DESC:FIELD OF INVENTION
The present disclosure generally relates to the field of plurality of cable identification. More particularly, the present disclosure relates to a system and a method for automated identification of a cable within live power networks. BACKGROUND
The background information herein below relates to the present disclosure but is not necessarily prior art.
In the realm of power utilities managing extensive underground cable networks, the manual identification of cables within cable trenches has proven to be a persistently challenging task. The current methodology involves injecting audio frequency signals into cables and relying on engineers to interpret these signals on-site manually. However, this manual process is fraught with inherent risks, including the potential for human error in distinguishing the correct signal amidst induced sounds from adjacent cables and ambient noise, such as humming from live power cables. Instances of misidentification in various power utilities have led to hazardous consequences, including network disturbances, consumer dissatisfaction, revenue loss, and increased repair costs. The gravity of this issue is underscored by the fact that an error in cable identification could result in spiking the wrong cable, potentially causing major accidents. Therefore, this technical problem necessitates a robust technical solution to ensure precise plurality of cable identification, particularly before activities like fault repair and cable route diversion.
Therefore, there is felt a need for a system and a method for automated identification of a cable within live power networks that alleviates the aforementioned drawbacks.

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 for automated identification of a cable within live power networks.
Another object of the present disclosure is to provide the develop an automated system for the accurate identification of live and dead power cables within cable trenches.
Still another object of the present disclosure is to enhance safety by eliminating the risks associated with manual plurality of cable identification, such as spiking the wrong cable.
Yet another object of the present disclosure is to improve operational efficiency by reducing the manpower required for a plurality of cable identification.
Still another object of the present disclosure is to provide a cost-effective technical solution that can be adopted by power utilities for plurality of cable identification.
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 envisages a system for automated identification of a cable within live power networks comprising a plurality of cables installed underground.
The system comprises a plurality of cables, a audio frequency genrator, a sensor, a wireless receiver device, a receiver amplifier, an analyzer, and a wireless or wired communication protocol.
The plurality of cables are installed underground for power transmission in real-time.
The audio frequency generator device is configured with to inject an audio frequency signal into the power cable to generate an audio frequency signal.
The wireless receiver device is configured with a sensor configured to cooperate with the wireless transmitter device to receive the audio frequency signal and amplify the audio frequency signal by means of a receiver amplifier to generate an amplified audio frequency signal.
The analyzer is configured to connect with the receiver device over a wireless or wired communication protocol to
o receive the amplified frequency signal;
o process the frequency signals to evaluate, and compare both the audio frequency signal and the amplified audio frequency signal by means of a set of AI-based analytic rules;
o further accurately identify the specific power cable in accordance with an originated signal; and
o further configured to automatically generate a document report upon successful authentication and identification of the power cable.
In an aspect, the analyzer is selected from a group consisting of a mobile device, computer, remote device, tablet, or any device capable of performing the operation.
In an aspect, the document report is selected from a group consisting of a portable document format, word document, text file, or any executable document file to store record.
In an aspect, the set of AI-based analytic rules is a set of instructions configured to perform
• analyze the characteristics of both the injected audio frequency signal and the amplified audio freque\ncy signal to determine any ‘/deviations or anomalies that could indicate specific cable properties or conditions;
• compare the processed frequency signals against a database or reference signals to identify unique patterns or signatures associated with different power cables;and
• for live and dead cable detection system will take the input data of live power signal from cable. This signal will be sent to analyzer through sensors, receivers, amplifiers, and communication. Then AI Application will analyse data and will confirm if cable is live or dead.
In an aspect, the system further comprises a data repository and a microprocessor.
In an aspect, the data repository is configured to store predefined commands, injected audio frequency signals, detected audio frequency signals, the detailed portable document format (PDF) report.
In an aspect, the microprocessor is configured to fetch and execute one or more modules of the system.
In an aspect, the AI-based software module is further configured to mitigate the risk of human error by automating the identification process, thereby enhancing safety during maintenance and fault repair activities.
In an aspect, the hardware module is designed to be portable and easy to deploy, enabling a single operator to perform a plurality of cable identification tasks efficiently.
In an aspect the cost-effective fabrication of the hardware module reduces the overall cost of the system, facilitating broader adoption within the utility sector.
In an aspect, the detailed portable document format (PDF) report generated by the report generation module includes timestamped identification results, signal strength data, and any anomalies detected during the identification process.
In an aspect, the transmitter and the wireless receiver amplifier are configured to operate within the environmental conditions typical of underground cable trenches, ensuring reliable performance.
In an aspect, the AI-based software module is configured to update and refine its signal processing algorithms based on historical data and user feedback, thereby improving the accuracy of future plurality of cable identifications.
In an aspect, the audio frequency signals are injected at a frequency of approximately 982 Hz can be any other frequency also ranging 1 to 9800 Hz and more.
The present disclosure also envisages a method for automated identification of a cable within live power networks. The method comprises the following steps:
• installing/selecting, by a plurality of cables, underground for power transmission in real-time;
• injecting, by an audio frequency generator device, an audio frequency signal into the power cable;
• receiving, by the wireless sensor transmitter device, an audio frequency signal;
• amplifying, by a wireless receiver device, the audio frequency signal by means of a receiver amplifier to generate amplified audio frequency signal;
• connecting, an analyzer ( Mobile, PC, Laptop, tablet and any other electrocinc device), connect with the receiver device over a wireless or wired communication protocol;
• receiving, by the analyzer, the amplified frequency signal;
• processing, by the analyzer, the frequency signals to evaluate, and compare both the injected audio frequency signal and the amplified audio frequency signal by means of a set of AI-based analytic rules;
• identifying, by the analyzer, the specific power cable in accordance with an originated signal; and
• generating, by the analyzer, a document report upon successful authentication and identification of the power cable.
BRIEF DESCRIPTION OF THE ACCOMPANYING DRAWING
A system and a method for automated identification of a cable within live power networks the present disclosure will now be described with the help of the accompanying drawing, in which:
Figure 1 illustrates a block diagram for the automated identification of a cable within live power networks in accordance with an embodiment of the present disclosure;
Figures 2A-2B illustrate a flow chart depicting the steps involved in a method for automated identification of a cable within live power networks in accordance with an embodiment of the present disclosure;
Figure 3 illustrates the working of an automatic live and dead identification plurality of cable identification system for power utilities in accordance with an embodiment of the present disclosure;
Figure 4 illustrates the schematic drawing of the wireless communication transmission in accordance with the disclosure;
Figure 5 illustrates the schematic flow chart of the automated identification of a cable within live power networks in accordance with an embodiment of the present disclosure;
Figure 6 illustrates the layout of underground live cables in accordance with an embodiment of the present disclosure;
Figures 7A-7B-7C illustrate a mobile interface designed for an AI-based live/dead detection system; and
Figure 8 illustrates the schematic drawing of a cable identification system.
LIST OF REFERENCE NUMERALS
100 - System
102 - Cables
102a,102b,102c - Plurality of Cables
102aR,102bR,102cR - Receviers
102aT,102bT,102cT - Terminating Switchgears,Equipments
104 - Audio frequency generator Device
106 - Audio frequency Sensor an Audio Signal Capturing Device
108 - Wireless Receiver Device
110 - Receiver Amplifier
112 - Analyzers (Mobile. Laptop, PC , Tablet or any other device)
114 - Wireless or Wired Communication Protocol
116 - Data Repository
118 - Microprocessor
120 - Hardware
122 - Stop
124 - Artificial Intelligence (AI) Detector Result
124a - Dead Cable
124b - Live Cable
126 - User Device
128 - Audio frequency Signal
130- Live Power signal
132- Artificial Intelligence (AI) Application
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 “including,” and “having,” are open ended transitional phrases and therefore specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not forbid the presence or addition of one or more other features, integers, steps, operations, 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.
When an element is referred to as being “engaged to,” “connected to,” or “coupled to” another element, it may be directly engaged, connected, or coupled to the other element. As used herein, the term “and/or” includes any and all combinations of one or more of the associated listed elements.
In the realm of power utilities managing extensive underground cable networks, the manual identification of cables within cable trenches has proven to be a persistently challenging task. The current methodology involves injecting audio frequency signals into cables and relying on engineers to interpret these signals on-site manually. However, this manual process is fraught with inherent risks, including the potential for human error in distinguishing the correct signal amidst induced sounds from adjacent cables and ambient noise, such as humming from live power cables. Instances of misidentification in various power utilities have led to hazardous consequences, including network disturbances, consumer dissatisfaction, revenue loss, and increased repair costs. The gravity of this issue is underscored by the fact that an error in cable identification could result in spiking the wrong cable, potentially causing major accidents. Therefore, this technical problem necessitates a robust technical solution to ensure precise plurality of cable identification, particularly before activities like fault repair and cable route diversion.
To address the issues of the existing systems and methods, the present disclosure envisages a system(hereinafter referred to as “system 100”) a system for automated identification of a cable within live power networks and safety and a method (hereinafter referred to as “method 200”) automated identification of a cable within live power networks. The system 100 will now be described with reference to Figure 1,3 and the method 200 will be described with reference to Figure 2 to Figure 9.
Referring to Figure 1, the system 100 comprises a plurality of cables (102a,102b,102c), an audio frequency generator device 104, an audio frequency sensor an audio signal capturing device 106, a wireless receiver device 108, a receiver amplifier 110, an analyzer 112, a wireless or wired communication protocol 114, a data repository 116 and a microprocessor 118, Artificial Intelligence (AI) Detector Result 124.
The plurality of cables (102a,102b,102c) are installed underground for power transmission in real-time.
The audio frequency generator device 104 is configured to inject an audio frequency signal 128 into the plurality of cables (102a,102b,102c) to generate an audio frequency signal 128.
In an aspect, the audio frequency generator device 104 and the wireless receiver amplifier 110 are configured to operate within the environmental conditions typical of underground cable trenches, ensuring reliable performance.
In an aspect, the audio frequency signals 128 are injected at a frequency of approximately 982 Hz and can be any other frequency also ranging 1 to 9800 Hz and more.
The wireless receiver device 108 is configured with a sensor 106 configured to cooperate with the audio frequency generator device 104 to receive the audio frequency signal 128 and amplify the audio frequency signal 128 by means of a receiver amplifier 110 to generate an amplified audio frequency signal 128.
The analyzer 112 is configured to connect with the receiver device 108 over a wireless or wired communication protocol 114 to receive the amplified frequency signal 128, process the frequency signals 128 to evaluate, and compare both the audio frequency signal 128 and the amplified audio frequency signal 128 by means of a set of AI-based analytic rules, further accurately identify the plurality of cables (102a,102b,102c) in accordance with an originated signal; and further configured to automatically generate a document report upon successful authentication and identification of the plurality of cables (102a,102b,102c).
In an aspect, the analyzer 112 is selected from a group consisting of a mobile device, computer, remote device, tablet, or any device capable of performing the operation.
In an aspect, the detailed portable document format (PDF) report generated by the report generation module 118,132,124 includes timestamped identification results, signal strength data, and any anomalies detected during the identification process.
In an aspect, the document report is selected from a group consisting of a Portable Document Format, Word document, text file, or any executable document file to store records.
In an aspect, the set of AI-based analytic rules is a set of instructions configured to perform
• analyze the characteristics of both the audio frequency signal 128 and the amplified audio frequency signal 128 to determine any deviations or anomalies that could indicate specific cable properties or conditions;
• compare the processed frequency signals 128 against a database or reference signals to identify unique patterns or signatures associated with different power cables;and
• for live 124a and dead cable 124a detection system will take the input data of live power signal 130 from cable 102. This signal will be sent to analyzer 112 through 106 sensors, 108 receivers, amplifiers 110 , and 114 communication. Then AI Application 132 will analyse data and will confirm if cable is live 124a or dead 124d.
In an aspect, the system 100 is further configured to mitigate the risk of human error by automating the identification process, thereby enhancing safety during maintenance and fault repair activities.
In an aspect, the system 100 is configured to update and refine its signal processing algorithms based on historical data and user feedback, thereby improving the accuracy of future cable identifications.
In an aspect, the system 100 is further configured to the hardware module is designed to be portable and easy to deploy, enabling a single operator to perform the plurality of cable identification tasks efficiently.
In an aspect, the system 100 is the cost-effective fabrication of the hardware module that reduces the overall cost of the system, facilitating broader adoption within the utility sector.
In an aspect, the system 100 further comprises a data repository 116 and a microprocessor 118.
In an aspect, the data repository 116 is configured to store predefined commands, injected audio frequency signals 128, detected audio frequency signals 128, and the detailed portable document format (PDF) report.
In an aspect, the microprocessor 118 is configured to fetch and execute one or more modules of the system 100.
In an aspect, system 100 may include a microprocessor 118. The processor may be implemented as microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, state machines, logic circuitries, and/or any devices that manipulate signals based on operational instructions. Among other capabilities, the microprocessor 118 may fetch and execute computer-readable instructions stored in memory. The functions of the microprocessor 118 may be provided through the use of dedicated hardware 120 as well as hardware capable of executing machine-readable instructions. The microprocessor 118 may be configured to execute functions of various modules of the system 100 such as the plurality of cables (102a,102b,102c), the audio frequency generator device 104, the audio frequency sensor an audio signal capturing device 106, the wireless receiver device 108, the receiver amplifier 110, the analyzer 112, the wireless or wired communication protocol 114.
In an aspect, the system 100 may also include a communication interface. The communication interface may include a variety of interfaces, for example, interfaces for data input and output devices, referred to as I/O devices, transceivers, storage devices, and the like. The communication interface may facilitate communication of the system 100 with various devices coupled to the system 100 or the microprocessor 118. The communication interface may also provide a communication pathway for one or more components of the system 100 and the microprocessor 118.
Also, the system 100 or the microprocessor 118 may include, or be coupled with, one or more transceivers to communicate with various devices coupled to the system 100 or the microprocessor 118.
Figures 2A-2B illustrate a flow chart depicting the steps involved in a method 200 for automated identification of a cable within live power networks in accordance with an embodiment of the present disclosure. The order in which method 200 is described is not intended to be construed as a limitation, and any number of the described method steps may be combined in any order to implement method 200, or an alternative method. Furthermore, method 200 may be implemented by processing resource or computing device(s) through any suitable hardware, non-transitory machine-readable medium/instructions, or a combination thereof. The method 200 comprises the following steps:
At step 202, the method 200 includes installing/selecting, by a plurality of cables (102a,102b,102c), underground for power transmission in real-time.
At step 204, the method 200 includes injecting, by a audio frequency genrator device 104, audio frequency signal 128 into the plurality of cables (102a,102b,102c).
At step 206, the method 200 includes receiving, by the wireless sensor transmitter device, an audio frequency signal 128.
At step 208, the method 200 includes amplifying, by a wireless receiver device 108, the audio frequency signal 128 by means of a receiver amplifier 110 to generate amplified audio frequency signal 128.
At step 210, the method 200 includes connecting, an analyzer 112 ( Mobile, PC, Laptop, tablet and any other electrocinc device), and connecting with the receiver device 108 over a wireless or wired communication protocol 114.
At step 212, the method 200 includes receiving, by the analyzer 112, the amplified frequency signal 128.
At step 214, the method 200 includes processing, by the analyzer 112, the frequency signals 128 to evaluate, and compare both the injected audio frequency signal 128 and the amplified audio frequency signal 128 by means of a set of AI-based analytic rules.
At step 216, the method 200 includes identifying, by the analyzer 112, the plurality of cables (102a,102b,102c) in accordance with an originated signal.
At step 218, the method 200 includes generating, by the analyzer 112, a document report upon successful authentication and identification of the plurality of cables (102a,102b,102c).
Figure 3 illustrates the working of an automatic identification plurality of cable identification system for power utilities in accordance with an embodiment of the present disclosure. In accordance with one embodiment the system 100 presents an automated solution that heralds a transformative era in live 124a and dead 124b identification within underground plurality of cables (102a,102b,102c) networks.
The core of this innovation lies in a sophisticated network of components seamlessly working in unison and the presence of live power signal 130 is checked at the site in a bunch of cables which are exposed cables meticulously numbered within the cable trenches. This process initiates a data flow that is captured by a wireless receiver amplifier 110, strategically attached to mobile or laptop 112 devices. Wireless communication 114 technology ensures real-time transmission of comprehensive audio data, laying the groundwork for precise identification.
Delving deeper into the system’s mechanics, the heart of this disclosure lies in the cost-effective hardware 120 fabrication. Here, the audio signal sensor 106, amplifier 110, wireless communication 114, and hardware 120 are harnessed utilizing locally available components, thereby significantly reducing the overall cost of the system 100. This economic approach opens avenues for broader accessibility and adoption within the utility sector. The system’s intrinsic safety enhancements elevate its significance further. By automating the cable identification process, the system 100 inherently mitigates the risk of human error, a crucial factor in the context of safety during maintenance and fault repair activities.
Moving into the nuanced features, in accordance with one embodiment the integration of advanced signal processing algorithms within the Artificial Intelligence, (AI)-based software 132 stands as a testament to the system’s technical sophistication. This ensures identification based on live power frequency signal 130 adding a layer of precision to the cable 102 identification process. Operational efficiency is a hallmark of this system 100, where a single operator can seamlessly carry out cable 102 live 124a and dead 124b identification tasks, significantly reducing the manpower traditionally required for such activities. The immediate generation of a detailed portable document format (PDF) report post-live 124b and dead cable 124a identification adds an organizational layer to the innovation, contributing to effective record-keeping and decision-making.
Figure 4 illustrates the schematic drawing of the wireless communication transmission in accordance with the disclosure. In this communication setup, the utilization of an audio frequency sensor an audio signal capturing device 106 takes center stage, serving as a critical component designed to detect and measure various electrical and other properties within its environment. The sensor’s primary function is to gather pertinent data. The cable 102 is introduced into the system 100 to transmit power to customers. These customers must be powered off during cable 102 cutting, jointing, repair, or diversion work.The desired cable 102 is given an audio freq electrical signal using the transmitter (Audio signal injector ) 104 from the substation end. At the site, there are many cables, and the an audio frequency sensor an audio signal capturing device 106 senses the signal from all cables and then it is transmitted to a receiver and then to software in the laptop 112 or mobile. The software generates reports by using the artificial intelligence software 132 mentioning the desired cable 102 number having a frequency signal 128. So from multiple cablers desired cable 102 is identified
In accordance with one embodiment the heart of the communication system 100 lies in wireless transmission, a key feature enabling the seamless transfer of information between devices without the limitations imposed by physical cables. Technologies like Wi-Fi, Bluetooth, or other wireless protocols are likely employed to facilitate efficient data exchange, forming the core of the setup’s communication infrastructure.
In accordance with one embodiment, on the receiving end of this wireless communication 114, the system 100 stands as a dedicated receiver 108. This device plays a role in capturing wireless signals transmitted by other components, potentially including data from the audio frequency sensor an audio signal capturing device 106. Functioning as an intermediary, the receiver collects and processes the transmitted information before passing it along for further utilization.
Completing this cohesive communication ecosystem is a computer device, such as a laptop or mobile device 112 or desktop, that significantly enhances the system’s functionality. This versatile computing tool is employed for tasks like data analysis, visualization, and additional communication functions, underscoring the adaptability and utility of the overall setup. The inclusion of a laptop or mobile etc device 112 forms part of a comprehensive system 100 that seamlessly integrates an audio frequency sensor an audio signal capturing device 106, wireless transmission, receivers, and a computer device. This integration enables efficient and flexible communication and data processing. Consequently, there exists a demand for a technical solution that offers a more reliable and automated approach to cable 102 identification. The system 100, Artificial Intelligence Software 132 typically developed using Python and Android language, integrates advanced an audio frequency sensor an audio signal capturing device 106 technology with wireless communication 114 and AI-based signal processing.
Figure 5 illustrates the schematic flow chart of the automated identification of a cable within live power networks in accordance with an embodiment of the present disclosure. The system 100 initiates a process of cable 102 identification, employing a dedicated identification system 100. Subsequently, a signal 128 is injected into the identified cable, with the assistance of a transmitter(Audio signal injector) 104 at the substation end.
The injected signal undergoes a series of processes related to signal processing. Following this, a comprehensive report is generated based on the outcomes of the processing. The system 100 then confirms the identification of the cable 102, signaling a positive confirmation. Simultaneously, the system 100 checks for the output confirmation, determining whether it was successfully done or not. Depending on this outcome, the system 100 reaches its conclusion, marking the end of the entire process. This structured sequence of actions outlines a systematic approach to cable 102 identification and signal processing, culminating in a decisive confirmation and the termination of the system 100.
The AI signal processing module employs advanced algorithms within the AI-based software 132 to analyze the injected signals. Following successful processing, the system 100 proceeds to generate a detailed portable document format (PDF) report in the generate PDF report module.
Ultimately, if the cable 102 identification is successful, the system 100 concludes with the “End System (Successful Cable Identification)” module. This comprehensive flow ensures a systematic and automated approach to cable 102 identification, enhancing efficiency and mitigating the risk of human error in the underground plurality of cable 102 networks.
Figure 6 illustrates the layout of underground live cables in accordance with an embodiment of the present disclosure. In accordance with one embodiment, the system 100 presents an advanced solution aimed at revolutionizing cable identification within underground power cable networks.
In accordance with one embodiment, the core of disclosure is centered around a network of components that function cohesively to ensure accurate and efficient cable identification.
The transmitter (audio signal injector) 104 injects audio frequency signals 128, typically at 982 Hz or any audio signal, into the target cable 102 from the substation end. These signals travel through the cable (102a, 102b, 102c), which are connected to Terminating Switchgears,Equipments etc (102aT, 102bT, 102cT) at one end and receivers (102aR, 102bR, 102cR) at the other. The presence of the injected signal is then checked at the site among a group of exposed cables, meticulously numbered within the cable trenches.
The system 100 incorporates a wireless receiver amplifier 110, which captures this signal data and transmits it in real-time to mobile or laptop devices 112 via wireless communication technology 114. This real-time transmission is crucial for precise cable identification, ensuring that the correct cable is accurately and efficiently identified with minimal delay. The hardware fabrication 120 utilized in this system leverages locally available components, such as the audio signal sensor 106, amplifier 110, and wireless communication module 114, assembled in a manner that significantly reduces the overall cost.
In accordance with one embodiment, the integration of AI-based software 132 within the system exemplifies its technical prowess. The software employs advanced signal processing algorithms to analyze the audio signal’s frequency and magnitude.
Figures 7A-7B-7C illustrate a mobile interface designed for an AI-based live/dead detection system. The interface incorporates various labeled elements and interactive controls that streamline the detection process, enhance usability, and provide immediate access to critical system information. At the top of the interface, represents the wireless receiver device 108. The wireless receiver device 108 is configured to communicate with external sources to receive real-time data, which is then relayed to the interface for processing. The wireless receiver device 108 has the capability to facilitate the receipt of live input signals, which are essential for the system’s detection and analysis operations.
The analyzer 112 provides status information or control over the analyzers, which are computational units responsible for processing the incoming data. The analyzers 112 perform calculations or data manipulations necessary for determining the live 124b or dead 124a status of a component, such as a cable or electrical connection AI Application 132.
The stop 122 button is positioned below the analyzer 112 and serves as an actionable item to halt specific processes or indicate the stopped status of a particular component within the system. By providing a distinct stop function, the interface allows users to control the flow of data or terminate ongoing processes if necessary. The artificial intelligence (AI) detector result 124 corresponds to the main result displayed on the screen, where the AI-driven analysis outcome is presented. The AI Detector is integrated into the system to assess the data received and generate an accurate live/dead determination based on pre-defined criteria. The AI Detector processes signals received from the wireless device, enabling real-time detection and output display.
The interface also includes dead cable 124a and live cable 124b. The cables differentiate between inactive and active cable statuses within the system. The dead cable 124a is used to indicate a non-functional or inactive cable component, whereas live cable 124b denotes an active or functional cable connection. This distinction enables the system to classify components and provide users with clear information about the operational status of each analyzed element.
At the bottom of the screen, a partially visible data chart is displayed, featuring a y-axis with a range from 2,000,000 to 4,000,000 or any and an x-axis ranging from 0 to 2,500 or any . This chart likely presents data related to the system’s performance or analysis results, potentially in real-time or as a record of past detections. The chart format allows for a visual representation of variations in detected signals, magnitudes, or other metrics that may be significant in assessing the status of cables or connections.
Figure 8 illustrates the schematic drawing of a cable identification system. The disclosed system for cable identification involves injecting an audio frequency signal 128 at one end of a cable to be identified. At the exposed location of the cables, an audio frequency sensor an audio signal capturing device 106 detects this injected signal. Each cable is marked with a unique identifier using stickers for proper identification. The captured signal data is then transmitted wirelessly via Bluetooth to a user device 112,126 such as a mobile, tablet, or laptop, equipped with an AI-based software application. The software autonomously generato the signal data to accurately identify the cable, thus eliminating potential human judgment errors. The system further generates a PDF report 124 of the identification results and automatically sends this report via email to designated personnel. This method and system provide a reliable, efficient, and error-free approach to cable identification at worksites, significantly enhancing operational accuracy.
In an operative configuration, the system 100 functions by integrating several components to automate the identification of multiple cables within live power networks. The system includes at least one underground plurality of cables (102a,102b,102c) used for real-time power transmission. An audio frequency generator device 104, equipped with an audio frequency sensor an audio signal capturing device 106, injects an audio frequency signal 128 into the plurality of cables (102a,102b,102c). This signal is then captured by a wireless receiver device 108, which works in conjunction with the transmitter to receive and amplify the audio frequency signal 128 using a receiver amplifier 110. The amplified signal is transmitted to an analyzer 112 via a wireless or wired communication protocol 114. The analyzer 112 processes and evaluates the frequency signals 128, using AI-based analytic rules to compare the original and amplified signals, thereby accurately identifying the plurality of cables (102a,102b,102c). Upon successful identification, the system automatically generates a detailed document report.
Advantageously, the system 100 for automated plurality of cable identification within underground power networks seamlessly integrates multiple advanced technologies to enhance cable management. The features a plurality of cables (102a,102b,102c) designed for real-time power transmission and an audio frequency generator device 104 equipped with an audio frequency sensor an audio signal capturing device 106 to inject and generate an audio frequency signal 128 into the cable. This signal is then captured and amplified by a wireless receiver device 108 with a receiver amplifier 110. The analyzer 112, connected to the receiver via a wireless or wired protocol 114, receives and processes the amplified signal. Utilizing AI-based analytic rules, it evaluates and compares the original and amplified signals to accurately identify the plurality of cables (102a,102b,102c). Furthermore, the system automatically generates a document report upon successful identification, thereby streamlining maintenance and improving operational efficiency in power network management.
An exemplary pseudo-code depicting the working of to automated identification of a cable within live power networks function–
initialize_system() # Initialize system components
inject_signal() # Inject signal at substation end
sensing_transmitting_signal() # Sensing and transmitting a signal at the site
receiving_signal() # Receiving signal in laptop /mobile through the receiver
ai_signal_processing() # Perform AI signal processing
generate_pdf_report() # Generate PDF report
end_system_successful() # End system (successful cable identification)
else:
end_system_no_cable_detected() # End system (no cable detected)
The foregoing description of the embodiments has been provided for purposes of illustration and is 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 ADVANCEMENTS
The present disclosure described herein above has several technical advantages including, but not limited to a system and a method for automated identification of a cable within live power networks that:
• provides audio frequency generator device transmitter for injecting audio frequency signals into cables;
• audio frequency Sensor a audio signal capturing Device serving as a critical component designed to detect and measure various electrical and other properties within its environment. The sensor's primary function is to gather pertinent data.
• provides a wireless receiver amplifier to capture audio signals from cables, transmitting data to both mobile and laptop devices;
• provides Python and Android-based AI software for processing audio signals and automatically identifying cables based on frequency and magnitude;
• provides fabricated cost-effective audio signal transmitters and receivers with inexpensive and easily available components;
• provides a solution that enhances safety by automating cable identification, minimizing reliance on human judgment, and reducing the risk of misidentification;
• provides operational and cost efficiencies through automation, diminishing the need for manual labor and providing a compelling alternative to existing instruments in the market;
• provides cost-effective fabrication of audio signal transmitter and receiver components further strengthens the solution’s economic viability; and
• provides technical innovation that represents a paradigm shift in underground cable management, offering power utilities a safer, more efficient, and economically sound approach.
The embodiments herein and the various features and advantageous details thereof are explained with reference to the non-limiting embodiments in the following description. Descriptions of well-known components and processing techniques are omitted so as to not unnecessarily obscure the embodiments herein. The examples used herein are intended merely to facilitate an understanding of ways in which the embodiments herein may be practiced and to further enable those of skill in the art to practice the embodiments herein. Accordingly, the examples should not be construed as limiting the scope of the embodiments herein.
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.
The use of the expression “at least” or “at least one” suggests the use of one or more elements or ingredients or quantities, as the use may be in the embodiment of the disclosure to achieve one or more of the desired objects or results.
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 system (100) for automated identification of a cable within live power networks comprising a plurality of cables (102a,102b,102c) installed underground, wherein said system (100) comprises:
• an audio frequency generator device (104) to inject an audio frequency signal (128) into said plurality of cables (102a,102b,102c) to generate an audio frequency signal (128);
• a wireless receiver device (108) configured with a sensor (106)configured to cooperate with said audio frequency generating device (104) to receive said audio frequency signal (128) and amplify said audio frequency signal (128) by means of a receiver amplifier (110) to generate an amplified audio frequency signal (128); and
• an analyzer (112) configured to connect with said receiver device (108) over a wireless or wired communication protocol (114) to
o receive said amplified frequency signal (128);
o process said frequency signals (128) to evaluate, and compare both said audio frequency signal (128) and said amplified audio frequency signal (128) by means of a set of AI-based analytic rules;
o further accurately identify said plurality of cables (102a,102b,102c) in accordance with an originated signal; and
o further configured to automatically generate a document report upon successful authentication and identification of said plurality of cables (102a,102b,102c).
2. The system (100) as claimed in claim 1, wherein said analyzer (112) is selected from a group consisting of a mobile device, computer, remote device, tablet, or any device capable of performing the operation.
3. The system (100) as claimed in claim 1, wherein said document report is selected from a group consisting of a Portable Document Format, Word document, text file, or any executable document file to store record.
4. The system (100) as claimed in claim 1, wherein said set of AI-based analytic rules is a set of instructions configured to perform:
• analyze the characteristics of both the audio frequency signal (128) and the amplified audio frequency signal (128) to determine any deviations or anomalies that could indicate specific cable properties or conditions;
• compare the processed frequency signals (128) against a database or reference signals to identify unique patterns or signatures associated with different power cables; and
• for live and dead cable 124a detection system will take the input data of live power signal (130) from cable (102). This signal will be sent to analyzer (112) through (106) sensors, (108) receivers, (110) amplifiers, and (114) communication. Then AI Application (132) will analyse data and will confirm if cable is live (124a) or dead (124d).
5. The system (100) as claimed in claim 1, wherein said system (100) further comprises:
• a data repository (116) configured to store predefined commands, injected audio frequency signals (128), detected audio frequency signals (128), the detailed portable document format (PDF) report; and
• a microprocessor (118) configured to fetch and execute one or more modules of said system (100).
6. The system (100) as claimed in claim 1, wherein said system 100 is further configured to mitigate the risk of human error by automating the identification process, thereby enhancing safety during maintenance and fault repair activities.
7. The system (100) as claimed in claim 1, wherein said system 100 is further configured to the hardware module is designed to be portable and easy to deploy, enabling a single operator to perform cable identification tasks efficiently.
8. The system (100) as claimed in claim 1, wherein the cost-effective fabrication of the hardware module reduces the overall cost of the system, facilitating broader adoption within the utility sector.
9. The system (100) as claimed in claim 1, wherein the detailed portable document format (PDF) report generated by the report generation module (118) includes timestamped identification results, signal strength data, and any anomalies detected during the identification process.
10. The system (100) as claimed in claim 1, wherein the audio frequency generator /transmitter (104) and the wireless receiver amplifier (110) are configured to operate within the environmental conditions typical of underground cable trenches, ensuring reliable performance.
11. The system (100) as claimed in claim 1, wherein said system 100 is configured to update and refine its signal processing algorithms based on historical data and user feedback, thereby improving the accuracy of future cable identifications.
12. The system (100) as claimed in claim 1, wherein the audio frequency signals (128) are injected at a frequency of approximately 982 Hz can be any other frequency also ranging 1 to 9800 Hz and more.
13. A method (200) for automated identification of a cable within live power networks, wherein said method (200) comprises the following steps:
• installing/selecting, a plurality of cables (102a,102b,102c), underground for power transmission;
• injecting, by an audio frequency generator device (104), an audio frequency signal into the power cable;
• receiving, by the wireless sensor(106) transmitter device, an audio frequency signal;
• amplifying, by a wireless receiver device (108), said audio frequency signal (128) by means of a receiver amplifier (110) to generate an amplified audio frequency signal (128);
• connecting, an analyzer (112) ( Mobile, PC, Laptop, tablet and any other electrocinc device), to said receiver device (108) over a wireless or wired communication protocol (114);
• receiving, by said analyzer (112), said amplified frequency signal (128);
• processing, by said analyzer (112), said frequency signals (128) to evaluate, and compare both said injected audio frequency signal (128) and said amplified audio frequency signal by means of a set of AI-based analytic rules;
• identifying, by said analyzer (112), at least one of said plurality of cables (102a,102b,102c) ; and
• generating, by said analyzer (112), a document report upon successful authentication and identification of at least one of said plurality of cables (102a,102b,102c).
14. The method (200) as claimed in claim 13, wherein the step of generating the report further comprises additional details in the report, such as timestamped identification results, signal strength data, and any detected anomalies during the cable identification process.
15. The method (200) as claimed in claim 13, wherein the set of AI-based analytic rules used by said analyzer (112) for processing the frequency signals (128) includes a machine learning algorithm trained to recognize and classify different types of signal patterns associated with various power cable types and conditions, thereby improving the accuracy of identifying said plurality of cables (102a,102b,102c).

Dated this 30th day of November, 2024

_______________________________
MOHAN RAJKUMAR DEWAN, IN/PA – 25
of R.K. DEWAN & CO.
Authorized Agent of Applicant

TO,
THE CONTROLLER OF PATENTS
THE PATENT OFFICE, AT MUMBAI