Technical Field

The invention relates to a thermal steam flowmeter with an artificial intelligence based software and a smart sensor technology, which steam flowmeter is able to produce its own energy.

State of the Art

Today, steam technology is used extensively in all fields. There is multiple critical equipment in the steam lines with high pressure and temperature used in the production processes of the Oil and Gas, Chemical, Food, Pharmaceutical, Paper, Power Plants and Textile industries. In the globally increasing energy costs, companies desire to increase energy and process efficiency, and to gain a competitive advantage in the product costs by controlling the amount of steam production and consumption.

Steam flowmeters are mechanical equipment used on steam lines and controlled by modernizing the pipes and combining the auxiliary apparatus and electronic systems. The steam flowmeters of vortex or orifice type cause failures which are both costly and caused by connection equipment by modernizing the steam lines on the pipe.

Conventional steam flowmeters are affected by problems such as vibration, contamination in the pipeline, sudden pressure fluctuations, leakage, and cause false measurements to occur. In addition, these flowmeters, which have calibration and leakage problems that cannot be performed on time, require serious revisions in the steam lines. Ultrasonic steam flowmeters, on the other hand, are affected by the vibrations on the line and have a very high margin of error, even though they take measurements from outside of the pipe.

In a research in the literature, a number of patents related to steam flowmeters were cited. Patent application publication no. CN114046833A relates to a steam flow metering method and device based on a vortex shedding flowmeter. The patent discloses a steam flow metering method and device based on a vortex shedding flowmeter, which are applied to a power plant comprising a steam supply pipeline, and the steam supply pipeline is provided with a thermal resistor and a vortex shedding flowmeter. The method includes the following steps: Acquiring a steam pocket temperature value in a steam header of a user and an instantaneous steam flow value and a steam temperature value in a steam supply pipeline in real time; according to the temperature difference value between the steam drum temperature value and the steam temperature value, determining the steam using state of a user; and determining the steam flow used by the user based on the instantaneous flow value and the steam use state of the user, wherein a thermal resistor is used for measuring the temperature value of the steam pocket. Therefore, the steam flow used by a user can be metered when the steam flow is lower than the measurable lower limit of the vortex shedding flowmeter.

The patent application publication no. CN114216056A discloses a method for measuring the local pressure loss of a steam conveying pipe, and the method comprises the following steps: Step 1 , allowing the steam to pass through the pipeline, allowing the steam to pass through a turbine flowmeter, opening the exhaust valves on both sides, removing the air in the pipeline, so that the reading of the sides of a differential pressure instrument and a display instrument is zero, Step 2, bringing the water outlet regulating valve to maximum, allowing the maximum flow to pass through the pipe, after the water flow is stable, recording the readings on the pressure gauge and turbine flowmeter and thus obtaining a pressure difference and flow according to the readings on the differential pressure gauge and turbine flowmeter; and step 3, turning the water outlet regulating valve downwards in an inclined manner when the different flows pass through the pipe. In the method, the signal measured is transmitted to a lower computer connected a computer thereunder, the lower computer converts the signal and transmits the same to an upper computer, the upper computer calculates a correct value of a local pressure loss, the accuracy of the local pressure loss measurement may be increased as much as possible, and it is important to guide the production process for the design and transport of the steam pipes.

Consequently, there is a need for a development in the related technical field due to the above-mentioned problems and the inadequacy of the existing solutions. Object of the Invention

The present invention relates to a thermal steam flowmeter with an artificial intelligence based software and a smart sensor technology, eliminating the above-mentioned disadvantages and providing novel advantages for the related technical field, wherein the steam flowmeter is able to produce its own energy.

The main object of the invention is to develop a steam flowmeter with a smart sensor technology, comprising an integration of the artificial intelligence based thermodynamics and fluid mechanics formulation, wherein the steam flowmeter is able to produce its own energy and may be mounted externally without any modernization to the pipes of the steam lines used in different industrial fields (energy, oil & gas, textile, pharmaceutical, food & drink, packaging, chemical, paper, etc.)

Another object of the invention is to develop a sensor technology which is able to produce electric energy required to operate the sensor system by converting the temperature difference and/or vibration and motion to electric energy.

A further object of the invention is to monitor the steam flow through the pipe in real time via the steam flowmeter of the invention developed based on the thermal measurement.

The steam flowmeter of the invention comprises artificial intelligence based software based on thermal measurement and a smart sensor technology which is able to produce its own energy, and thus, a measurement method has been developed with a design which does not require a modernization outside the pipe.

An algorithm was developed using the thermodynamic values of the saturated steam and superheated steam based on the continuous measurement of temperature data, and the trend change was combined with the artificial intelligence-based LSTM method and the flow rate graph was obtained. This flow rate graph is displayed in the cloudbased software, allowing it to be monitored continuously with the Internet of things technology. In addition, this monitoring system was created by using the smart sensor technology which produces its own energy. Description of Figures

Fig. 1 is a top view of the steam flowmeter of the invention.

Fig. 2 is a side view of the steam flowmeter of the invention.

Fig. 3 is a front view of the steam flowmeter of the invention.

Fig. 4 is a perspective view of the steam flowmeter of the invention.

Fig. 5a is a perspective view of a energy generator.

Fig. 5b is a perspective view of an alternative energy generator.

Fig. 6 is a schematic view of the electronic circuit box of the steam flowmeter of the invention.

Description of the Part References

A. Steam flowmeter

B. Pipe

1. Flowmeter connecting element

2. Sensor connecting element

3. Inlet temperature sensor

4. Outlet temperature sensor

5. Input temperature transmitting cable

6. Output temperature transmitting cable

7. Energy transmitting cable

8. Thermoelectric material

9. Cooling fin

10. Electronic circuit box

11. Super capacitor/Rechargeable battery

12. Electronic board with a microprocessor

13. Wi-fi module

14. Electromagnetic material

15. Vibration/Ultrasonic Sensor Detailed Description of the Invention

The invention relates to an artificial intelligence based steam flowmeter A with a smart sensor technology, which is able to produce its own energy and may perform measurement by being mounted externally without any modernization to the pipes B in the steam lines used in different industrial fields (energy, oil & gas, textile, pharmaceutics, food & drink, packaging, chemistry, paper, etc.).

Fig. 1 , Fig. 2, Fig. 3 and Fig. 4 are views of the steam flowmeter A of the invention from different angles. The steam flowmeter A may be mounted externally without any modernization to the pipes B of the steam lines, perform a measurement process, and may produce its own energy, wherein the steam flowmeter has artificial intelligence based software and a smart sensor technology.

The steam flowmeter A of the invention comprises a sensor technology which is able to produce electric energy required to operate the sensor system by converting the temperature difference and/or vibration and motion to electric energy. The steam flow through the pipe B is monitored in real time via the steam flowmeter A of the invention developed based on the thermal measurement.

The steam flowmeter A of the invention comprises artificial intelligence based software based on thermal measurement and a smart sensor technology which is able to produce its own energy, and thus, may perform a measurement with a design which does not require a modernization outside the pipe B.

An algorithm was developed using the thermodynamic values of the saturated steam and superheated steam based on the continuous measurement of temperature data, and the trend change was combined with the artificial intelligence-based LSTM method and the flow rate graph was obtained. This flow rate graph is displayed in the cloudbased software, allowing it to be monitored continuously with the Internet of things technology. In addition, this monitoring system was created by using the smart sensor technology which produces its own energy.

As seen in the figures, the steam flowmeter A of the invention performs the measurement with 2 sensors spaced 1 meter apart on the pipe B. The inlet temperature sensor 3 mounted on the pipe B via the sensor connecting element 2 measures the temperature value and transmits the same to the steam flowmeter A via the input temperature transmitting cable 5.

The outlet temperature sensor 4 mounted on the pipe B via the flowmeter connecting elements 1 measures the temperature value and transmits the same to the steam flowmeter A via the output temperature transmitting cable 6.

The related temperature values are transmitted to the electronic board with a microprocessor 12 in the electronic circuit box 10, which controls the steam flowmeter A, The corresponding input and output temperature values are sent to the artificial intelligence based data analyzing and informing display operating on a smart device in an instant and wireless manner by the Wi-fi module 13 and LoraWAN in the electronic circuit box 10 and transmits the same to the authorized persons/units as graphical and/or numeric values. Abnormal increases or decreases in values may be detected instantly.

The energy required for the operation of the electronic equipment such as the electronic board with a microprocessor 12 and Wi-fi module 13 is provided by a super capacitor/rechargeable battery 11 in the electronic circuit box 10. The super capacitor/rechargeable battery 11 , on the other hand, may provide energy with a thermoelectric material 8 and/or electromagnetic material 14 or solar panel, which are mounted on the pipe B. The thermoelectric material 8 is used, which generates electrical energy from the temperature difference through a cooling fin 9 located on a flexible or rigid surface and containing multiple fins.

Alternatively, an electromagnetic material 14 which generates electrical energy from the vibration and motion energy on the pipeline may be used in the pipelines operating at high temperatures. Or, by using both thermoelectric material 8 and electromagnetic material 14 together, the electrical energy may be produced from both temperature difference and vibration and motion energy.

The electrical energy generated is continuously fed to the super capacitor/rechargeable battery 11 via an energy transmitting cable 7, and the energy needed by the system is supplied. The need for electrical energy may be obtained by using the temperature difference between the temperature on the pipeline 1 and the cooling fin 9. Similarly, the fluid of high temperature and pressure passing through the pipeline 1 is converted into electrical energy via the electromagnetic material 14, and the electrical energy is fed to, and stored in, the super capacitor/rechargeable battery 11. Therefore, the electrical energy of the system is provided by the system itself, and the problems such as battery depletion are eliminated.

Thanks to the sensor system, an alarm for steam leakage, calculation of maintenance cost, energy recovery and status report, maintenance plan information may be provided. Due to the artificial intelligence algorithm used, data analysis maybe made, possible errors and risks may be detected in advance, and the system is enabled to learn by itself.

In the system of the invention, the temperature measurements are performed from different points on the pipeline, and the system heat transfer and pressure drop are monitored in a time dependent manner depending on the proportional monitoring of the primary fluid and secondary fluid measurement, and clogging, unsuccessful operation, component failure and percentage of contamination calculations may be performed according to the system threshold values. Mathematical modeling (Multivariate Anormaly Detection Using Long Short Term Memory (LSTM) Network For Forecasting) is used to detect abnormal conditions in fluid temperature values.

Thanks to the system and method of the invention, the mathematical algorithm may be interpreted instantaneously, daily and monthly by calculating Reynolds, velocity and mass and volumetric steam flow according to the fluid temperatures.

A notification is provided by a sensor 15 located in the system of the invention according to the time-dependent temperature values and the threshold values using a detection of water hammers on the devices at a certain threshold value and a mathematical modelling (Multivariate Anormaly Detection Using Long Short Term Memory (LSTM) Network For Forecasting).

In the system of the invention, interpretation and notification are provided by making calculations according to the values of the data analysis thermodynamic equations, and an analysis is performed using the (LSTM) autoencoder network for anomaly detection, and any failures are reported.

The system of the invention reports the data during the fluid temperature-dependent period of time, the input and output temperature values and the failures by the Vibration/Ultrasonic Sensor 15 using a comparative analysis of Multivariate Anormaly Detection Using Long Short Term Memory (LSTM) Network For Forecasting.

The method applies the combined matrix solutions according to fluid temperature values in critical equipment and reports by LSTM autoencoder network for anomaly detection.