Upgrading Sustainable Pipeline Monitoring with Piezoelectric Energy Harvesting

Abstract

This study presents the design and implementation of a piezoelectric power harvesting device to capture vibrational energy from pipelines to self-powered IoT devices. The device utilizes key components along with the PPA-1001 piezoelectric sensor, the STM32F103C8T6 microcontroller, and LTC-3588 energy harvesting power supply. Experimental results verified the system’s performance in harvesting power within a specific frequency range of 10 Hz to 50 Hz, with the foremost overall performance at 30 Hz. The device generated the highest voltage of 3.3 V, delivering a power output of 2.18 mW, which is sufficient to power low-power electronic devices. The device maintained solid performance across a temperature range of 40 °C to 50 °C, underscoring its robustness in various environmental situations. The findings highlight the capacity of this form of generation to offer a sustainable power source for remote pipeline tracking, contributing to stronger protection and operational efficiency.

1. Introduction

The transportation of fluids such as water, gas, and oil over vast distances relies heavily on pipeline networks. Ensuring the safety and integrity of these pipelines is crucial to prevent leaks, corrosion, and other potential hazards that could lead to environmental damage and economic losses [1,2,3]. However, powering monitoring systems for these pipelines, especially in remote locations with limited access to the electrical grid, presents a significant challenge [4]. Energy harvesting has emerged as a promising solution to power pipeline monitoring devices without relying on wired connections or batteries, by utilizing locally available energy sources [4,5,6].

Flow-induced vibration (FIV) is a common phenomenon in pipelines due to turbulent fluid flow. These vibrations can be harnessed to generate electricity using piezoelectric materials [5,7]. Piezoelectric materials have the unique ability to convert mechanical stress into electrical energy, making them ideal for capturing vibrational energy from pipelines [7]. When subjected to mechanical stress, piezoelectric materials produce an electrical charge, which can be harvested and used to power electronic devices.

Previous studies have explored various approaches to harvesting energy from pipelines. In addition to advancements in pipeline-based energy harvesting techniques, there are exciting developments in the field of piezoelectric materials themselves. Despite these advancements in pipeline-based energy harvesting, a significant gap remains in integrating these technologies into practical, self-sustaining monitoring systems. While individual components have been studied, there is a lack of comprehensive solutions that combine energy harvesting, real-time data logging, and adaptive power management in a single, efficient system for pipeline monitoring. This research aimed to address this gap by presenting an integrated approach that overcomes the limitations of previous studies.

The novel contribution lies in the following.

(a)

The integration of the PPA-1001 piezoelectric sensor with the LTC-3588 energy harvesting power supply, optimizing energy capture across a wide range of pipeline vibrations;

(b)

The use of the STM32F103C8T6 microcontroller for intelligent power management, enhancing the system’s efficiency;

(c)

Development of a custom data logging application for real-time visualization and analysis of both the harvested energy and the pipeline’s conditions;

(d)

Demonstrating robust performance across a specific frequency range (10–50 Hz) and temperature range (40–50 °C), making it more adaptable to the real-world conditions of pipelines.

By addressing these aspects comprehensively, the research aimed to bridge the gap between theoretical energy harvesting concepts and practical, deployable solutions for pipeline monitoring. Recent studies have shown great potential for new materials, particularly glycine, in sensing and energy harvesting applications. For instance, Wang et al. demonstrated the possibility of using biodegradable piezoelectric nanofiber membranes made of PVA-GLY in air filtration masks, highlighting the versatility of piezoelectric material applications [8]. In a more pipeline-relevant context, Okosun et al. proved the effectiveness of glycine-based sensors in detecting and distinguishing the severity of water pipe leaks in real time, outperforming traditional PVDF sensors in sensitivity [9].

For a deeper understanding of glycine’s piezoelectric properties, Guerin et al. provided a fundamental study on the piezoelectric coefficients of different glycine crystal polymorphs, emphasizing the importance of the β-polymorph for sensing applications [10]. Building on this knowledge, Zhang et al. developed a novel fabrication method for large-area, high-quality β-glycine nanocrystalline films, leading to significantly improved piezoelectric performance [11].

These advancements in piezoelectric materials open new avenues for enhancing the efficiency and sensitivity of energy harvesting and pipeline monitoring systems. While the current study focused on using the PPA-1001 piezoelectric sensor, these recent research findings point to the potential for future improvements in the system’s performance through the integration of advanced piezoelectric materials such as glycine. For instance, one study investigated the use of serpentine-shaped piezoelectric cantilever beams attached to pipes for energy collection. The research demonstrated that the power harvester may produce an open-circuit voltage of 10.28–15.45 V with 1 g of vibration acceleration [3]. Another observer tested a circular plate-type piezoelectric power harvester, which may generate 1.22 V and 13.8 µW at a fluid pressure amplitude of 1724 Pa [12].

While these studies have made significant contributions to the field, this work introduces a comprehensive, integrated system that combines energy harvesting, real-time data logging, and adaptive power management. This holistic approach represents a significant advancement in sustainable pipeline monitoring technology. Unlike previous research that focused on single aspects of pipeline monitoring, this system uniquely combines high efficiency in a specific frequency range (10–50 Hz) with robust performance across varying temperatures (40 °C and 50 °C), making it more versatile for real-world applications.

This innovative design incorporates the PPA-1001 piezoelectric sensor in conjunction with the LTC-3588 energy harvesting power supply, which optimizes energy capture from a wide range of pipeline vibrations. The integration of the STM32F103C8T6 microcontroller enables intelligent power management and data processing, allowing for more efficient use of harvested energy. Furthermore, developing a custom data logging application that provides real-time visualization and analysis of the harvested energy and pipeline conditions, enhanced the system’s usefulness for monitoring and maintenance purposes.

This research presents a substantial step towards sustainable pipeline monitoring by demonstrating the feasibility of harvesting energy from pipelines’ vibrations to power remote IoT devices. By utilizing piezoelectric energy harvesting sensors, this design aimed to reduce reliance on traditional energy sources and diminish environmental impact. The system’s ability to operate effectively in various environmental conditions and its potential to provide continuous power to monitoring devices make it a promising solution for enhancing pipelines’ safety and operational efficiency.

2. Methodology

2.1. Structure of the System

The components of the system were as follows:

• Microcontroller (stm32f103c8t6) [13],
• Piezoelectric energy sensor (PPA-1001) [14],
• Vibration sensor (Adxl345) [15],
• Temperature sensor (LM35) [16],
• Piezoelectric energy harvesting power supply (LTC-3588) [17].

2.2. Hardware Design

Figure 1 illustrates the complete layout for a vibration-based electricity harvesting machine, with the PPA-1001 piezoelectric sensor serving as the number one power supply. The PPA-1001 sensor is strategically located to capture mechanical vibrations from a pipe and convert those vibrations into electric signals. These signals are routed to the LTC3588 power harvester, a specialized integrated circuit designed to optimize the low-stage power produced by the piezoelectric sensor. The LTC3588 correctly regulates and conditions the entering signals, converting them into a stable 3.3 V output, which is essential for the steady operation of the downstream electronic components. To further ensure voltage balance, a 10 µF capacitor was attached, which helped smooth out any fluctuations and reducing voltage fluctuations. This strong voltage is then fed into a battery charger module, designed to keep an output voltage in the range of 3.7 to 4.2 V. This range is specifically crucial because it ensures that the machine remains within secure running limits even while providing enough power to the connected components. The charged battery serves as a reliable power supply, imparting energy to the microcontroller unit (MCU), which, in this example, is the STM32F103C8T6. The STM32F103C8T6 is an effective and versatile MCU that acts as the central processing unit, coping with the flow of information and controlling the system’s operations.

The STM32F103C8T6 is interfaced with the ADXL345 accelerometer through an I2C interface, which makes use of the SDA (serial data) and SCL (serial clock) lines for communication. The ADXL345 accelerometer is tasked with measuring the acceleration and vibrations of the pipe, offering real-time information that is critical for tracking the mechanical behavior of the system. This information is processed through the MCU to determine the device’s overall performance and make any vital adjustments. Additionally, the system consists of the LM35 temperature sensor, which is connected to one of the analog inputs of the STM32F103C8T6. The LM35 provides accurate temperature readings of the pipe, which can be crucial for monitoring the thermal conditions that can affect the system’s performance. The MCU utilizes the temperature information alongside the statistics on vibration, ensuring comprehensive tracking and management of the system’s operational parameters. The battery, which is constantly charged by way of the harvested power, guarantees that the system stays operational even in the absence of direct vibrations. This layout guarantees the energy’s sustainability, imparting non-stop electricity to the system and permitting it to function efficaciously in far-flung or tough environments wherein upkeep and energy supply are constrained. This layout effectively harvests and stabilizes energy from mechanical vibrations and also integrates specific monitoring and management mechanisms, making it a robust answer for long-term, independent operation in field operations. The design and assembly of the system is depicted in Figure 2.

2.3. Working Mechanism

The flowchart in Figure 3 introduces an in-depth step-by-step system for dealing with energy harvesting and battery charging in a piezoelectric device. It starts with the machine initializing and immediately reading the acceleration information from the ADXL345 sensor, which measures the vibrations in the x-, y-, and z-axis of the pipeline. These measurements are critical, as they immediately have an impact on the amount of mechanical power that can be harvested. Following this, the machine reads the voltage output from the LTC3588, an efficient energy harvester that converts the vibrations into electricity and regulates the output voltage.

The system then compares the harvested voltage against two crucial thresholds: 3.3 V and 1 V. If the voltage reaches or exceeds 3.3 V, this suggests that sufficient electricity has been accumulated, prompting the system to turn on the battery charging system. This threshold guarantees that the electricity being stored is adequate for powering the connected IoT devices and forestalls premature charging that could cause inefficient electricity storage.

If the voltage is much less than 3.3 V but still above 1 V, the system recognizes that the degree of energy is not the most efficient for charging, so it maintains tracking without starting up the charging system. This guarantees that the battery is most effectively charged when sufficient power is to be had, to avoid partial or inefficient charging cycles. However, if the voltage drops to 1 V or beneath, the device routinely turns off the battery charging system. This motion prevents the depletion of the saved power and protects the battery from being charged with inadequate power, which could lead to inefficiencies or damaged capacity. The loop then resets, usually assessing the conditions and responding dynamically to the ranges of electricity detected by the system. Smart management ensures that the energy harvesting system operates optimally, holding power and maintaining the longevity and performance of the battery and the overall system.

3. Results

3.1. Results of Data Logging and Analysis via Graphical Interface

The energy harvesting application is a graphical user interface (GUI), shown in Figure 4, that was built using MATLAB and was designed to collect, record, and analyze data from the Adxl345, LM35, and PPA-1001 sensors. The software’s interface is broken down into four distinct sections: ADXL345 settings, control panel, data settings, and real-time data. The ADXL345 settings allow users to configure the accelerometer’s operational parameters such as the measurement range, data output frequency, and resolution.

Figure 4 depicts the interface of the energy harvesting data logger application. The interface includes several sections as described below.

1. ADXL345 Settings

-

These set the acceleration range (e.g., ±2 g to ±16 g), the output data rate (100 Hz to 3200 Hz), and the resolution (e.g., 10-bit or 13-bit). Initialization, configuration, live plot, and saving settings are available.

2. Control Panel

-

This manages the sensors’ connections via COM ports, start/stop data logging, saving data in different formats, and configuring the file names.

3. Data Settings

-

This selects the axes (x, y, z) to be displayed, and sets the buffer size for processing the data.

4. Real-Time Data

-

This enables a live data display, plots data in real time, performs FFT analysis, and controls the update rate and number of data points for visualization.

The experimental results received from the designed piezoelectric power harvesting device were collected and analyzed. The results were divided into many categories, each highlighting unique elements of the device’s overall performance, along with time-domain analysis, frequency-domain analysis, temperature, and the voltage harvested by the piezoelectric sensor.

3.2. Time-Domain Analysis

In Figure 5, the graph shows vibration data from an ADXL345 accelerometer, displaying amplitudes over 300 s across three axes: x (blue), y (orange), and z (yellow). The vertical axis ranged from −4 to 4, representing the acceleration in units of g-force (g). The z-axis experienced the strongest vibrations, with amplitudes ranging from 0 to 3 g, indicating significant movement in this direction. The y-axis showed moderate vibrations, fluctuating between −1.5 g and 1.5 g, while the x-axis exhibited minimal vibrations, staying between −1 g and 1 g. This suggests that the system’s primary vibration occurred in the z direction, with less pronounced movement in the y direction and the least in the x direction.

3.3. Frequency-Domain Analysis

Frequency-domain analysis was conducted using the fast Fourier transform (FFT). The system was most efficient at harvesting power from the pipeline’s vibrations within a particular frequency varying between 10 Hz and 50 Hz. The results showed that 30 Hz was one of the key frequencies in which the system displayed first-rate overall performance. At these frequencies, the system was most efficient at changing kinetic energy into electric power, which meant that those frequencies matched the natural frequency of the pipeline’s vibrations and were perfect for achieving maximum power harvesting performance. These results confirmed the significance of designing the device to function inside this particular frequency range to ensure first-rate overall performance in realistic contexts.

To better understand the vibration analysis, refer to Figure 6, which illustrates the frequency-domain analysis for each axis. Each axis represents a direction, and by analyzing them separately, researchers can understand how vibration impacts movement along each direction.

The z-axis experienced the strongest vibrations. This suggests that whatever is being measured vibrated most significantly in the direction of the z-axis.

The y-axis showed less vibration than the z-axis.

The x-axis showed the least amount of vibration.

This detailed analysis of vibration across different axes provided insights into the directional nature of vibrations and could be valuable in various applications such as understanding the device’s orientation or analyzing structural movements.

3.4. Temperature Analysis

The temperature analysis highlighted the piezoelectric energy harvesting system’s thermal stability across various temperatures. The LM35 temperature sensor recorded values indicating that the pipeline’s temperature fluctuated between 40 °C and 50 °C (with a mean of 47 °C) during the testing period, as shown in Figure 7. Despite those variations, the harvested voltage remained extraordinarily strong, suggesting that temperature adjustments inside this range did not appreciably affect the tool’s overall performance. This stability is vital for ensuring the reliability of the energy harvesting machine in various environmental situations, in which temperature fluctuations are commonplace. The capability to preserve normal electricity output despite temperature variations underscores the robustness and rational applicability of the system in real-world pipeline tracking situations.

3.5. Voltage and Output Power Acquired from the Sensor

In the system analyzed in Figure 8, the output voltage of the power harvesting process suggested a clear cyclic sample characterized by way of gradual charging and discharging phases. During the procedure, the voltage first rose steadily and reached the highest level of 3.3 V, which represented the maximum energy storage potential of the machine. When this threshold was reached, the system entered the discharge phase, namely the use of the saved energy, resulting in a slow reduction in the voltage from 3.3 V to 0. This cycle of charging and discharging was repeated over and over, highlighting the performance of the device in changing mechanical vibrations into usable electrical energy. The repeatability of the technique guaranteed that electricity was continuously supplied even in environments with fluctuating or intermittent vibration, permitting the related digital components to keep operating.

In this energy harvesting device, the voltage range was from 0 V to 3.3 V whilst driving a 5 kΩ load. The current related to this load was 0.66 mA. When the device reached the peak voltage of 3.3 V, it gave an energy output of about 2.18 mW to the load. This electricity was received from the mechanical vibrations detected by means of the piezoelectric sensor and transformed into electric power.

The importance of the 2.18 mW output power lies in its capability to powering low-energy electronics consisting of microcontrollers and sensors. The steady current of 0.66 mA ensured that the power supply remained dependable and consistent even when the voltage fluctuated during the electricity generation process. This let the system effectively provide a strong energy supply, which is crucial for the continuous operation of linked devices, especially in environments in which traditional power assets are unavailable or impractical. Therefore, the harvested electricity does not simply power the direct load, but can also be stored for later use, thereby improving the overall efficiency and sustainability of the system.

4. Discussion

• The experimental results of the piezoelectric energy harvesting system exhibited its great effectiveness in collecting pipelines’ vibration energy. The time-domain evaluation suggested that the voltage generated with the aid of the piezoelectric sensor would stay stable through the years, making sure non-stop and dependable powering of linked IoT devices. This stability is critical to maintaining the operation of self-powered devices, particularly in environments in which pipeline vibration is a consistent element. The frequency-domain analysis also showed that the device was optimized to utilize electricity within a specific frequency range that coincided with the natural vibrational frequency of the pipeline, confirming the efficiency of the system’s design in real-world applications. In addition, the evaluation of temperature showed that the system maintained its performance under extreme temperature conditions, which is important for use in different environments. The generator’s potential to operate effectively in an extensive variety of thermal situations contributes to its robustness and makes it appropriate for monitoring pipelines in numerous climates. In addition, the voltage output discovered in the experiments confirmed a correlation between the amplitude of the vibration and the energy generated. This correlation highlights the system’s ability to adequately power IoT devices, especially in conditions wherein pipelines are subject to strong vibrations.
• The results verified the effectiveness of the piezoelectric electricity harvesting system in harnessing pipelines’ vibration energy and offering a sustainable electricity supply for IoT devices. The device’s adaptability to extreme frequency and temperature situations suggested its capacity for widespread application within the field of pipeline monitoring and may help enhance the safety and performance of industrial procedures.
• This study’s findings on the optimal frequency range for energy harvesting (10–50 Hz) aligned with the work of Rahman et al. [12], who reported efficient energy harvesting from pipeline vibrations across a similar frequency range. However, the system demonstrates improved performance at 30 Hz, which could be attributed to the unique combination of the PPA-1001 sensor and the LTC-3588 power supply.
• The temperature stability of the system (40–50 °C) compared favorably with the findings of Yazawa et al. [4], who reported efficient thermoelectric energy harvesting from pipelines at higher temperatures. The piezoelectric approach offers the advantage of operating effectively at lower, more common pipeline temperatures.
• The power output of 2.18 mW achieved by the system at 3.3 V represents a significant improvement over the 13.8 µW reported by Bakhtiar and Khan [7] for their pulsating fluid flow energy harvester. This increased power output enhanced the potential for powering a wider range of IoT devices in pipeline monitoring applications.
• The system’s ability to maintain stable performance across temperature variations addressed a key challenge identified by Shen et al. [1] in their work on wireless sensor systems for monitoring oil pipelines. This stability is crucial for ensuring reliable long-term operation in varying environmental conditions.

The deployment of the energy harvesting system involves several key steps:

• Site assessment: prior to installation, a comprehensive evaluation of the pipeline’s vibration traits was carried out using accelerometers to find out the most appropriate placement locations for maximum power harvesting.
• Installation: the PPA-1001 piezoelectric sensor was securely fixed to the pipeline’s floor with a specialized adhesive that guaranteed the transmission of real vibrations whilst withstanding environmental situations. The sensor was orientated to align with the dominant axis of vibration diagnosed at an earlier stage in the online assessment.
• Power management setup: The LTC-3588 power harvesting electricity supply and battery charging module were housed in a weatherproof enclosure close to the sensor. This setup included surge protection and voltage regulation components to ensure secure transport of electricity to the IoT devices.
• Integration of the microcontroller and sensors: The STM32F103C8T6 microcontroller, ADXL345 accelerometer, and LM35 temperature sensor were integrated completely in a compact, low-power circuit board. This board was also contained within a weatherproof enclosure.
• Data logging system: The custom information logging device was connected to a nearby low-power PC or transmitted to a cloud-based system for remote monitoring. This system was configured to provide real-time visualization of the records and indicatorsm primarily based on predefined thresholds.
• Calibration and testing: post-setup, a series of calibration tests was conducted to ensure correct data collection and the most efficient energy harvesting. This consisted of verifying the device’s overall performance across the anticipated range of the pipelines’ working conditions.
• Maintenance protocol: A routine maintenance agenda was set up, together with periodic cleaning of the sensors’ surface, checking of the electric connections, and recalibration of the sensors to ensure certain long-term reliability.

5. Conclusions

In conclusion, this study demonstrated the efficacy of a novel piezoelectric energy harvesting system for powering IoT devices in pipeline monitoring applications. The key findings include the following.

• Optimal energy harvesting: the system efficiently harvested energy in the 10–50 Hz frequency range, with peak performance at 30 Hz, generating a maximum voltage of 3.3 V and a power output of 2.18 mW.
• Temperature resilience: stable performance was maintained across a temperature range of 40–50 °C, showcasing the system’s robustness in varying environmental conditions.
• Real-time monitoring capability: The integration of the ADXL345 accelerometer and the LM35 temperature sensor, coupled with the custom data logging application, enabled comprehensive real-time pipeline monitoring.
• Energy storage solutions: The incorporation of a battery charging module allowed for energy storage, ensuring continuous operation during periods of low vibration.
• Practical deployment: The system demonstrated potential for real-world applications, offering a sustainable power solution for remote pipeline monitoring that would reduce reliance on traditional power sources.

This study opens several key avenues for future research as follows.

• Field studies: extending field trials to assess the system’s durability and performance in different pipeline environments;
• Optimization of energy harvesting: investigating advanced materials and designs to enhance the efficiency of energy conversion;
• Scalability and IoT integration: exploring scalability for larger networks and standardizing protocols for seamless IoT integration.