DESC:FIELD
The present disclosure generally relates to a recovery unit. More particularly, the present disclosure relates to a computer-implemented system for a Sulphur recovery unit.

DEFINITIONS
As used in the present disclosure, the following terms are generally intended to have the meaning as set forth below, except to the extent that the context in which they are used to indicate otherwise.
Claus process: The term “Claus process” refers to a multi-step process of recovering elemental Sulphur from hydrogen sulfide found in the crude natural fuel.
Impact factor analysis: The term “impact factor analysis” refers to a machine learning (ML) technique that infers and forecasts the condition parameters of the components of Sulphur recovery unit and then apply parameter ranking algorithms to investigate the behavioral data to find the highest 'impact' of the parameters on the condition of the components of Sulphur recovery unit.
Sensible heat transfer: The term “sensible heat transfer” refers to the exchange of heat that changes the temperature of a body or a thermodynamic system, and some macroscopic variables of the body or system, but leaves unchanged certain other macroscopic variables of the body or system, such as volume or pressure.
Latent heat transfer: The term “latent heat transfer” refers to the energy released or absorbed, by a body or a thermodynamic system, during a constant-temperature process.
SRU: The term “latent heat transfer” refers to Sulphur Recovery Unit.
BACKGROUND
The background information herein below relates to the present disclosure but is not necessarily prior art.
Sulfur recovery unit is a crucial unit in the refineries or gas plants which converts H2S in a crude natural fuel to valuable elemental Sulphur through the Claus process and ultimately minimizes the release of the amount of sulfur compounds to the atmosphere. An unplanned/sudden shutdown or outage of the Sulphur recovery units in the refineries is an unexpected event that negatively impacts the recovery rate of Sulphur and the quality of the recovered Sulphur. This event may cause an unplanned delay which can subsequently turn into major hurdles to the productivity. This may adversely affect the production cost, and leads to undue utilization of labor and time. The efficiency of the Sulphur recovery may be compromised if the outage is not detected well in advance. Further, focus on most Sulphur Recovery Unit’s monitoring scheme is emphasized over the process and not on the Utilities front. While the Sulphur recovery process in itself is very sensitive to different process parameters, some of the most crucial parameters that determine the smooth functioning if the SRU are the process temperatures. These temperatures are functions of the steam distribution and the condensate network. Effective management of the steam distribution and condensate evacuation allows for better control over the entire process. Most Sulphur Recovery Units (SRUs) rely on manual intervention for maintenance of these Steam jacketed lines.

Therefore, there is felt a need to provide a system for Sulphur recovery units in the refineries or gas plants that mitigates the drawbacks mentioned herein above
OBJECTS
Some of the objects of the present disclosure, which at least one embodiment herein satisfies, are as follows:
It is an object of the present disclosure to ameliorate one or more problems of the prior art or to at least provide a useful alternative.
An object of the present disclosure is to provide a computer-implemented system for Sulphur recovery unit.

Yet another object of the present disclosure is to provide a computer-implemented system for Sulphur recovery unit to prevent any unplanned shutdown/outage.

Still another object of the present disclosure is to provide a computer-implemented system for Sulphur recovery unit to ensure efficient recovery of Sulphur.

Another object of the present disclosure is to provide a computer-implemented system for Sulphur recovery unit based on the prediction model.

Yet another object of the present disclosure is to provide a computer-implemented system for estimating the life of Sulphur recovery unit.

Other objects and advantages of the present disclosure will be more apparent from the following description, which is not intended to limit the scope of the present disclosure.
SUMMARY
The present disclosure describes a computer-implemented system for a Sulphur recovery unit.
The system comprises a repository, a data acquisition module, a monitoring module, a prediction module and an alert module.
The repository is configured to store a set of pre-determined prediction rules, a list of at least one critical component and a plurality of parameters associated with the component and a threshold value corresponding to each of the parameter.
The data acquisition module is configured to acquire at least one value corresponding to each of the parameter for the critical component by a set of sensors installed at a plurality of critical locations.
In an embodiment, the parameters include capturing steam related parameters at different location within the system.

In an embodiment, the critical locations includes steam traps, sulphur lines, sulphur locks, steam based preheaters, catalyst bed and condenser lines.

In another embodiment, the sensor includes:
• a set of temperature sensors for capturing the thermal profile;
• a set of pressure sensors for estimating the saturated steam properties; and
• a set of flow meters to capture the different flow rates of different fluids at different sections within the system.
In an embodiment, the critical components include:

• at least one knockout drum;
• at least one pre-heater;
• at least one combustion chamber;
• at least one boiler;
• at least one condenser;
• at least one reactor;
• at least one reheater;
• at least one degassing unit; and
• at least one storage pit.

The monitoring module is configured to cooperate with the data acquisition module to monitor malfunctions and deviations of the values of each of the parameter for the critical component with at least one premise/off premise connected device based on the threshold value.
The monitoring module includes a health monitoring module, a correlation matrix module and an impact factor analysis module.

The health monitoring module is configured to monitor health of the critical component based on the threshold value and the value of each of the parameter.
The correlation matrix module is configured to create a correlation matrix based on the monitored health. The impact factor analysis module is configured to cooperate with the correlation matrix module to evaluate a degree of an effect of the parameters on each other based on the correlation matrix.

The prediction module is configured to cooperate with the monitoring module to predict the approximate life of each of the critical component based on the monitoring and the prediction rules.

The alert module is configured to cooperate with the prediction module to alert a user based on the prediction.

The data acquisition module, the monitoring module, the prediction module and the alert module are implemented using one or more processor(s).
The present disclosure describes a method to implement a Sulphur recovery unit. The steps include:
• storing, by a repository, a set of pre-determined prediction rules, a list of at least one critical component and a plurality of parameters associated with the component and a threshold value corresponding to each of the parameter;
• acquiring, by a data acquisition module, at least one value corresponding to each of the parameter for the critical component by a set of sensors installed at a plurality of critical locations;
• monitoring, by a monitoring module, malfunctions and deviations of the values of each of the parameter for the critical component with at least one premise/off premise connected device based on the threshold value;
• predicting, by a prediction module, the approximate life of each of the critical component based on the monitoring and the prediction rules; and
• alerting, by an alert module, a user based on the prediction.
BRIEF DESCRIPTION OF ACCOMPANYING DRAWING
A computer-implemented system for a Sulphur recovery unit, of the present disclosure will now be described with the help of the accompanying drawing, in which:

Figure 1 illustrates a block diagram depicting a computer-implemented system for a Sulphur recovery unit;

Figure 2 illustrates a basic schematic representing the various components of the system in Figure 1;
Figure 3 illustrates a temperature profiling for the system in Figure 1; and
Figure 4 illustrates a method depicting the steps to implement a Sulphur recovery unit.
LIST OF REFERENCE NUMERALS USED IN DETAILED DESCRIPTION AND DRAWING
100 system
102 repository
104 data acquisition module
106 monitoring module
108 prediction module
110 alert module
112 health monitoring module
114 correlation matrix module
116 impact factor analysis module
DETAILED DESCRIPTION
Embodiments, of the present disclosure, will now be described with reference to the accompanying drawing.
Embodiments are provided so as to thoroughly and fully convey the scope of the present disclosure to the person skilled in the art. Numerous details are set forth, relating to specific components, and methods, to provide a complete understanding of embodiments of the present disclosure. It will be apparent to the person skilled in the art that the details provided in the embodiments should not be construed to limit the scope of the present disclosure. In some embodiments, well-known processes, well-known apparatus structures, and well-known techniques are not described in detail.
The terminology used, in the present disclosure, is only for the purpose of explaining a particular embodiment and such terminology shall not be considered to limit the scope of the present disclosure. As used in the present disclosure, the forms "a,” "an," and "the" may be intended to include the plural forms as well, unless the context clearly suggests otherwise. The terms "comprises," "comprising," “including,” and “having,” are open ended transitional phrases and therefore specify the presence of stated features, elements, modules, units and/or components, but do not forbid the presence or addition of one or more other features, elements, components, and/or groups thereof.
The particular order of steps disclosed in the method and process of the present disclosure is not to be construed as necessarily requiring their performance as described or illustrated. It is also to be understood that additional or alternative steps may be employed.
A computer-implemented system for a Sulphur recovery unit, is now being described with reference to Figure 1 till Figure 4.
The present disclosure envisages a computer-implemented system for sulphur recovery unit. The computer-implemented system for sulphur recovery unit is a diagnostic system that ensures the maximum uptime of the sulphur recovery unit and prevents any unwanted outage or shutdown. This system ensures maximum recovery of sulphur and the most efficient operations.
Referring to Figure 1, the computer-implemented system (100) for a Sulphur recovery unit (hereinafter referred as “system (100)”) comprises a repository (102), a data acquisition module (104), a monitoring module (106), a prediction module (108) and an alert module (110).
The repository (102) is configured to store a set of pre-determined prediction rules, a list of at least one critical component and a plurality of parameters associated with the component and a threshold value corresponding to each of the parameter.
The data acquisition module (104) is configured to acquire at least one value corresponding to each of the parameter for the critical component by a set of sensors installed at a plurality of critical locations.
In an embodiment, the parameters include capturing steam related parameters at different location within the system (100).
In an embodiment, the set of sensors enable active real time diagnosis of malfunctions and deviations of critical process parameters to ensure efficient operation of the unit.
In another embodiment, the data acquisition module (104) includes, but is not limited to, a supervisory control and data acquisition (SCADA) or proprietary (data acquisition) DAQ system. Other known data acquisition system can also be used.
In an embodiment, the critical locations include steam traps, sulphur lines, sulphur locks, steam based preheaters, catalyst bed and condenser lines.

In another embodiment, the sensor includes:
• a set of temperature sensors for capturing the thermal profile;
• a set of pressure sensors for estimating the saturated steam properties; and
• a set of flow meters to capture the different flow rates of different fluids at different sections within the system (100).
The monitoring module (106) is configured to cooperate with the data acquisition module (104) to monitor malfunctions and deviations of the values of each of the parameter for the critical component with at least one premise/off premise connected device based on the threshold value.

In an embodiment, the critical components of any sulphur recovery unit include, but is not limited to, knock out drum, combustion chambers, reactors, reheater, preheaters, waste heat boiler, condensers, preheaters, Sulphur locks, Sulphur pit, degassing unit, storage pit, stage tank, steam tracers, steam traps and Sulphur cooler. Other suitable known critical components can also be considered. The details pertaining to some critical components is provided below:
Knockout Drums:
This is where the H2S gas is accumulated before it enters into the preheating stage and further into the Sulphur recovery process:

Waste heat Boiler:
This is where the thermal stage of SRU occurs. Here H2S gas is burnt to produce extremely high temperature flue gases containing gaseous form of pure elemental Sulphur.

Condensers:
Condenser’s play a critical role in effective condensation and recovery of molten Sulphur. While doing this, it also generates high amounts of steam which might be further used in the jacketing lines and elsewhere in the process. The number of condensers is determined by the number of stages.

Reactors:
Reactors contain catalysts where assist the catalytic reaction for the recovery of more Sulphur. This is also called the catalytic stage. There are usually multiple stages of catalytic reactions and similarly each stage will have its own reactor.

Storage Tanks:
Some storage tanks will also constitute the deaeration of the unnecessary gases from the molten Sulphur. The role of the storage tank is the maintain the molten Sulphur at the required temperature and state.

In an embodiment, the monitoring includes, but are not limited to, the various components of the sulphur recovery unit such as waste heat boiler, individual condensers and reactors, sulphur locks, tracers, and traps. Other known components of the sulphur recovery unit can also be included for monitoring.

In an embodiment, the monitoring module (106) can monitor
• the real time conditions of the various components of the unit with premise/off premise connected devices;
• the reactor condition;
• detect the sensor malfunction;
• monitor the condition of sulphur condenser;
• ensures adequate steam generation;
• smooth movement of the process gas/fluid;
• recovery of elemental sulphur;
• efficient operation of the thermal system; and
• efficient performance of waste heat boiler.
The computer-implemented system for sulphur recovery unit takes into account the individual performance of all the critical components of the sulphur recovery units including, but is not limited to the waste heat boiler, individual condensers and reactors, sulphur locks, tracers, and traps. The performances of other known critical components can also be monitored using the computer-implemented system.

In another embodiment, the system (100) can be applied to any sulphur recovery unit having the four stages of the Claus process. These stages include, but are not limited to thermal stage, condenser stage, catalytic stage and storage stage (Figure 2). The system (100) can also be applied to other suitable known stages. However, the system (100) is independent of the number of stages in any Sulphur recovery unit. Figure 2 refers to
KD – knockout drum
Contains the H2S gas before it is sent for processing

PH – Pre-Heater (Process Gas)
Preheating the H2S gas before the thermal reaction in the combustion chamber

CC – Combustion Chamber
This is where the thermal reaction of the Claus process occurs

C1 – Condenser 1
Pure sulphur gas is cooled and condensed by using water and generating into steam.

RH1 – Reheater 1 (Steam Based)
Steam based reheater before the process gas enters the reactor chamber

R1 – Reactor 1
This is where the catalytic reaction of the Claus process takes place.

DEGAS
Degassing unit

PIT
Storage pit
Boiler
Waste heat Boiler

The monitoring module (106) includes a health monitoring module (112), a correlation matrix module (114) and an impact factor analysis module (116).

The health monitoring module (112) is configured to monitor health of the critical component based on the threshold value and the value of each of the parameter.

In an embodiment the health of the components is monitored by measuring the ratio of the value of each of the parameter to the threshold value for each of the parameter. For example, for monitoring the condenser health, below is the ratio:

(Threshold of steam generation capacity/ Actual steam generation) *100 eq-1

The condition otherwise for all the other critical components within the Sulphur recovery unit can be evaluated by using eq-1.

In another embodiment, the temperature profiling can be done as per Figure 3. The parameters used for temperature profiling can ensure the smooth operation and flow of the process fluid.

The correlation matrix module (114) is configured to create a correlation matrix based on the monitored health.

A correlation matrix allows understanding the statistical correlation of different parameters of the sulphur recovery unit. This allows evaluating the degree of effect of an independent variable on the dependent variable/s, however there can be multiple independent and dependent variables.

The Correlation Matrix can be calculated using the following formulation:
eq-6

If R is the correlation matrix, then each elements of R can be calculated using the following formula:
eq-7

The above is the basic formulation for the calculation of the Pearson correlation coefficient.

The impact factor analysis module (116) is configured to cooperate with the correlation matrix module (114) to evaluate a degree of an effect of the parameters on each other based on the correlation matrix.

In an embodiment, the system (100) performs impact factor analysis to identify and trace the source of problem.

The prediction module (108) is configured to cooperate with the monitoring module (106) to predict the approximate life of each of the critical component based on the monitoring and the prediction rules.

In an embodiment, the prediction module (108) predicts performance loss and uptime for the critical components based on the monitoring and the prediction rules. In an embodiment, the critical components include, but are not limited to condenser, reactor, boiler, sulphur cooler and preheater. Other suitable known critical components can also be considered in the prediction model.

In another embodiment, the prediction rules are based on thermodynamic and statistical formulation.

The thermodynamic formulation can be given by the relations-

Sensible heat transfer:
mCp ?T eq-2
wherein ?T = T2 - T1; m is mass flow rate for the fluid (process and utility), Cp is specific heat of the fluid (process and utility), T1 is temperature of the cooler end, and T2 is temperature of the hotter end.

Latent heat transfer:
? T2 eq-3
wherein ? is latent heat of vaporization, and T2 is temperature of the hotter end.

The statistical formulation is given by the relations:
For normalization:
X’ = ( X - Xmin) / (Xmax - Xmin) eq-4
wherein X’ is normalized value of an independent variable, X is actual value of the independent variable, Xmin is minimal value of X for the observational data set, and Xmax is maximum value of X for the observational data set.

For non - linear polynomial extrapolation:
Y = ß0x0 + ß1x1 + ß2x2 + ß3x3 + ß4x4 + e eq-5
wherein Y is dependent variable, ß is coefficient in conjunction to X, and e is a constant.

The prediction module (108) provides guide to the various factors which leads to performance loss using Machine learning.

The alert module (110) is configured to cooperate with the prediction module (108) to alert a user based on the prediction to prevent any unplanned shutdown/outage and to ensure efficient recovery of sulphur. In an embodiment, the alert module (110) includes, but not limited to, an audio alert, a visual alert, a message, an email and a scheduled alert.

The data acquisition module (104), the monitoring module (106), the prediction module (108) and the alert module (110) are implemented using one or more processor(s).

The system (100) provides:
? Timely advice for planned shutdown
? Typical savings through efficient recovery of Sulphur.
? Ensuring adequate steam generation.
? Ensuring smooth movement of the process gas
? Ensuring efficient operation of the thermal system
? Impact factor analysis for identify and trace problem sources
? Ensuring efficient performance of the waste heat boiler
? Monitoring reactor condition
? Detection of sensor malfunction
? Condition monitoring of Sulphur condenser
? Prediction of condenser condition degradations.
? Scheduling maintenance through data insights
Figure 4 illustrates a flow diagram depicting steps involved in a method (200) to implement a Sulphur recovery unit. The steps include:
• Step 202: storing, by a repository (102), a set of pre-determined prediction rules, a list of at least one critical component and a plurality of parameters associated with the component and a threshold value corresponding to each of the parameter;
• Step 204: acquiring, by a data acquisition module (104), at least one value corresponding to each of the parameter for the critical component by a set of sensors installed at a plurality of critical locations;
• Step 206: monitoring, by a monitoring module (106), malfunctions and deviations of the values of each of the parameter for the critical component with at least one premise/off premise connected device based on the threshold value;
• Step 208: predicting, by a prediction module (108), the approximate life of each of the critical component based on the monitoring and the prediction rules; and
• Step 210: alerting, by an alert module (110), a user based on the prediction.

The foregoing description of the embodiments has been provided for purposes of illustration and not intended to limit the scope of the present disclosure. Individual components of a particular embodiment are generally not limited to that particular embodiment, but, are interchangeable. Such variations are not to be regarded as a departure from the present disclosure, and all such modifications are considered to be within the scope of the present disclosure.
TECHNICAL ADVANCES AND ECONOMICAL SIGNIFICANCE
The present disclosure described herein above has several technical advantages including, but not limited to, the realization of a computer-implemented system for a Sulphur recovery unit:
• prevent any unplanned shutdown/outage;
• ensure efficient recovery of Sulphur;
• based on the prediction model; and
• estimate the life of Sulphur recovery unit
One of the objects of the Patent Law is to provide protection to new technologies in all fields and domain of technologies. The new technologies shall or may contribute to the country’s economy growth by way of involvement of new efficient and quality method or product manufacturing in India.
Providing protection to new technologies by patenting the product or process will contribute significantly towards innovation and development in the country. Further by granting patent the patentee can contribute to manufacturing the new product or new process of manufacturing by himself or by technology collaboration or through the licensing.
The applicant submits that the present disclosure will contribute to the country’s economy, which is one of the purposes to enact the Patents Act, 1970. The product in accordance with present invention will be in great demand in country and worldwide due to novel technical features of the present invention being a technical advancement. The technology in accordance with present disclosure will provide an efficient system to recover sulfur. The product is developed in the national interest and will contribute to country economy.
The economy significance details requirement may be called during the examination. Only after filing of this Patent application, the applicant can work publicly related to present disclosure product/process/method. The applicant will disclose all the details related to the economic significance contribution after the protection of invention.
The foregoing description of the specific embodiments so fully reveals the general nature of the embodiments herein that others can, by applying current knowledge, readily modify and/or adapt for various applications such specific embodiments without departing from the generic concept, and, therefore, such adaptations and modifications should and are intended to be comprehended within the meaning and range of equivalents of the disclosed embodiments. It is to be understood that the phraseology or terminology employed herein is for the purpose of description and not of limitation. Therefore, while the embodiments herein have been described in terms of preferred embodiments, those skilled in the art will recognize that the embodiments herein can be practiced with modification within the spirit and scope of the embodiments as described herein.
Throughout this specification the word “comprise”, or variations such as “comprises” or “comprising”, will be understood to imply the inclusion of a stated element, step, or group of elements, steps, but not the exclusion of any other element, step, or group of elements, or steps.
While considerable emphasis has been placed herein on the components and component parts of the preferred embodiments, it will be appreciated that many embodiments can be made and that many changes can be made in the preferred embodiments without departing from the principles of the disclosure. These and other changes in the preferred embodiment as well as other embodiments of the disclosure will be apparent to those skilled in the art from the disclosure herein, whereby it is to be distinctly understood that the foregoing descriptive matter is to be interpreted merely as illustrative of the disclosure and not as a limitation.
,CLAIMS:WE CLAIM:

1. A computer-implemented system (100) for a Sulphur recovery unit providing a digital intervention for effective performance evaluation maintenance of the Steam distribution network, said system (100) comprising:
• a repository (102) configured to store a set of pre-determined prediction rules, a list of at least one critical component and a plurality of parameters associated with said component and a threshold value corresponding to each of said parameter;
• a data acquisition module (104) configured to acquire at least one value corresponding to each of said parameter for said critical component by a set of sensors installed at a plurality of critical locations;
• a monitoring module (106) configured to cooperate with said data acquisition module (104) to monitor malfunctions and deviations of said values of each of said parameter for said critical component with at least one on-premise/off premise connected device based on said threshold value;
• a prediction module (108) configured to cooperate with said monitoring module (106) to predict the approximate life of each of said critical component based on said monitoring and said prediction rules; and
• an alert module (110) configured to cooperate with said prediction module (108) to alert a user based on said prediction,
wherein said data acquisition module (104), said monitoring module (106), said prediction module (108) and said alert module (110) are implemented using one or more processor(s).

2. The system (100) as claimed in claim 1, wherein said parameters includes capturing steam related parameters at different location within the system (100).
3. The system (100) as claimed in claim 1, wherein said critical locations includes steam traps, sulphur lines, sulphur locks, steam based preheaters, catalyst bed and condenser lines.

4. The system (100) as claimed in claim 1, wherein said sensor includes:
• a set of temperature sensors for capturing the thermal profile;
• a set of pressure sensors for estimating the saturated steam properties; and
• a set of flow meters to capture the different flow rates of different fluids at different sections within the system (100).
5. The system (100) as claimed in claim 1, wherein said critical components include:

• at least one knockout drum;
• at least one pre-heater;
• at least one combustion chamber;
• at least one boiler;
• at least one condenser;
• at least one reactor;
• at least one reheater;
• at least one degassing unit; and
• at least one storage pit.

6. The system (100) as claimed in claim 1, wherein said monitoring module (106) includes:
• a health monitoring module (112) configured to monitor health of said critical component based on said threshold value and said value of each of said parameter;
• a correlation matrix module (114) configured to create a correlation matrix based on said monitored health; and
• an impact factor analysis module (116) configured to cooperate with said correlation matrix module (114) to evaluate a degree of an effect of said parameters on each other based on said correlation matrix.

7. The system (100) as claimed in claim 1, wherein said prediction module (108) predicts performance loss and uptime for said critical components based on said monitoring and said prediction rules.

8. A method (200) to implement a Sulphur recovery unit, said method (200) comprising the steps of:
• storing (202), by a repository (102), a set of pre-determined prediction rules, a list of at least one critical component and a plurality of parameters associated with said component and a threshold value corresponding to each of said parameter;
• acquiring (204), by a data acquisition module (104), at least one value corresponding to each of said parameter for said critical component by a set of sensors installed at a plurality of critical locations;
• monitoring (206), by a monitoring module (106), malfunctions and deviations of said values of each of said parameter for said critical component with at least one on-premise/off premise connected device based on said threshold value;
• predicting (208), by a prediction module (108), the approximate life of each of said critical component based on said monitoring and said prediction rules; and
• alerting (210), by an alert module (110), a user based on said prediction.