Apparatuses having movable mechanical parts are present in most industrial contexts. A typical such apparatus has some kind of motor or actuator acting on a body that is movable in a translational and/or rotational sense. The body may interact with other mechanical parts or components in order to perform one or more predetermined tasks. These tasks may be of various types, e.g. closing a valve, moving a part between two predetermined positions, applying a force, adjusting positions, compression of gases, pumping of fluids, rotating filters, fans etc.
Monitoring of mechanical apparatuses for the purpose of detecting signs of maintenance need or erroneous operation is requested in many areas. Emergency faults typically involve large costs in terms of production losses, spare parts and short-notice labour costs. An early detection of e.g. wear or faults may allow any maintenance operations to be performed in a well-planned manner, and may reduce the actual damage caused in the apparatuses. A common approach is to supply the apparatuses with different kinds of sensors, measuring vibrations, torques, forces, temperatures, pressures, sound etc. The sensors are then connected to a monitoring or diagnosing equipment performing an evaluation of the measured quantities.
In many industrial applications, mechanical apparatuses are sometimes present in areas with hazardous or aggressive environments, in limited spaces or simply in positions which are difficult to reach from outside. In such cases, it may be difficult to provide sensors directly on the apparatus or connections to the evaluation devices. A remote monitoring or diagnosing is thus required.
When mechanical equipment is re-mounted when being opened for inspection, there is a finite probability that the mechanical equipment is not in operative condition or its settings for proper operation have been changed. In purpose to avoid future need of maintenance to correct the introduced errors it is valuable to find such errors in advance.
In the U.S. Pat. No. 4,965,513 is a motor current signature analysis method disclosed. A current supplied to an electrical motor driving e.g. a valve is measured at a position remote from the actual motor. The current signal is analysed in the frequency domain, i.e. in principle a vibrational analysis. The frequency spectrum comprises typically a number of more or less pronounced peaks, which are possible to relate to mechanical parts performing a periodic motion. By comparing the amplitudes of the frequency components in a spectrum with a spectrum recorded when a fault-free operation was assured, trends may indicate abnormalities or degradation. There are some remaining problems with the method disclosed in U.S. Pat. No. 4,965,513. Non-periodic motions are not possible at all to monitor or evaluate and the evaluation is basically performed as an associative evaluation, i.e. comparison with earlier spectra, which means that even if some trends are detected, there is basically no detailed information about what fault signal really is present.
Also the monitoring system disclosed in WO 99/05501 is based on an analysis of cyclical tasks. The power consumption as a function of time is compared with pre-determined upper and lower limit thresholds. The number of crossings of the thresholds is counted and evaluations are performed based on these figures and according to pre-determined sample recordings for a set of known faults. Here, the system is trained for a specific task by measuring the operation at well-defined situations. The analysis is a pure associative procedure. This implies that the total system has to be rather simple, in order to be able to cover possible behaviours. Also, all faults that are requested to be identified have to be caused on purpose and measured in order to provide the associative sample recordings.
The U.S. Pat. No. 4,888,996 describes a method and a device for registration of the work performed when a DC motor operates a valve. The mechanical output torque is determined by registering the electrical power supplied to the motor and compensating for electrical losses in the motor. The output torque, or a quantity proportional thereto is monitored as a function of time. A series of events can be monitored and interpreted as different operational phases. Certain quantities related to the state of the valve and its operation are possible to diagnose by relating the main features of the output torque curve to the course of events occurring when operating the valve. However, the analysis is based on simple and well-known models related to dimensioning of actuators.
The analysis in U.S. Pat. No. 4,888,996 is based entirely on static interpretations of the valve as one collective item. Such analysis is typically based on differences between different operation phases, where different sets of movable parts are in operation. Referring to FIG. 6 in U.S. Pat. No. 4,888,996, “c” refers to a duration of a first operation phase, “a” refers to a difference in collective average load between a fourth and second operation phase, “b” again refers to a duration of an operation phase, in this case the fourth one and “d” refers to the total load at the onset of the sixth operation phase. All such parameters are closely linked to changes in operation phase and are based on a collective view of the system. Although some information about the actual existence of operation problems is possible to extract, it is not possible to conclude what the details causing the problem are.
The U.S. Pat. No. 5,748,469 discloses a method of detecting errors in components in an automatically operated valve. A mathematical model of a control valve assembly is defined. The mathematical model is fitted to data that consists at least several values of a control signal and corresponding values of a position of the control valve. The analysis is thus based on a response analysis between an input signal and a resulting behaviour of a measured quantity, in this case a position. For deeper analysis, further measured data are needed. Certain parameters of the mathematical model are selected as “critical” parameters. The “critical parameters” are supposed to be mainly dependent on a part system, which is why the occurrence of errors readily may be detected to a certain part system if the associated critical parameter changes considerably.
The method is entirely dependent on a measured position as well as a control signal as an input, which as discussed above is unacceptable in many applications. The model is further based on a collective approach, i.e. where the valve-operating device is considered as one unit having statistically averaged properties that can be expressed as parameters. This is emphasized in that e.g. one single friction coefficient is used that is only dependent on the rotational angle. Furthermore, a reduced mass is used for the piston, i.e. a weighted averaged value of different interacting masses. Also a combined inertia moment for the valve and piston is used. Such a model thus enables a description of the behaviour of the valve system as one integrated single item. However, even if such errors may be detected and associated to a certain part system, such models do not provide any means to efficiently precisely localise the error within the part, and certainly not to estimate any error sizes.