Inte­grated diag­nostic system for fans

The life span calcu­la­tion gener­ally applied to fans today is based on the assump­tion of statis­tical aver­ages. For this, there are various calcu­la­tion formulas and eval­u­a­tion criteria for loads such as temper­a­ture, speed or dust and humidity. If oper­ating condi­tions greatly deviate from the norm, this approach cannot provide any mean­ingful values for the actual service life of an indi­vidual on-site fan. In order to achieve a more reli­able state­ment about the actual service life poten­tial here as well, in addi­tion to general labo­ra­tory find­ings, the actual on-site loads have to be measured during oper­a­tion, added up and included in the calcu­la­tion. A new diag­nostic tool for fans collects the rele­vant data for this and calcu­lates the indi­vidual remaining service life under the actual oper­ating condi­tions. Thus oper­a­tion and main­te­nance of diffi­cult-to-reach fans are deci­sively improved and the reli­a­bility of the overall system increases.

Statis­tical state­ments are only as good as permitted by the assumed input data. Even the best calcu­la­tion program is not able to provide any real­istic state­ment about the service life of a product if the assump­tions are incor­rect. However, precisely with fans for exposed appli­ca­tions in a safety area or for systems that are diffi­cult to access, such as cellular tele­phone stations on moun­tains, the most exact possible deter­mi­na­tion of (remaining) service life is impor­tant to the oper­a­tors. There­fore it is ideal if the calcu­la­tion includes the actual load of the indi­vidual fan where it is used. If this takes place right in the fan, and if the fan can issue an alarm signal when a config­urable safety threshold is exceeded, that improves the reli­a­bility of the overall system. There­fore there is no need for any cost-inten­sive preven­tive replace­ments; that saves time, money and personnel.

Existing eval­u­a­tion method

Figure 1: In the endurance test room – the data for the conven­tional life span calcu­la­tion is acquired using the climate chamber.

Existing, conser­v­a­tive cata­logue infor­ma­tion regarding service life refers to an accepted, average oper­ating point; for example, service life L10 of 70,000 hours at 40°C ambient temper­a­ture and 3,600 revo­lu­tions per minute. There­fore they are more of a stan­dard value for the prac­tical eval­u­a­tion, since oper­ating temper­a­ture and speed contin­u­ously change throughout the day and over the seasons, thereby affecting the service life. To this are added unfore­see­able factors, such as dust or humidity, which are taken into account only in special cases in the labo­ra­tory. Usually, current eval­u­a­tions of life­time are based on labo­ra­tory testing with defined stan­dard condi­tions for temper­a­ture and speed (Figure 1).

For theo­ret­ical consid­er­a­tions of statis­tics and testing, the average service life of the entire produc­tion is used. To achieve shorter testing periods, often the thermal load is also set unre­al­is­ti­cally high in order to achieve faster ageing of the compo­nents. Changing oper­ating condi­tions, which always occur in real-world appli­ca­tions, are not taken into consid­er­a­tion in this proce­dure. In order to make statis­tical state­ments concerning fans, it is enough to take into consid­er­a­tion the service life of the rotor bearing. Fail­ures of the elec­tronics or the motor winding are signif­i­cantly smaller and can normally be neglected. On this basis, ebm-papst devel­oped a diag­nostic tool imple­mented in the fan that deter­mines the indi­vidual service life of the fan while taking into consid­er­a­tion the respec­tive ambient and oper­ating condi­tions. This way the existing limi­ta­tions of the oper­ating statis­tics are completely rede­fined by exact funda­mental data and the latest methods of calcu­la­tion.

New approach

Figure 2: Compact fans with high output and internal self-diag­nos­tics for service life.

The new service life predic­tion takes into account the indi­vidual history of the fan in its respec­tive oper­a­tion and thus state­ments about an expected remaining service life can be made in indi­vidual cases using the appli­ca­tion condi­tions. Changing temper­a­tures (day/night cycles or seasonal fluc­tu­a­tions) are taken into account, as are the accepted dust pollu­tion on-site and the actual speed. This data is used by the elec­tronics inte­grated in the fan to calcu­late the service life (Figure 2). The new early failure detec­tion is conceived partic­u­larly for users who can replace the fan only at high cost or at certain times (for example, remote measuring stations, radio buoys). With the new options, the replace­ment inter­vals can be planned in a timely manner or adapted to the indi­vidual require­ments. Fans no longer have to be “preven­tively” replaced, which reduces invest­ment and main­te­nance costs and increases oper­ating reli­a­bility.

Real-world appli­ca­tions

Instead of oper­ating on preset values, the new system uses data that is updated on an ongoing basis, such as oper­ating speed, ambient temper­a­ture and down­times. Basic data, such as the bearing design (ball or sleeve bearing), the type of bearing lubri­ca­tion and the grease used, and other ambient condi­tions is preset. That way service life reserves can be used, since the current fore­cast always takes into account the overall history of the fan.

Figure 3a and 3b: The remaining service life can also be output digi­tally via a PWM signal a) high, b) low or as an analogue value via an addi­tional RC element.

The diag­nos­tics system is based on empir­ical corre­la­tions from real-world appli­ca­tions and decades of endurance tests under various condi­tions. Customer-specific output formats, such as L5 instead of L10, can be taken into account. The output can be wired out via either the alarm wire or an addi­tional wire and can be called up digi­tally. The remaining service life can also be output as an analogue value via a PWM signal to an RC element. Thus the product can be used nearly up to the actual end of its life without losing reli­a­bility. That conserves resources, increases value creation and reduces costs of procuring replace­ments and main­te­nance costs (Figure 3a, b).