A density analyser

GB2701823APending Publication Date: 2026-05-13STANHOPE SETA
View PDF 5 Cites 0 Cited by

Patent Information

Authority / Receiving Office
GB · GB
Patent Type
Applications
Current Assignee / Owner
STANHOPE SETA
Filing Date
2024-09-20
Publication Date
2026-05-13

Smart Images

  • Figure 00000000_0000_ABST
    Figure 00000000_0000_ABST
Patent Text Reader

Abstract

A density analyser 100, comprising: a vessel 105 to receive a sample fluid; an imaging apparatus 110 configured to capture at least one image of the vessel; and a processor 120 arranged to perform ima
Need to check novelty before this filing date? Find Prior Art

Description

FIELD OF THE INVENTION The present invention relates to a density analyser with image capture capabilities and a corresponding method. More particularly, the present invention relates to a density analyser including a vessel to receive a sample fluid, an imaging apparatus to capture an image of the vessel when sample fluid is contained therein, and a processor to perform image analysis on the captured image to identify the presence or absence of an anomaly, such as a gas or air bubble, in the sample fluid. BACKGROUND A density analyser may be used to measure the density of a sample fluid. There are various known techniques and instruments for measuring the density of a sample fluid which a density analyser may employ. In the context of measuring the density of a sample fluid, it is preferable for there to be no anomalies present in the sample fluid. For example, the sample fluid should be free from any gas or air bubbles that may have inadvertently been introduced into the vessel containing the sample fluid, which is often a problem faced with providing sample fluids for measurement purposes. Density is defined as the mass of a substance per unit volume and the presence of any anomalies in the sample fluid to be measured that have a different mass to the sample fluid can lead to an inaccurate density measurement. For example, bubbles of air or other gases which may have substantially lower density compared to the sample fluid to be measured will occupy a portion of the volume of a vessel containing the sample fluid but contribute negligibly to the mass. As a result, the mass-to-volume ratio will be artificially reduced, leading to an erroneously low density measurement. An inaccurate density measurement can have adverse effects on processes that rely on accurate density values, such as quality control, formulation of mixtures, and other applications where the physical properties of fluids are critical. Anomalies such as gas bubbles can be small and, therefore, may go unnoticed by certain methods of inspection. This presents a problem because density measurements may be measured from sample fluids with anomalies present therein, therefore resulting in inaccurate and unreliable density measurements. Ensuring that the sample fluid is anomaly free can help obtain accurate and reliable density data. SUMMARY OF THE INVENTION According to a first aspect of the invention there is provided a density analyser. The density analyser includes a vessel to receive a sample fluid, an imaging apparatus configured to capture at least one image of the vessel, and a processor arranged to perform image analysis on the at least one image captured by the imaging apparatus to identify the presence or absence of an anomaly in the sample fluid that is received in the vessel. According to another aspect of the invention, there is provided a method. The method includes receiving a sample fluid in a vessel of a density analyser, capturing at least one image of the vessel using an imaging apparatus, and performing image analysis on the at least one image captured by the imaging apparatus using a processor, to identify the presence or absence of an anomaly in the sample fluid that is received in the vessel. According to another aspect of the invention, there is provided a system. The system includes an analytical apparatus and the density analyser according to the first aspect of the invention. Further optional features are provided in the appended dependent claims. BRIEF DESCRIPTION OF THE FIGURES These and other aspects of the present invention will now be described, by way of example only, with reference to the following drawings, in which: Figure 1 illustrates a schematic representation of a density analyser; Figure 2 illustrates a U-Tube vessel containing a sample fluid with gas bubble anomalies; Figure 3 illustrates a flowchart for determining a density measurement of a plurality of density measurements of a sample fluid; Figure 4 illustrates a system including a density analyser coupled to an analytical apparatus; Figure 5 illustrates a chamber and piston for transferring the sample fluid. DETAILED DESCRIPTION Density analyser Figure 1 is a schematic representation of a density analyser 100. Figure 1 illustrates a density analyser 100 including a vessel 105 to receive a sample fluid, an imaging apparatus 110 positioned so that the vessel 105 is within the field of view 115 of the imaging apparatus 110, and a processor 120 arranged to perform image analysis on an image captured by the imaging apparatus. At least a portion of the vessel that contains the received sample may be within the field of view 115. Imaging apparatus 110 is configured to capture at least one image of vessel 105 when vessel 105 has received a sample fluid for density measurement. The at least one image captured of vessel 105 can be used to identify the presence or absence of an anomaly in the sample fluid received in vessel 105 using processor 120. The density analyser may be used to measure the density of a sample fluid and may employ a variety of known techniques and instruments such as a density sensor (not shown) for measuring the density of a sample fluid. The vessel Vessel 105 may receive a sample fluid and may further hold or retain the sample fluid while a density measurement of the sample fluid is obtained and while an image is captured of vessel 105. A plurality of density measurements may be obtained and a plurality of images may be captured of the sample fluid. An image may be captured at substantially the same time as a density measurement is obtained so that the image captured is a true or substantially true representation of the sample fluid measured at the time of the density measurement. Vessel 105 may be further configured to receive at least two different samples of the sample fluid where the sample fluid comprises a plurality of samples. For example, vessel 105 may receive one sample of the sample fluid, and after image capture and density measurement of the one sample, eject this sample to receive a different sample of the sample fluid. For example, the total volume of sample fluid to be measured may be 6ml and vessel 105 may retain 1ml of the sample fluid at any one time. In this example, vessel 105 may receive six 1ml samples of the sample fluid in total and for each 1ml sample at least one density measurement may be obtained and at least one image of vessel 105 may be captured whilst each respective sample is retained in vessel 105. A plurality of images of the sample fluid may be captured for each sample of the sample fluid received in vessel 105 and a plurality of density measurements of the sample fluid may be obtained for each sample of the sample fluid received in vessel 105. For each image captured of the sample fluid, one density measurement may be assigned to this one image captured. For example, one density measurement may be made per one image captured. Alternatively, where multiple density measurements are obtained and one image is captured for one sample, then an average value for the multiple density measurements may be calculated to assign one density measurement (the average value) to the one image captured. Equally, where multiple images are captured per density measurement, the multiple images may be fused to generate one image for the one density measurement to be assigned to the one fused image. Vessel 105 may be any hollow container that can suitably hold or retain a sufficient volume of a sample fluid in an appropriate position or form at conditions required for the density measurement to be carried out. For example, where the sample fluid is a liquid, the vessel may include a fluid receptacle, lidded chamber, tube, ll-Tube or oscillating ll-Tube or any other suitable liquid vessel, or the like Vessel 105 may be at least partially transparent so that the sample fluid received by vessel 105 is viewable by the imaging apparatus 110. In one example, it may be advantageous for vessel 105 to be entirely, or substantially formed from transparent materials. For example, glass may be used to form at least part of a transparent, or substantially transparent, vessel. The skilled person, with the benefit of this disclosure, will appreciate that different types of vessel 105 that receive a sample to be viewed may be used in the density analyser. Vessel 105 is housed within density analyser 100 whereby density analyser 100 may include, be formed by, or be at least partially formed by housing that houses vessel 105. Alternatively, vessel 105 may be housed within density analyser 100 where housing for vessel 105 is separate to the housing formed by density analyser 100. Housing vessel 105 within density analyser 100 may allow vessel 105 to be at least partially or entirely isolated from any outside apparatus, ambient conditions, ora user for example. Imaging apparatus Imaging apparatus 110 is positioned so that vessel 105 or at least the received sample in the vessel 105 is within the field of view 115 of imaging apparatus 110. The field of view 115 of imaging apparatus 110 may include at least a portion of vessel 105. The field of view 115 may include the entirety of vessel 105. Imaging apparatus 110 may be any suitable device, for example, a camera, that is capable of capturing at least one image of vessel 105 to be used for identifying the presence or absence of an anomaly in the sample fluid received in vessel 105. The at least one image captured and output by imaging apparatus 110 may be in the form of image data. Image data may comprise pixel information, for example, the numerical value of each pixel in an image, where the numerical value of each pixel in an image is indicative of the pixel’s colour or grayscale level. Imaging apparatus 110 may be housed within density analyser 100 whereby density analyser 100 may include, be formed by, or be at least partially formed by housing that houses imaging apparatus 110. Vessel 105 and imaging apparatus 110 may be housed in or by the same housing or may be housed or otherwise arranged separately. For example, imaging apparatus 110 may be arranged in a position exterior to the housing of the vessel in a module or selfcontained unity that is releasably attached to the density analyser 100. Housing or any other component part positioned between vessel 105 and imaging apparatus 110 within the field of view 115 may include one or more windows, viewing holes, or the like so that the field of view 115 is not obscured by the housing or any other component part. Where vessel 105 and imaging apparatus 110 are isolated from each other, for example, by being housed separately, any window or viewing hole provided so that vessel 105 is within the field of view 115 of the imaging apparatus 110 may include an at least partially transparent component so that vessel 105 is viewable by imaging apparatus 110 while also being isolated from imaging apparatus 110. Isolating vessel 105 and imaging apparatus 110 may isolate imaging apparatus 110 from the conditions in which vessel 105 is maintained for the density measurement procedure. For example, imaging apparatus 110 may be contained in a chamber, container, sub-portion, or compartment intended to at least partially isolate imaging apparatus 110 from one or more environments or materials that may cause damage to imaging apparatus 110 or otherwise compromise its operation. Additionally, imaging apparatus 110 may be configured in a manner and / or formed from materials to ensure that it is not adversely affected by the conditions in which vessel 105 is maintained for the density analysis procedure or affected by contact with the sample fluid or the like. Imaging apparatus 110 is configured to capture at least one image of vessel 105 when vessel 105 has received a sample fluid for density measurement. Additionally, imaging apparatus 110 may be configured to capture and output a plurality of images, or a video of the vessel from which at least one image may be extracted. Image data from the at least one captured image may be output to a display device for displaying to a user. Density analyser 100 may include a lighting device (not shown) positioned to illuminate the sample fluid received by vessel 105 so that imaging apparatus 110 can capture an image of the sample fluid sufficiently illuminated such that any image captured is of sufficient image detail for the purpose of identifying the presence or absence of an anomaly in the sample fluid. For example, vessel 105 may be positioned between a backlight lighting device and imaging apparatus 110 such that the entirety of vessel 105 in the field of view 115 of imaging apparatus 110 is back lit by the lighting device. While the configuration of imaging apparatus 110 and vessel 105 are described with reference to a single imaging apparatus 110 and single vessel 105, a plurality of vessels 105 may be included in density analyser 100 and positioned within density analyser 100 so that vessels 105 are within the field of view 115 of one or more imaging apparatus’ 110. Sample fluid The sample fluid received in vessel 105 may be any substance that is not entirely solid, has no fixed shape and is able to flow. In one example, the sample fluid may be a petroleum distillate and / or a viscous oil and density analyser 100 is configured to measure the density of the petroleum distillate and / or the viscous oil. An anomaly An anomaly in the sample fluid may include any anomaly of and / or contaminant in the sample fluid, which includes anything present in the sample fluid that does not form part of the sample fluid itself. The sample fluid may be a liquid and the anomaly may be a liquid, gas, semi-solid or solid in the sample fluid. Any combination of sample fluid and anomaly may be possible, for example, the sample fluid may be a liquid and an anomaly of the sample fluid may also be a liquid where the liquid sample fluid and liquid anomaly are immiscible liquids, for example. In another example, the sample fluid may be a liquid and an anomaly may be a gas bubble in the liquid sample fluid. Figure 2 illustrates a ll-Tube vessel 205 holding a sample fluid where gas bubble anomalies have been identified 210. Density meter Density analyser 100 may employ features of a density meter or sensor (such as a digital density meter) which is one example instrument for measuring the density of a sample fluid received by vessel 105. In this example, vessel 105 operates by oscillating a sample fluid-filled vessel 105 and measuring its resonant frequency. The vessel 105 to be oscillated is generally a U-shaped Tube, known in the art as a ‘U-Tube’ (a specific type of vessel as mentioned above). The vessel 105 is set to oscillate at its resonant frequency by using, for example, an electronic exciter, whereby the resonant frequency is dictated by and varies according to the mass of the vessel 105 and the sample fluid inside if the vessel 105 is filled. The mass of the vessel 105 itself is unchanged between measurements, any difference in frequency measurement is related to the mass of the sample fluid, which is a function of the sample fluid’s density. Assuming the volume of the sample fluid to be measured remains constant, the relationship between resonant frequency and density for that particular volume can be determined by using a number of calibration standard fluids with known density values. Calibration parameters are determined, indicative of the relationship between resonant frequency and density for that particular vessel. Calibration parameters will be different for different volumes. In this way, density may be calculated by measuring only the resonant frequency and using the set of calibration parameters, where Density oc 1 / f2, where f = the resonant frequency (density is inversely proportional to the square of the measurement frequency). The skilled person will appreciate that other devices or methods for determining the density may be used. Density analyser 100 may include a controller or multiple controllers to control the condition or environment in which density analyser 100 operates and a sensor or multiple sensors to sense the condition or environment in which density analyser 100 operates. By employing such sensors and controllers, a feedback system may be implemented to maintain the required conditions of operation. For example, density analyser 100 may include a temperature controller for controlling the temperature of vessel 105 and its contents and a temperature sensor to sense the temperature of vessel 105 and its contents. The temperature of vessel 105 and its contents thereby may be controlled and set to a user defined temperature where the temperature may be maintained at this set temperature for the duration of the density analysis procedure. The temperature may be set before the sample fluid is received by vessel 105, whereby vessel 105 may, for example, be pre-heated or pre-cooled, or the temperature may be set after the sample fluid is received. In any case, the temperature of the sample fluid may be monitored once received to determine whether the temperature of the sample fluid has adjusted to the set temperature and stabilised. Once the temperature has adjusted and stabilised, the density analysis procedure may begin wherein at least one density measurement is made of the sample fluid and at least one image is captured of vessel 105. As an example, the temperature may be controlled using a Peltier cell in combination with a PT100 PRT for accurate temperature measurement, where a Peltier cell is a solid-state device that creates a temperature difference when an electric current passes through it and a PT100 PRT is a precise temperature sensor that works on the principle of resistance change in a metal with temperature. The temperature may be maintained at a set, stable temperature by implementing a feedback system as noted above and / or by providing walls on all sides of vessel 105 to insulate vessel 105. These walls may, for example, be provided by the housing of the density analyser 100. In this arrangement, the density analyser housing effectively provides an oven for vessel 105. It is common practice to report a density measurement with an associated temperature at which the measurement was made because the density of a substance will vary according to its temperature. Therefore, it is preferable that the temperature of the sample fluid being measured is stable and maintained at a constant temperature throughout the density analysis procedure so that the temperature recorded at which density measurement is made at is accurate. Additionally, because the density of a substance will vary according to its temperature, it is common practice to use conversion calculations and / or conversion tables to convert density measurements to values at different temperatures. Generally, not having to convert the density measurement based on temperature results in a more accurate density measurement value. It is therefore advantageous to be able to control the temperature at which the density measurement is made so that the density measurement value does not need to be converted prior to being reported, and instead can be measured at the relevant reporting temperature. When the sample fluid is received by vessel 105, there may be a time delay between vessel 105 receiving the sample fluid and measuring the density of the sample fluid and / or capturing an image of vessel 105 to allow for the sample fluid to adjust to the set temperature of density analyser 100 and be sufficiently stabilised. The time delay may, for example, be approximately 20 seconds. Density analyser 100 may include a storage or memory unit as well as a processor 120 to store and / or process data, where data relates to for example captured image(s), density measurement(s) and temperature measurement(s). The storage or memory unit and processor 120 may be coupled to each other and all or a subset of components of density analyser 100 for the purposes of transferring data. For example, the imaging apparatus may be coupled to the storage or memory unit and processor 120 to transfer image data and / or the temperature sensor may be coupled to the storage or memory unit and / or processor 120 to transfer temperature data. Example of determining a more accurate and reliable density measurement of a sample fluid Figure 3 illustrates a flowchart 300 for determining a more accurate and reliable density measurement of a sample fluid. This flowchart will be described with respect to an example where the total volume of the sample fluid to be measured is 6ml and the capacity of vessel 105 is 1ml. However, it should be understood that the total volume of the sample fluid to be measured and the capacity of vessel 105 may be different. At step 305, vessel 105 receives a first 1ml sample of the sample fluid. In accordance with the above description, the temperature of density analyser 100 may be set to a user defined temperature and the temperature of the sample fluid may be monitored once received in vessel 105 to determine whether the temperature of the sample fluid has adjusted to the set temperature and stabilised. Once the temperature has adjusted and stabilised, the density analysis procedure may begin wherein at least one density measurement is made of the sample fluid and at least one image is captured of vessel 105. In this example, once the density measurement is made and the image is captured for the first 1ml sample, the captured image along with the corresponding density measurement may be stored for later processing. The first 1ml sample is ejected from vessel 105 for vessel 105 to receive a second 1ml sample of the sample fluid (a different 1ml sample of the sample fluid). Following receipt of the second 1ml sample, the same procedure as described above with respect to receipt of the first 1ml sample is repeated such that at least one density measurement is made and at least one image is captured for the second 1ml sample received and are stored. In this example, where a 6ml sample fluid is to be measured and vessel 105 has a capacity of 1ml, the procedure will be repeated six times. Though multiple density measurements may be made and multiple images may be captured per 1ml sample of the sample fluid received by vessel 105, in this example, one density measurement is made per 1ml sample of the sample fluid and one image is captured per 1ml sample of the sample fluid. Therefore, in this example, six images of the sample fluid are captured, one for each 1ml sample of the sample fluid, each having an associated density measurement. Each image captured will be assigned an image ID. In this example, the six images captured will each have an image ID assigned to them such that the first image captured for example is assigned image ID(1) and the second image for example is assigned image ID(2) etc. A storage or memory unit and / or processor 120 may store and / or process data including the set temperature, the captured images and their IDs and density measurements. At step 310, each of the six images captured may be pre-processed prior to performing image analysis whereby the processor 120 may perform the image pre-processing. Alternatively, only a sub portion of images captured may be pre-processed. Alternatively, images may not be pre-processed prior to image analysis and image analysis may be performed without preprocessing (i.e., step 310 is optional). Image pre-processing may be performed to prepare images for image analysis by modifying images such that they are more suitable for extraction of relevant features. For example, many known image pre-processing methods modify an image so that features of the image are more pronounced and identifiable and / or to reduce the complexity of the image to reduce the computational demands of image processing to be performed. Various known image pre-processing methods may be employed. For example, grey scaling may be employed, to convert colour images to greyscale, reducing the complexity of subsequent processing steps. Additionally, noise reduction techniques may be employed, such as Gaussian blur, median filtering, and bilateral filtering, which reduce unwanted variations in image pixel intensity, to improve the clarity of the image. Additionally, various contrast enhancing techniques may be employed to make features more distinguishable, for example, Histogram equalization may be employed. Additionally, thresholding methods may be employed to convert images into binary format based on intensity values, making features more distinguishable. These various methods may be implemented by applying a mask to an image. Additionally, images may be resized and / or cropped to regions of interest, to reduce computational demands. Additionally, images may be compressed to reduce the size of image files without significant loss of quality. One of or multiple of the above-described image preprocessing methods may be employed. Additionally, or alternatively, imaging apparatus 110 may be configured to capture images in a pre-processed state where pre-processing may not be needed. For example, images may be captured in grey scale format. At step 315, pairwise difference images are generated. This is an image analysis step and may be performed by the processor 120. The number of pairwise difference images generated (Q) is equal to the number of image pair combinations which is equal to NI / ((N-2)I x 2), where N = the number of images captured. In this example where six images are captured, there are fifteen image pair combinations, listed below, where numbers 1, 2, 3, 4, 5, 6 represent the image IDs of the first, second, third, fourth, fifth and sixth image captured respectively: [1, 2], [1, 3], [1, 4], [1, 5], [1, 6], [2, 3], [2, 4], [2, 5], [2, 6], [3, 4], [3, 5], [3, 6], [4, 5], [4, 6], [5, 6] From the above fifteen pairs, the following fifteen pairwise difference images are generated: Diff[1, 2], Diff[1, 3], Diff[1, 4], Diff [1, 5], Diff [1,6], Diff [2, 3], Diff [2, 4], Diff [2, 5], Diff [2, 6], Diff [3, 4], Diff [3, 5], Diff [3, 6], Diff [4, 5], Diff [4, 6], Diff [5, 6] Where each pair of images has a first and second image, each pairwise difference image is the image that results from subtracting the first image from the second image. Where a first image has a first set of pixels, each pixel of the first image has a pixel value and associated coordinate representing the pixel’s location in the first image and where a second image has a second set of pixels, each pixel of the second image has a pixel value and associated coordinate representing the pixel’s location in the second image. Subtracting the first image from the second image comprises subtracting for each pixel of the first image, the value of the pixel from the value of the pixel of the second image with the corresponding pixel coordinate. Subtraction may be bitwise absolute subtraction. Additionally, noise from the pairwise difference images may be filtered at this stage. At step 320 an overlap difference image for each of the image IDs is generated (each image ID being associated with a captured image). This is an image analysis step and may be performed by the processor 120. In this example, where six images have been captured by the imaging apparatus 110, six overlap images are generated, one for each of image IDs: 1, 2, 3, 4, 5, 6. Each overlap difference image generated for each image ID is generated by combining each pairwise difference image that includes the image ID (i.e. each pairwise difference image that was generated using the captured image associated with the image ID). For example, for the image ID(1), the overlap difference image generated, Overlap(1), is generated using pairwise difference images: Diff[1,2], Diff[1, 3], Diff[1, 4], Diff[1, 5], Diff[1,6] and for the image ID(2), the overlap difference image generated, Overlap(2), is generated using pairwise difference images: Diff[1, 2], Diff[2, 3], Diff[2, 4], Diff[2, 5], Diff[2,6], This processing is carried out for each image ID (for each captured image) based on the relevant pairwise difference images for the specific image ID, to generate six overlap images, Overlap(1),Overlap(2), Overlap(3), Overlap(4), Overlap(5), Overlap(6). In this example, where six images are captured, each overlap image is generated using five pairwise difference images. Where each of the five pairwise difference images used in generating each overlap image has a set of pixels, each pixel of each set of pixels has a pixel value and an associated coordinate representing the pixel’s location in the respective pairwise difference image. Combining each of the five pairwise difference images comprises, for each pixel coordinate, using an AND operator to find the conjunction of the five pixel values of the five pixels of the pairwise difference images. This ‘adds’ the pairwise difference images together only where they overlap. At step 325, the presence or absence of a feature in each overlap difference image is identified, where a feature is representative of an anomaly in the associated captured image. This is an image analysis step and may be performed by the processor 120. For each overlap image, pixel coordinates of the image corresponding to the location of a feature identified in the image may be determined where the pixel coordinates determined represent the location of an anomaly (or several anomalies) in vessel 105. A set of morphological transformations may be applied prior to feature detection to emphasise image features. This may include erosion and dilation techniques. Various known feature detection methods may be employed to identify the presence or absence of features in the images. For example, edge detection methods may be employed, such as the Sobel operator and Canny edge detector. These methods are used to identify and outline significant boundaries within an image to detect features. Such methods may output pixel coordinates of an image corresponding to the location of feature boundaries identified in the image. In the context of the invention, pixel coordinates identified represent the location of anomaly boundaries (boundaries between anomalies and the sample fluid) in vessel 105. Additionally, segmentation feature detection methods may be employed. These methods divide an image into regions or segments based on similar characteristics, using techniques such as thresholding, clustering, and region growing. Such methods may output pixel coordinates of an image corresponding to the location of feature regions identified in the image. In the context of the invention, pixel coordinates identified represent the location of anomaly regions (regions where an anomaly is and the sample fluid is not) in vessel 105. Additionally, more complex feature detection or object detection methods may be employed to detect the location of features in an image. Such methods may for example identify key attributes or patterns within an image, which can be used for classification, matching, and recognition tasks. For example, template matching, deep learning-based models or machine learning algorithms may be employed to identify features in an image. In the context of the invention, anomalies in the sample fluid, where present, may generally have a particular shape, for example, a gas bubble may generally have a circular shape. Where this is the case, an image may be searched for features of this particular shape. Such methods may output pixel coordinates of an image corresponding to the location of feature shape regions identified in the image. In the context of the invention, pixel coordinates identified represent the location of anomaly regions (regions where an anomaly is and the sample fluid is not) in vessel 105. For example, Figure 2 illustrates a ll-Tube vessel containing a sample fluid with gas bubble anomalies 210 where circular shapes of the gas bubble anomalies 210 are identified following feature detection 325. For each image ID, the number of anomalies identified in this way (if any) may be counted. The anomaly count for each image ID may be stored by the storage or memory unit. For example, COUNT(1) = 2 may denote that two anomalies have been identified in image ID(1) (i.e. that two anomalies have been identified in the first image captured). Alternatively, where it is only relevant whether at least one anomaly is present in the captured image or whether no anomalies are present, just a binary indication of the presence or absence of an anomaly may be stored with each image ID. Advantageously, comparing images in this way (for example, by generating pairwise difference images and / or by generating overlap images) eliminates any unfavourable imperfections in the original captured images that result from any unstable conditions of the density analyser. For example, stray reflections present in the density analyser may impact images of vessel 105. Stray reflections for example may be captured as imperfections in the captured images and risk being mistaken as anomalies in the sample fluid. Due to the imperfections captured in the captured images being consistent across the multiple images captured of vessel 105 during the density measurement procedure, because images are taken at substantially the same time, any imperfections can be eliminated by comparing images as described because the imperfections are cancelled out by the image subtraction. At step 330, the identification of the presence or absence of an anomaly in each captured image may be validated to eliminate false negatives. This is an image analysis step and may be performed by the processor 120. Alternatively, anomaly detection may not be validated, and image analysis may be performed without this validation step (i.e., step 330 is optional). In the context of this disclosure, a false negative is where an image contains an anomaly but is falsely identified as anomaly free (e.g. COUNT(X) = 0). This can occur, for example, where at least two of the captured images have an anomaly at the same location and / or anomalies of a similar size because the image subtraction / addition procedure can cancel out these anomalies, thus they do not appear in the resulting images generated (e.g. the pairwise difference images and / or overlap images). This is unlikely but possible, hence the need for it to be accounted for. To validate the anomaly detection, firstly, all of the image IDs for which no anomalies were identified are identified, the validation image IDs (for example, all of the image IDs for which COUNT(X)=0). In this example, four of the six image IDs may have been identified as ‘anomaly free’, for example, therefore, validation image IDs may be: ID(1), ID(2), ID(3), ID(4). After these validation image IDs have been identified, the pairwise difference images including only these validation image IDs are identified, the validation pairwise difference images. In this example, where validation image IDs are ID(1), ID(2), ID(3), ID(4), the validation pairwise difference images are Diff[1, 2], Diff[1, 3], Diff[1, 4], Diff [2, 3], Diff [2, 4], Diff [3, 4], After these validation pairwise difference images have been identified, validation overlap images are generated. The validation overlap images are generated in the same way as the overlap images (as described above) but validation overlap images are only generated for validation image IDs and the validation pairwise difference images are omitted from the pairwise difference images used to generate the overlap images. In this example, validation overlap images will be generated for ID(1), ID(2), ID(3), ID(4). In this example, the validation overlap image generated for image ID(1), ValidationOverlap(l), will be generated using pairwise difference images: Diff[1, 5], Diff[1,6] where pairwise difference images: Diff[1,2], Diff[1, 3], Diff[1, 4] have been omitted. Once each of the validation overlap images have been generated these images are analysed to identify the presence or absence of features representing anomalies in the images, in the same way as described above with respect to the overlap images. Outputs from anomaly identification of validation overlap images replaces the outputs from anomaly identification of the corresponding overlap images. In this example, anomaly detection of the overlap images may have determined that COUNT(1)=0, COUNT(2)=0, COUNT(3)=0, COUNT(4)=0 but after validation, anomaly detection of the validation overlap images may determine that COUNT(1)=2, COUNT(2)=2, COUNT(3)=0, COUNT(4)=0. Therefore, in this example, the number of anomalies identified for image IDs 1 and 2 will be updated following the identification of false negatives. At step 335, the density measurement for the sample fluid is determined. The processor 120 is configured to disregard the density measurement of the sample fluid in the case that an anomaly is identified in the image captured associated with the density measurement and / or retain the density measurement of the sample fluid in the case that an anomaly is not identified in the image captured associated with the density measurement. For example, in the example of six captured images, an anomaly may be identified in four of the six captured images, and so the density measurement associated with each of these four images may be disregarded and the density measurement associated with the other two images may be retained. Additionally, the processor 120 may be further configured to calculate the average value of any retained density measurements of the sample fluid. For example, in the example of the six images captured, where two density measurements are retained, the average of these two values is calculated and this value is output as the density measurement for the sample fluid. This density measurement value may be output with the associated temperature recorded. In another example, the density analyser may retain density measurements for images with and without anomalies identified, storing them in such a way to distinguish density measurements associated with an image with or without anomalies identified. Accordingly, in this example, an average density measurement can be calculated based on retained density measurements associated with images captured without anomalies identified. In another example, the imaging apparatus may capture an image and identify the presence or absence of anomalies in the sample fluid before a density measurement may be made and the density analyser may only make a density measurement where it is identified that the image is anomaly free (i.e., a density measurement may only be made after image analysis has been performed). In this example, the density analyser may disregard the sample fluid received in the vessel 105 where an anomaly is identified in the image captured and / or retain the sample fluid received in the vessel in the case that an anomaly is not identified in the image captured so that a density measurement can be made for the sample fluid in the vessel 105. Therefore, in this example, only density measurements associated with anomaly free images are made. Accordingly, in this example, an average density measurement may be calculated based on all density measurements made. Alternatively, the measurement procedure may end once an anomaly free image is identified, and a density measurement is made. In this example, the presence or absence of an anomaly in captured images may be determined using the image analysis processes described above (e.g. one of more of processes 315 to 330 of fig. 3) including the generating of pairwise difference images and overlap images, where at least two images have been captured and can therefore be compared in this way. In this example, it may not be necessary to determine whether the temperature of the sample fluid received in vessel 105 has adjusted to the set temperature and stabilised because a density measurement may not necessarily be made. In this example, it may only be necessary to determine whether the temperature of the sample fluid has adjusted to the set temperature and stabilised when an image is identified as anomaly free because it is only if the image is identified as anomaly free that a density measurement is made. Advantageously, in this example, the time taken for the measurement procedure may be reduced as compared to the measurement procedure where, for each sample of the sample fluid received by vessel 105, there is a delay corresponding to the time taken for the temperature of each sample of the sample fluid to adjust and stabilise. By identifying the presence or absence of an anomaly in the sample fluid, or for each sample of the sample fluid where the sample fluid comprises a plurality of samples, it can be determined for the sample fluid or for each separate sample of the sample fluid, whether the associated density measurement is accurate or not. For the sake of clarity, if an anomaly is identified in the sample fluid, the associated density measurement is considered to be inaccurate and if an anomaly is not identified, the associated density measurement is considered to be accurate. Advantageously, this procedure allows for samples with and without anomalies to be distinguished and / or accurate and inaccurate density measurements of the sample fluid to be distinguished such that samples with anomalies and / or inaccurate density measurements can be disregarded. In this way, an accurate density measurement for the sample fluid can be determined even where not all samples of the sample fluid are anomaly free and / or even where not all density measurements of the sample fluid are accurate. Therefore, where the sample fluid comprises a plurality of samples, the entire measurement procedure for the sample fluid does not have to be carried out again to obtain an accurate density measurement, even where not all samples are anomaly free and / or not all density measurements of the sample fluid are accurate. Though the above description relating to flowchart 300 describes an example of six images captured whereby one image is captured per sample of the sample fluid received by vessel 105 and each image is processed according to steps 310-335, in an alternative embodiment, vessel 105 may receive only one sample of the sample fluid (e.g. where the total volume of the sample fluid is equivalent to the capacity of vessel 105). In this alternative embodiment, multiple images may be captured of the one sample and the multiple images may still be processed according to steps 310-335. Though the above description relating to flowchart 300 describes an example of images captured and processed according to steps 310-335, in an alternative embodiment, images captured, or just one image captured, may be processed to identify the presence or absence of anomalies by implementing feature detection methods described above directly on captured images (i.e., images are not compared, pairwise difference images and / or overlap images are not generated). Additionally, identifying the presence or absence of an anomaly in the sample fluid received by vessel 105 of density analyser 100 may include first analysing the at least one image to identify the presence or absence of an anomaly via visual inspection and then performing automated image analysis as described above to verify or compare the result of visual inspection against the result of automated image analysis. Visual inspection of the at least one image may be carried out where imaging apparatus 110 and / or the processor 120 is coupled to a display device for example. In any case, the present invention improves the accuracy and reliability of density measurements determined for a sample fluid by providing a method of accurately and reliably determining anomalies in the sample fluid. Detail on the processor The processor 120 may be a plurality of components and may, in one example, be in the form of a computer integrated with density analyser 100. The processor 120 may be a programmable logic controller (PLC) or other computing device that can carry out instructions. The processor 120 may include one or multiple processing elements that are integrated in a single device or distributed across devices. The processor 120 may have a data input / output interface unit to receive input data from internal or external components or send data to internal or external components. The processor 120 may process all data flow between all components. The processor 120 may be any of a central processing unit, a semiconductorbased microprocessor, an application specific integrated circuit (ASIC), and / or other device suitable for retrieval and execution of instructions. The density analyser 100 may further include a storage or memory unit (not shown) to store any data or instructions which may need to be accessed by, for example, a processor. Data stored may be retrieved by a user and / or accessed for display on a display device at any time. Where present, the storage unit may be any suitable storage unit such as a magnetic storage device, a solid-state storage device, or the like. Where present, the memory unit may be any form of storage device capable of storing executable instructions, such as a nontransient computer readable medium, for example Random Access Memory (RAM), Electrically-Erasable Programmable Read-Only Memory (EEPROM), a storage drive, an optical disc, or the like. In an example, the processor 120 may include a PLC (programmable-logic-controller. In another example, the processor 120 may include a PID (proportionalintegral-derivative) controller, and / or a FO (fractional-order) controller, and / or an IO (integerorder) controller. The processor 120 may operate in a closed-loop or an open-loop manner dependent upon the wider functions to be carried out by the processor 120. Density analyser as part of a system including an analytical apparatus Figure 4 illustrates density analyser 405, in accordance with the above description of the density analyser, that may form part of a system 400. System 400 includes density analyser 405 and analytical apparatus 410. Density analyser 405 may be coupled to analytical apparatus 410 as a separate device or may provided as a module that fits into analytical apparatus 410. For example, density analyser 405 may be a module or self-contained unit that can be releasably attached to an analytical apparatus 410. An analytical apparatus 410 may include multiple analytical apparatus 410. Housing vessel 105 in density analyser 405 may allow vessel 105 to be at least partially isolated from any outside analytical apparatus 410, for example as part of the described system. Where density analyser 405 forms part of a system 400 including the density analyser 405 and further analytical apparatus 410, the system 400 may be arranged such that the sample fluid is transferred from analytical apparatus 410 to vessel 105 of the density analyser 405 after analytical apparatus 410 has performed analysis on the sample fluid. Equally, the system may be arranged such that the sample fluid is transferred from vessel 105 of the density analyser 405 to analytical apparatus 410 after density analyser 405 has performed density analysis on the sample fluid. The sample fluid may be transferred between density analyser 405 and analytical apparatus 410 for example through a connecting tube. To facilitate transfer of the sample fluid between vessel 105 of density analyser 405 and analytical apparatus 410, a chamber and piston arrangement including a chamber and a piston disposed within the chamber may be provided as part of system 400. The chamber and piston may be included as part of analytical apparatus 410 and / or density analyser 405 and / or may be separate to analytical apparatus 410 and density analyser 405. As the piston is moved in one direction, the sample fluid is drawn into the chamber and as the piston is moved in an opposing direction, the sample fluid is ejected into vessel 105 of density analyser 405. Multiple chamber and piston arrangements may be provided as part of system 400 to facilitate transfer of the fluid in, through, between and / or out of various components of the system 400. Alternatively, a pump may be used to transfer the sample fluid between density analyser 405 and analytical apparatus 410. The pump may be automatically or manually operated. The skilled person will appreciate that other devices or methods for transferring the sample fluid may be used. Where a chamber and piston arrangement are employed to facilitate transferring of the sample fluid, the chamber 510 and piston 505 may be arranged in a vertical orientation as illustrated in Figure 5 whereby the chamber 510 and piston 505 are configured to draw the sample fluid into chamber 510 as piston 505 is moved in an upward direction through chamber 510 and configured to eject the sample fluid into vessel 105 of density analyser 405 as piston 505 is moved in a downward direction through chamber 510. In this vertical orientated arrangement, any anomalies in the sample fluid that are less dense than the sample fluid (for example, gas bubbles in a sample fluid) that are present in chamber 510, will rise to the top of chamber 510 and sit flush against the face of piston 505. Advantageously, because these anomalies such as air bubbles sit flush against the face of piston 505, as piston 505 is moved in a downward direction through chamber 510 to eject the sample fluid from chamber 510 into vessel 105 of density analyser 505, downward movement of piston 505 can be controlled to stop before any anomalies such as air bubbles are ejected into density analyser 505 with the sample fluid. This may limit or reduce anomalies introduced into density analyser 505, such that the sample fluid received by vessel 105 is less likely to include anomalies. It will be understood that the orientation of the piston and chamber may be reversed where the relative densities of the anomalies and sample fluid is reversed (i.e. the sample fluid is less dense than the anomalies) to achieve the same result of limiting / reducing introduced anomalies into density analyser 505. Where density analyser 405 is part of such a system 400, the temperature of the sample fluid received in vessel 105 of density analyser 405 may be controlled to match the operating temperature of the analytical apparatus 410 to which it is coupled. In this example, advantageously, it may take less time for the temperature of the sample fluid to adjust and stabilise to the set temperature of the density analyser and / or analytical apparatus upon being transferred from one to the other. The sample fluid received in vessel 105 at any one time may be a sample of the total sample fluid to be measured as described above, for example where the total volume of the sample fluid to be measured is 6ml and the capacity of vessel 105 is 1ml. Where this is the case, density analyser 100 may be configured to gradually move the total volume of the sample fluid to be measured through vessel 105 to separately analyse each sample of the sample fluid, as described above. Where density analyser 405 is part of system 400, the sample fluid may be configured to move through vessel 105 and analytical apparatus 410 at the same time such that different samples of the sample fluid are received by vessel 105 for density analysis and received by the analytical apparatus 410 for other analysis. In this configuration, density analyser 405 and analytical apparatus 410 may simultaneously perform analysis on different samples of the sample fluid. Density analyser as part of a system including a vapour pressure analyser In such a system 400, the analytical apparatus 410 may be a vapour pressure analyser. A vapour pressure analyser may be any suitable device capable of measuring the vapour pressure of the sample fluid. The vapour pressure analyser may be arranged to measure vapour pressure according to ASTM D5191. The vapour pressure analyser may include a chamber to receive and hold the sample fluid during the vapour pressure analysis procedure. The chamber may be sealed to ensure that the pressure measured is only due to the vapor of the sample fluid. The vapour pressure analyser may include a controller or multiple controllers to control the condition or environment in which the vapour pressure analyser operates and a sensor or multiple sensors to sense the condition or environment in which the vapour pressure analyser operates. By employing sensors and controllers, a feedback system may be implemented to maintain the required conditions of operation. For example, the vapour pressure analyser may include a temperature controller and sensor. The temperature of the chamber may be controlled to allow the sample fluid to reach thermal equilibrium. Once thermal equilibrium is reached, the pressure exerted by the vapour of the sample fluid within the sealed chamber may be measured. The temperature of the sample fluid received by the chamber of the vapour pressure analyser may be controlled and maintained to approximately 20 degrees Celsius. Where the vapour pressure analyser is coupled to density analyser 405, the temperature of the sample fluid received by vessel 105 of density analyser 405 may also be controlled to approximately 20 degrees Celsius, to match the operating temperature of the vapour pressure analyser. The vapour pressure analyser and density analyser 405 may be coupled in configurations according to the above description with respect to analytical apparatus 410 and density analyser 405. Advantageously, in the configuration where the sample fluid is transferred from the vapour pressure analyser to density analyser 405 instead of being transferred from density analyser 405 to the vapour pressure analyser interference with the vapour pressure analysis is minimised. The sample fluid may be ejected from density analyser 100, 405 or analytical apparatus 410 into a waste container once analysis has been performed to be disposed of. It will be appreciated that alternative types of analytical apparatus can be used with the image analysis process and / or density analyser described herein. Further, the invention is not limited for use with an analytical apparatus. In addition to the examples described in detail above, the skilled person will recognize that various features described herein can be modified and / or combined with additional features, and the resulting additional examples can be implemented without departing from the scope of the system of the present disclosure, as this specification merely sets forth some of the many possible example configurations and implementations for the claimed solution. The following paragraphs provide a list of additional embodiments which may serve as basis for embodiments in this application or in any subsequently filed divisional application(s). Embodiment 1. A method comprising: receiving a sample fluid in a vessel of a density analyser; capturing at least one image of the vessel using an imaging apparatus; and performing image analysis on the at least one image captured by the imaging apparatus using a processor, to identify the presence or absence of an anomaly in the sample fluid that is received in the vessel. Embodiment 2. The method of embodiment 1, wherein the sample fluid comprises a plurality of samples, and the method further comprises receiving in the vessel of the density analyser at least two different samples of the plurality of samples. Embodiment 3. The method of embodiment 2, further comprising capturing at least one image of the vessel for each different sample of the sample fluid received by the vessel using the imaging apparatus to identify the presence or absence of an anomaly in each sample of the sample fluid that is received in the vessel. Embodiment 4. The method of any preceding embodiment, wherein performing image analysis comprises identifying the presence or absence of a feature in the at least one image captured wherein the feature is representative of an anomaly. Embodiment 5. The method of any preceding embodiment, wherein performing image analysis comprises comparing at least two images captured by the imaging apparatus to identify the presence or absence of an anomaly in each of the at least two images. Embodiment 6. The method of embodiment 5, wherein comparing at least two images comprises comparing from a pair of two images for at least one pair to identify the presence or absence of an anomaly in each of the two images of the at least one pair. Embodiment 7. The method of embodiment 6, wherein comparing two images from a pair of images for at least one pair comprises subtracting one image from the pair from the other image of the pair to generate a pairwise difference image. Embodiment 8. The method of embodiment 7, wherein performing image analysis further comprises: generating an overlap difference image for each of the captured images whereby an overlap difference image is generated by combining each pairwise difference image that was generated using the captured image; and identifying the presence or absence of a feature in each overlap difference image wherein the feature is representative of an anomaly in the associated captured image. Embodiment 9. The method of embodiment 8, further comprising validating the identification of the presence or absence of an anomaly in each captured image to eliminate false negatives. Embodiment 10. The method of any preceding embodiment, further comprising measuring the density of the sample fluid using the density analyser such that the at least one image captured is associated with a density measurement. Embodiment 11. The method of embodiment 10, further comprising disregarding the density measurement of the sample fluid in the case that an anomaly is identified in the image captured associated with the density measurement and / or retaining the density measurement of the sample fluid in the case that an anomaly is not identified in the image captured associated with the density measurement using the processor. Embodiment 12. The method of any of embodiments 1 to 9, further comprising disregarding the sample fluid in the vessel in the case that an anomaly is identified in the image captured and / or retaining the sample fluid in the vessel in the case that an anomaly is not identified in the image captured and, where the sample fluid is retained, measuring the density of the retained sample fluid using the density analyser, such that the image captured is associated with the density measurement. Embodiment 13. The method of embodiment 11 or 12, further comprising calculating the average value of any density measurements of the sample fluid for which an anomaly is not identified, using the processor. Embodiment 14. The method of any preceding embodiment, wherein the vessel is a ll-Tube or an oscillating ll-Tube. Embodiment 15. The method of any preceding embodiment, wherein the sample fluid received in the vessel is a petroleum distillate and / or a viscous oil. Embodiment 16. The method of any preceding embodiment, further comprising determining the temperature of the vessel using a temperature sensor and controlling the temperature of the vessel using a temperature controller. Embodiment 17. The method of any preceding embodiment, further comprising maintaining a temperature inside the vessel by surrounding the vessel on all sides by walls. Embodiment 18. The method of any preceding embodiment, wherein the density analyser is a module or self-contained unit that is releasably attachable to an analytical apparatus. Embodiment 19. The method of any preceding embodiment, wherein the sample fluid is a liquid and an anomaly in the sample fluid is a gas bubble.

Claims

1. A density analyser, comprising:a vessel to receive a sample fluid;an imaging apparatus configured to capture at least one image of the vessel; anda processor arranged to perform image analysis on the at least one image captured by the imaging apparatus to identify the presence or absence of an anomaly in the sample fluid that is received in the vessel.

2. The density analyser of claim 1, wherein the sample fluid comprises a plurality of samples and the vessel is configured to receive at least two different samples of the plurality of samples.

3. The density analyser of claim 2, wherein the imaging apparatus is configured to capture at least one image of the vessel for each different sample of the sample fluid received by the vessel to identify the presence or absence of an anomaly in each sample of the sample fluid that is received in the vessel.

4. The density analyser of any preceding claim, wherein image analysis performed comprises identifying the presence or absence of a feature in the at least one image captured wherein the feature is representative of an anomaly.

5. The density analyser of any preceding claim, wherein image analysis performed comprises comparing at least two images captured by the imaging apparatus to identify the presence or absence of an anomaly in each of the at least two images.

6. The density analyser of claim 5, wherein comparing at least two images comprises comparing from a pair of two images for at least one pair to identify the presence or absence of an anomaly in each of the two images of the at least one pair.

7. The density analyser of claim 6, wherein comparing two images from a pair of images for at least one pair comprises subtracting one image from the pair from the other image of the pair to generate a pairwise difference image.

8. The density analyser of claim 7, wherein image analysis further comprises:generating an overlap difference image for each of the captured images whereby an overlap difference image is generated by combining each pairwise difference image that was generated using the captured image; andidentifying the presence or absence of a feature in each overlap difference image wherein the feature is representative of an anomaly in the associated captured image.

9. The density analyser of claim 8, wherein the identification of the presence or absence of an anomaly in each captured image may be validated to eliminate false negatives.

10. The density analyser of any preceding claim, wherein the density analyser is configured to measure the density of the sample fluid such that the at least one image captured is associated with a density measurement.

11. The density analyser of claim 10, wherein the processor is configured to disregard the density measurement of the sample fluid in the case that an anomaly is identified in the image captured associated with the density measurement and / or retain the density measurement of the sample fluid in the case that an anomaly is not identified in the image captured associated with the density measurement.

12. The density analyser of any of claims 1 to 9, wherein the density analyser is configured to disregard the sample fluid in the vessel in the case that an anomaly is identified in the image captured and / or retain the sample fluid in the vessel in the case that an anomaly is not identified in the image captured and, where the sample fluid is retained, the density analyser is configured to measure the density of the retained sample fluid such that the image captured is associated with the density measurement.

13. The density analyser of claim 11 or 12, wherein the processor is configured to calculate the average value of any density measurements of the sample fluid for which an anomaly is not identified.

14. The density analyser of any preceding claim, wherein the vessel is a ll-Tube or an oscillating ll-Tube.

15. The density analyser of any preceding claim, wherein the sample fluid received in the vessel is a petroleum distillate and / or a viscous oil.

16. The density analyser of any preceding claim, further comprising a temperature sensor and temperature controller to determine and control the temperature of the vessel.

17. The density analyser of any preceding claim, wherein the vessel is surrounded on all sides by walls to maintain a temperature inside the vessel.

18. The density analyser of any preceding claim, wherein the density analyser is a module or self-contained unit that is releasably attachable to an analytical apparatus.

19. The density analyser of any preceding claim, wherein the sample fluid is a liquid and an anomaly in the sample fluid is a gas bubble.

20. A method comprising:receiving a sample fluid in a vessel of a density analyser;capturing at least one image of the vessel using an imaging apparatus; andperforming image analysis on the at least one image captured by the imaging apparatus using a processor, to identify the presence or absence of an anomaly in the sample fluid that is received in the vessel.

21. A system comprising:an analytical apparatus; andthe density analyser of any of claims 1 to 19.

22. The system of claim 21, wherein the density analyser and the analytical apparatus are coupled, and the system is configured to transfer the sample fluid between the vessel of the density analyser and the analytical apparatus.

23. The system of claim 21 or 22, wherein the density analyser is provided as a part or subpart of the analytical apparatus.

24. The system of any one of claims 21 to 23, wherein the system is configured to transfer the sample fluid from the analytical apparatus to the vessel of the density analyser after the analytical apparatus has performed analysis on the sample fluid.