title: Ultrasonic Air Leak Detection: An Investigation to Improve Accuracy of Leak Rate Estimation

authors: Wolstencroft, Hamish Roger

subjects: ultrasonic

abstract: A compressed air test rig was designed to develop new procedures and improve the reliability of results that are obtained when conducting a leak survey using an Ultrasonic leak detector such as the UE Systems Ultraprobe.

A test rig was designed that allowed the pressure of air in a compressed air system to be controlled by a regulator. This allowed experiments to be conducted that were able to recreate leak situations in a controlled environment. The pressure of the air through the test rig was measured both at the supply end and at the proximity of the leak site, while the volume flow rate was measured at the supply end of the rig.

A number of leak geometries were examined, with compressed air being passed through open ended tubing and also discs with different leak geometries, some round holes and some rectangular. Initial studies were also carried out on flange leaks and pinpricks and slits in lengths of tubing. These were omitted from the study at this stage to allow further experimentation to be conducted in both areas.

The experimentation was carried out using an Ultraprobe 9000 leak detector which was positioned at a set distance from the leak at a series of angles to the flow. The ultrasound level was measured at each point and compared with the pressure and volume flow rate of the air in the system.

The results showed that the ideal angle to ensure the maximum level of ultrasound is at 30 to the axis of the leak. While the optimum distance for ensuring a consistent level of ultrasound is 150mm from the leak.

The length of any air lines branching from the main distribution network is shown to be an important factor when quantifying the volumetric flow rate of air from an open ended tube or tubing with a significant orifice in it. The pressure drop in a 1m length of tubing was shown to be approximately 50%, and if you consider that often the flow rate being used has been obtained using the outside diameter of the tubing rather than the inside diameter this can become a considerable over estimation of leak rate.

The geometry of a regular shaped orifice, such as a round, or rectangular hole was shown to have little to no effect on the flow rate through it for a constant area. However a coefficient of discharge to account for imperfections in the flow was developed for round and rectangular geometries, these were 0.74 for a round hole and 0.79 for a rectangular hole. These correction factors in tandem with the length effect factor for tubing and the improvements to the measurement procedure, allow a higher degree of accuracy to be obtained when conducting a leak survey.

text: Ultrasonic Air Leak Detection: An Investigation to Improve Accuracy of Leak Rate Estimation A compressed air test rig was designed to develop new procedures and improve the reliability of results that are obtained when conducting a leak survey using an Ultrasonic leak detector such as the UE Systems Ultraprobe.

A test rig was designed that allowed the pressure of air in a compressed air system to be controlled by a regulator. This allowed experiments to be conducted that were able to recreate leak situations in a controlled environment. The pressure of the air through the test rig was measured both at the supply end and at the proximity of the leak site, while the volume flow rate was measured at the supply end of the rig.

A number of leak geometries were examined, with compressed air being passed through open ended tubing and also discs with different leak geometries, some round holes and some rectangular. Initial studies were also carried out on flange leaks and pinpricks and slits in lengths of tubing. These were omitted from the study at this stage to allow further experimentation to be conducted in both areas.

The experimentation was carried out using an Ultraprobe 9000 leak detector which was positioned at a set distance from the leak at a series of angles to the flow. The ultrasound level was measured at each point and compared with the pressure and volume flow rate of the air in the system.

The results showed that the ideal angle to ensure the maximum level of ultrasound is at 30 to the axis of the leak. While the optimum distance for ensuring a consistent level of ultrasound is 150mm from the leak.

The length of any air lines branching from the main distribution network is shown to be an important factor when quantifying the volumetric flow rate of air from an open ended tube or tubing with a significant orifice in it. The pressure drop in a 1m length of tubing was shown to be approximately 50%, and if you consider that often the flow rate being used has been obtained using the outside diameter of the tubing rather than the inside diameter this can become a considerable over estimation of leak rate.

The geometry of a regular shaped orifice, such as a round, or rectangular hole was shown to have little to no effect on the flow rate through it for a constant area. However a coefficient of discharge to account for imperfections in the flow was developed for round and rectangular geometries, these were 0.74 for a round hole and 0.79 for a rectangular hole. These correction factors in tandem with the length effect factor for tubing and the improvements to the measurement procedure, allow a higher degree of accuracy to be obtained when conducting a leak survey.

year: 2008

title: Predicting apple bruising relationships using machine learning

authors: Holmes, Geoffrey

subjects: computer science

abstract: Many models have been used to describe the influence of internal or external factors on apple bruising. Few of these have addressed the application of derived relationships to the evaluation of commercial operations. From an industry perspective, a model must enable fruit to be rejected on the basis of a commercially significant bruise and must also accurately quantify the effects of various combinations of input features (such as cultivar, maturity, size, and so on) on bruise prediction. Input features must in turn have characteristics which are measurable commercially; for example, the measure of force should be impact energy rather than energy absorbed. Further, as the commercial criteria for acceptable damage levels change, the model should be versatile enough to regenerate new bruise thresholds from existing data. 
Machine learning is a burgeoning technology with a vast range of potential applications particularly in agriculture where large amounts of data can be readily collected [1]. The main advantage of using a machine learning method in an application is that the models built for prediction can be viewed and understood by the owner of the data who is in a position to determine the usefulness of the model, an essential component in a commercial environment.

text: Predicting apple bruising relationships using machine learning Many models have been used to describe the influence of internal or external factors on apple bruising. Few of these have addressed the application of derived relationships to the evaluation of commercial operations. From an industry perspective, a model must enable fruit to be rejected on the basis of a commercially significant bruise and must also accurately quantify the effects of various combinations of input features (such as cultivar, maturity, size, and so on) on bruise prediction. Input features must in turn have characteristics which are measurable commercially; for example, the measure of force should be impact energy rather than energy absorbed. Further, as the commercial criteria for acceptable damage levels change, the model should be versatile enough to regenerate new bruise thresholds from existing data. 
Machine learning is a burgeoning technology with a vast range of potential applications particularly in agriculture where large amounts of data can be readily collected [1]. The main advantage of using a machine learning method in an application is that the models built for prediction can be viewed and understood by the owner of the data who is in a position to determine the usefulness of the model, an essential component in a commercial environment.

year: 1998-04

title: Wearable technology for hazardous remote environments: Smart shirt and Rugged IoT network for forestry worker health

authors: Hinze, Annika

subjects: software engineering

abstract: This paper introduces the architecture and details of our wearable IoT solution for workplace health and safety in rugged outdoor environments. We focus on the specific requirements defined by the New Zealand forestry environment as it is the industry with the most fatalities and highest accident rate in New Zealand. Neither consumer-level products nor professional wearables have been found to be suitable for forestry conditions. Furthermore, forestry workplaces cannot rely on existing networking infrastructure, and due to their remote and rugged nature, no permanent setup is possible.

We describe the Hakituri project in which we integrate wearable devices, networking, data analytics, and a buddy system into a novel monitoring solution for worker health and safety. Our wearable IoT solution includes a dynamic network set-up, wearables suitable for forestry conditions, contextual rule-based data analytics, and real-time alerts. A wearable smart shirt carries sensors for collecting personal data from forestry workers, while further environmental sensors capture contextual data. The IoT network is set up for communication in unreliable and rugged outdoor environments. We explore a variety of setups to achieve the best quality outcomes for health and safety in the forestry domain.

text: Wearable technology for hazardous remote environments: Smart shirt and Rugged IoT network for forestry worker health This paper introduces the architecture and details of our wearable IoT solution for workplace health and safety in rugged outdoor environments. We focus on the specific requirements defined by the New Zealand forestry environment as it is the industry with the most fatalities and highest accident rate in New Zealand. Neither consumer-level products nor professional wearables have been found to be suitable for forestry conditions. Furthermore, forestry workplaces cannot rely on existing networking infrastructure, and due to their remote and rugged nature, no permanent setup is possible.

We describe the Hakituri project in which we integrate wearable devices, networking, data analytics, and a buddy system into a novel monitoring solution for worker health and safety. Our wearable IoT solution includes a dynamic network set-up, wearables suitable for forestry conditions, contextual rule-based data analytics, and real-time alerts. A wearable smart shirt carries sensors for collecting personal data from forestry workers, while further environmental sensors capture contextual data. The IoT network is set up for communication in unreliable and rugged outdoor environments. We explore a variety of setups to achieve the best quality outcomes for health and safety in the forestry domain.

year: 2022