mud pump condition monitoring manufacturer

Distributor of engineered fluid handling pumps, packaged pumping systems, repairs, parts, & integrated pump control systems. Mud pumps, chiller/condenser pumps, plumbing pumps, boiler feed systems, in-line circulators, condensate systems, sump & sewage pumps, end suction pumps, submersible sump & sewage, non-clogs & grinders, self primers, packaged lift stations, variable speed pump systems, metering pumps, chemical injection systems, chemical mixing systems, peristaltic pumps for chemical feed, high viscous & shear sensitive fluids, self primers, stainless steel, trash pumps, hot oil pumps, vertical turbine pumps, sanitary pumps, marine pumps, industrial pumps, ANSI end suction, vertical cantilever, double suction, non-clogs, progressive cavity pumps, helical gear pumps, well pumps, lab pumps, hose pumps, control valves, check valves, air release valves, tanks, pressure vessels.

The 2,200-hp mud pump for offshore applications is a single-acting reciprocating triplex mud pump designed for high fluid flow rates, even at low operating speeds, and with a long stroke design. These features reduce the number of load reversals in critical components and increase the life of fluid end parts.

The pump’s critical components are strategically placed to make maintenance and inspection far easier and safer. The two-piece, quick-release piston rod lets you remove the piston without disturbing the liner, minimizing downtime when you’re replacing fluid parts.

Valmet DNA Condition Monitoring is an online monitoring system. By utilizing wireless or wired sensors and highly developed applications, the system provides real-time vibration condition monitoring data available anywhere, anytime. Valmet DNA Condition Monitoring can be used as a standalone solution or as a built-in part of the Valmet DNA Automation System, enabling all the relevant process and condition monitoring data to be available in a single system.

Valmet Maintenance Pad is a portable data collector and analyzer for route-based vibration condition monitoring, predictive maintenance tasks, and advanced vibration measurements. The collector consists of a rugged tablet PC, analysis software, and wireless measurement units.

Valmet’s comprehensive services for condition and runnability monitoring include everything from audits to planning, analysis, and diagnosis with expert specialist support. Our in-depth know-how helps you ensure board and paper, tissue, pulp, as well as energy production applications, run smoothly. The availableservicescan be an integral turnkey function in your monitoring program or part of a targeted effort to resolve issues or improve performance. We can easily customize services to suit requirements according to location, application process area, or specific machinery.

Our Analysis and Diagnosis service can be as simple as remote expert support for your condition monitoring organization, or Valmet can carry out regular online or periodical offline monitoring for you. Specialist Services include technical support for specific problems, such as bearing or gear wear, or full system maintenance using online vibration monitoring. For internal teams, we also offer a range of training services to help your operators carry out monitoring tasks themselves.

We keep your mud pumps running in first class condition – providing onsite inspections, repairs and complete overhaul as well as all associated parts.

Periodically we’ll inspect for wear, cracks and damage to critical components such as bearings, bull gear and pinion, conrods and crossheads. We’ll check the condition of your seals and other rubber goods and look for oil contamination. We’ll inspect your frame and ensure your pump is set up as per the manufacturer’s recommended tolerances, providing feedback and detailed reporting.

Where overhaul is required we’ll take care of complete disassembly, cleaning and NDT. Repairs will be made to machined components as necessary. Bearings, seals and other components will be replaced in line with our inspections. Motors will be overhauled, lube systems serviced and pulsation dampeners recertified. We’ll also check your fluid ends are in spec and can repair or replace. Your pump is then fully reassembled and commissioned.

Pumps are vital to industries including water treatment and wastewater facilities, power generation, oil and gas, food processing and more. In the oil and gas industry, the uptime of industrial pumps is especially critical. The total world consumption of global petroleum and other liquid fuels averaged 92.30 million barrels per day in 2020, according to the U.S. Energy Information Administration. That total has risen by approximately 5 million in 2021 and will continue to grow in 2022. Any unplanned downtime can impact the ability to meet this growth.

There are three basic types of pumps, and they are classified by how they transport fluid: positive-displacement, centrifugal and axial-flow. Pumps can experience several different types of failures, including cavitation, bearing failures and seal failures, among others. In oil and gas, conditions in which pumps operate are often challenging, dirty and hazardous, resulting in wear and tear. Failure of these pumps not only results in unexpected operation delays and increased costs, but it can lead to dangerous oil and gas leaks, impacting labor safety and the environment. To avoid these unexpected failures, many companies increase preventative maintenance and create aggressive inspection schedules. These practices, however, can sometimes lead to unnecessary part replacement, maintenance costs and labor.

Others may rely on condition-based maintenance, which focuses on maintenance performed after monitoring real-time data and detecting unacceptable condition levels. However, this may not come with the advanced warning needed to prevent impending failure events or avoid downtime. By taking a predictive approach, past maintenance data and current sensor measurements can be used to determine early signs of failure, allowing companies to perform maintenance only at the exact time it is needed.

IMAGE 1: An example of a deployed solution for predictive monitoring and failure detection of critical mud pumps in the oil and gas industry. (Images courtesy of Predictronics)

Developing and deploying a predictive maintenance solution for pumps is challenging. It requires a combination of sensing and instrumentation expertise, domain knowledge, and a practical perspective on applying machine learning and analytics for predictive monitoring. The instrumentation aspect is crucial since this data will be analyzed and will serve as the foundation of the actionable information. The decisions made from this information include what maintenance actions are needed and when they should be taken given the current pump health, as well as any trends or patterns that could emerge.

Vibration is typically the most crucial signal to use for monitoring the condition of a pump, but information on the rotating or reciprocating motion is also useful, especially for performing the more advanced signal processing methods. In addition, pressure and flow rate measurements are important for understanding pump operation and providing context for understanding the vibration data. A balance must be struck between the benefit of including these important measurements versus the hardware and implementation costs of doing so. This challenge is especially true for vibration sensors. Domain expertise is needed to place a minimal set of sensors to keep the hardware cost down and monitor the pump properly and accurately.

When handling the analytics, it is challenging to apply machine learning for this application without any domain-specific preprocessing and signal processing steps. Typically, pump failures are rare, so using a supervised machine learning model is not typically practical. Instead, a combination of domain-specific feature extraction methods for the vibration signals coupled with a baseline-based anomaly index machine learning algorithm is a more reasonable approach. The deployment and user interface should be closely aligned with the industrial use case and expected user, as well as the problem being solved. For some applications, it is not feasible to transmit the data to a remote monitoring center or central server, requiring the analytics and deployment to be performed closer to the data source.

A global oil and gas contractor with a specialty in automated drilling equipment and rig components wanted to develop a health monitoring solution for its mud pumps in the field. The contractor wanted to reduce unplanned downtime and unexpected failures. Not only did the company want to prevent these failure events, but they also wanted to distinguish between anomalies caused by maintenance issues and anomalies due to sensor issues.

By working with a predictive analytics company, this client sought to differentiate these anomalies, address the pump failures, and validate the solution by utilizing the induced fault data collected on its test rig.

The user provided the analytics company with a year’s worth of historical data from test bed data sets and sensors on the piston, suction and discharge mechanisms on two pumps in the field. The team of analytics experts was able to pull crucial features from the data by considering vibration patterns in the frequency and time-frequency domain. These features were integral to the development of health assessment models. The models then helped determine key indicators of pump seal failure, as well as establish the accuracy and necessity of the sensors.

By using advanced signal processing and vibration-based pattern recognition, the health monitoring system was able to detect and diagnose pump failures. This solution provided a baseline health assessment, failure identification and pattern recognition diagnosis capabilities.

The predictive analytics company was able to identify potential issues, as well as establish the best locations for sensor placement. The final solution predicted mud pump failure at least one day in advance, providing the data needed to take action and proactively perform maintenance. This approach helped reduce downtime, increase productivity, improve safety and prevent leaks.

Criticality analysis is essential in order to select the pumps for which predictive maintenance solutions can best be applied and to choose a solution that can provide the most value.

After determining the target pumps, the most critical failure modes should be identified, along with any relevant maintenance records for unplanned and planned downtime.

Based on the data and common failure modes, determine sensor placement and what, if any, additional sensors need to be added to the monitored pumps for the predictive solution.

These initial steps are essential when partnering with a technology provider and can help companies develop and adopt a predictive maintenance solution for their pumps that is robust and accurate.

A mud pump is a reciprocating piston/plunger device designed to circulate drilling fluid under high pressure down the drill string and back up the annulus.

Mud pumps come in a variety of sizes and configurations, but for the typical petroleum drilling rig, the triplex (three piston/plunger) mud pump is the pump of choice. Duplex mud pumps (two piston/plungers) have generally been replaced by the triplex pump, but are still common in developing countries. A later development is the hex pump with six pistons/plungers.

The normal mud pump consists of two main sub-assemblies—the fluid end and the power end. The fluid end produces the pumping process with valves, pistons, and liners. Because these components are high-wear items, modern pumps are designed to allow for quick replacement.

To reduce severe vibration caused by the pumping process, mud pumps incorporate both suction and discharge pulsation dampeners. These are connected to the inlet and outlet of the fluid end.

The number of mud pumps varies per drilling rig depending on the size of the drilling rig. The larger the rig the more mud pumps that will be needed. The mud pumps are considered vital to the operation of the drilling rig. If the mud pumps fail it affects production and can be very costly to repair due to the downtime in production.

To avoid any failures of the pumps, an online monitoring system was selected to collect and transmit vibration data back to a software system for analysis. This online monitoring and diagnostic system can also be expanded by a series of program modules (MUXs) that are specific to the application:

As an integral part of onshore and offshore drilling, mud pumps circulate drilling fluids to facilitate drilling oil and natural gas wells. Mud pumps stabilize pressure and support the well during the drilling process and drilling fluids provide friction reduction and a means to remove cuttings. A leak detection system for hex pumps was created for a hex mud pump with six pistons, six suction valves, and six discharge valves. The six pistons are driven by a rotating, asymmetric cam. The system monitors the suction and discharge valves using accelerometers.

Valve leaks in piston pumps are often discovered at a late stage when the leaks are so severe that they induce large discharge pressure fluctuations and create washout damage (Figure 1). When a severe leak is detected, it is localized manually by listening to the fluid modules while the pump is running but it is difficult to uniquely localize the leak and distinguish between a suction valve leak and a discharge valve leak.

Human exposure to hazards is the main disadvantage of manual detection, verification, and localization. Mud pumps convert large amounts of power and often output high pressures up to 350 Bar discharge. Additional equipment in pump rooms also generates high acoustic noise pressure levels that can exceed 100 dBA and cause health and hearing damage if humans are not correctly protected.

During a vibration monitoring project for hex pumps, a Norwegian oil well company discovered the possibility of detecting leaks using accelerometers. Vibrations were recorded at different locations, both on the pump and on the discharge line, along with suction pressure, discharge pressure, and pump speeds for different pump conditions. A 20-kHz sampling frequency was used and 5-second snapshots were taken with intervals of a few minutes. On one occasion, the vibration signature significantly changed during a 15-minute period; the spot was a growing valve leak.

Based on that encouraging experience, the company wanted to include this condition-based maintenance system as a standard feature on all hex pumps, so it developed the system as a standalone module to add to the existing hex pump control system. Slightly simplified, it consists of the following components: accelerometers (one per valve block), a proximity sensor picking up pump speed and phase, a discharge pressure sensor, an embedded monitoring system (an NI CompactRIO system with acquisition modules for powering the accelerometers and acquiring high-frequency data), signal processing software and alarm logics implemented using NI LabVIEW software running on the CompactRIO monitoring system, and an HMI user interface developed in LabVIEW.

The data acquisition and signal processing are briefly described by the following steps: Capture high-rate data (25-kHz sample rate) from all sensors during a short time interval covering at least one pump cycle.

The default sampling frequency of the signals is 25 kHz but the system can handle higher rates if necessary. The bandpass filter is optional but experience shows that it improves contrast and detection sensitivity. Signal strength normalization by the median vibration level makes the detection nearly independent of the inherent ambient vibrations, which increase rapidly with increasing pump speed and discharge pressure. The last requirement — that the detected leaks last for a set time — eliminates erratic alarms caused by debris or large particles that can cause temporary seal malfunction.

Figure 2 shows a diagnosis screen from the hex pump control screen delivered by the leak detection system. It shows a very clear overview of the valve status and a vibration level trend of all valves.

The NI tools for prototyping the system provided an embedded deployment system that can reliably retrofit to existing pumps. In comparison to other leak detection methods based on analyzing discharge pressure, the vibration-based methods are more robust and reliable, especially when it comes to localizing a leak. Studies showed that an alternative method can be applied for shaft-driven piston pumps having either an integrated valve block or split blocks with a high vibration transfer. Leak localization for this kind of pump is mainly based on the phase of the pulsating vibration level. It can be used to localize one dominating leaky valve at a time.

Compounding this growth are aging plants with critical equipment at the end of its life—increasing demands for reliability—and an aging workforce reaching retirement in the next few years. All these factors exponentially increase the need for effective and automatic knowledge transfer, training and new approaches to the maintenance of power generation assets. Today, the process of condition monitoring is largely conducted manually, meaning technicians and operators monitor equipment on their walking rounds or tours within a plant (Figure 1). This includes capturing data logs, inspections and assessments, performance testing, maintenance, and capturing history and events. In addition, this provides limited access to equipment condition monitoring.

difference between generating a profit or a loss. However, increased inspection through online monitoring and data collection can mitigate these risks.

To optimize machine maintenance and, therefore, machine reliability and use, monitoring health indicators such as mechanical vibration, temperature and power factor is a widely accepted practice. However, the cost of cabling the sensor and data acquisition hardware to the control room has impeded the use of monitoring for reliability and usage improvements. Today, with the use of wireless vibration and power monitoring devices, reliability engineers can overcome historical cost barriers.

Power generation providers are taking advantage of the cost effectiveness of wireless devices to add low-cost sensors to equipment. Without the need to connect wires to transfer data, reliability engineers can expand instrumentation beyond critical assets and communicate condition monitoring data for many assets across systems.

Online machine monitoring monitors equipment as it runs. Data are acquired by an embedded device and are transmitted to a main server for data analysis and maintenance scheduling.

Most machine condition monitoring sensors require some form of signal conditioning to optimally function, such as excitation power to an accelerometer. Filtering on the signal to reduce line noise and unwanted frequency ranges is also common.

Implementing an asset monitoring system provides other advantages in addition to cost savings. For example, organizations can plan replacement parts inventory to meet maintenance demands by ensuring that the correct parts are available at the right location as needed, ensuring better fleet management. Also, with a longer maintenance cycle based on machine health, a longer equipment life span can be expected.

Another benefit is the production assurance that an asset monitoring system provides. The system can identify developing faults with enough lead time to properly schedule maintenance during planned downtimes, avoiding unnecessary and expensive site shutdowns.

Most important, by monitoring the machine and its performance parameters, the condition monitoring system can signal a system shutdown before serious injury or other harm occurs.

With the advent of advanced maintenance methods, industrial machinery and asset monitoring systems continue to become more sophisticated. As a result, the requirements for such systems are constantly evolving, which creates new challenges for selecting the appropriate instrumentation for asset monitoring.

In power plants, for example, plant operations personnel access the business network of the plant using mobile devices such as tablets and cell phone technologies. With an industrial wireless network available within the plant, personnel can access email, internal documents and drawings, and other resources that they may need while performing operations in the field. Incorporating Wi-Fi access points with process plants, including power generation and oil and gas plants, offers a clear business benefit beyond condition monitoring. However, transmission of vibration time waveforms may use all the available bandwidth even with an 802.11n implementation.

To mitigate bandwidth issues with Wi-Fi, or any other radio technologies, a report featuring exception or decision-based data recording with store and forward capabilities is most appropriate (see Figure 2). Decision-based data recording devices are often referred to as a Data Acquisition and Analysis Node (DAAN). When the DAAN can evaluate all sensor values for exception and log sensor values locally, two main benefits are achieved. First, when reporting by exception sensory, data are filtered for changes, exceptions or required periodic reports. Second, recording sensor data and condition indicators is possible even when the wireless communications network is not available or experiences bandwidth degradation.

By leveraging a DAAN to filter data and to store sensor data and condition indicators locally, engineers can use the Wi-Fi networks in both process and manufacturing facilities. This makes deploying condition monitoring DAANs possible without the need to deploy communications cabling. Even with these capabilities, plant motors and equipment can cause communication noise. Both Cisco and N-Tron recommend and offer wireless network surveys to help determine the best wireless networking topology for individual applications.

Part Two of this series, which will appear in the December 2013 issue, will address the importance of reducing human exposure to hazardous environments—such as manual maintenance inspections on industrial mud pumps—during onshore and offshore drilling. It will discuss the hardware and software tools used to deploy an embedded system to monitor and analyze mud pump vibrations.

Power and high pressure mud management system is a core function in any oil field operation. Consequential cost of any failure results in an exponential manner through out the chain of drilling activity. Under an open pay zone condition, the effect would compound leading to complications in oil recovery, where such far flung effects are involved in terms of cost of failure, the demand of availability and reliability is not the final requirement of a maintenance manager. Monitoring the trend of all the achievements and failure also becomes an important activity to device a means for all the time injection of dependability. In this trend analysis the diverse and concurrent behavior of different group of equipments are to be monitored in a manageable manner for setting up the hypothesis structures to derive fairly repeatable and accurate predictions.

Optimizing production under dynamic well conditions requires flexible and adaptive electrical submersible pumping (ESP) solutions. ESP pumps from Baker Hughes incorporate innovative hydraulic designs to expand the application range of your ESP systems.

Our flexible pumps have the broadest operating range in the industry to deliver unsurpassed levels of efficiency, reliability, and speed to your production operations. You get customized pumping solutions to improve your operating economics, regardless of your field application.