can be sensed by a dedicated sensor within housing 260. However, T referenceIt can also be sensed or inferred in other ways. For example, a temperature sensor can be placed outside the transmitter to replace the final temperature measurement in heat transfer calculations. This external sensor will measure the temperature of the environment surrounding the transmitter. As another example, industrial electronic equipment usually has on-board temperature measurement capabilities. The temperature measurement value of this electronic equipment can be used in heat transfer calculations instead of the final temperature. As another example, if the thermal conductivity of the system is known and the ambient temperature around the transmitter is fixed or user-controlled, the fixed or user-controlled temperature can be used as the reference temperature.

[0012] R pipe is the thermal impedance of the conduit and can be artificially obtained by obtaining pipe material information, pipe wall thickness, etc. Alternatively, the parameters related to R pipe can also be determined and stored for use during calibration of the parameters. Therefore, using an appropriate heat flux calculation as described above, the circuit within the housing 260 can calculate an estimated value (T corrected ) of the process fluid temperature and transmit an indication regarding such process fluid temperature to an appropriate device and / or control room. In the example shown in FIG. 1, such information can be transmitted wirelessly via the antenna 212.

[0013] FIG. 1B is a block diagram of a circuit 210 within a housing 260 of a heat flux measurement system 200 to which embodiments of the present invention are particularly applicable. The circuit 210 includes a communication circuit 220 coupled to a control device 222. The communication circuit 220 can be a suitable circuit capable of transmitting information regarding an estimated process fluid temperature. The communication circuit 200 enables the heat flux measurement system 200 to send a process fluid temperature output via a process communication loop or segment. Suitable examples of process communication loop protocols include a 4 - 20 milliamp protocol, a Highway Addressable Remote Transducer (HART®) protocol, a FOUNDATION™ fieldbus protocol, and a WirelessHART protocol (IEC62591).

[0014] The heat flux measurement system 200 also includes a power supply module 224 that provides power to all components of the system 200 as indicated by arrow 226. In embodiments where the heat flux measurement system 200 is coupled to a wired process communication loop, such as a HART® loop or a FOUNDATION™ fieldbus segment, the power supply module 224 can include suitable circuitry for conditioning the power received from the loop or segment to operate the various components of the system 200. Thus, in such wired process communication loop embodiments, the power supply module 224 can provide suitable power conditioning to enable the entire device to be powered by the loop to which it is coupled. In other embodiments, where wireless process communication is used, the power supply module 224 can include a power source such as a battery and suitable conditioning circuitry.

[0015] The control device 222 includes a suitable structure capable of generating a heat flux-based process fluid temperature estimate using measurement values from sensors within the capsule 206 and a further reference temperature, for example the final temperature within the housing 260. In one example, the control device 222 is a microprocessor. The control device 222 is communicatively coupled to the communication circuit 200.

[0016] A measurement circuit 228 is coupled to the control device 222 and provides a digital indication regarding measurement values obtained from one or more temperature sensors 230. The measurement circuit 228 can include one or more analog-to-digital converters and / or a suitable multiplexing circuit for interfacing one or more analog-to-digital converters to the sensors 230. Additionally, the measurement circuit 228 can include suitable amplification and / or linearization circuitry appropriate for the various types of temperature sensors used.

[0017] In the case of a heat flux-based temperature sensor, its heat transfer function is denoted as H(t), which represents its thermal response to changes in the process fluid temperature. Additionally, Tp(t) is defined as the calculated process temperature and Tm(t) is defined as the measurement output. And the problem is to determine the value of Tp(t) (i.e., the process fluid temperature) given the measured values of H(t) and Tm(t). Since the process temperature is directly extracted in real time, this procedure essentially excludes the time response of the heat flux sensor.

[0018] This approach can be better understood by considering a simple case that can be generalized to more complex systems. In the case of the heat flux-based temperature estimation system shown in Figure 1A, the fluid, pipe, and module are approximated as a lumped-parameter thermal system as shown in Figure 1C. Such a system can be regarded as an electrical circuit composed of heat resistors and capacitors, where the nodal temperatures are voltage analog equivalents.

[0019] In Figure 1C, R convection is the effective thermal impedance due to heat convection from the process fluid to the inner wall of the pipe. R pipe and Cpipe represents the thermal resistance and heat capacity of the pipe (note that the lumped parameter model can be decomposed into smaller elements to better approximate the continuum system, but the solution procedure is essentially the same, so this simplified model can be used). Finally, the thermal resistance and heat capacity associated with the module remain constant regardless of the process fluid conditions.

[0020] Figure 2 shows the same lumped parameter thermal model along with the corresponding time constants (tau) and temperature nodes for each section. Since the module sections are fixed, they can be added later once the basic system is understood. Therefore, for clarity, they are ignored in the following analysis.

[0021] Figure 3 is a diagram of a simplified form of the lumped parameter thermal model. In Figure 3, a simplified form of the problem is shown. R convection and R pipe are in series, so note that they are combined into R total . The R-C product has units of time and is denoted by tau (i.e., tau = R total ·C pipe ). Typically, to solve such problems by finding any input Tp(t) (abbreviation for T process (t)) and Tm(t) (abbreviation for T measured (t), i.e., the measured response temperature), one can work in the time domain by solving the convolution integral or in the complex frequency domain using the Laplace transform. The Laplace transform representation of the simplified system can be written as follows.

[0022] T m (s) = T p (s)·H(s) Equation 1

[0023] where, for the configuration shown in Figure 3, H(s) is simply 1 / (1 + s·tau). In general, the Laplace transform of any function is defined as follows.

[0024]

Equation

[0025] where s is the complex frequency parameter s = σ + iω (σ and ω are real numbers). The advantage of this equation is that the solution of Tp(s) is a simple algebraic expression, namely

[0026]

Number

[0027] which can be obtained by

[0028] However, for it to be effective, Tp(s) needs to be transformed back to the time domain using the inverse Laplace transform. This can be expressed symbolically as follows.

[0029]

Number

[0030] where the inverse Laplace transform is defined as follows.

[0031]

Number

[0032] Unfortunately, inverse Laplace calculations are difficult to implement in real time on a continuous basis. Because of this difficulty, the Laplace transform is usually rewritten into the Z-transform, which is more suitable for discrete sampled data. This is the preferred method for complex transfer functions, but in the case of Figure 3, it can be solved in a simpler and more direct way. Recall the problem of finding the measured temperature Tm(t) to be solved. Tp(t) must be calculated on a continuous-time basis. R total and C pipe are known, and thus τ (= R total ·C pipe ) is also known. Therefore, Tp(t) can be calculated mathematically. The differential equation for solving the first-order system in Figure 3 is as follows.

[0033] [Number]

[0034] This can be converted into a finite difference equation for the discrete time step Δt.

[0035] [Number]

[0036] Equation 7 is an example of a discretized differential equation that can be used to improve the time response of the process fluid temperature estimation system. This equation can be solved in real time on a computer or microprocessor using data acquired at the sampling period of Δt.

[0037] Figures 4A and 4B show an exemplary problem (using an arbitrary tau value of 140 seconds) where the input temperature T process (reference number 30) is presented to the thermal system of FIG. 3. The resulting T measured temperature is labeled at reference number 302 in FIG. 4B. Comparing the two curves, a significant delay on the order of tau can be observed during the measured response. This is the time response that should be accelerated.

[0038] Applying Equation 7 to the measurement data results in the curve labeled 304 in FIG. 4C. Clearly, the calculated T process (Calc) curve in FIG. 4C coincides with the actual input T process curve (300) in FIG. 4A. Therefore, the use of Equation 7 effectively eliminates the delay in the response at T measured if the correct tau (τ) value (i.e., the value of tau for the actual system response) is given. The input process temperature is not predicted, but T measuredIt should be noted that it is extracted from

[0039] Figures 5A and 5B show another example where the input temperature T process (reference number 306) is composed of a rising temperature ramp and a falling temperature ramp. Again, assuming that the system response has a τ value of 140 seconds, Equation 7 is used to obtain T measured (the curve of reference number 308 in Figure 5B), and T process (Calc) (the curve of reference number 310) is extracted. As in the previous example, the calculated T process (Calc) line 310 in Figure 5B using Equation 7 reproduces the actual T process value (the curve 306 in Figure 5A) at a high level.

[0040] The last example, shown in Figure 6A, shows an input composed of steps and a sinusoidal temperature swing. Figure 6B shows the measured response (reference number 312) and the calculated response (reference number 314) using Equation 7. Again, excellent fidelity in extracting the actual process temperature from the measured temperature data is shown.

[0041] The above examples illustrate the effectiveness of the above-described method, and present a method for effectively accelerating the response time of a heat flux-based process fluid temperature estimation system using a measured signal under the condition that the process response function is known or equivalently the system effective tau value. Although the time response of the module is ignored in the above calculations, its time constant can be easily characterized and added to the process tau as an approximation (under the condition that it is much smaller than the process tau), or more precisely, incorporated into the transfer function through the Z-transform equation and added to the system response function.

[0042] Knowing the process tau value is important for the said method and depends on the pipe details (e.g., line size, wall thickness, and pipe material) as well as the properties of the fluid (e.g., liquid or gas, flow rate, temperature, etc.). There are equations suitable for estimating the thermal impedance value and the convection value with reasonable accuracy regarding the pipe material, line size, and flow conditions. However, it is more desirable and accurate to directly extract the system response time constant from the raw measured temperature data. To see a way to achieve this, consider Equation 6 and its second time derivative (labeled as Equation 8).

[0043]

Equation

[0044] There are two specific cases where these equations can be used to determine the value of τ from the measured temperature data.

[0045] In the first case, if the process changes the temperature in a stepwise manner, immediately after the end of the step, there is a period during which the process temperature is constant but the measured temperature is still changing. In the range of this region, for two different times t1 and t2, Tp(t1) = Tp(t2) (where Tm(t1) ≠ Tm(t2)). When this condition is met, Equation 6 can be used to evaluate τ as follows.

[0046]

Equation

[0047] where Tm = T measured is true.

[0048] In the second case, when the process temperature ramps up or ramps down and the ramp rate is approximately constant (i.e., the derivatives at two different time steps are almost the same, and as a result, dTp(t1) / dt ≒ dTp(t2) / dt), the following can be shown from Equation 8.

[0049] [Number]

[0050] In order to use Equation 9 or 10, some knowledge regarding the cases where they can be applied appropriately is required. Unfortunately, this is not directly apparent from Tp(t), because that is precisely what has to be extracted. However, there is information embedded in the time derivative of Tm(t) that can be useful in determining the region of application.

[0051] In the case of Case 1, the effective range can be determined by monitoring the first and second time derivatives of the measured temperature. Consider the case in FIG. 7 where there is a step in the process temperature (designated by reference numeral 316 in FIG. 7) and a measurement response (designated by reference numeral 318).

[0052] FIGS. 8A and 8B plot the first time derivative (reference numeral 320 in FIG. 8A) and the second time derivative (reference numeral 322 in FIG. 8B) of the measured temperature for a step change in the process temperature (324). The derivative values are shown on the right - hand axis. Upon examining FIG. 8A, there is a sharp discontinuity in the first time derivative of Tm(t) at the start of the step change. Additionally, in FIG. 8B, an inversion of sign is shown in the second time derivative of Tm(t) at the start of the step. These are signals that a temperature step transition has occurred in the process temperature and that the application of Equation 9 for extracting the value of tau is justified. process There is a sharp discontinuity in the first time derivative of Tm(t) at the start of the step change. Additionally, in FIG. 8B, an inversion of sign is shown in the second time derivative of Tm(t) at the start of the step. These are signals that a temperature step transition has occurred in the process temperature and that the application of Equation 9 for extracting the value of tau is justified.

[0053] FIG. 9 shows the real - time extracted tau value at reference numeral 326 using Equation 9 during the effective period. The extracted tau value (right - hand axis) is very close to 140 seconds, which is the actual system response. Note that after the system reaches the steady state and T measured (t)=T process (t), the derivative is zero and the extraction method of Equation 9 can no longer be used.

[0054] In the case of Case 2 and the temperature lamp input, the effective range can be determined, as in the case of Case 1, by monitoring the first and second time derivatives of the measured temperature in real time. The process lamp (reference number 328) and the measurement response (reference number 330) are shown in FIG. 10.

[0055] FIGS. 11A and 11B show the first time derivative (332) and the second time derivative (334) of the measured temperature, respectively, for the ramp change of the process temperature (336). Again, the differential values are on the right axis. Examining FIG. 11A, there is a gradual increase in the first time derivative of Tm(t) during the ramp. In addition, an inversion is seen in the second time derivative of Tm(t) during the ramp. The region of the gradual change is a signal that a temperature ramp transition is occurring in the process temperature and justifies the application of Equation 10 to extract the value of tau. process During the ramp, there is a gradual increase in the first time derivative of Tm(t). In addition, an inversion is seen in the second time derivative of Tm(t) during the ramp. The region of the gradual change is a signal that a temperature ramp transition is occurring in the process temperature and justifies the application of Equation 10 to extract the value of tau.

[0056] FIG. 12A shows the real-time extracted tau value (338) using Equation 10 during the effective period. The extracted tau value is very close to 140 seconds, which is the actual system response. In addition, Equation 9 can also be applied if the ramp ends with the results shown in FIG. 12. As in Case 1, after the system reaches the steady state and T measured =T process Note that after reaching, the derivative is zero and the extraction methods of Equation 9 or 10 can no longer be used, as demonstrated by the increase in noise (the small fluctuations in lines 338 and 340 in FIGS. 12A and 12B, respectively).

[0057] The above example illustrates that it is possible to enhance the time response of a heat flux-based process fluid temperature estimation system using only the measured output, provided that the system transfer function is known. In the case of a thermal system, this translates to knowing what the time response function of the system is, or in most cases, knowing the primary response time, i.e., the value of tau. The appropriate value of tau for the system can be determined from the process conditions and the pipe structure, or directly from the measured temperature under specific conditions, as illustrated.

Claims

1. An attachment assembly configured to attach a process fluid temperature estimation system to the outer surface of a process fluid conduit; A sensor capsule having at least one temperature sensing element disposed therein and configured to sense at least the temperature of the outer surface of the process fluid conduit; A measurement circuit coupled to the sensor capsule and configured to detect a characteristic of the at least one temperature sensing element that varies with temperature and provide sensor capsule temperature information; A control device coupled to the measurement circuit and configured to obtain a measured value of the temperature of the outer surface of the process fluid conduit, obtain a reference temperature, and use a heat transfer calculation using the reference temperature, the measured outer surface temperature value, and a known thermal relationship between the outer surface temperature sensor in the sensor capsule and the reference temperature to generate an estimated process fluid temperature output; comprising; A process fluid temperature estimation system, wherein the control device is configured to obtain a system response function and use the system response function to adjust the estimated process fluid temperature output.

2. The process fluid temperature estimation system according to claim 1, wherein the system response function models a time constant (τ) of the system.

3. The process fluid temperature estimation system according to claim 2, wherein the control device is configured to use a plurality of discretized differential equations.

4. The process fluid temperature estimation system according to claim 3, wherein the control device is configured to select one of the plurality of discretized differential equations based on a type of heat change.

5. The process fluid temperature estimation system according to claim 4, wherein the type of heat change is a step change.

6. The process fluid temperature estimation system according to claim 4, wherein the type of heat change is a ramp change.

7. The process fluid temperature estimation system according to claim 4, wherein the control device is configured to select one of the plurality of discretized differential equations by calculating a first derivative of the measured outer surface temperature value over time.

8. The process fluid temperature estimation system according to claim 7, wherein the control device is configured to select one of the plurality of discretized differential equations by calculating a second derivative of the measured outer surface temperature value over time.

9. The process fluid temperature estimation system according to claim 1, wherein the control device is configured to extract a response time (tau) from a set of raw temperature measurement values on the outer surface of the process fluid conduit.

10. A method of operating a process fluid temperature estimation system, comprising: receiving an indication of the temperature on the outer surface of a process fluid conduit; receiving an indication of a reference temperature having a known thermal relationship with the outer surface of the process fluid conduit; receiving a system response function; using a processor of the process fluid temperature estimation system to perform a heat flow calculation based on the indication of the temperature on the outer surface of the process fluid conduit and the indication of the reference temperature to provide a process fluid temperature output; and executing at least one discretized differential equation by a control device to adjust the process fluid temperature output based on the system response function The method including the steps.

11. The method according to claim 10, wherein the differential equation uses a first-order time constant tau.

12. The method according to claim 11, wherein the time constant tau is determined using an equation describing the thermal properties of the process fluid conduit.

13. The method according to claim 11, wherein the time constant tau is determined using an equation describing the thermal properties of the process fluid conduit and the process fluid.

14. The method according to claim 11, wherein the time constant tau is extracted over time from a series of indications of the temperature on the outer surface of the process fluid conduit.

15. The method according to claim 10, wherein a region for effective tau extraction is determined over time from a first time derivative of a series of indications of the temperature on the outer surface of the process fluid conduit.

16. The method according to claim 11, wherein a region for effective tau extraction is determined over time from a second time derivative of a series of indications of the temperature on the outer surface of the process fluid conduit.

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