Abstract:
Apparatus and corresponding method are invented for detecting indoor liquid leak in equipment, such as a pump in a pump station. The apparatus includes an image analyzer configured to receive video from one or more cameras and analyze the video to determine if a leak on the equipment is present by comparing the video with a reference and a target color and the image analyzer having an output port for delivering a notification upon the image analyzer determining that a leak is present on the equipment. If a leak alarm happens, the operator can check the remote live video and/or stored clips to confirm the leak and activate a response to stop it.

Description:
TECHNICAL FIELD 
       [0001]    Indoor leak detection. 
       BACKGROUND 
       [0002]    Indoor liquid leak detection is very important for many facilities, such as a home water tank, gasoline pump station, etc. Detecting a leak and generating an alert can avoid the damage of the facility, save money and protect the environment. 
       SUMMARY 
       [0003]    An indoor liquid leak detection system for the detection of a leak from a gasoline pump station is disclosed. The system may be used for other liquid containers and carriers. The system makes use of color video camera(s) to monitor the pumps. An alarm is activated when a leak is detected over a predetermined time interval. The invention can be used for industrial applications where the detection of leaking liquids is desirable to prevent environmental damage or other unwanted results. The invented system in some embodiments may be easy to install, not disturb the equipment&#39;s operation, and not change the equipment&#39;s architecture. 
         [0004]    In an embodiment, there is provided a video-based indoor leak detection system. The detection system comprises a video capturing device (for example, a video camera) having a field of view; an image analyzer configured to analyze the video to determine if a leak on the equipment is present; and an output port for delivering a notification upon the image analyzer determining that a leak is present. Further embodiments may also include one or more of the following features: a video recording unit for recording events, for example video corresponding to an alarm, which may be stored according to the time and the classification for further reference; a server may comprise the image analyzer and video recording unit; the server may be connected to the video capturing device via a telecommunications network; and the video may comprise pixel values that are representative of color and the image analyzer may determine if a leak on the equipment is present from the pixel values that are representative of color. 
         [0005]    In an embodiment, there is provided a method of detecting a leak in equipment, the method comprising acquiring video of the target with video camera, in which the video comprises pixel values that are representative of color, sending the video to an image analyzer, the image analyzer analyzing video to determine if a leak is present on the equipment from the pixel values that are representative of color; and upon the image analyzer determining that a leak is present, generating a notification of the presence of a leak. Further embodiments may have one or more of the following features: at the time a leak is determined, events such as video data corresponding to an alarm may be stored to the local hard disk of the server or a removable disk for further reference; analyzing the video may comprise comparing the color of the video with color information from a reference frame; analyzing the video may comprise comparing the color of the video with a target color; analyzing the video may comprise comparing a difference between a frame being analyzed and a reference frame to a difference between two reference images; analyzing the video comprises comparing a difference between a frame being analyzed and a reference frame to a difference between two reference images; analyzing the video comprises comparing a difference between a frame being analyzed and a reference frame to a difference between two reference images; analyzing the video may comprise comparing a difference between a frame being analyzed and a reference frame to a difference between two reference images; analyzing the video may comprise comparing the color of the video with a target color and comparing a difference between a frame being analyzed and a reference frame to a difference between two reference images; and in which the presence of a leak is determined upon determining that a portion of the frame being analyzed is similar to or darker than the reference frame and is also darker than the reference frame and the difference between the frame being analyzed and the reference frame is larger than the difference between the two thresholds by an amount exceeding a threshold according to a metric; analyzing may carried out by analysis of one or more regions of interest (ROIs) in the video; the one or more regions of interest may be user selected; and the equipment may comprise a pump. 
         [0006]    These and other aspects of the device and method are set out in the claims, which are incorporated here by reference. 
     
    
     
       BRIEF DESCRIPTION OF THE FIGURES 
         [0007]      FIG. 1  is a block diagram of the video based leak detection system. 
           [0008]      FIG. 2  illustrates method steps carried out by the image analyzer. 
       
    
    
     DETAILED DESCRIPTION 
       [0009]    Immaterial modifications may be made to the embodiments described here without departing from what is covered by the claims. 
         [0010]    A video based leak detection system is shown in  FIG. 1  where one or more video cameras  102  are installed to view a scene  100 , here a pump station with several pumps. The camera  102  acquires the video of the scene  100  including the pumps. Regions of interest (ROIs)  101  may be defined within the scene as described below. 
         [0011]    A video is a sequence of consecutive frames. A frame is a set of pixel values determined by light received in the one or more cameras  102  at locations on an imaging device in the camera corresponding to locations of the view. The video can be sent to a conventional input port of a server  105  directly, for example via a conventional cable, or indirectly via a suitable communications channel  103  such as a radio that communicates through a telecommunications network  104 . A direct connection can also use a radio and an indirect connection through a network  104  can also use a cable. In some embodiments, the server  105  may be formed of a local processor (for example, to carry out basic control of the camera) as well as a remote processor for carrying out other functions such as image analysis. In some embodiments with a local processor and a remote processor, the local processor may be directly connected to the one or more video cameras  102  and the remote processor may be connected to the local processor via network  104 . 
         [0012]    In the embodiment shown, the server  105  analyzes the video and then determines if the scene  100  has a leak or not. The server comprises an image analyzer. Here, “comprises” may indicate that either the image analyzer is a separate physical component of the server or the image analyzer is software operating on a processor of the server. The server may also comprise a video recording unit, in the same sense of “comprise.” The video recording unit may be connected to the image analyzer, with a connection that can be a physical connection or a software connection. A pump is an example of a target to which the method and apparatus may be applied. The method and apparatus may be applied to other targets. The server  105  may cause a notification  111  to be generated and output from an output port of the server  105 , which may be any of a variety of notifications, and may be communicated directly to an operator or through a network  106 , which may be the same network as network  104 , via suitable methods such as through a fixed station  107 , web interface  108 , email  109  or smart phone  110 . The output port may be, for example, a USB port, network interface, display driver or other conventional output port of a computer. The notification  111  may comprise an electronic message indicative of a leak, or the generation of a sound, light signal, mechanical signal or other signal that may be observed by a human or monitoring equipment. The server  105  may communicate two-way with a further remote server (not shown) or other remote device such as smart phone  110 . In on demand operation, the remote device may instruct the server  105  to acquire video from the camera  102  and the video is then processed by the server  105 . In some embodiments, the server  105  may be a remote server and need not be situated with the camera  102 . 
         [0013]    The server  105  performs the image analysis, leak detection and notification sending tasks. For image analysis, color information is proposed to be used. If there is a leak, some portions of the current frame, for example, the part of floor with accumulated leaking liquid, should be darker than the reference and similar to or darker than the target color. In some embodiments, the analyzer  105  may intelligently compare the video with a reference, using more sophisticated statistical analysis than a greater than-less than analysis. For example, where a suite of training images is available, including some leak and non-leak images, perhaps being separated in time by hours or days, statistical analysis such as Bayesian or neural network analysis may be applied to determine a probability of a leak. 
         [0014]    Since the video is captured at various distance, direction and zoom levels, the users may be required in an initialization step  112  to defined one or more regions of interest (ROI). In an embodiment, a software interface in the server  105  lets the users draw rectangle boxes around ROIs  101 . In other embodiments, the user may draw other shapes to define ROIs. The use of regions within a scene allows the detection unit to individually check the leak in each region. 
         [0015]    For each ROI  101  defined in step  112 , the users can set one or more target color (TC) through the user interface (not shown) in step  113 . The target color may be a color representing a color of a potentially leaking liquid. The target color representing a color of a potentially leaking liquid may represent an expected color of the liquid in an expected context, for example, a mixed color of the floor and the liquid when the leaking liquid is poured on the floor. 
         [0016]    After the ROI is defined in step  112  and TC is set in step  113 , a reference frame (RF) and a reference frame difference (RFD) are saved in step  114  for further processing. The RFD is obtained by subtracting two frames. 
         [0017]    In step  115 , for each ROI  101 , the current frame is compared with the TC set in step  113 . The points that are similar to or darker than the TC are considered. If the considered points are changed a lot compared with the RF, for example if the differences from the reference frame are greater than a threshold, they are defined as potential points. 
         [0018]    Because of the lighting change (or reflection) in the environment, some potential points may not be related to a leak. Therefore, in step  116  we will filter them out by comparing with the reference frame difference (RFD). Even though there is no leak at the time that the RFD is obtained in step  114 , we still can see some difference in the image. This is because of the background lighting change or some reflection by the floor. If there is a leak, the amount of frame difference should be much larger than the reference frame difference. For each region of interest, if the amount of potential points is larger than the frame difference according to a metric by a threshold, and if the area occupies a certain percentage of the whole region, the server determines that there is a leak in that ROI in step  117 . If any ROI is determined to have a leak in step  117 , the server generates an alarm in step  118 . The metric listed above can be the number of pixels that differ from the reference frame by more than a second threshold, and the threshold can be a fixed number of pixels or a multiple of the reference frame difference. 
         [0019]    Events, for example video corresponding to an alarm, can be stored by the server  105  to a local hard disk of the server or a removable disk according to time or classification for further reference.