Abstract: A telescopic lance, comprising a lance handle (5) with a fixed inner pipe (3), an extractable outer pipe (4) and at least one locking mechanism (10,20), wherein the extractable outer pipe (4) is located outside, and slidably longitudinally arranged with the fixed inner pipe (3), and said locking mechanism (10,20) is arranged to allow motion of the extractable outer pipe (4) with respect to the fixed inner pipe (3). A first locking mechanism (20) comprises a protrusion (21) for engagement with a locking slot (22), wherein twisting of the extractable outer pipe (4) brings the protrusion (21) into or out of engagement with the locking slot (22), and a second locking mechanism (10) comprises a spring loaded lock handle (13) with a through going aperture (15) for trapping and releasing the extractable outer pipe (4). The invention also relates to a combination of a telescopic lance and a trigger gun (8) for use with a high pressure washer.

Abstract: A bendable telescopic lance device was disclosed. It is comprised of a flexible inner tube (1), a bendable telescopic element (2), and an outer pipe (4). These components are arranged such that sliding the outer pipe (4) with respect to the inner pipe (1) causes the telescope end element to either telescopically expand or retract. Bends in the components of the telescopic end element allow for the spraying angle to be changed. Associated methods for the adjustment of the spraying angle by adjusting relative the position of the inner tube (1) with respect to the outer pipe (4) were also disclosed.

Abstract: A sensor is disclosed specifically for detecting stress waves for use in a stress wave analysis system. The stress waves-are preferably detected in a narrow frequency range of 35-40KHz. At this range, stress waves from friction and impact sources typically propagate through machine structures at detectable amplitudes. In order to maximize the signal to noise ratio of stress waves, relative to background noise and vibration, the sensor of the present invention is designed and calibrated with a frequency response and damping features that are specifically tailored for stress wave analysis.

Abstract: A sensor for detecting stress waves for use in a stress wave analysis system. The stress waves are preferably detected in a narrow frequency range of 35-40 KHz. At this range, stress waves from friction and impact sources typically propagate through machine structures at detectable amplitudes. In order to maximize the signal to noise ratio of stress waves, relative to background noise and vibration, the sensor of the present invention is designed and calibrated with a frequency response and damping features that are specifically tailored for stress wave analysis. The sensor is a multi-functional sensor that can measure a number of logically related parameters for indicting the mechanical condition of a machine. It is often desirable to measure both friction and one or more other parameters appropriate for indication of a machine's health, where all of the measuring capability is contained in one sensor.

Abstract: A method for stimulating a sensor and measuring it's output over a frequency ranges starting at a frequency f1 and ending at a frequency f2 is disclosed, which can include the following steps: (a) placing an assembled sensor on a shaker table; (b) setting the shaker table at a specified frequency and exciting the sensor by moving the sensor up and down at an amplitude at least approximately equal to a reference “g” level of acceleration; (c) measuring the sensor's output and recording the measured output as a first value; (d) incrementally changing an excitation frequency of the shaker table and adjusting the amplitude to achieve the reference “g” level; (e) measuring the sensor's output and recording the measured output as a second value; and (f) repeating steps (d) and (e) for one or more discrete frequencies within the frequency range to provide a frequency response curve for the sensor over the frequency range.

Abstract: A Foreign Object Damage (FOD) detection system is disclosed for detecting and analyzing ultrasound or stress waves emitted when an object enters the intake of a turbine engine and impacts one or more of the blades in the engine. Upon detection the FOD detection system can immediately inform the operator, inform another electronic device (computer, etc.) and/or latch the event for review by maintenance personnel. The detection system generally consists of one or more stress wave sensors and an electronic assembly to process the stress wave signal received from the sensor(s). The electronic assembly is in communication with the sensor(s) via conventional cabling.

Abstract: A sensor for detecting stress waves for use in a stress wave analysis system. The stress waves are preferably detected in a narrow frequency range of 35-40 KHz. At this range, stress waves from friction and impact sources typically propagate through machine structures at detectable amplitudes. In order to maximize the signal to noise ratio of stress waves, relative to background noise and vibration, the sensor of the present invention is designed and calibrated with a frequency response and damping features that are specifically tailored for stress wave analysis. The sensor is a multi-functional sensor that can measure a number of logically related parameters for indicting the mechanical condition of a machine. It is often desirable to measure both friction and one or more other parameters appropriate for indication of a machine's health, where all of the measuring capability is contained in one sensor.

Abstract: A distributed stress wave analysis system is disclosed for detecting structure borne sounds cause by friction. The detected information is processed using feature extraction and neural network artificial intelligence software. The system consists of stress wave sensors, interconnect cables, and preferably three modules: (1) distributed processing units, (2) maintenance advisory panel, and (3) laptop computer. A derived stress wave pulse train which is independent of background levels of vibration and audible noise is used to extract signature features, which when processed by neural networks of polynomial equations, characterize the mechanical health of the monitored components. The system includes an adjustable data fusion architecture to optimize indication thresholds, maximize fault detection probability, and minimize false alarms.